Fetal growth The role of maternal factors and placenta

Marie Cecilie Paasche Roland

Section for Obstetrics Rikshospitalet

Women and Childrenrsquos Division

Oslo University Hospital

Faculty of Medicine

University of Oslo

2014

2

3

Contents

Contents 3

Acknowledgements 4

List of papers 7

Abbreviations 8

1 Introduction 10 11 Summary 10

12 Background 14

13 Fetal growth 15

131 Size at birth 15

132 Intrauterine growth 17

14 Maternal aspects of fetal growth 19

141 Maternal nutritional status 19

142 Maternal metabolism 22

143 Other maternal factors 23

15 Placental aspects of fetal growth 25

151 Development structure and growth of the placenta 25

152 Placental functions 29

16 Sexual dimorphism in fetal growth and placental function 34

17 Preeclampsia 35

2 Aims of the study 42 Paper 1 42

Paper 2 42

Paper 3 42

Paper 4 43

3 Materials and methods 44 The STORK study 44

The STORK-Placenta study 48

4 Summary of results 51 Paper 1 51

Paper 2 53

Paper 3 53

Paper 4 54

5 Discussion 56 51 Methodological issues STORK 56

52 Data collection STORK 64

53 Methodological issues STORK-Placenta 69

54 Data collection STORK-Placenta 71

55 Interpretation of results 73

6 Conclusions 80

7 Further research 80

8 References 82

Appendix

Papers 1-4

4

Acknowledgements

This work was carried out at Section for Obstetrics Department of Obstetrics and

Gynaecology at Rikshospitalet Oslo University Hospital The thesis has been supported by

grants from the Norwegian Extrafoundation for Health and Rehabilitation through the

Norwegian Health Association

I would like to thank Professor Thomas Aringbyholm as Head of Department for giving me the

opportunity to work at Oslo University Hospital Rikshospitalet where I have received most of

my clinical training My journey into research started with and has been closely linked to

clinical work There are a number of colleagues who have been important role models for me

at various stages of this journey The Section for Obstetrics has an excellent teaching

environment filled with enthusiastic colleagues who constantly share their experience with

younger colleagues My supervisors Tore Henriksen and Bjoslashrg Lorentzen together with Liv

Ellingsen have been my role models in clinical work and their influence has inspired me to

choose the challenging and fascinating field of obstetrics After basic training in obstetrics and

gynaecology I got the opportunity to spend four years combining data collection with clinical

training

This work is based on results from two studies The STORK study is a collaboration between

the Department of Endocrinology and the Department of Obstetrics Thanks to Professor Jens

Bollerslev and the continuous efforts of Kari Kvamsdal Hege H Boslashyum Tove Lekva the

late Gunhild Aker Isaksen Elisabeth Qvigstad and Kristin Godang this projected has

succeeded as an example of research drawing experience across clinical specialities Nanna

Voldner as the first PhD candidate in the study made a huge effort in setting up the study and

I would like to thank her especially Kathrine Frey Froslashslie joined the group as a statistician

She has played an important role by making statistics not just understandable but even

interesting due to her outstanding teaching skills She has also created a great weekly meeting

for all those interested in discussing methodological issues in research We were two PhD

candidates entering the project together Camilla M Friis has been my closest colleague

throughout the years sharing all thoughts and experiences during data collection analyses and

publishing We have had some memorable trips to various conferences Most importantly she

has become a trusted friend and I am confident we will continue our work together hopefully

5

bringing the STORK study forward I would also like to acknowledge our secretaries Rakhee

Sharma and Esther Gangsoslash and all the efforts made by midwives and childrenrsquos nurses

The second study was started during my time as a PhD candidate I would like to thank

anaesthesiologists Eldrid Langesaeligter and Leiv Arne Rosseland both for their contribution in

the project and for their interest in anaesthesia to our obstetric patients in general The study is

now expanding with Trond Melbye Michelsen as a postdoc and several PhD candidates Ane

Moe Holme has been my co-author and with her enthusiastic approach and endless efforts I

am sure the project will continue to grow

My three supervisors have been of great importance and together they have provided me with

all the necessary support to reach the end of this PhD

Guttorm Haugen has shared valuable knowledge in the field of fetal medicine Always

friendly and I am grateful for his accurate and thorough comments which have improved my

work substantially

Bjoslashrg Lorentzen has actively taken part in all parts of my work She has taught me all about

high risk pregnancies and preeclampsia in particular She has collected blood samples at any

time of the day (and night) and spent hours with me in the lab She has always been there to

cheer me up in times of frustration or share moments of joy I have enjoyed her company at

several conferences around the world Her extraordinary clinical skills are valued by all her

patients including myself

Tore Henriksen as my main supervisor has been the source of scientific ideas in both

projects He has the ability to be visionary and to build a larger picture from the small

contributions produced by each independent PhD candidate he has supervised over the years I

am so grateful for the hours he has spent discussing ideas reading my papers and sharing his

experience His is open-minded and always willing to listen to emerging ideas By

questioning surprising findings and not necessarily accepting the conventional view he has

taught me critical thinking and to trust my own judgement which are the most important

lessons I have learnt from this work

We have been several PhD candidates at our department over the years Among them I would

like to thank Anne Helbig for critical questioning and valuable discussions and Julie Holm

Tveit for her warm and caring personality Hilde Skuterud Wik did her PhD in a different

field but nevertheless is a valued friend and colleague

6

Thanks to Oslashystein H Horgmo University of Oslo for making the illustrations used in this

thesis

Last but not least I am grateful for the support of my family My mother has always been

there for me believed in me and showed interest in my work Together with Aase and Per my

parents in law she has helped out when family life and work was challenging to combine

Finally my husband Lars and our three wonderful sons Fredrik Kristian and Magnus are the

most important people in my life You have given me the energy and joy needed to complete

this work

7

List of papers

1 Roland MCP Friis CM Voldner N Godang K Bollerslev J Haugen G and Henriksen T

Fetal growth versus birthweight Placenta versus other determinants

PLoS One 2012 7(6)e39324 doi 101371journalpone0039324

2 Roland MCP Friis CM Godang K Bollerslev J Haugen G and Henriksen T

Maternal factors associated with fetal growth and birth weight are independent determinants

of placental weight and exhibit differential effects by fetal sex

PLoS One 2014 9(2) e87303 doi101371journalpone0087303

3 Holme AM Roland MCP Lorentzen B Michelsen TM and Henriksen T

Human in vivo studies of glucose transfer across the placenta

4 Roland MCP Lorentzen B Godang K and Henriksen T

Uteroplacental arterio-venous difference in soluble VEGFR-1 (sFlt-1) but not in soluble

endoglin concentrations in preeclampsia

Placenta 2012 Mar33 (3)224-6 doi 101016jplacenta201201001

2

3

Contents

Contents 3

Acknowledgements 4

List of papers 7

Abbreviations 8

1 Introduction 10 11 Summary 10

12 Background 14

13 Fetal growth 15

131 Size at birth 15

132 Intrauterine growth 17

14 Maternal aspects of fetal growth 19

141 Maternal nutritional status 19

142 Maternal metabolism 22

143 Other maternal factors 23

15 Placental aspects of fetal growth 25

151 Development structure and growth of the placenta 25

152 Placental functions 29

16 Sexual dimorphism in fetal growth and placental function 34

17 Preeclampsia 35

2 Aims of the study 42 Paper 1 42

Paper 2 42

Paper 3 42

Paper 4 43

3 Materials and methods 44 The STORK study 44

The STORK-Placenta study 48

4 Summary of results 51 Paper 1 51

Paper 2 53

Paper 3 53

Paper 4 54

5 Discussion 56 51 Methodological issues STORK 56

52 Data collection STORK 64

53 Methodological issues STORK-Placenta 69

54 Data collection STORK-Placenta 71

55 Interpretation of results 73

6 Conclusions 80

7 Further research 80

8 References 82

Appendix

Papers 1-4

4

Acknowledgements

This work was carried out at Section for Obstetrics Department of Obstetrics and

Gynaecology at Rikshospitalet Oslo University Hospital The thesis has been supported by

grants from the Norwegian Extrafoundation for Health and Rehabilitation through the

Norwegian Health Association

I would like to thank Professor Thomas Aringbyholm as Head of Department for giving me the

opportunity to work at Oslo University Hospital Rikshospitalet where I have received most of

my clinical training My journey into research started with and has been closely linked to

clinical work There are a number of colleagues who have been important role models for me

at various stages of this journey The Section for Obstetrics has an excellent teaching

environment filled with enthusiastic colleagues who constantly share their experience with

younger colleagues My supervisors Tore Henriksen and Bjoslashrg Lorentzen together with Liv

Ellingsen have been my role models in clinical work and their influence has inspired me to

choose the challenging and fascinating field of obstetrics After basic training in obstetrics and

gynaecology I got the opportunity to spend four years combining data collection with clinical

training

This work is based on results from two studies The STORK study is a collaboration between

the Department of Endocrinology and the Department of Obstetrics Thanks to Professor Jens

Bollerslev and the continuous efforts of Kari Kvamsdal Hege H Boslashyum Tove Lekva the

late Gunhild Aker Isaksen Elisabeth Qvigstad and Kristin Godang this projected has

succeeded as an example of research drawing experience across clinical specialities Nanna

Voldner as the first PhD candidate in the study made a huge effort in setting up the study and

I would like to thank her especially Kathrine Frey Froslashslie joined the group as a statistician

She has played an important role by making statistics not just understandable but even

interesting due to her outstanding teaching skills She has also created a great weekly meeting

for all those interested in discussing methodological issues in research We were two PhD

candidates entering the project together Camilla M Friis has been my closest colleague

throughout the years sharing all thoughts and experiences during data collection analyses and

publishing We have had some memorable trips to various conferences Most importantly she

has become a trusted friend and I am confident we will continue our work together hopefully

5

bringing the STORK study forward I would also like to acknowledge our secretaries Rakhee

Sharma and Esther Gangsoslash and all the efforts made by midwives and childrenrsquos nurses

The second study was started during my time as a PhD candidate I would like to thank

anaesthesiologists Eldrid Langesaeligter and Leiv Arne Rosseland both for their contribution in

the project and for their interest in anaesthesia to our obstetric patients in general The study is

now expanding with Trond Melbye Michelsen as a postdoc and several PhD candidates Ane

Moe Holme has been my co-author and with her enthusiastic approach and endless efforts I

am sure the project will continue to grow

My three supervisors have been of great importance and together they have provided me with

all the necessary support to reach the end of this PhD

Guttorm Haugen has shared valuable knowledge in the field of fetal medicine Always

friendly and I am grateful for his accurate and thorough comments which have improved my

work substantially

Bjoslashrg Lorentzen has actively taken part in all parts of my work She has taught me all about

high risk pregnancies and preeclampsia in particular She has collected blood samples at any

time of the day (and night) and spent hours with me in the lab She has always been there to

cheer me up in times of frustration or share moments of joy I have enjoyed her company at

several conferences around the world Her extraordinary clinical skills are valued by all her

patients including myself

Tore Henriksen as my main supervisor has been the source of scientific ideas in both

projects He has the ability to be visionary and to build a larger picture from the small

contributions produced by each independent PhD candidate he has supervised over the years I

am so grateful for the hours he has spent discussing ideas reading my papers and sharing his

experience His is open-minded and always willing to listen to emerging ideas By

questioning surprising findings and not necessarily accepting the conventional view he has

taught me critical thinking and to trust my own judgement which are the most important

lessons I have learnt from this work

We have been several PhD candidates at our department over the years Among them I would

like to thank Anne Helbig for critical questioning and valuable discussions and Julie Holm

Tveit for her warm and caring personality Hilde Skuterud Wik did her PhD in a different

field but nevertheless is a valued friend and colleague

6

Thanks to Oslashystein H Horgmo University of Oslo for making the illustrations used in this

thesis

Last but not least I am grateful for the support of my family My mother has always been

there for me believed in me and showed interest in my work Together with Aase and Per my

parents in law she has helped out when family life and work was challenging to combine

Finally my husband Lars and our three wonderful sons Fredrik Kristian and Magnus are the

most important people in my life You have given me the energy and joy needed to complete

this work

7

List of papers

1 Roland MCP Friis CM Voldner N Godang K Bollerslev J Haugen G and Henriksen T

Fetal growth versus birthweight Placenta versus other determinants

PLoS One 2012 7(6)e39324 doi 101371journalpone0039324

2 Roland MCP Friis CM Godang K Bollerslev J Haugen G and Henriksen T

Maternal factors associated with fetal growth and birth weight are independent determinants

of placental weight and exhibit differential effects by fetal sex

PLoS One 2014 9(2) e87303 doi101371journalpone0087303

3 Holme AM Roland MCP Lorentzen B Michelsen TM and Henriksen T

Human in vivo studies of glucose transfer across the placenta

4 Roland MCP Lorentzen B Godang K and Henriksen T

Uteroplacental arterio-venous difference in soluble VEGFR-1 (sFlt-1) but not in soluble

endoglin concentrations in preeclampsia

Placenta 2012 Mar33 (3)224-6 doi 101016jplacenta201201001

3

Contents

Contents 3

Acknowledgements 4

List of papers 7

Abbreviations 8

1 Introduction 10 11 Summary 10

12 Background 14

13 Fetal growth 15

131 Size at birth 15

132 Intrauterine growth 17

14 Maternal aspects of fetal growth 19

141 Maternal nutritional status 19

142 Maternal metabolism 22

143 Other maternal factors 23

15 Placental aspects of fetal growth 25

151 Development structure and growth of the placenta 25

152 Placental functions 29

16 Sexual dimorphism in fetal growth and placental function 34

17 Preeclampsia 35

2 Aims of the study 42 Paper 1 42

Paper 2 42

Paper 3 42

Paper 4 43

3 Materials and methods 44 The STORK study 44

The STORK-Placenta study 48

4 Summary of results 51 Paper 1 51

Paper 2 53

Paper 3 53

Paper 4 54

5 Discussion 56 51 Methodological issues STORK 56

52 Data collection STORK 64

53 Methodological issues STORK-Placenta 69

54 Data collection STORK-Placenta 71

55 Interpretation of results 73

6 Conclusions 80

7 Further research 80

8 References 82

Appendix

Papers 1-4

4

Acknowledgements

This work was carried out at Section for Obstetrics Department of Obstetrics and

Gynaecology at Rikshospitalet Oslo University Hospital The thesis has been supported by

grants from the Norwegian Extrafoundation for Health and Rehabilitation through the

Norwegian Health Association

I would like to thank Professor Thomas Aringbyholm as Head of Department for giving me the

opportunity to work at Oslo University Hospital Rikshospitalet where I have received most of

my clinical training My journey into research started with and has been closely linked to

clinical work There are a number of colleagues who have been important role models for me

at various stages of this journey The Section for Obstetrics has an excellent teaching

environment filled with enthusiastic colleagues who constantly share their experience with

younger colleagues My supervisors Tore Henriksen and Bjoslashrg Lorentzen together with Liv

Ellingsen have been my role models in clinical work and their influence has inspired me to

choose the challenging and fascinating field of obstetrics After basic training in obstetrics and

gynaecology I got the opportunity to spend four years combining data collection with clinical

training

This work is based on results from two studies The STORK study is a collaboration between

the Department of Endocrinology and the Department of Obstetrics Thanks to Professor Jens

Bollerslev and the continuous efforts of Kari Kvamsdal Hege H Boslashyum Tove Lekva the

late Gunhild Aker Isaksen Elisabeth Qvigstad and Kristin Godang this projected has

succeeded as an example of research drawing experience across clinical specialities Nanna

Voldner as the first PhD candidate in the study made a huge effort in setting up the study and

I would like to thank her especially Kathrine Frey Froslashslie joined the group as a statistician

She has played an important role by making statistics not just understandable but even

interesting due to her outstanding teaching skills She has also created a great weekly meeting

for all those interested in discussing methodological issues in research We were two PhD

candidates entering the project together Camilla M Friis has been my closest colleague

throughout the years sharing all thoughts and experiences during data collection analyses and

publishing We have had some memorable trips to various conferences Most importantly she

has become a trusted friend and I am confident we will continue our work together hopefully

5

bringing the STORK study forward I would also like to acknowledge our secretaries Rakhee

Sharma and Esther Gangsoslash and all the efforts made by midwives and childrenrsquos nurses

The second study was started during my time as a PhD candidate I would like to thank

anaesthesiologists Eldrid Langesaeligter and Leiv Arne Rosseland both for their contribution in

the project and for their interest in anaesthesia to our obstetric patients in general The study is

now expanding with Trond Melbye Michelsen as a postdoc and several PhD candidates Ane

Moe Holme has been my co-author and with her enthusiastic approach and endless efforts I

am sure the project will continue to grow

My three supervisors have been of great importance and together they have provided me with

all the necessary support to reach the end of this PhD

Guttorm Haugen has shared valuable knowledge in the field of fetal medicine Always

friendly and I am grateful for his accurate and thorough comments which have improved my

work substantially

Bjoslashrg Lorentzen has actively taken part in all parts of my work She has taught me all about

high risk pregnancies and preeclampsia in particular She has collected blood samples at any

time of the day (and night) and spent hours with me in the lab She has always been there to

cheer me up in times of frustration or share moments of joy I have enjoyed her company at

several conferences around the world Her extraordinary clinical skills are valued by all her

patients including myself

Tore Henriksen as my main supervisor has been the source of scientific ideas in both

projects He has the ability to be visionary and to build a larger picture from the small

contributions produced by each independent PhD candidate he has supervised over the years I

am so grateful for the hours he has spent discussing ideas reading my papers and sharing his

experience His is open-minded and always willing to listen to emerging ideas By

questioning surprising findings and not necessarily accepting the conventional view he has

taught me critical thinking and to trust my own judgement which are the most important

lessons I have learnt from this work

We have been several PhD candidates at our department over the years Among them I would

like to thank Anne Helbig for critical questioning and valuable discussions and Julie Holm

Tveit for her warm and caring personality Hilde Skuterud Wik did her PhD in a different

field but nevertheless is a valued friend and colleague

6

Thanks to Oslashystein H Horgmo University of Oslo for making the illustrations used in this

thesis

Last but not least I am grateful for the support of my family My mother has always been

there for me believed in me and showed interest in my work Together with Aase and Per my

parents in law she has helped out when family life and work was challenging to combine

Finally my husband Lars and our three wonderful sons Fredrik Kristian and Magnus are the

most important people in my life You have given me the energy and joy needed to complete

this work

7

List of papers

1 Roland MCP Friis CM Voldner N Godang K Bollerslev J Haugen G and Henriksen T

Fetal growth versus birthweight Placenta versus other determinants

PLoS One 2012 7(6)e39324 doi 101371journalpone0039324

2 Roland MCP Friis CM Godang K Bollerslev J Haugen G and Henriksen T

Maternal factors associated with fetal growth and birth weight are independent determinants

of placental weight and exhibit differential effects by fetal sex

PLoS One 2014 9(2) e87303 doi101371journalpone0087303

3 Holme AM Roland MCP Lorentzen B Michelsen TM and Henriksen T

Human in vivo studies of glucose transfer across the placenta

4 Roland MCP Lorentzen B Godang K and Henriksen T

Uteroplacental arterio-venous difference in soluble VEGFR-1 (sFlt-1) but not in soluble

endoglin concentrations in preeclampsia

Placenta 2012 Mar33 (3)224-6 doi 101016jplacenta201201001

4

Acknowledgements

This work was carried out at Section for Obstetrics Department of Obstetrics and

Gynaecology at Rikshospitalet Oslo University Hospital The thesis has been supported by

grants from the Norwegian Extrafoundation for Health and Rehabilitation through the

Norwegian Health Association

I would like to thank Professor Thomas Aringbyholm as Head of Department for giving me the

opportunity to work at Oslo University Hospital Rikshospitalet where I have received most of

my clinical training My journey into research started with and has been closely linked to

clinical work There are a number of colleagues who have been important role models for me

at various stages of this journey The Section for Obstetrics has an excellent teaching

environment filled with enthusiastic colleagues who constantly share their experience with

younger colleagues My supervisors Tore Henriksen and Bjoslashrg Lorentzen together with Liv

Ellingsen have been my role models in clinical work and their influence has inspired me to

choose the challenging and fascinating field of obstetrics After basic training in obstetrics and

gynaecology I got the opportunity to spend four years combining data collection with clinical

training

This work is based on results from two studies The STORK study is a collaboration between

the Department of Endocrinology and the Department of Obstetrics Thanks to Professor Jens

Bollerslev and the continuous efforts of Kari Kvamsdal Hege H Boslashyum Tove Lekva the

late Gunhild Aker Isaksen Elisabeth Qvigstad and Kristin Godang this projected has

succeeded as an example of research drawing experience across clinical specialities Nanna

Voldner as the first PhD candidate in the study made a huge effort in setting up the study and

I would like to thank her especially Kathrine Frey Froslashslie joined the group as a statistician

She has played an important role by making statistics not just understandable but even

interesting due to her outstanding teaching skills She has also created a great weekly meeting

for all those interested in discussing methodological issues in research We were two PhD

candidates entering the project together Camilla M Friis has been my closest colleague

throughout the years sharing all thoughts and experiences during data collection analyses and

publishing We have had some memorable trips to various conferences Most importantly she

has become a trusted friend and I am confident we will continue our work together hopefully

5

bringing the STORK study forward I would also like to acknowledge our secretaries Rakhee

Sharma and Esther Gangsoslash and all the efforts made by midwives and childrenrsquos nurses

The second study was started during my time as a PhD candidate I would like to thank

anaesthesiologists Eldrid Langesaeligter and Leiv Arne Rosseland both for their contribution in

the project and for their interest in anaesthesia to our obstetric patients in general The study is

now expanding with Trond Melbye Michelsen as a postdoc and several PhD candidates Ane

Moe Holme has been my co-author and with her enthusiastic approach and endless efforts I

am sure the project will continue to grow

My three supervisors have been of great importance and together they have provided me with

all the necessary support to reach the end of this PhD

Guttorm Haugen has shared valuable knowledge in the field of fetal medicine Always

friendly and I am grateful for his accurate and thorough comments which have improved my

work substantially

Bjoslashrg Lorentzen has actively taken part in all parts of my work She has taught me all about

high risk pregnancies and preeclampsia in particular She has collected blood samples at any

time of the day (and night) and spent hours with me in the lab She has always been there to

cheer me up in times of frustration or share moments of joy I have enjoyed her company at

several conferences around the world Her extraordinary clinical skills are valued by all her

patients including myself

Tore Henriksen as my main supervisor has been the source of scientific ideas in both

projects He has the ability to be visionary and to build a larger picture from the small

contributions produced by each independent PhD candidate he has supervised over the years I

am so grateful for the hours he has spent discussing ideas reading my papers and sharing his

experience His is open-minded and always willing to listen to emerging ideas By

questioning surprising findings and not necessarily accepting the conventional view he has

taught me critical thinking and to trust my own judgement which are the most important

lessons I have learnt from this work

We have been several PhD candidates at our department over the years Among them I would

like to thank Anne Helbig for critical questioning and valuable discussions and Julie Holm

Tveit for her warm and caring personality Hilde Skuterud Wik did her PhD in a different

field but nevertheless is a valued friend and colleague

6

Thanks to Oslashystein H Horgmo University of Oslo for making the illustrations used in this

thesis

Last but not least I am grateful for the support of my family My mother has always been

there for me believed in me and showed interest in my work Together with Aase and Per my

parents in law she has helped out when family life and work was challenging to combine

Finally my husband Lars and our three wonderful sons Fredrik Kristian and Magnus are the

most important people in my life You have given me the energy and joy needed to complete

this work

7

List of papers

1 Roland MCP Friis CM Voldner N Godang K Bollerslev J Haugen G and Henriksen T

Fetal growth versus birthweight Placenta versus other determinants

PLoS One 2012 7(6)e39324 doi 101371journalpone0039324

2 Roland MCP Friis CM Godang K Bollerslev J Haugen G and Henriksen T

Maternal factors associated with fetal growth and birth weight are independent determinants

of placental weight and exhibit differential effects by fetal sex

PLoS One 2014 9(2) e87303 doi101371journalpone0087303

3 Holme AM Roland MCP Lorentzen B Michelsen TM and Henriksen T

Human in vivo studies of glucose transfer across the placenta

4 Roland MCP Lorentzen B Godang K and Henriksen T

Uteroplacental arterio-venous difference in soluble VEGFR-1 (sFlt-1) but not in soluble

endoglin concentrations in preeclampsia

Placenta 2012 Mar33 (3)224-6 doi 101016jplacenta201201001

5

bringing the STORK study forward I would also like to acknowledge our secretaries Rakhee

Sharma and Esther Gangsoslash and all the efforts made by midwives and childrenrsquos nurses

The second study was started during my time as a PhD candidate I would like to thank

anaesthesiologists Eldrid Langesaeligter and Leiv Arne Rosseland both for their contribution in

the project and for their interest in anaesthesia to our obstetric patients in general The study is

now expanding with Trond Melbye Michelsen as a postdoc and several PhD candidates Ane

Moe Holme has been my co-author and with her enthusiastic approach and endless efforts I

am sure the project will continue to grow

My three supervisors have been of great importance and together they have provided me with

all the necessary support to reach the end of this PhD

Guttorm Haugen has shared valuable knowledge in the field of fetal medicine Always

friendly and I am grateful for his accurate and thorough comments which have improved my

work substantially

Bjoslashrg Lorentzen has actively taken part in all parts of my work She has taught me all about

high risk pregnancies and preeclampsia in particular She has collected blood samples at any

time of the day (and night) and spent hours with me in the lab She has always been there to

cheer me up in times of frustration or share moments of joy I have enjoyed her company at

several conferences around the world Her extraordinary clinical skills are valued by all her

patients including myself

Tore Henriksen as my main supervisor has been the source of scientific ideas in both

projects He has the ability to be visionary and to build a larger picture from the small

contributions produced by each independent PhD candidate he has supervised over the years I

am so grateful for the hours he has spent discussing ideas reading my papers and sharing his

experience His is open-minded and always willing to listen to emerging ideas By

questioning surprising findings and not necessarily accepting the conventional view he has

taught me critical thinking and to trust my own judgement which are the most important

lessons I have learnt from this work

We have been several PhD candidates at our department over the years Among them I would

like to thank Anne Helbig for critical questioning and valuable discussions and Julie Holm

Tveit for her warm and caring personality Hilde Skuterud Wik did her PhD in a different

field but nevertheless is a valued friend and colleague

6

Thanks to Oslashystein H Horgmo University of Oslo for making the illustrations used in this

thesis

Last but not least I am grateful for the support of my family My mother has always been

there for me believed in me and showed interest in my work Together with Aase and Per my

parents in law she has helped out when family life and work was challenging to combine

Finally my husband Lars and our three wonderful sons Fredrik Kristian and Magnus are the

most important people in my life You have given me the energy and joy needed to complete

this work

7

List of papers

1 Roland MCP Friis CM Voldner N Godang K Bollerslev J Haugen G and Henriksen T

Fetal growth versus birthweight Placenta versus other determinants

PLoS One 2012 7(6)e39324 doi 101371journalpone0039324

2 Roland MCP Friis CM Godang K Bollerslev J Haugen G and Henriksen T

Maternal factors associated with fetal growth and birth weight are independent determinants

of placental weight and exhibit differential effects by fetal sex

PLoS One 2014 9(2) e87303 doi101371journalpone0087303

3 Holme AM Roland MCP Lorentzen B Michelsen TM and Henriksen T

Human in vivo studies of glucose transfer across the placenta

4 Roland MCP Lorentzen B Godang K and Henriksen T

Uteroplacental arterio-venous difference in soluble VEGFR-1 (sFlt-1) but not in soluble

endoglin concentrations in preeclampsia

Placenta 2012 Mar33 (3)224-6 doi 101016jplacenta201201001

6

Thanks to Oslashystein H Horgmo University of Oslo for making the illustrations used in this

thesis

Last but not least I am grateful for the support of my family My mother has always been

there for me believed in me and showed interest in my work Together with Aase and Per my

parents in law she has helped out when family life and work was challenging to combine

Finally my husband Lars and our three wonderful sons Fredrik Kristian and Magnus are the

most important people in my life You have given me the energy and joy needed to complete

this work

7

List of papers

1 Roland MCP Friis CM Voldner N Godang K Bollerslev J Haugen G and Henriksen T

Fetal growth versus birthweight Placenta versus other determinants

PLoS One 2012 7(6)e39324 doi 101371journalpone0039324

2 Roland MCP Friis CM Godang K Bollerslev J Haugen G and Henriksen T

Maternal factors associated with fetal growth and birth weight are independent determinants

of placental weight and exhibit differential effects by fetal sex

PLoS One 2014 9(2) e87303 doi101371journalpone0087303

3 Holme AM Roland MCP Lorentzen B Michelsen TM and Henriksen T

Human in vivo studies of glucose transfer across the placenta

4 Roland MCP Lorentzen B Godang K and Henriksen T

Uteroplacental arterio-venous difference in soluble VEGFR-1 (sFlt-1) but not in soluble

endoglin concentrations in preeclampsia

Placenta 2012 Mar33 (3)224-6 doi 101016jplacenta201201001

7

List of papers

1 Roland MCP Friis CM Voldner N Godang K Bollerslev J Haugen G and Henriksen T

Fetal growth versus birthweight Placenta versus other determinants

PLoS One 2012 7(6)e39324 doi 101371journalpone0039324

2 Roland MCP Friis CM Godang K Bollerslev J Haugen G and Henriksen T

Maternal factors associated with fetal growth and birth weight are independent determinants

of placental weight and exhibit differential effects by fetal sex

PLoS One 2014 9(2) e87303 doi101371journalpone0087303

3 Holme AM Roland MCP Lorentzen B Michelsen TM and Henriksen T

Human in vivo studies of glucose transfer across the placenta

4 Roland MCP Lorentzen B Godang K and Henriksen T

Uteroplacental arterio-venous difference in soluble VEGFR-1 (sFlt-1) but not in soluble

endoglin concentrations in preeclampsia

Placenta 2012 Mar33 (3)224-6 doi 101016jplacenta201201001

8

Abbreviations

AC abdominal circumference

ACOG American College of Obstetrics and Gynecology

AGA appropriate for gestational age

BAT brown adipose tissue

BM fetal-facing basal membrane

BMI body mass index

DIC disseminated intravascular coagulation

DXA dual x-ray absorptiometry

EDTA ethylenediaminetetraacetic acid

ELISA enzyme-linked immunosorbant assay

FFA free fatty acids

FL femur length

FSH follicular stimulating hormone

GLUT glucose transporter protein

GWG gestational weight gain

HC head circumference

HAPO Hyperglycemia and Adverse Outcomes in Pregnancy

HCG human chorionic gonadotropin

HELLP hemolysis elevated liver enzymes low platelets

HPL human placental lactogen

IQR inter quartile range

IUGR intrauterine growth restriction

LDL low density lipoprotein

LGA large for gestational age

LH luteinizing hormone

MBR Medical Birth Registry

mRNA messenger RNA

MVM maternal-facing microvillous membrane

NEFA non-esterified fatty acids

OGTT oral glucose tolerance test

PE preeclampsia

PI ponderal index

9

PGH placental growth hormone

PlGF placental growth factor

RCT randomized controlled trial

SD standard deviation

sEng soluble Endoglin

sFlt-1 soluble Flt-1

SGA small for gestational age

STORK store barn og svangerskapskomplikasjoner

TG triglycerides

TGF-β transforming growth factor β

TSH thyroid stimulation hormone

VEGF vascular endothelial growth factor

VEGFR-1 vascular endothelial factor receptor -1

VEGFR-2 vascular endothelial factor receptor -2

VLDL very low density lipoprotein

WAT white adipose tissue

WHO World Health Organization

10

1 Introduction

11 Summary

The STORK study was initiated to address the observed increase in proportions of large

babies in Norway and the growing acknowledgement that birthweight and fetal growth have

consequences for health and disease both in short and long term In Norway the proportion of

babies with high birthweightmacrosomia (gt4000 g) increased from approximately 17 in

1990 to 22 around the year 2000 after which the proportion has returned to 17 in 2008

[1] The STORK study was designed to study maternal risk factors for macrosomia as

reflected in the acronym STORK rdquostore barn og komplikasjonerrdquo which translates into large

babies and complications The name of the study reflects the original research questions

asked when the study was planned The cohort consists of two periods referred to as STORK

1 (2001-2005) and STORK 2 (2005-2008) The cohort was extended to STORK 2 in order to

address wider research questions The outcome was expanded to include not only birthweight

but intrauterine growth and body composition at birth Placenta is central in determining the

nutritional and endocrinological conditions for fetal growth and development Virtually no

compound reaches the fetus without passing the placenta We therefore first included

placental weight in the analyses of the STORK data with an underlying assumption that

placental size to some extent reflects functional capacity During these analyses placental

weight emerged as a determinant of fetal growth parameters These observations led us to

initiate studies on functional aspects of placenta and we decided to establish an in vivo model

in the human (the STORK-Placenta study)

Two approaches were chosen in this study

1 To study nutrient transport

2 To investigate placental factors in pathological pregnancies like preeclampsia

Preeclampsia is a leading cause of mortality and morbidity in obstetrics and a condition in

which the placenta is thought to play a major pathophysiological role Importantly a

prominent feature of preeclampsia is placental insufficiency and fetal growth restriction

11

2001 2005 2008

STORK 1 STORK 2

birthweight

fetal growth

body composition ( fat)

maternal characteristics

placental aspects

Camilla M Friis

Kathrine Frey Froslashslie

Marie Cecilie Paasche Roland

Inclusion

period

Timeline for the STORK and STORK-Placenta project

STORK-Placenta

2013

Outcome

Determinants

PhD candidate

birthweight gt 4200 g

maternal characteristics

Nanna Voldner

placental functions

glucose transport across placenta

anti-angiogenic factors

Marie Cecilie Paasche Roland

Ane Moe Holme

This thesis consists of four papers of which Paper 1 and Paper 2 are based on the STORK

study and Paper 3 and Paper 4 are based on the STORK-Placenta Study

12

In Paper 1 we studied how maternal factors were associated with birthweight and intrauterine

fetal growth For the reasons indicated above we included placental weight as a determinant

of birthweight and fetal growth

Paper 1

-parity

-BMI

-GWG

-glucose

Given the importance of placental weight on birthweight and fetal growth we then wanted to

study placental weight in Paper 2 We studied the influence of maternal factors on placental

weight and whether these associations differed with fetal sex

Paper 2

-parity

-BMI

-GWG

-glucose

13

In Paper 3 we reported initial studies of transfer of glucose across the human placenta and

how maternal and fetal glucose and insulin levels were related

Paper 3

Glucose and insulin

In Paper 4 the role of placenta in producing pathogenic factors of preeclampsia was

investigated choosing anti-angiogenic factors because of their endothelial-disturbing

properties

Paper 4

Anti-angiogenic

factors

14

12 Background

Fetal growth has implications for the newborn child both in short and long term The link

between events in early life and risk of disease in later life is now a widely recognized field of

research known as developmental programming and often called Developmental Origins of

Health and Disease Developmental programming refers to how an event at a critical or

sensitive period results in a long-term change in the structure or function of the organism

[23] Organs and systems in the human body are sensitive to the environment in certain

periods The critical periods are mainly those characterized by rapid growth and maturation

and for most organs and systems this happens to a large extent in utero

The idea of linking events in early life to later risk of disease is however not new The

association between poor living conditions in childhood and increased risk of cardiovascular

disease was observed by Anders Forsdahl who worked as a physician in Finnmark Northern

Norway in the 1970s He found a positive correlation between infant mortality which was

considered to be an index of standard of living and mortality from arteriosclerotic heart

disease as well as cholesterol values [45]

The link between early life events and later disease received more publicity when the late

David Barker introduced what is commonly referred to as the rdquoBarker hypothesisrdquo He was

probably the most acknowledged scientist in this field and established an association between

birthweight and increased risk of cardiovascular disease insulin resistance and type 2 diabetes

mellitus [6ndash8] His work has been followed by a range of publications that have not only

confirmed these associations but also provided mechanistic insight into the link between

intrauterine growth and increased risk of disease A large body of evidence have shown that

structural or functional changes that last throughout life can result from nutritional factors in

utero [2] Extensive work on animal models has demonstrated how dietary changes affect fetal

growth and lead to functional and structural changes The availability of nutrients to the fetus

is influenced not only by the motherrsquos diet during pregnancy but by maternal nutrient stores

and metabolism The placenta has multiple roles in fetal nutrition by its capacity to transport

nutrients from the maternal to the fetal circulation by its own metabolic demand for nutrients

and by producing hormones which influence fetal and maternal nutritional supply [9]

15

13 Fetal growth

Fetal growth comprises the entire process of differentiation maturation and development that

occurs between conception and birth This process starts with the fusion of two cells and ends

up with an estimated 50-100 trillion cells in the newborn child The terminology used to

describe and evaluate fetal growth is complex and the terms need to be defined First there is

a need to draw a distinction between size at birth and intrauterine growth Secondly the

difference between size which is most commonly measured as weight and body composition

must be addressed

131 Size at birth

Birthweight

Size at birth is routinely measured as birthweight (grams or kg) Birthweight is a summary

measure of fetal growth throughout pregnancy Categories based on birthweight are used both

in clinical settings and for research Low birthweight is generally defined as birthweight

lt 2500 grams whereas a definition for high birthweight (macrosomia) is more arbitrary Both

4000 4200 and 4500 grams have been used as cut-off values in various settings [1011]

Birthweight for gestational age

Birthweight as a function of gestational age gives information of size relative to expected size

for a particular gestational age Birthweight for gestational age can be given as a percentile

between 0 and 100 Birthweight for gestational age can also be categorized and the most

commonly used categories are large for gestational age (LGA) appropriate for gestational age

(AGA) and small for gestational age (SGA) The conventional cut-off percentiles for these

categories are given beneath

Population based charts for birthweight are often based on large samples including both low-

risk and high-risk pregnancies representing the underlying population On the other hand a

so-called standard chart is usually based on low-risk pregnancies with a normal outcome [12]

Furthermore customized charts have been made to accommodate for differences in eg

ethnicity parity age and BMI in individual patients Such charts have been developed for

different populations and there are electronically available charts [13]

16

Body composition

In addition to weight of the newborn baby length and head circumference give some

information about the body composition of the newborn Further evaluation of body

composition can be derived from these measurements The Ponderal Index (PI) is calculated

as a relationship between mass and height as is the body mass index (BMI) but the mass is

normalized with the third power of body height

Because it yields valid results even for very short (and very tall) persons it is more suitable

in pediatrics than BMI [14] Body composition can further be assessed by measuring

circumference of the abdomen and the extremities or by skin fold thickness measurements by

calipers to obtain an estimation of fat distribution [15] There are other methods that are either

expensive or difficult to perform on newborns Dual energy x -ray absorptiometry (DXA)

enables an estimation of bone mass fat mass and fat free (lean) mass A reasonable good

correlation between estimated fat mass by DXA and skin fold thickness measured by calipers

has been shown [16]

Categories Cut-offs

SGA lt 10 p

AGA 10-90 p

LGA gt 90 p

PI

= weight (g)

[height (cm)]3

17

132 Intrauterine growth

Fetal growth is a continuous process that starts at conception and ends at birth but is

commonly measured as just the end result which is size at birth However the distinction

between size and growth applies also to the intrauterine period Fetal size is estimated based

on a single observation or measurement whereas estimation of fetal growth requires at least

two measurements

Symphysis-fundus height

Palpation of the abdomen and measuring the symphysis-fundal height is used to estimate

intrauterine growth in low-risk pregnancies Reference curves for the symphysis-fundus

height to assess fetal growth have recently been updated in Scandinavia [17]

Ultrasound measurements

Estimation of fetal size

Estimation of fetal size by ultrasound combines measurements of the fetus and transforms

these measurements into volume and weight to estimate fetal size There are a number of

equations that use combinations of circumferences andor diameters and combinations of

measurements of head and abdominal size andor femural length to estimate fetal size The

equations differ in their ability to predict fetal size but generally perform more accurately in

predicting average fetal sizes than at the extremes of birthweight [18]

Estimation of fetal growth and fetal growth charts

To estimate fetal growth two or more measurements separated in time are needed and the rate

of growth can be assessed by using fetal growth charts There are a multitude of charts

available that are constructed by different methods and from different populations Fetal

growth charts can be derived from cross-sectional or longitudinal data In cross-sectional

charts each pregnant woman contributes with data from one observation whereas longitudinal

studies have repeated measurements from each participant The longitudinal studies provide

better references for fetal growth [12]

18

The ambiguous terminology

The lack of distinction between fetal size and fetal growth complicates the terminology Small

for gestational age (SGA) is often defined as birthweight lt 10 p The term intrauterine growth

restriction (IUGR) is often used interchangeably with SGA IUGR more strictly is used as a

term for true intrauterine growth restriction based on data that shows a decline in intrauterine

growth over time assessed by ultrasound There are however no universally accepted

definition of how much decline in fetal growth that would define IUGR although some

authors have defined IUGR as either a fall in fetometric percentiles or a combination of fall in

percentiles and low birthweight [19] On the same note accelerated fetal growth can be seen

during intrauterine life and may or may not result in a LGA newborn

Figure 1 Schematic overview of categories of fetal growth

growth

restrictionexcessive

growth

AGASGA LGA

19

14 Maternal aspects of fetal growth

141 Maternal nutritional status

Maternal nutritional status is vital for fetal growth as the fetus is dependent on nutrients being

transported from the maternal circulation across the placenta to the fetal circulation The

nutritional status of the mother is generally assessed by indirect means of which Body Mass

Index is a commonly used measurement

Body Mass Index (BMI)

BMI is calculated from a persons weight and height according to the following equation

BMI is used as a surrogate for body fat and has been shown to correlate to direct measures of

body fat such as underwater weighing and dual energy x-ray absorptiometry (DXA) [20]

Although the correlation between BMI and body fatness is fairly strong the correlation varies

by sex race and age At the same BMI women tend to have more body fat than men At the

same BMI older people tend to have more body fat than younger adults Highly trained

athletes may have a high BMI because of increased muscularity rather than increased body

fatness [21] In pregnancy the correlation between BMI and percent body fat is better in early

gestation than in late gestation [22]

The World Health Organisation (WHO) classifies BMI for adults in the following groups [23]

BMI

weight (kg)

[height (m)]2

BMI Weight Status

Below 185 Underweight

185 ndash 249 Normal

250 ndash 299 Overweight

300 and above Obese

20

For adults BMI is interpreted using standard weight status categories that are the same for all

ages and for both men and women For children and adolescents on the other hand the

interpretation of BMI is both age- and sex-specific [24]

Biological effects of high BMI

BMI is used as a surrogate for body fat which is made up of adipose tissue Adipose tissue can

be classified as white adipose tissue (WAT) and brown adipose tissue WAT is excess energy

stored as triglycerides in adipocytes which secrete a variety of substances including

hormones (eg leptin adiponectin and resistin) as well as inflammatory factors [25] Brown

adipose tissue is thought to have a function in thermo genesis Excess adipose tissue can be

estimated by anthropometric measures such as skin fold thickness measured by calipers [26]

Consequences of BMI for pregnancy and labour

Prepregnancy BMI is a major determinant of pregnancy outcome and increasing BMI is

associated with an increased risk of the majority of pregnancy complications like congenital

abnormalities miscarriages gestational diabetes preeclampsia obstructed labour and

operative deliveries [27] Low prepregnancy BMI is associated with low birthweight and

IUGR [28]

Gestational weight gain (GWG)

Gestational weight gain in pregnancy includes growth of the fetus placenta and uterus

increase in maternal plasma volume and accumulation of maternal fat mass [29] The total

amount of weight gained during pregnancy varies considerably among women and lean

women tend to accumulate more fat than obese women [30] Accumulation of fat is primarily

centrally and represents a combination of subcutaneous fat and visceral fat Visceral fat

correlates with metabolic risk factors like hypertension insulin sensitivity and plasma lipids

[31] The ideal gestational weight gain differs depending on the maternal or neonatal outcome

of interest Recommendations for gestational weight gain were revised by the Institute of

Medicine USA in 2009 and highlights both that women should be within a normal BMI range

when they conceive and gain weight within the ranges recommended The recommended

21

weight gain is based on four categories of prepregnancy BMI Higher categories of

prepregnancy BMI are recommended a lower weight gain [29]

Consequences of gestational weight gain

Gestational weight gain has consequences for both mother and child in the short and long

term Low GWG is associated with low birthweight and IUGR [32] and high GWG is

associated with macrosomia and increased neonatal fat mass [3334] High GWG is

associated with increased risk of pregnancy complications like preeclampsia and diabetes [35]

Restricted GWG in obese women with type 2 diabetes has been shown to influence fetal

growth [36] There are reports on associations between GWG and cesarean section

instrumental deliveries and low Apgar scores but it has been suggested that the effects are

mediated by high birthweight [35] The most consistent adverse outcome for mothers with

large GWG is weight retention post-partum [35]

BMI Weight Status Recommended Gestational

Weight Gain

Below 185 Underweight 13-18 kg

185 ndash 249 Normal 11-16 kg

250 ndash 299 Overweight 7-11 kg

300 and above Obese 5-9 kg

22

142 Maternal metabolism

As the fetus is dependent on nutrients from the maternal circulation not only the maternal

intake of nutrients but also the maternal metabolism plays a major role in fetal nutrition There

are adaptations to maternal metabolism that occur during pregnancy to ensure that the

increasing nutritional demands of the mother the placenta and the fetus are met Adaptations

are made in the metabolism of all major groups of nutrients

Glucose metabolism in pregnancy

The human fetus is highly dependent on glucose derived from the maternal circulation for

growth and development [2] Changes occur in the maternal glucose metabolism during

pregnancy to ensure that the increasing nutritional demands of the mother the placenta and

the fetus are met Previously published data on glucose metabolism suggested a decrease in

fasting glucose with gestation [37] Fasting glucose levels of pregnant women have been

shown to decline in early pregnancy and thereafter not decrease much further [38] In our

cohort we found fasting glucose to increase slightly with gestational age [39] There is an

increase in basal hepatic glucose production by up to 30 with increasing gestational age

[37] The insulin sensitivity shows a marked change in pregnancy Overall insulin sensitivity

decreases during pregnancy and in late pregnancy a reduction of 50-70 is estimated

compared with non-pregnant women [40] Insulin secretion increases by up to 200-250

[40]

Lipid and amino acid metabolism in pregnancy

The lipid metabolism in pregnancy is characterized by a marked hyperlipidemia Triglyceride

concentration increases and in particular very low-density lipoprotein (VLDL) triglyceride

concentration which increases 3-fold from week 14 to term Plasma cholesterol levels rise to

a lesser degree In obese women the hyperlipidemia is further exaggerated [27] There is an

overall increase in protein synthesis in pregnancy This includes maternal tissues like breasts

uterus and the liver as well as the fetus and the placenta [27]

23

143 Other maternal factors

Age and parity

Both maternal age and parity have an effect on fetal growth Young women especially

adolescents give birth to smaller newborns than older women [41] Birthweight increases with

maternal age until the 30s after which there is a decline resulting an inverse u-shaped curve

[42] Age is however closely linked to parity Birthweight increases with parity and the

largest increment of approximately 200 grams is between the first and second child [43] In

multiple models birth order exerted a greater influence on birthweight than maternal age [42]

The biological explanation behind these associations is only partly understood The effect of

parity may be partly explained by the capacity of the spiral arteries to expand which is higher

in the subsequent pregnancies than in the first pregnancy [44]

Maternal blood supply to the uterus

The uterus receives blood mainly from the uterine arteries which are branches of the internal

iliac artery The uterine arteries branch into thinner vessels first the arcuate arteries then the

radial arteries followed by the basal arteries which continue into the endometrium as the

spiral arteries The spiral arteries undergo remodeling in early pregnancy which means they

loose smooth muscle and elastic tissue from their walls This remodeling of maternal vessels

is a key aspect of early pregnancy and vital for a successful outcome Ultrasound studies have

estimated both the changes in diameters of the uterine artery and the blood flow velocity in

these vessels Several studies have reported that the diameter of the uterine artery increases

approximately 3-4 fold from non-pregnant state to term [4546] The flow velocity increases

with gestational age but reported values differ somewhat depending on whether the

measurements are made on one or both uterine arteries and the laterality of the placenta

[4546] The fraction of the cardiac output that is distributed to the uterus has been estimated

to be 35 in early pregnancy and near 12 at term [46]

24

Figure 2 Blood supply to the uterus

From Grayrsquos Anatomy 20th US edition electronically retrieved from Wikimedia commons

25

15 Placental aspects of fetal growth

151 Development structure and growth of the placenta

Normal placental development and maternal adaptation to pregnancy are crucial factors for a

successful pregnancy The placentation process and maternal adaptation are closely linked and

happen as parallel processes ensuring a healthy outcome for both mother and child Many

complications of pregnancy can be ascribed to defects in early placentation andor inadequate

maternal adaptation to pregnancy Therefore knowledge of these processes is essential in

understanding the pathophysiology of pregnancy complications

The development of the placenta begins as soon as the conceptus reaches the uterus on day 3-

4 after fertilisation By this stage the blastocyst has an outer wall and an inner cell mass The

outer wall consists of trophoblast cells which undergo transformation to either fuse into a

syncytial cell layer or form individual cytotrophoblasts Extra villous trophoblasts are named

so because of their location in the maternal endometrial (decidual) tissue and play an

important role by starting the trophoblast invasion and the adaptation of the maternal vessels

to pregnancy During this process the endometrial stromal cells differentiate into decidual

cells The extra villous trophoblasts migrate through the decidua basalis and into the inner

third of the myometrium aided by a range of proteases that degrade or remodel the maternal

extra cellular matrix

The amnion arises from the inner cell mass and makes contact with the chorion by early

second trimester Lacunae are formed within the syncytiotrophoblast and the lacunar system is

transformed into the intervillous space

The majority of the villous mass forms the placenta whereas the remainder of the villous

tissue begins to regress resulting in the chorion This remodeling ensures that rupture of

membranes and delivering of the baby can occur at birth without tearing through the placenta

This remodeling occurs at the same time as the maternal blood flow starts in the periphery of

the developing placenta

26

Figure 3 The structure of placenta

From Grayrsquos Anatomy 20th US edition electronically retrieved from Wikimedia commons

The villous mass is made up of a tree of branching villi The branches are classified according

to caliber position within the villous tree and function and goes from the larger stem villi via

intermediate villi to the thinner and distal terminal villi In a mature normal placenta stem

villi account for 20-25 intermediate villi approximately 25 and terminal villi around 40

of the total villous volume The maternal-fetal exchange takes place primarily at the

terminal villi and to some extent at the intermediate villi [47]

Figure 4 Terminal villi

Illustration by Oslashystein H Horgmo University of Oslo

27

Figure 5 Development of the placenta

Fertilized egg

blastocyst

Trophoblast

Cytotrophoblasts

Syncytiotrophoblasts

Extravillous

Villous

Inner cell mass

Fetus

Amnion

Yolk sac

-Primary villi

-Secondary villi

-Tertiary villi

-mesenchymal villi

-immature intermediate villi

-stem villi

-mature intermediate villi

-terminal villi

Matu

ratio

n

ofvilli

Angiogenesis

Transformation of

spiral arteries

Placental villi

Modified after Bernischke et al Pathology of the Human Placenta 2012

The syncytiotrophoblast layer covers a surface area of 12-14 m2

at term [48] It is covered by

microvilli which increase the surface area by a factor of five- to seven The

syncytiotrophoblast layer is comprised by two membranes the maternal-facing microvillous

membrane (MVM) and the fetal-facing basal membrane (BM) The syncytiotrophoblasts act

as an epithelium and contain high densities of transporter proteins There are transport

proteins for the major groups of nutrients Glucose transport proteins belonging to the GLUT

family transport glucose across the placenta by facilitated diffusion [49] Amino acids are

transported by transporter proteins by an active process [50] Lipids are mainly transported as

free fatty acids (FFA) by simple diffusion or by specific binding proteins [5152] Transporter

proteins for micronutrients and drug transporters involved in the transport of drugs have also

been identified [5354] The syncytiotrophoblast also transport ions and solutes to maintain

membrane potential and cell volume regulation

28

Figure 6 The syncytiothrophoblast cell

Modified by Oslashystein H Horgmo after SLager J Pregnancy 2012

Growth of the placenta

The placenta grows close to linearly throughout pregnancy [5556] Cytotrophoblast cells fuse

continuously to maintain and expand the syncytiotrophoblast layer Little is known regarding

the control of this coordinated sequence of events After around 32 weeks of gestation the

fetal capillaries and syncytiotrophoblast layer come closer as the syncytiotrophoblast becomes

thinner and free of nuclei and most organelles This thinning of the membrane separating the

maternal and fetal circulations aids gaseous exchange and the membrane is known as the

rdquovasculosyncytial membranerdquo [47] The volume of the terminal villi and hence the surface

area increases exponentially throughout pregnancy a process that appears to be dependent on

branching of the villi and angiogenesis [57] Although the villous tree undergoes continuous

growth and differentiation during pregnancy relatively little is known about the regulation of

this process Maternal factors like prepregnancy BMI and GWG have been shown to be

associated with placental growth measured both as placental weight thickness and area [58]

Little is known about fetal factors that may affect placental growth Studies in mice do

however indicate that the fetus itself influences the functional properties of placenta [59]

29

152 Placental functions

The placenta has a range of important functions to ensure a successful pregnancy outcome

including transport of nutrients and gases metabolism and endocrine and protective

functions

Transport of nutrients and gases

a Transport of gases

Oxygen provided by the maternal blood is transferred to the fetal circulation by diffusion

Carbon dioxide and other waste products are removed from the fetus and transported to the

mother by the placenta [9] Chronic exposure during pregnancy to hypoxia as seen at high

altitudes is associated with reduced fetal growth [60] However comparisons of fetal oxygen

extraction between pregnant women at high altitude (3600 m) and sea level (400 m) showed

that the fetus had the ability to adapt and to increase oxygen extraction [60] Studies on

pregnant sheep in vivo showed the O2 consumption per kg of the fetus to be twice that of an

adult and the uteroplacental tissues to consume four-fivefold that of the fetus [61]

b Transport of nutrients

Glucose

Glucose is the primary energy source for the fetus As the fetus to a very limited degree

produces its own glucose the fetus needs to obtain glucose from the maternal circulation

Glucose is transported from the maternal circulation across the syncytiotrophoblasts of the

placenta by facilitated diffusion [49] The syncytiotrophoblast is the main barrier in the human

placenta and is comprised by two cell membranes the maternal-facing microvillous

membrane (MVM) and the fetal-facing basal membrane (BM) The glucose transporters found

in the human placenta belong to the GLUT-family of which there are multiple isoforms The

GLUT 1 is the predominant transport protein in the human placenta at term and is found in

higher concentration on the microvillous membrane than the basal membrane [49] Glucose

transport across the endothelial layer is not well studied

30

The maternal-fetal glucose transfer depends on several factors

Glucose supply Glucose supply is determined by both maternal blood glucose

concentration and blood flow to the placenta

Placental glucose metabolism The placenta not only transfers glucose to the fetus but

consumes considerable amounts of glucose itself Insight into the placental glucose

transfer and metabolism is largely based on data from animal studies in particular on

pregnant sheep Placental glucose consumption is normally very high Estimates

suggest that the placenta consumes about 50 of the glucose extracted from the

maternal circulation [62] Placental glucose metabolism can be altered as a result of

alterations in the supply of other energy-generating substrates like oxygen Hypoxic

conditions has been suggested to increase glucose consumption in the placenta thus

making less glucose available to the fetus [63]

The total surface area of the membranes

Placental glucose transporter density and functions [64]

Maternal-fetal glucose gradient The maternal glucose concentration is higher than the

fetal concentration which creates a maternal-fetal gradient This gradient is thought to

be the driving force for the transfer of glucose from the mother to the fetus The

maternal and fetal glucose concentrations are closely related [65ndash67] The gradient

increases with gestation and so does the placental transport capacity Together this

ensures that placental glucose transfer to the fetus is increased which is needed to meet

the increasing needs of the growing fetus A lower fetal glucose concentration leads to

a larger maternal-fetal glucose concentration gradient which increases transfer of

glucose to the fetus In IUGR fetuses the glucose level is lower which creates a larger

gradient and hence increases the transfer of glucose [66] The regulation of fetal

glucose utilization in humans is only partially understood but has been studied in

more detail in pregnant sheep In sheep the rate of fetal glucose utilization depends on

the interaction between fetal plasma glucose and insulin concentrations and the supply

of glucose to the fetus [61] Fetal glucose uptake seems to be regulated by fetal glucose

concentration rather than maternal supply [68]

Insulin Maternal insulin is not transferred across the placenta The major glucose

transport protein in the human placenta at term is GLUT 1 which does not have

insulin receptors [64] The fetal pancreas develops in the first half of pregnancy and

31

sheep experiments have shown that by mid-gestation measurable insulin is produced

[69] Fetal insulin secretion consists of both basal secretion and glucose-stimulated

secretion Studies on pregnant sheep have revealed that both basal and glucose-

stimulated insulin secretion increases over gestation and responds to changes in fetal

glucose concentration as well as duration and pattern of change Chronic marked

hyperglycemia in sheep gave down-regulation of both glucose-stimulated and basal

insulin secretion whereas pulsatile hyperglycemia increased fetal insulin secretion

[7071] Hypoglycemia has been shown to decrease basal- and glucose-induced insulin

secretion [72] Insulin is an important growth hormone in utero and deficiency of

insulin leads to growth restriction in the fetus Fetal hyperinsulinaemia leads to

increased weight gain particularly in species with a high body fat content at birth like

the humans [73] The mechanism in which insulin stimulates fetal growth is in part

thought to be its anabolic effects on glucose and amino acid metabolism through

increased cellular uptake of glucose that maximizes the transplacental concentration

gradient for glucose and hence increases transport of glucose across the placenta

Lipids

Fatty acids are necessary for the fetus for various purposes as a source of energy as elements

of cellular membranes and for development of tissues and organs Maternal triglycerides (TG)

have been suggested as a more important source of fatty acids than nonsesterified fatty acids

(NEFAs) TG are hydrolyzed by placental lipases (lipoprotein lipase) to free fatty acids which

can diffuse freely across the placenta or be taken up by the placenta via fatty acid transport

proteins [51] Total levels of fatty acids are lower in the fetal than the maternal circulation but

the fatty acid profile is different with higher proportions of long chain polyunsaturated fatty

acids [9]

Amino acids

Fetal plasma amino acid concentrations are higher than maternal concentrations Amino acids

are taken up against a concentration gradient by secondary active transport systems in the

MVM More than 20 amino acid transport systems are expressed in the human placenta [74]

These are categorized as heterodimeric (eg system L) or monomeric (eg system A) Amino

32

acids are required by the fetus for protein synthesis but can also be metabolized by the fetus

[9] Reduced fetal plasma concentration of a number of amino acids have been reported in

studies of IUGR [75]

c Endocrine functions

The placenta metabolizes a number of substances and releases metabolic products into the

maternal andor fetal circulations The placenta thus has endocrine paracrine and autocrine

functions There are numerous hormones that are produced by the placenta in order to

maintain and regulate pregnancy [9]

Estrogen

Estrogens are produced by the syncytiotrophoblasts in large amounts during pregnancy 80-

90 of the the steroids produced in the placenta are secreted into the maternal blood The

fetus is the main source of the precursors used for production of estrogens and they are

produced in the fetal adrenal gland and the fetal liver [76] The estrogens act as specialized

growth hormones for the reproductive organs of the mother [9]

Progesterone

Progesterone is produced by the corpus luteum in the first weeks of pregnancy and later by

the trophoblasts in the placenta The plasma levels increase throughout pregnancy

Progesterone is synthesized largely from maternal plasma low density lipoprotein (LDL)

cholesterol The fetus contributes few or no precursors for progesterone synthesis In normal

pregnancy there is little de novo synthesis of progesterone in the fetus The progesterone

preferentially enter the maternal circulation and very little crosses to the fetus [76]

Progesterone inhibits uterine contractions

Human Chorionic Gonadotropin (HCG)

HCG is a glycoprotein which is structurally similar to Luteinizing Hormone (LH) Follicle

Stimulating Hormone (FSH) and Thyroid Stimulating Hormone (TSH) and is mainly

33

synthesized in the syncytiotrophoblasts HCG enters the maternal circulation at the time of

implantation and is detectable in maternal plasma and urine The concentration peeks at week

8-10 of pregnancy after which it declines The biological function is believed to be

maintenance of the corpus luteum stimulation of fetal testicular testosterone secretion and

stimulation of the maternal thyroid gland [76]

Human Placental Lactogen (HPL)

HPL is a polypeptide which is structurally similar to human growth hormone and human

prolactin It is mainly produced by the syncytiotrophoblasts It is detectable in the maternal

circulation by week 5 and rises steadily and approximately proportional to placental mass

until week 34-36 There is little HPL detectable in maternal urine or in fetal plasma HPL

participates in metabolic processes by stimulating lipolysis HPL thereby functions primarily

to ensure nutrient supply to the fetus by efficient mobilization of maternal tissue stores [76]

34

16 Sexual dimorphism in fetal growth and placental function

There are well-known sex specific differences in fetal growth Birthweight of boys is

generally higher than that of girls Body composition also differs boys being longer and

having larger head circumference than girls whereas girls have higher fat percentage than

boys [16] Fetal-placental weight ratio is greater in boys than in girls indicating a higher

placental efficiency among boys [77] Male fetuses grow faster than girls in utero and one

study reported that the difference was statistically different from week 28 onwards [78] Boys

outnumber girls at birth A study from the Norwegian Birth Registry (MBR) found a ratio of

106 among all births This ratio was higher among births in lower gestational age groups as

high as 248 in 16-19 weeks of gestation [79] Similar findings have been reported in multiple

populations [80] Perinatal mortality is generally higher in boys than in girls and in the study

from MBR of Norway it was approximately 20 higher in boys than girls across the whole

range of gestational age groups [79] Attempts have been made to explain the increased

vulnerability observed in boys by sex specific differences in the developmental environment

including possible differences in placental functions Although there are obvious differences

in fetal growth to my knowledge there are no published data on sex specific differences in

nutrient transport across the placenta However there are reports on sex specific differences

in other aspects of placental function especially related to inflammatory responses and

endocrine functions In pregnancies complicated with maternal asthma there was increased

cytokine production in male placentas compared to female placentas [81] Differences in

cytokine production have been suggested to contribute to the observed increased incidence of

preterm delivery in males [82] Glucocorticoids given as repeated doses have been shown to

reduce fetal growth [83] Data suggest that the male and female fetal-placental unit responds

to cortisol in a differential manner Among pregnant women with asthma there were similar

levels of maternal cortisol but female fetuses responded with a reduction in birthweight

whereas the growth of the male fetuses was normal [84] Data on placental properties from

male and female are generally pooled but significant findings may be lost as male placentas

might have different responses than female placentas The different strategies to cope with

the same maternal environment has been summarized by V Clifton [84] She proposed that

male responses lead to minimal placental adjustment in gene and protein expression and that

the target is to increase or continue growth resulting in a greater risk of adverse outcome

Females on the other hand have multiple adaptations in placental gene and protein expression

and minor reduction in growth resulting in increased survival

35

17 Preeclampsia

Preeclampsia is defined as new onset hypertension (blood pressure gt14090) and proteinuria

(gt03 g per 24 hours) in the second half of pregnancy [85] This pregnancy complication

affects between 3 to 5 of all pregnancies depending on the population Preeclampsia is a

leading cause of mortality and morbidity for both mother and child worldwide particularly in

the developing world Worldwide preeclampsia accounts for more than 50 000 maternal

deaths annually [86] Risk factors include genetic factors multiple pregnancies high maternal

age obesity insulin resistance preexisting hypertension diabetes mellitus and renal disease

[87] Around 70 of cases of preeclampsia occur after 37 weeks of gestation [88]

Clinical picture

The symptoms of preeclampsia are diverse reflecting the underlying syndrome The systemic

vascular involvement is reflected not only in hypertension and proteinuria but can likewise

affect the vasculature in other organs like the liver and the brain When the liver is involved

symptoms and signs include abdominal pain nausea vomiting and elevated liver enzymes In

the case of HELLP (hemolysis elevated liver enzymes and low platelets) all these are present

along with the disturbances in the coagulation system In case of brain involvement visual

disturbances and eclampsia can occur Cerebrovascular complications like stroke and cerebral

hemorrhage are other feared maternal complications The fetus of preeclamptic pregnancies

faces increased risk of oligohydramnios IUGR and prematurity [89]

Classification

Preeclampsia has both a multifactorial pathogenesis and a heterogeneous clinical presentation

which complicates classification Classifications in use are according to pathophysiological

characteristics clinical severity presence of other maternal or fetal characteristics or

gestational age at presentation Classification based on pathogenesis suggests two broad types

of preeclampsia placental and maternal preeclampsia reflecting which element is more

prominent in the pathophysiology These subtypes are more of a theoretical framework than

different biological entities as most cases will rather be represented by a combination of both

The dichotomized pathophysiological classification can briefly be described as placental

preeclampsia when there is an abnormal placentation but basically a normal maternal

36

endothelium and maternal preeclampsia when the maternal endothelium is dysfunctional and

the placentation normal Classification according to severity of disease is used by American

College of Obstetrics and Gynecology (ACOG) Severe preeclampsia is defined as

hypertension (gt160110) and proteinuria (gt5 g per 24 hours or +3 on dipstick) or

accompanying symptoms and signs like oliguria cerebral disturbances impaired liver

function thrombocytopenia or fetal growth restriction [85] Early onset preeclampsia is often

defined as presentation before 34 weeks and late onset as after 34 weeks of gestation These

subtypes have different clinical presentations with the early-onset typically exhibiting more

serious clinical featuressymptoms and fetal growth restriction than the late onset [90]

Pathophysiology

Clinical symptoms of preeclampsia arise in the second half of pregnancy which can be

considered the last stage in the development of the disorder The preceding stages include the

placentation process which involves an immunologically regulated interaction between the

placenta and the maternal endothelium Placenta is necessary for the development of

preeclampsia but preeclampsia can occur without a fetus as in hydatidiform mole The

symptoms disappear after delivery of the placenta In preeclampsia the trophoblast invasion is

restricted to the decidua and does not reach the inner third of the myometrium resulting in

inadequate remodeling of spiral arteries The normal loss of smooth muscle and enlargement

of the spiral arteries is therefore restricted

Normal placentation further requires immune tolerance for fetal and placental antigen which

might be altered in preeclampsia There is a low-grade systemic inflammatory response

present in normal pregnancy which is enhanced in preeclampsia [91] The maternal

endothelium becomes activated and eventually dysfunctional Preexisting maternal vascular

dysfunction might render the maternal endothelium more sensitive to the burden of these

factors leading to endothelial dysfunction

Disturbed endothelial maintenance

In patients with preeclampsia there is an angiogenic imbalance in the circulation resulting in

more anti-angiogenic than angiogenic factors ie more of endothelium-disturbing and less

endothelium-supportive factors The vascular endothelial growth factors (VEGF-family) are

37

involved in angiogenesis and endothelial maintenance by affecting migration and

differentiation of endothelial cells [92] The family consists of several glycoproteins

including VEGF-A and PlGF among others Both of these have pro-angiogenic effect The

VEGF receptors are present on vascular endothelial cells and include VEGFR-1 (Flt-1) and

VEGFR-2 (KDR) VEGF binds to both receptors whereas PlGF binds exclusively to VEGFR-

1 (Flt-1)

Figure 7 Angiogenic imbalance

sFlt-1

sFlt-1 is a soluble form of the VEGFR-1 produced by alternative splicing [93] Placentas from

preeclamptic pregnancies show higher expression of sFlt-1 mRNA than normal placentas [94]

How much placenta actually contributes to the circulating sFlt-1 is however not settled sFlt-1

binds free VEGF and free PlGF and thereby inhibits their beneficial actions on the vascular

endothelium sFlt-1 increases with gestational age in normal pregnancy but is significantly

higher in women destined to develop preeclampsia from approximately week 26 and peaks

around week 34 [95]

38

sEndoglin

The transforming growth factor-β (TGF- β) family of proteins is known to be involved in

angiogenesis but has diverse actions in many cells Endoglin is a TGF-β coreceptor expressed

in endothelial cells and syncytiotrophoblasts of the placenta [87] A soluble form of endoglin

(sEng) is present in sera from preeclamptic patients There is a three- five- and tenfold

increase in sEng in mild PE severe PE and HELLP syndrome respectively [96] Endoglin

mRNA expression in placentas from preeclamptic pregnancies is fourfold increased compared

to healthy pregnancies [96] But again the placental contribution to circulating sEng is

unclear sEng increases with gestational age but in women destined to develop preeclampsia

the increase is significantly higher than healthy controls from week 23 (preterm PE) and week

30 (term PE) Interestingly women destined to deliver a SGA infant had increased sEng

levels from week 10 [95]

sEng and sFlt-1 given together increased capillary permeability in the lungs liver and kidney

of mice and induced hypertension in pregnant rats [96] demonstrating a possible combined

action of sFlt-1 and sEng in the pathogenesis of PE

PlGF

Placental growth factor is one of the members of the VEGF-family which has proangiogenic

activity [92] In non-pregnant women circulating levels are low but PlGF can be produced by

the heart and lungs skeletal muscle and adipose tissue PlGF is expressed by the placenta in

particular the syncytiotrophoblasts [97] In pregnancies complicated by preeclampsia PlGF

concentrations are lower than normal pregnancies [98] In normal pregnancy PlGF can be

detected from first trimester and increases until around week 33 after which it declines

towards term PlGF binds to the VEGFR-1 (Flt-1) receptor PlGF is necessary to stimulate

angiogenesis eg after myocardial injury The function of PlGF in pregnancy is not clear but

might be to regulate maternal vascular function by displacing VEGF from the Flt-1 receptor

so that it binds to the more active Flt-2 receptor (KDR) [87]

39

Figure 8 Endothelial integrity and dysfunction

VEGF

PlGF

Flt1

(VEGFR-1)

VEGF

PlGF

Endothelial integrity

Tore Henriksen 2006

VEGF

PlGF

Flt1

(VEGFR-1)

VEGF

PlGF

Endothelial dysfunction

Tore Henriksen 2005

Treatment

There is no causal treatment besides delivery of the baby and the placenta Symptomatic

antihypertensive treatment should be given to reduce maternal complications [85]

Preeclampsia can be complicated by eclampsia stroke disseminated intravascular coagulation

(DIC) HELLP placental abruption and acute renal failure Because the only treatment is

delivery preeclampsia leads to prematurity and increased risk of perinatal mortality and

morbidity

Prevention

40

Studies assessing interventions to reduce rate or severity of preeclampsia have been

conducted There is insufficient evidence to recommend rest reduced salt intake fish-oil

supplementation and antioxidant vitamins as preventive measurements [99] A Cochrane

review concluded that low-dose aspirin had small to moderate benefits (15 risk reduction)

when used for prevention of preeclampsia but that more information is needed to assess

which women are most likely to benefit when to start treatment and at what dose [100]

Calcium supplementation reduced risk of preeclampsia and can be considered for high risk

groups in low-intake populations [101]

Prediction

Many features of preeclampsia are exaggerated responses also present in normal pregnancies

In terms of diagnosis or prediction it is difficult to draw a clear distinction between normal

and abnormal No test predictive or diagnostic can be expected to distinguish absolutely

between different degrees of features that are common to all pregnancies Many tests have

been assessed as potential predictors of preeclampsia but no single test has yet met the

clinical standards for a predictive test Combinations of tests such as ultrasound assessment of

uterine artery Doppler waveforms and serum markers have been suggested as have ratios of

antiangiogenic and proangiogenic factors However sensitivity and specificity of the markers

PlGF sFlt-1 and sEng are too poor for accurate identification of preeclampsia in clinical

practice and hence not recommended used alone for the prediction of preeclampsia [102]

Predictive tests could ideally either identify those destined to develop preeclampsia during

pregnancy or differentiate between a serious or mild form among those diagnosed with

preeclampsia The latter would be of clinical importance in handling these patients

Long-term complications

Risk of recurrent preeclampsia depends on severity and onset of preeclampsia in the previous

pregnancy but can be up to 40 for severe disease [103] Women with a history of

preeclampsia have an elevated risk of cardiovascular disease later in life According to a

meta-analysis the risk of hypertension is 3-4 times the risk for women without preeclampsia

41

and the risk of death from cardiovascular and cerebrovascular disease about twice as high as

in women without preeclampsia [104] The mechanisms for the increased risk are not yet fully

understood but shared risk factors for preeclampsia and cardiovascular disease may jointly

predispose [105] This could be the case for chronic hypertension diabetes mellitus and renal

disease

42

2 Aims of the study

Overall aim

The overall aim of this thesis was to gain insight into the associations between maternal

nutritional and metabolic factors and fetal growth and aspects of placental function in normal

and preeclamptic pregnancies

Specific aims

Paper 1

The aims were to

1) Estimate and compare the effects of maternal characteristics on birthweight and on fetal

growth in third trimester

2) Introduce placental weight as a possible determinant of birthweight and of fetal growth in

third trimester

We hypothesized that maternal factors and placental size were associated with birthweight

and fetal growth

Paper 2

Given the findings in Paper 1 the aim was to study the effects of maternal factors (parity

BMI gestational weight gain and fasting glucose) on placental weight stratified by fetal sex

We hypothesized that the maternal factors mentioned above affected placental weight Based

on emerging evidence we also hypothesized that there were differential effects between fetal

sexes

Paper 3

Based on the observations in Paper 1 and 2 the aims were to

1) Establish an in vivo model in the human

2) To use the model to study human placental transfer of glucose in vivo to describe the

glucose and insulin concentrations in the uteroplacental and umbilical circulation in healthy

43

pregnancies at term and to explore the relation between maternal and fetal glucose

concentrations

We hypothesized that maternal plasma glucose was the major determinant of the fetal venous-

arterial gradient

Paper 4

Preeclampsia is a pregnancy specific placenta dependent disorder Preeclampsia has two

prominent features maternal vascular dysfunction and placental insufficiency Using the in

vivo model the aim was to investigate factors that may link placental disturbance to maternal

vascular dysfunction For this purpose sFlt-1 and sEng were chosen

We hypothesized that both sFlt-1 and sEng originate in placenta by finding that the plasma

concentration was higher in the maternal venous than the arterial side of the uteroplacental

circulation

44

3 Materials and methods

This thesis consists of four papers based on two separate studies that differ in design

population and methodological issues and will therefore be described separately

The STORK study

The STORK study is a prospective longitudinal study performed in the period 2001-2008 A

total of 1031 healthy pregnant women who gave birth at Oslo University Hospital

Rikshospitalet Norway and their newborn infants were included in the study Inclusion

criteria were healthy women of Scandinavian heritage with singleton pregnancies Exclusion

criteria were multiple pregnancies known pregestational diabetes and any severe chronic

diseases (lung cardiac gastrointestinal or renal) as well as any malformations discovered at

the routine ultrasound examination at week 17-19

Population

Eligible women were identified by one of the three PhD candidates in the project Invitation to

participate was sent to eligible women as they were registered for obstetric care at the

beginning of pregnancy Those interested in participating confirmed by phone to a secretary

who enrolled them in the study The number of women invited to participate varied over time

due to capacity The capacity for the oral glucose tolerance test (OGTT) was the ldquorate-limiting

steprdquo The drop-out rate was very low 33 of those who were included Thirty-two women

were excluded because of twin pregnancies or malformations that were diagnosed at the

routine ultrasound scan

45

Figure 9 Flow chart showing inclusion of participants in the STORK study

Withdrawn before

inclusion

n=141

Excluded

n=32

Lost

n=37

Invited to participate

n=4122

Accepted invitation

n=1241

Included

n=1100

Followed up

n=1031

Study design

The STORK study has a longitudinal design Each pregnant woman had four antenatal visits

(visit 1-4) scheduled at weeks 14-16 22-24 30-32 and 36-38 of pregnancy The newborns

were examined shortly after birth

Data collection

Clinical data

Background data was collected at the first visit including past medical and obstetric history

Clinical examination was repeated at every visit Data on the delivery and postpartum period

were extracted from hospital records

Blood samples

Blood samples were drawn at each visit between 0730 and 0830 after an overnight fast

centrifuged and stored at -80ordm C immediately Plasma glucose was measured by Accucheck

(Roche Diagnostics Mannheim Germany)

46

Birthweight

Newborns were weighed on a calibrated scale and measured by the attending midwife or

childrenrsquos nurse within two hours after birth

Ultrasound

Ultrasound examinations were done at visit 2 - visit 4 using an Acuson Aspen machine

(Acuson Mountain View CA USA) Biometric measurements included head circumference

(HC) abdominal circumference (AC) and femur length (FL) Each measurement was made

three times and the mean value was calculated and used in the analyses Estimated fetal

weight (EFW) was calculated by Combs formula [106] Percentiles for estimated fetal weight

and the individual biometric measurements were calculated according to Norwegian charts

[107108] Fetal growth in the third trimester was calculated as the difference between

measurements made at visit 3 and visit 4 for EFW and HC AC or FL respectively

Table 1 Data collection in the STORK study

Statistical analysis

Descriptive statistics were used to characterize the study population Bivariate associations

were explored by scatter plots and correlation analyses Univariate linear regression was used

to study the associations between selected maternal characteristics and the dependent

variablesoutcome variables birthweight and several fetal growth parameters in Paper 1 and

placental weight in Paper 2 Variables with a p-value lt 01 were considered in the multiple

linear regression models Multiple linear regression models were used to study the

Visit 1

14-16 w

Visit 2

22-24 w

Visit 3

30-32 w

Visit 4

36-38 w

At birth

Clinical examination + + + + +

Anthropometric measures

(skin fold thickness)

+ + + + +

Fasting blood samples + + + +

Oral glucose tolerance test + +

Ultrasound

(evaluation of fetal growth)

+ + +

Diet questionnaire + +

Physical activity questionnaire + +

47

associations between selected maternal characteristics and the outcome variables birthweight

fetal growth and placental weight A p-value lt 05 was considered statistically significant

All analyses were done by SPSS 180

Ethical aspects

All participants signed a written consent The study was approved by The Regional

Committee for Ethics South Norway (S- 01191)

48

The STORK-Placenta study

Study design

The STORK-Placenta study was designed to serve several purposes One purpose was to

study placental aspects of fetal growth and this was done as a cross-sectional study among

healthy pregnant women Secondly the study served as a case-control study with two groups

one consisting of preeclamptic patients and one with healthy controls

Population

There are two subgroups of the STORK-Placenta study in Paper 3 and Paper 4 respectively

In Paper 3 we included 40 women Inclusion criteria were healthy non-smoking women with

uncomplicated singleton pregnancy who were scheduled for elective caesarean section

Exclusion criteria were pre-existing co-morbidity any medication and pregnancy

complications like preeclampsia or insulin-dependent gestational diabetes Women who

arrived at the delivery ward with contractions prior to scheduled caesarean section were

excluded The recruitment was done at the out-patient clinic either during the appointment

when caesarean section was decided or during scheduled preoperational information

In paper 4 we included 12 patients with preeclampsia and 7 healthy pregnant women

Inclusion criteria for the study group were the diagnosis of preeclampsia and indication for

caesarean section prior to labour The control group consisted of healthy pregnant women

scheduled for elective caesarean section

Data collection

Medical and obstetrical history was taken at inclusion Clinical data was collected at inclusion

and at the day of delivery

Blood sampling

Blood samples were drawn from both the maternal and the umbilical (fetal) circulation during

caesarean section in spinal anaesthesia Fasting maternal blood samples were obtained by the

obstetrician from the uterine vein preferable on the same side as placenta just before uterine

49

incision Simultaneously blood was drawn by the anaesthesiologist from an arterial line in the

radial artery We assumed similar blood composition in the radial and the uterine artery In

addition blood was drawn from a venous catheter in the cubital vein or dorsal vein network of

the hand Directly after delivery blood samples were obtained from the umbilical artery and

vein immediately after cord clamping Blood was drawn into SAFETY Blood Collection Set

with Luer Adapter (Vaccuette Geiner Bio-One GmbH Austria) Blood samples were

immediately transferred to ethylenediaminetetraacetic acid (EDTA) vacutainers and stored on

ice until all samples were obtained They were then centrifuged at 4-6ordmC 2500 G for 20

minutes before the supernatants were removed and aliquotted and stored at -80ordmC until

analyses were performed

Analyses of samples

Glucose and insulin

Analyses were performed according to standard laboratory methods (Department of Medical

Biochemistry Oslo University Hospital Rikshospitalet) during three consecutive days

Glucose was measured using the hexokinaseglucose-6-phosphate dehydrogenase method

(Roche) Insulin was analysed using the Elecsys insulin analysis which is an enzyme-linked

immunosorbant assay (ELISA) technique with two monoclonal antibodies (Roche)

sFlt-1 and sEng

The concentrations of sFlt-1 and sEng were measured by commercially available ELISA kits

(RampD Systems Minneapolis MN USA) Assays were conducted in duplicate and in one run

The coefficients of variance were lt 10

50

Statistical analyses

Descriptive data were reported as mean values with standard deviations (SD) or percentages

as appropriate The differences in maternal characteristics between groups were compared by

unpaired t-test (Paper 4)

Glucose values were reported as mean values (SD) Comparisons between concentrations of

glucose in maternal and fetal vessels respectively were performed by paired t-tests Due to

skewed distributions insulin concentrations were reported as median values with inter quartile

ranges (IQR) and comparisons of related samples were performed by Wilcoxon sign rank test

Correlations were reported as Pearsonrsquos correlation coefficient if one variable was normally

distributed whereas Spearmanrsquos rank correlation coefficient was used in the case of

correlation between two skewed variables

The distribution of the concentrations for sFlt-1 and sEng were not normally distributed

hence they were log transformed to obtain normal distribution in order to use parametric

methods for statistical analyses Arithmetic median levels are reported in the text and figures

The differences in concentrations between groups were compared by unpaired t-test and the

concentrations in the radial artery and uterine vein from the same individual were compared

by paired t-test However non-parametric tests on the original data gave the same results

Ethical aspects

All participants signed a written consent The study was approved by The Regional

Committee for Medical Research Ethics South Norway (S-071742011-2419)

51

4 Summary of results

Paper 1

In Paper 1 we analyzed the associations between selected maternal characteristics and

birthweight measured as z-scores adjusted for gestational age and fetal sex We found that the

following maternal characteristics were independent determinants of birthweight and

statistically significant in the multiple regression model

Parity (B 046 95 CI 033-059 plt0001)

BMI (B 0048 95 CI 003-006 plt0001)

Gestational weight gain (B 006 95 CI 004-008 plt0001)

Fasting glucose (B 033 95 CI 018-048 plt0001)

In addition placental weight was a determinant for birthweight

Placental weight (B 041 95 CI 038-044 plt0001)

Adjusting for placental weight in the multiple model left the following maternal determinants

statistically significant

Parity (B 036 95 CI 025-047 plt0001)

BMI (B 0018 95 CI 0004-003 p= 0012)

Gestational weight gain (B 0036 95 CI 002-005 plt0001)

Fasting plasma glucose (B 022 95 CI 0009-034 plt0001)

Introducing placental weight as a covariate reduced the effect estimate of the other variables

in the model by 62 for BMI 40 for weight gain 33 for glucose and 22 for parity

The magnitude of reduction was estimated by change in the regression coefficient B of the

linear regression

Fetal growth in third trimester was estimated as the difference in EFW percentiles between

visit 3 and visit 4

In the multiple model the following maternal determinants remained statistically significant

Parity (B 473 95 CI 016-807 p=0006)

BMI (B 064 95 CI 023-106 p=0002)

Gestational weight gain (B 070 95 CI 024-116 p=0003)

52

In addition placental weight was a determinant for intrauterine growth

Placental weight (B 260 95 CI 16-36 plt0001)

Adjusting for placental weight in the multiple model left the following determinants

significant

Parity (B 39 95 CI 075-70 p=0015)

BMI (B 049 95 CI 008-089 p=002)

Gestational weight gain (B 060 95 CI 015-106 p=001)

Introducing placental weight reduced the effect of BMI on intrauterine fetal growth by 23

weight gain by 17 and parity by 14

We also analyzed the associations between maternal factors and the individual biometric

measurements Results from the multiple analyses for the increase in abdominal

circumference showed statistically significant associations for

Parity (B 018 95 CI 007-029 p=0001)

BMI (B 0022 95 CI 0005-003 p=0002)

Gestational weight gain (B 0026 95 CI 0008-004 p=0001)

Fasting glucose (B 044 95 CI -008-017 p=048)

In addition placental weight was a determinant for increase in abdominal circumference

Placental weight (B 011 95 CI 008-014 plt0001)

In the multiple model adjusting for all listed variables and placental weight fasting plasma

glucose was not significant (B 0016 95 CI -011-014 p=08) BMI reached borderline

significance (B 0014 95 CI 000-0028 p=0048) as an independent determinant when

adjusted for parity weight gain and placental weight For growth of the fetal abdominal

circumference BMI showed the largest reduction in B (36 ) when placental weight was

included

53

Paper 2

Given the importance of placental weight for birthweight and fetal growth we studied the

associations between maternal factors and placental weight in Paper 2 Mean placental weight

was 711 g (SD 156)

In the multiple regression model the following maternal factors were independent

determinants of placental weight

Parity (B 292 95 CI 101-484 p=0003)

BMI (B 67 95 CI 41-93 plt0001)

Gestational weight gain (B 56 95 CI 28-84 plt0001)

Fasting glucose (B 329 95 CI 100-557 p=0005)

Boys were heavier (3667 g vs 3494 plt0001) and longer (513 cm vs 503 cm plt0001)

than girls Boys also had a higher fetal placental ratio than girls (526 g vs 508 plt0001)

When stratified by fetal sex fasting glucose was significantly associated with placental

weight in females but not in males

Paper 3

We measured glucose and insulin concentrations in the uteroplacental and umbilical

circulations and calculated arterio-venous gradients The subjects were 40 healthy women

with a mean age of 36 years (SD 32) Mean birthweight was 3571 (SD 527) g range 2680-

4955g

The highest concentration of glucose was found in the maternal arterial circulation with a

mean concentration of 471 mmoll (SD 048) The uterine vein had a lower concentration

giving an arterio-venous difference of 029 mmoll on the maternal side The maternal

concentration of glucose was higher than the fetal concentration The maternal-fetal gradient

was 122 mmoll (SD 042) The concentration in the umbilical vein was 384 mmoll (SD

041) In the umbilical artery the concentration was lower 348 mmoll (SD 045) giving a

fetal venous-arterial difference of 038 (SD 031)

54

Maternal arterial and fetal venous concentrations of glucose were highly correlated (r=086

plt0001) Maternal arterial glucose concentration was not significantly correlated to the fetal

glucose v-a difference (r=03 p=007) The maternal a-v glucose difference was neither

correlated to the level of glucose in the umbilical vein nor the fetal glucose difference The

maternal-fetal gradient was highly correlated to the fetal glucose difference (r=08 plt0001)

The maternal-fetal glucose gradient was also correlated to the glucose concentration in the

umbilical artery (r=-038 p=0017) whereas it was not correlated to the glucose concentration

in the umbilical vein Similarly the fetal glucose v-a difference was only correlated with the

glucose concentration in the umbilical artery (r=-045 p=0004) but not with the glucose

concentration in the umbilical vein

The glucose concentration in the umbilical vein was not correlated to birthweight or placental

weight whereas correlation between the fetal glucose v-a difference and birthweight just

reached borderline significance (r=032 p=0049)

We found no relation between maternal and fetal insulin values (rho=-01 p=057) Maternal

and fetal concentrations of insulin were not statistically different On the maternal side

glucose and insulin concentrations were correlated (r=052 p=0001) On the fetal side

however no such correlation was found (r=012 p=048) Fetal insulin was correlated to both

placental weight (r=046 p=0003) and birthweight (r=058 plt0001)

Paper 4

We measured the anti-angiogenic factors sFlt-1 and sEng in a group of preeclamptic patients

and in healthy controls Both factors have been suggested to be released by the placenta and

involved in the pathogenesis of preeclampsia

Preeclamptic women had

Higher concentration of sFlt-1 than healthy controls (median of 17450 pgml of sFlt-1

compared to 5055 pgml in the control group p= 0003)

Higher concentration of sEng than healthy controls (median of 687 ngml in the

preeclampsia group versus a median of 287 ngml in the control group p= 0003)

55

We compared the concentration in the blood entering the uteroplacental unit (radial artery as a

proxy for uterine artery) and the blood leaving the uteroplacental unit (uterine vein)

Preeclamptic women had

Higher concentration of sFlt-1 in the uterine vein than in the radial artery (22450 vs

17450 pgml p=0005) whereas the concentration of sEng was not statistically different

(757 vs 687 ngml p=012)

Among healthy controls

No significant differences in the concentration between the uterine vein and the radial

artery for sFlt-1 (6193 vs 5055 pgml p=039)

No significant differences in the concentration between the uterine vein and the radial

artery for sEng (307 vs 287 ngml p=059)

56

5 Discussion

51 Methodological issues STORK

511 Design

The STORK study has a longitudinal design with four antenatal visits and observations at

birth for the 1031 women and children included Longitudinal studies are well suited to study

associations between explanatory variables and outcomes but not suitable to assess causality

The associations found in our study would need to be tested in a RCT or experimental model

to assess causality

512 Validity

The word valid is derived from the Latin validus meaning strong Validity in terms of

research refers to whether the results obtained answer the questions asked in the study

Validity can further be divided into internal and external validity [109]

Internal validity

Internal validity refers to whether the conclusions reached are likely to be correct for the

circumstances of that particular study Bias undermines the internal validity and includes

selection bias information bias and confounding bias [110]

Selection bias

Selection bias can result when the selection of subjects into a study (subject selection bias) or

their likelihood of being retained in the study (loss to follow up bias) leads to a result that is

different from what you would have obtained if you had enrolled the entire target population

[110]

57

Subject selection bias

In the current study invitation to participate was sent to 4122 and 1241 accepted the invitation

The number of invitations sent per week varied according to the capacity to enroll in the study

and the limiting factor was four Oral Glucose Tolerance Tests per day There were periods of

reduced capacity like holidays when fewer invitations were sent but it is not likely that the

women invited would be any different to the ones not invited due to varying capacity

The self-selection procedure (the women themselves phoned to be enrolled) might have

resulted in selection of women that were particularly motivated to participate The opportunity

to get closer follow-up than standard antenatal care may have caused selection bias Three

evaluations of fetal well-being and fetal growth by ultrasound could theoretically have

attracted women with a previous history of fetal growth abnormalities Data on birthweight of

previous children revealed that for those who had one previous child average birthweight was

3655 g (SD599) whereas the second child on average weighed 3808 g (SD 706) The data was

normally distributed with no overrepresentation of SGA or LGA (data not shown) Thus there

was no obvious selection of women with a history of fetal growth abnormalities in our study

population

Loss to follow up bias

The number of patients lost was 37 giving a drop-out rate of only 33 The number of

patients excluded was 32 The numbers lost are small and not likely to have influenced the

results substantially All participants had birthweight and placental weight recorded

However the outcome intrauterine fetal growth could only be estimated for those who

attended both third and fourth visit 918 in total Those who gave birth prematurely (54)

were not included in this outcome Maternal characteristics were not different in this group

compared to the total group (data not shown)

The selection bias only influences the results if the women selected or lost differ in either their

characteristics or in the outcomes which does not seem to be the case in our study

Information Bias

Information bias arises if the information has not been gathered in the same way for all

participants It includes observational bias misclassification and measurement errors and can

58

occur during collection of data as well as coding and processing of the data Misclassification

includes classifying binary or discrete variables incorrectly We minimized misclassification

by using mostly continuous variables rather than categorical variables Bias might be

introduced by the observer (interviewer bias biased follow-up) by the study participants

(recall bias) or by measurement tools such as questionnaires or instruments

We might have introduced biased follow-up for at least one group of women The women

diagnosed with gestational diabetes mellitus at visit 3 were taught and encouraged to make

changes in diet and physical activity to prevent further deterioration in their glucose

metabolism This might have had an influence by reducing the outcomes birthweight and

intrauterine fetal growth in third trimester

Recall bias occurs when there are systematic differences in the way subjects remember or

report exposures or outcomes We tried to avoid recall bias by eg using measured weight and

height to calculate BMI instead of self-reported prepregnancy BMI Reviewing available data

on the relationship between self-reported and directly measured height and weight has shown

trends of under-reporting for weight and BMI and over-reporting for height [111]

Measurement errors will be discussed under data collection below

Confounding bias

A confounder is defined in epidemiological terms as a covariate that influence both the

independent and the dependent variable and can be controlled for by adding it to a multiple

regression model Confounders must be identified and then appropriately adjusted for in the

analyses [112] The statistical considerations around confounding will be discussed under

statistical issues in the discussion below

In Randomized Controlled Trials (RCT) confounding is avoided by randomly assigned groups

that differ only in the factor being studied and thereby removes the need to statistically control

for confounders In an observational study like STORK we tried to reduce the need for

adjusting for confounding factors related to comorbidities by selecting healthy women and to

avoid ethnic factors by selecting women of Scandinavian heritage

59

External validityRepresentativity

External validity or representativity refers to whether the results obtained in one study can be

generalized to other situations and to other populations [110]

To assess representativity we did two comparisons Our cohort was compared to a group of

women who delivered at Ullevaringl the largest obstetric unit in Oslo The comparison was

restricted to women of Scandinavian heritage and our cohort only differed in having fewer

smokers and single mothers (data not published)

We also compared our cohort to data from the Birth Registry of Norway Our study

population was comparable to women who gave birth in Oslo in 2009 on parameters like

maternal age parity gestational age (GA) at birth and birthweight (BW)

Figure 10 Comparison between STORK cohort and Oslo

0

10

20

30

40

50

60

Age P0 GA BW

STORK

OSLO 2009

Retrieved electronically from the Birth Registry of Norway [1]

60

513 Statistical issues

Longitudinal data

Analyzing longitudinal data with variables that are correlated over time is a statistical

challenge which can be solved by the use of mixed models However these methods are

complicated and require statistical knowledge that was not readily available to our group We

therefore chose our variables to be able to use conventional linear regression models Fetal

growth was defined as growth between visit 3 and visit 4 thereby confining fetal growth to

the third trimester The whole trajectory of fetal growth was thereby not fully explored

Similarly we only used fasting glucose concentrations at one time point as a covariate in the

multiple models instead of the change in glucose levels over time

Continuous versus categorical variables

We have chosen to use mostly continuous variables both as outcome and explanatory

variables instead of dichotomizing or creating groups This is based on both methodological

theory and published data on physiology in pregnancy Dichotomizing leads to several

problems [113] According to Altman much information is lost the statistical power is

reduced one may underestimate variation and non-linearity in the relation between variable

and outcome may be concealed [114] A large study of hyperglycemia in pregnancy (HAPO)

has shown that there is a linear relationship and no threshold value between fasting glucose

and adverse pregnancy outcomes [115] A similar relationship was seen between BMI and

adverse pregnancy outcomes [116]

Confounders mediators and colliders

A number of potential factors can influence the associations of interest These must be

identified and possibly corrected for in the regression models Whether to adjust for these

factors depend on classification of the factors into true confounders mediators and colliders

[112] Confounders should be included while colliders should no be included in regression

models to avoid introducing bias

A confounder (defined above) can be controlled for by adding it to a multiple regression

model The choice of which confounders to include in the model requires physiological

61

Independent variable Outcome

Confounder

Independent variable Outcome

Mediator

Independent variable Outcome

Collider

knowledge and requires statistical considerations when it comes to the number of observations

required [117] A mediator is considered a covariate that is on the causal pathway between the

independent and the dependent variable A collider is considered a covariate that is related to

both the independent and dependent variable in a common consequence [117] In our material

no included variables were considered to be colliders

Figure 11 Confounders mediators and colliders

62

Mediation

A mediator variable can either account for all or some of the observed relation between two

variables The effect of mediation can be assessed by judging what happens to the relation

between the independent and dependent variable when the mediator is included into the

regression model or not Full mediation would occur if inclusion of the mediation variable

removed the relation between the independent variable and dependent variable This rarely

occurs The most likely event is that the association becomes weaker yet still a significant

path with the inclusion of the mediator Partial mediation occurs when the mediating variable

accounts for some but not all of the relationship between the independent variable and

dependent variable Partial mediation implies that there is not only a significant relation

between the mediator and the dependent variable but also some direct relation between the

independent and dependent variable

One method to assess mediation was proposed by Baron and Kenny in 1986 [118] They laid

out several requirements that must be met to form true mediation relationships which are

summarized below

Step 1 Confirm that the independent variable is a significant predictor of the dependent

variable Independent Variable Dependent Variable

Y = β10 + β11 X + 1

β11 is significant

Step2 Confirm that the independent variable is a significant predictor of the mediator If the

mediator is not associated with the independent variable then it couldnrsquot possibly mediate

anything Independent Variable Mediator

Me = β20 + β21 X + 2

β21 is significant

Step 3 Confirm that the mediator is a significant predictor of the dependent variable while

controlling for the independent variable This step involves demonstrating that when the

mediator and the independent variable are used simultaneously to predict the dependent

63

variable the previously significant path between the independent and dependent variable is

now greatly reduced if not nonsignificant

Y = β30 + β31 X + β32 Me + 3

β32 is significant

β31 should be smaller in absolute value than the original mediation effect (β11 above)

Placental weight can be considered a mediator in this study Regression models are therefore

done with and without placental weight as a covariate in the model to show its role as a

possible mediator We applied the model by Baron and Kenny described above to show a

possible role of the placenta as a mediator Our results point at possible mediating pathways

involving the placenta on the causal pathway to fetal growth In order to quantify how much

of the effect that goes through the placenta we could have applied path analyses However

this method required more advanced statistical methods which were not available

64

52 Data collection STORK

521 Dependent variablesoutcomes

Birthweight

We chose to use birthweight as a summary measure of overall fetal growth It is widely used

and therefore suitable to compare our data to other publications We chose to use birthweight

as a continuous variable We wanted to report associations between maternal factors and

birthweight in the total STORK cohort as previous publications from the same cohort only

reported birthweight in sub cohorts andor using birthweight as a categorical value with a cut-

off of gt4200 g Birthweight was expressed as Z-scores adjusted for gestational age and fetal

sex

The standard score (Z-score) represents the distance between the raw score and the population

mean in units of the standard deviation Z is negative when the raw score is below the mean

positive when above The z-score is calculated as

where

x is the observed value

μ is the mean of the population

σ is the standard deviation of the population

Mean and standard deviation of the population were taken from a Norwegian reference

material [119]

Intrauterine fetal growth

There are no internationally accepted consensus on how to define and assess intrauterine fetal

growth [11] The longitudinal design of the STORK study enabled us to assess intrauterine

fetal growth We chose third trimester visit 3 to visit 4 which is the period of maximum

Z =

x - μ

σ

65

growth and a period in which maternal metabolic factors are important in terms of fetal

growth [120]

Fetal size and fetal growth were estimated by ultrasound Fetal size was expressed as both

estimated fetal weight (EFW) in grams and as EFW percentile according to Norwegian

growth charts [107] Intrauterine fetal growth was defined as the change in estimated fetal size

parameters from visit 3 to visit 4 expressed as either change in EFW (g) or change in

percentiles Combs formula was chosen as the equation to estimate fetal weight as it is the

formula in use in clinical practice at our department and the basis for the growth charts we

used as reference [106]

Errors in ultrasonographic assessment of fetal weight can be attributed to at least two factors

errors due to the equation and errors due to observer error Observer error can further be

divided into intra-observer and inter-observer error [121] Intra-observer error refers to the

variance in measurements performed by the same observer All measurements were

performed three times and we used the mean of the three values to minimize intra-observer

error Inter-observer error refers to the variance in measurements that occur because different

observers measure differently To minimize inter-observer error all measurements were done

by only three investigators and each participant was measured by the same investigator at all

visits Among errors in ultrasonographic assessment of fetal weight observer error has been

shown to be a relatively minor component compared to the larger error due to the equation

[18] To be able to assess fetal growth we compared our data to reference curves based on

data from University of Bergen Norway as that population was considered the most

comparable to our population [107] We also evaluated fetal growth as changes in each of the

three components that make up EFW according to Combs equation namely HC AC and

femur length Once again we compared our data with Norwegian reference data [108]

There are other types of fetal growth charts available Customized curves have been

developed to adjust for factors like race fetal sex parity and maternal size which are factors

known to influence birthweight and factors that differ in different populations [13] We chose

not to use customized growth charts since the aim of our study was to study the effect of

maternal factors on fetal growth In customized charts maternal factors are controlled for and

therefore unsuited to study the effect of maternal factors

Conditional growth curves take into account the estimated size measured at one point and

gives an estimation of the expected growth for a fetus of that particular size for a specified

period of time As an example a larger fetus at the 75 percentile at week 30 will be expected

to grow more during the next weeks than a smaller fetus at the 10 percentile at week 30 during

66

the same period of time Conditioning on a previous measurement gives information on

whether a particular fetus grows fast or slowly relative to other fetuses of the same size We

chose not to use conditional growth curves in the current study as preliminary analyses did not

indicate major changes in the results making use of the conceptionally more difficult variable

less justified

Placental weight

Placenta was weighed including umbilical cord and membranes by the midwife or childrenrsquos

nurse within one hour after birth The placental weight was expressed in grams The placentas

were not trimmed but there is a close correlation between trimmed and non-trimmed

placentas (r= 098) [122]

Rationale for using placental weight as a proxy for placental function

There is no single parameter that measures placental function as placenta has a range of

functions Placental weight was chosen as outcome as a surrogate for placental function

Placental weight is a measure commonly used to summarize placental growth and aspects of

placental function In normal pregnancy it is reasonable to assume that placental weight is

related to aspects of functional capacity of the placenta [123] We had no estimations of

placental weight or mass during pregnancy Placenta exhibits linear growth throughout

pregnancy [5556] making it reasonable to use placental weight after birth instead of

estimations of placental mass during pregnancy

We wanted to use a variable that reflects those aspects of placental function which are

relevant to fetal growth of which nutrient transport is an obvious factor Density or activity of

nutrient transport proteins in the placenta could have been used as an alternative measurement

of placental function but these data are not yet available in our cohort An underlying

assumption for nutrients to be transported across placenta is that the maternal or umbilical

blood flow is not impaired We performed Doppler measurements in the uterine artery and

umbilical artery In our cohort of healthy women only 35 had notching in the uterine artery

at visit 2 and 32 had a pulsatile index above 2 SD for gestational age at visit 4

(unpublished data)

67

Placental weight correlates well with surface area which is a major determinant for nutrient

transport [124] The maternal plasma level of hormones produced in the placenta are directly

related to placental weight [125]

522 Explanatory independent variables

The explanatory variables were chosen based on publications from our study [126ndash129] and

literature on fetal growth in general We selected some maternal characteristics that were

known to influence birthweight in order to study their relation to intrauterine fetal growth

Maternal factors

Maternal age was noted at the first visit in whole years Age was normally distributed

Parity was categorized into P0 and P1+ as the largest difference in birthweight is

known to be between the first child and second child and less between consecutive

children [43]

BMI was calculated based on height and weight measured at the first visit We did not

use pregestational BMI to avoid recall bias and false self-reporting

GWG was calculated as the difference in weight between visit 4 and visit 1 We did

not use weight measured at admission for delivery as there were many missing values

Fasting glucose was measured by the use of Accucheck (Roche Diagnostics

Mannheim Germany) in order to obtain the measured values immediately This

enabled us to inform the women of the result the same morning and in cases of

impaired glucose metabolism to give advice on diet and physical activity during the

consultation Analyses of glucose over the seven years of inclusion revealed that there

was an unexpected increase in fasting glucose of 06 mmolL over time We found no

accompanying increase in maternal age BMI or in insulin that could give a biological

plausible explanation for this increasing trend Thus the time trend in fasting glucose

most likely had an analytical cause The glucose values were de-trended according to

the coefficients from linear regression under the assumption of a linear increase

during the entire period and de-trending of the data removed the increasing trend

[130]

68

Placental weight

The rationale for using placental weight to reflect aspects of placental function has been

discussed above When placental weight was used as an explanatory variable in the regression

models placental weight was entered in 100 grams instead of 1 gram to avoid getting effect

estimates with too many decimals

Placental pathology

There were 55 placentas not characterized as normal which makes up 53 of the samples

Theoretically it is possible that the placental weight in these cases does not reflect function in

the same way as placentas characterized as normal Eg a placenta with infarctions has areas

of tissue that do not take part in nutrient transport Such a small percentage of pathological

placentas are not likely to have influenced the results to a significant extent

69

53 Methodological issues STORK-Placenta

Design

The STORK-Placenta study had a cross-sectional design which means the women were only

examined once which in our study was at delivery This design gives no opportunity to assess

earlier gestational ages or longitudinal changes throughout the pregnancy In Paper 3 all the

study subjects were healthy women and there was no need for a control group In paper 4 we

applied a case-control design in which the preeclampsia group was compared to a control

group of healthy pregnant women

Validity

Internal validity

Selection bias

Only women delivered by cesarean section were recruited to this study This lead to selection

bias for both the healthy women and the preeclamptic patients For the healthy women the

most common indications for cesarean section were prior cesarean section or patient request

due to traumatic previous delivery Few healthy primiparas are delivered by elective cesarean

the exception being breech presentation In Paper 3 the selection therefore resulted in age and

parity that were relatively higher than average Avoiding selection bias in a study like this was

not possible given the population eligible for participation

For the preeclamptic women the selection lead to overrepresentation of early onset

preeclampsia and cases of serious preeclampsia as late onset or less serious cases in many

cases can deliver vaginally In Paper 4 this was reflected in lower gestational age in the

preeclampsia group than the controls

Information bias

We assumed similar blood composition in the radial and the uterine artery This was done to

avoid puncturing the uterine artery as bleeding would be easier to control in the radial artery

As the blood is pumped out of the aorta it is reasonable to assume that the composition does

70

not change substantially between the blood reaching the radial artery compared to the blood

that reaches the uterine artery

External validityrepresentativity

The representativity of the results from the STORK-Placenta study is discussed in light of the

selection of the participants

Parity was higher in Paper 3 than average From our results in Paper 1 and Paper 2 we have

seen that parity was an independent variable with effect on fetal growth In Paper 3 the added

effect of parity on fetal growth could give a bias if the effect of parity also affects the glucose

transport across the placenta Hitherto the question can not be answered So far our results are

only valid for the glucose metabolism among healthy women with relatively normal BMI

Which changes that occur in the glucose metabolism in women with chronic diseases will

probably vary according to the disease Higher BMI would probably influence the glucose

metabolism both directly as higher BMI might lead to higher glucose levels in many cases

but possibly also indirectly by changes in inflammatory factors and by changes in the

transport of other nutrients as amino-acids and lipids

In Paper 4 gestational age was lower in the preeclampsia group than in controls Early-onset

and late-onset preeclampsia are by many considered two different subgroups of preeclampsia

due to the differences in risk factors pathogenesis and clinical presentation [90] Our findings

may not be valid for late-onset preeclampsia where maternal risk factors play a larger role in

the patophysiology and the endothelial dysfunction might be more prominent Therefore it is

possible that the results are valid only when the placental dysfunction is the major feature in

the pathophysiology like in early-onset preeclampsia

Statistical issues

In both papers from the STORK-Placenta study the numbers of participants were relatively

small due to the demanding logistics of the project Small numbers lead to some statistical

challenges that need to be discussed

In Paper 3 we included 40 patients which were sufficient to show significant glucose gradients

on both maternal and fetal side as well as a gradient across the placenta However the small

number restricted the possibilities to study interesting associations between maternal factors

and glucose transport or glucose transport in relation to fetal growth by the use of regression

71

models As an example we found an interesting association between maternal BMI and fetal

glucose v-a difference but the scatter plott revealed one woman with BMI 39 and analyses

showed that without that observation the association was no longer significant

In Paper 4 we found a significant difference in sFlt-1 but not in sEng across the uteroplacental

circulation among preeclamptic patients There is a possibility that lack of power influenced

this finding Possibly a larger sample could have given a significant difference for sEng in

which case our finding could represent a type 1 error (reject the hypothesis that there was a

difference even if it is true)

Both non-parametric tests on original data and parametric tests on log transformed data were

done giving the same results in terms of statistically significant differences We chose to use

the log transformed data for statistical analyses (as that seemed to be the most conventional

method used in relevant references) but presented arithmetic data in figures and tables to

make it easier for the reader

54 Data collection STORK-Placenta

Blood sampling

All procedures were standardized to minimize systematic errors Sampling was therefore done

by a small group of four trained obstetricians and handling the samples in the laboratory was

restricted to only three investigators In the few cases where sampling was inadequate it was

mostly due to failure in inserting the arterial line or in a few cases inadequate amount of blood

obtained from the umbilical artery Blood samples were kept on ice until centrifugation

Blood samples were taken in fasting condition to obtain a steady state situation This is

particularly relevant for glucose and insulin which show large post-prandial variation

Cesarean section was done under spinal anesthesia no participants received oxygen or

intravenous glucose infusion

Analyses

Glucose and insulin were analyzed at the laboratory at Oslo University Hospital The samples

were analyzed during three consecutive days

72

sFlt-1 and sEng were analyzed by commercially available ELISA kits (RampD systems) We

chose to use ELISA kits from RampD for comparison reasons as they were commonly used in

papers on preeclampsia published at the time

73

55 Interpretation of results

Paper 1 and 2

In Paper 1 and Paper 2 we have studied the associations between maternal characteristics

placental weight and fetal growth in healthy pregnant women ie these are studies of normal

physiological relations Together the results from these papers illustrate some of the interplay

between the mother the placenta and the fetus

Paper 1

Paper 1Paper 2

-parity

-BMI

-GWG

-glucose

We found largely the same determinants for both birthweight and intrauterine fetal growth in

third trimester with the exception of fasting glucose (see below) The weight of the placenta

was influenced by similar maternal metabolic and nutritional factors In summary our results

are compatible with the concept that maternal factors can influence fetal growth directly and

indirectly by promoting placental growth

We found a direct effect of maternal factors both on birthweight and intrauterine growth in the

third trimester For both birthweight and intrauterine fetal growth placental weight was an

independent determinant Hence as the placenta grows and becomes larger some of the effect

of maternal factors on fetal growth is likely to be mediated by growth of the placenta

We found independent effects of several maternal factors (parity BMI and GWG) on

intrauterine fetal growth in third trimester We did not find independent effect of age The

small variation in age (SD) might partly explain why we did not find any effect of age

74

Furthermore age has been shown to exhibit an inverse u-shaped relation to birthweight and we

only tested for linear relationships Somewhat surprisingly we did not find an independent

effect of fasting glucose on intrauterine fetal growth in third trimester The discrepancy

between the effect of glucose on birthweight and on intrauterine growth may have several

explanations One possible explanation lies in how fetal growth is assessed Fat accumulation

resulting from increased maternal glucose and subsequent increased insulin secretion in the

fetus is likely to be accumulated on extremities and truncus of the fetus as well as the

abdomen The estimation of fetal size and fetal growth used in our study included assessment

of head circumference abdominal circumference and femur length Of these only abdominal

circumference would be likely to reflect fat deposition We did not however find an

independent association between fasting glucose and change in abdominal circumference

There is no consensus on whether the diagnosis of abnormal growth should be based on EFW

or AC or both [11] Another possible explanation for the described discrepancy could be

found in the concept of conditional growth Conditional fetal growth refers to differences in

expected fetal growth depending on the size estimated at the last measurement As an

example a fetus that is large at week 30 will be expected to grow more in the remaining

weeks of the pregnancy than a fetus that is relatively smaller at week 30 Factors like impaired

glucose metabolism in early pregnancy leading to higher fasting glucose values might have

resulted in a large fetus already at week 30

Placental weight was used as a measure of placental function Introducing placental weight in

the multiple regression models gave two interesting results

First placental weight was an independent determinant of birthweight and fetal growth and

showed a positive effect on fetal growth A small placenta is commonly associated with a

growth restricted fetus hence a reduced placental function Fetalplacental ratio can be used

as an indicator of placental efficiency and includes both fetal weight and placental weight

Preliminary analyses in our material showed that the maternal factors associated with

fetalplacental ratio in the multiple model were maternal age parity and BMI Maternal

gestational weight gain was not significantly associated in the univariate model and hence not

included in the multiple model Fasting glucose was not significant in the multiple model

using fetalplacental ratio as outcome

Secondly placental weight can be viewed as a mediator in the associations between maternal

factors and fetal growth This implies that some of the effect of the maternal factors might

work through growth of the placenta There are several possible biological reasons for the

75

reduced effects of the maternal characteristics on birthweight or intrauterine fetal growth

when placental weight was included in the models The selected maternal characteristics may

exert their effects on fetal growth by affecting transplacental transport Transplacental

transport is affected by blood flow both on maternal and fetal side Furthermore the number

and efficiency of placental transport proteins may also be influenced by maternal factors The

total number of transport proteins is dependent on both the area of the syncytio-endothelial

membrane and the density of the transporting proteins In addition it can not be excluded that

placental production of growth factors may be affected

We have studied both modifiable and non-modifiable maternal factors Parity is a non-

modifiable factor present before pregnancy There is a well-known effect of parity on

birthweight We showed that this effect is evident also for intrauterine growth and placental

weight The effect of parity is relatively larger than many other maternal factors eg larger

than fasting glucose BMI and GWG Modifiable factors include BMI GWG and fasting

glucose BMI and fasting glucose may be modified before pregnancy and GWG and glucose

during pregnancy

The present study did not include data on neither fetal factors that stimulate or inhibit

placental growth function or maternal factors nor placental factors that influence maternal

metabolism Theoretically however there are possible pathways including signals from the

fetus that can stimulate placental growth and possibly placental factors that can influence

maternal metabolism

Taken together the results from Paper 1 and Paper 2 show that maternal factors influence

both placental weight and fetal growth and it is likely that some of the effect on fetal growth is

mediated through placental growth This does not exclude the possibility that an increased

fetal growth following increased maternal energy supply may lead to release of fetal growth

factors that feed back on placental growth

Clinical implications

We have only studied birthweight and intrauterine growth in third trimester which might be

too late to intervene in cases of abnormal fetal growth In order to intervene it is necessary to

know which factors influence intrauterine growth at different gestational ages As both low

76

BMI and low GWG is related to increased risk of IUGR patients with high risk of IUGR

could be advised to increase their BMI or make sure they gain sufficient weight according to

recommendations Similarly as high BMI and high GWG increase fetal growth women could

be advised to obtain a normal BMI prior to getting pregnant and not gain unnecessary weight

during pregnancy As there is a linear and continuous relation between fasting glucose and

adverse fetal outcomes including fetal growth pregnant women with fasting glucose values

just below the GDM criteria can benefit from the same advice concerning diet and physical

activity as GDM-patients receive In particular women with multiple risk factors of impaired

fetal growth should be given advice even if she does not meet the criteria of GDM or obesity

Paper 3

Glucose is the major source of energy for the fetus and the placenta and therefore has an

obvious importance in fetal nutrition Glucose transport across the placenta in humans is

interesting to study for several reasons There is a lack of human in vivo studies in contrast to

the body of evidence on mechanisms and transporter proteins etc from in vitro studies It is of

major importance to acknowledge the distinction between maternal nutrition and fetal

nutrition [2] The placenta is not just a simple conduit for gases nutrients and waste products

but has its own complex metabolism with corresponding requirements for oxygen and

nutrients

In this paper we found a close correlation between maternal and fetal glucose concentrations

which is in line with the concept that the maternal-fetal gradient is the driving force in the

transplacental transport of glucose across the placenta However the fetal v-a glucose

difference was not merely a reflection of the maternal glucose concentration or the

uteroplacental uptake of glucose but rather related to the maternal-fetal gradient and the

concentration in the umbilical artery The relation between maternal and fetal glucose

concentration has been shown in several papers Although the umbilical venous concentration

is closely related to the maternal concentration the fetal v-a difference seemed to be less

related to maternal concentrations but more to the concentration in the umbilical artery fetal

insulin placental weight and birthweight We therefore speculate that the fetus has a saying in

determining the fetal glucose consumption This might at first seem to be in conflict with the

Pedersen hypothesis which was first presented in 1952 [131] His theory was that high

maternal glucose was transferred to the fetus which responds by secreting more insulin

77

which in turn lowers the blood glucose of the newborn Compared to the 1950s pregnant

women of today are older when they get pregnant have higher prepregnancy BMI and gain

more weight in pregnancy The metabolic environment a fetus experiences today is likely to

differ from the environment some decades ago in several aspects more energy-rich altered

balance between glucose and lipids and more inflammation [132] The non-glucose factors

like lipids may have augmented their role as several factors have changed in the population

since the proposal was made by Pedersen We can only speculate as to how the relative

importance of these factors might influence the regulation of transport of nutrients to the

fetus

Our results can not explain or show the complex regulation of glucose transport and

metabolism and leaves us with some unanswered questions We only presented correlation

analyses as we did not yet have enough samples to do multivariate analyses to evaluate the

relative importance of the factors involved We were not able to do path analyses to quantify

the influence of each of these factors Do the relationships we have described work differently

in pathological pregnancies in which there is either abnormal placental function or the mother

exhibits abnormalities in her metabolism or the fetus experiences abnormal growth These

questions can hopefully be answered by future research

The amount of glucose consumed by the placenta can be changed under hypoxic conditions

[63] It is not likely that our participants were hypoxic to a large degree We only measured

oxygen in a few cases which were all normal

Clinical implications

In obstetric practice there are numerous examples of cases of abnormal fetal growth occurring

in pregnancies of healthy mothers with normal metabolism and apparently normal placental

function Placental function might still be compromised resulting in reduced fetal nutrition

Fetal under nutrition may result from compromised transplacental transfer of nutrients In the

other end of the spectrum are the fetuses that experience overgrowth despite strict glycemic

control of their diabetic mothers Some authors argue that this might be due to intermittent

hyperglycemia rather than constant hyperglycemia but another option is that hyperglycemia

is accompanied by other nutrients or other factors that increases the total energy supply to the

fetus

78

Human in vivo studies are rare and therefore valuable in terms of extrapolation to relevant

settings in clinical practice However in vivo settings include multiple factors working

together making it difficult to assess individual effects In vitro settings however can control

for one factor at a time to gain mechanistic knowledge which can hardly be drawn from in

vivo settings The clinical significance of factors operating in vitro is often difficult to assess

Paper 4

The multifactorial etiology and heterogeneous clinical presentations seen in preeclampsia

makes it an intriguing and challenging condition to study Since preeclampsia is a pregnancy

complication in which the placenta is believed to play a crucial role in the pathophysiology it

was both interesting and relevant to choose preeclampsia in order to study aspects of placental

function in pathological pregnancies Furthermore preeclampsia is still a leading cause of

mortality and morbidity worldwide Despite decades of research there is still no causal

treatment leaving timing of delivery the only intervention to balance the needs of the mother

and the fetus

In our study we found as expected that preeclamptic women had higher concentrations of sFlt-

1 and sEng than healthy controls as has been shown in numerous previous publications

Preeclamptic women further had higher concentrations of sFlt-1 in the uterine vein than the

radial artery giving a gradient across the uterus There was no gradient for sEng among

preeclamptic women and no gradients were found in the healthy controls for either of the two

factors tested The gradient across placenta is consistent with the concept that the placenta

secretes sFlt-1 into the maternal circulation The source of excess sFlt-1 and sEng in

preeclamptic patients is assumed to be the placenta based on enhanced expression of both

factors in trophoblastic tissue [133134] Enhanced expression of sFlt-1 and sEng in

trophoblastic tissue does not necessarily prove that the circulating sFlt-1 and sEng found in

preeclamptic patients originate from the placenta or that the placenta is the only source There

is a possibility that sFlt and sEng originate from circulating cells in the maternal circulation or

endothelial cells Peripheral blood mononuclear cells have been suggested to be an additional

extra-placental source of sFlt-1 [134]

Our results support the hypothesis that at least a part of the circulating sFlt-1 originates in the

placenta and is transported into the maternal circulation whereas we did not find evidence to

support that this holds for sEng The discrepancy between our results for sFlt-1 and sEng

could have several explanations

79

There might be a biological difference such that sFlt-1 only or to a larger extent than sEng is

released from the syncytiotrophoblasts in the placenta whereas sEng to a larger extent is

produced elsewhere [135] There might also be a statistical explanation suggesting that we had

inadequate power to show a statistically significant difference in sEng which would represent

a type 1 error (rejecting the hypothesis that there was a difference even if it is true)

In this paper as most studies involving preeclamptic patients and healthy controls there was a

difference in gestational age among cases and controls The difference in gestational age

raises some questions to be discussed There are publications reporting an increase in sFlt-1

and sEng with increasing gestational age both for controls and preeclamptic patients but more

so in preeclampsia [136137] Assuming this relationship for our controls we would expect to

find a lower concentration at week 30 among healthy controls than what we found near term

giving an even greater difference than we observed Thus we do not think that the difference

in gestational age can explain the observed difference in sFlt-1 and sEng between preclamptic

patients and healthy controls We did not include samples from preeclamptic patients at term

as they mostly deliver vaginally Our group of preeclamptic patients thus represents early-

onset preeclampsia In most cases preeclampsia was accompanied by a degree of intrauterine

growth restriction Whether our findings are representative for late onset preeclampsia in

which the placental dysfunction is perhaps less prominent and the endothelial dysfunction

more prominent is not clear from our study

Anti-angiogenic factors in a clinical setting

Anti-angiogenetic factors have been proposed used as diagnostic tools for preeclampsia

There is hope for a therapeutic option in treating preeclampsia in the future but whether

angiogenetic agents can be used to improve the angiogenic imbalance seen in preeclampsia is

not known At the moment the most useful implications of these types of studies is increased

knowledge on the pathogenesis including the possibility to differentiate between early- and

late-onset preeclampsia

80

6 Conclusions

In conclusion results from the first part of this thesis (Paper 1 and 2) underline the importance

of the placenta and placental functions in normal pregnancies Placenta is an important factor

to consider when studying associations between maternal factors and measures of fetal

growth birthweight intrauterine growth or body composition The effect of maternal

metabolic and nutritional factors on fetal growth is likely to go partly through growth of the

placenta There is an important distinction between maternal and fetal nutrition as one has to

consider the placenta as an active organ and not a passive conduit of nutrients and gases

In the second part of this thesis a method has been established that makes it possible to study

placental function in the human in both normal and pathological pregnancies like

preeclampsia

7 Further research

I believe the greatest challenges in the two studies that make up my thesis also reflect the

potentials for further research

In the STORK study we collected large amounts of data on a large group of women

Therefore selecting and analyzing the relevant outcomes and appropriate explanatory

variables was the greatest challenge There are large amounts of data still to be analyzed For

the STORK data my plans for a postdoc is to study in more detail the relations between

maternal metabolism and pregnancy outcomes More specifically to differentiate between

healthy and unhealthy obese pregnant women in metabolic terms and relate this to pregnancy

outcomes including fetal growth

In the STORK-Placenta study establishing the method and achieving the data collection were

the greatest challenges with demanding logistics at any time of the day There are few larger

human in vivo studies of placental nutrient transfer In particular studies of arterio-venous

differences on maternal side of placenta are scarce The main reason this kind of studies are so

limited is that such studies are logistically very requiring To our knowledge we are the only

group employing this procedure The samples obtained by this method give unique

opportunities to study concentration gradients and transplacental transfer of any nutrient

81

across placenta and how endocrine and inflammatory factors may interact with nutrient

transfer The study also includes measurements of maternal and fetal blood flow enabling us

to quantify the amounts of nutrients being transported The study has currently been

expanded to around 100 pregnancies Data collection still goes on aiming to get enough

samples to continue analyzing interesting associations linking maternal metabolism placental

functions and the fetus and extending the data to include cases of pathological pregnancies

like preeclampsia diabetes mellitus and abnormal fetal growth Samples from preeclamptic

women are currently being analyzed for Placental growth factor

The potential for further research lies in combining the data retrieved from the two studies

Ultimately I would like to be able to link preeclampsia and fetal growth in the two studies

82

8 References

Reference List

1 2009) wwwmfr-nesstaruibno Medical birth Registry Norway Available

2 Harding JE (2001) The nutritional basis of the fetal origins of adult disease Int J

Epidemiol 30 15-23

3 Barker DJ Thornburg KL (2013) The obstetric origins of health for a lifetime Clinical

Obstetrics and Gynecology 56 511-519

4 Forsdahl A (1978) Living conditions in childhood and subsequent development of risk

factors for arteriosclerotic heart disease The cardiovascular survey in Finnmark 1974-

75 J Epidemiol Community Health 32 34-37

5 Forsdahl A (1979) Are poor living conditions in childhood and adolescence and

important risk factor for arteriosclerotic heart disease Int J Rehabil Res 2 238-239

6 Barker DJ (2005) The developmental origins of insulin resistance Horm Res 64 Suppl

3 2-7

7 Barker DJ Shiell AW Barker ME Law CM (2000) Growth in utero and blood

pressure levels in the next generation J Hypertens 18 843-846

8 Barker DJ (1997) The long-term outcome of retarded fetal growth Clinical Obstetrics

and Gynecology 40 853-863

9 Gude NM Roberts CT Kalionis B King RG (2004) Growth and function of the

normal human placenta Thromb Res 114 397-407

10 Voldner N (2010) Modifiable determinants of newborn macrosomia and birth

complications [dissertation]

11 Mayer C Joseph KS (2013) Fetal growth a review of terms concepts and issues

relevant to obstetrics Ultrasound Obstet Gynecol 41 136-145

12 Zhang J Merialdi M Platt LD Kramer MS (2010) Defining normal and abnormal

fetal growth promises and challenges Am J Obstet Gynecol 202 522-528

13 Gardosi J Figueras F Clausson B Francis A (2011) The customised growth potential

an international research tool to study the epidemiology of fetal growth Paediatr

Perinat Epidemiol 25 2-10

14 Rohrer F (1921) The index of corpulence as measure of nutritional state Munchener

medizinische Wochenschrift 580-582

15 Catalano PM Thomas AJ Avallone DA Amini SB (1995) Anthropometric estimation

of neonatal body composition Am J Obstet Gynecol 173 1176-1181

16 Godang K Qvigstad E Voldner N Isaksen GA Froslie KF et al (2010) Assessing

body composition in healthy newborn infants reliability of dual-energy x-ray

absorptiometry J Clin Densitom 13 151-160

17 Pay AS Froen JF Staff AC Jacobsson B Gjessing HK (2013) A new population-

based reference curve for symphysis-fundus height Acta Obstet Gynecol Scand 92

925-933

18 Anderson NG Jolley IJ Wells JE (2007) Sonographic estimation of fetal weight

comparison of bias precision and consistency using 12 different formulae Ultrasound

Obstet Gynecol 30 173-179

19 Cetin I Alvino G (2009) Intrauterine growth restriction implications for placental

metabolism and transport A review Placenta 30 Suppl A S77-S82

20 Mei Z Grummer-Strawn LM Pietrobelli A Goulding A Goran MI et al (2002)

Validity of body mass index compared with other body-composition screening indexes

for the assessment of body fatness in children and adolescents Am J Clin Nutr 75

978-985

9

PGH placental growth hormone

PlGF placental growth factor

RCT randomized controlled trial

SD standard deviation

sEng soluble Endoglin

sFlt-1 soluble Flt-1

SGA small for gestational age

STORK store barn og svangerskapskomplikasjoner

TG triglycerides

TGF-β transforming growth factor β

TSH thyroid stimulation hormone

VEGF vascular endothelial growth factor

VEGFR-1 vascular endothelial factor receptor -1

VEGFR-2 vascular endothelial factor receptor -2

VLDL very low density lipoprotein

WAT white adipose tissue

WHO World Health Organization

10

1 Introduction

11 Summary

The STORK study was initiated to address the observed increase in proportions of large

babies in Norway and the growing acknowledgement that birthweight and fetal growth have

consequences for health and disease both in short and long term In Norway the proportion of

babies with high birthweightmacrosomia (gt4000 g) increased from approximately 17 in

1990 to 22 around the year 2000 after which the proportion has returned to 17 in 2008

[1] The STORK study was designed to study maternal risk factors for macrosomia as

reflected in the acronym STORK rdquostore barn og komplikasjonerrdquo which translates into large

babies and complications The name of the study reflects the original research questions

asked when the study was planned The cohort consists of two periods referred to as STORK

1 (2001-2005) and STORK 2 (2005-2008) The cohort was extended to STORK 2 in order to

address wider research questions The outcome was expanded to include not only birthweight

but intrauterine growth and body composition at birth Placenta is central in determining the

nutritional and endocrinological conditions for fetal growth and development Virtually no

compound reaches the fetus without passing the placenta We therefore first included

placental weight in the analyses of the STORK data with an underlying assumption that

placental size to some extent reflects functional capacity During these analyses placental

weight emerged as a determinant of fetal growth parameters These observations led us to

initiate studies on functional aspects of placenta and we decided to establish an in vivo model

in the human (the STORK-Placenta study)

Two approaches were chosen in this study

1 To study nutrient transport

2 To investigate placental factors in pathological pregnancies like preeclampsia

Preeclampsia is a leading cause of mortality and morbidity in obstetrics and a condition in

which the placenta is thought to play a major pathophysiological role Importantly a

prominent feature of preeclampsia is placental insufficiency and fetal growth restriction

11

2001 2005 2008

STORK 1 STORK 2

birthweight

fetal growth

body composition ( fat)

maternal characteristics

placental aspects

Camilla M Friis

Kathrine Frey Froslashslie

Marie Cecilie Paasche Roland

Inclusion

period

Timeline for the STORK and STORK-Placenta project

STORK-Placenta

2013

Outcome

Determinants

PhD candidate

birthweight gt 4200 g

maternal characteristics

Nanna Voldner

placental functions

glucose transport across placenta

anti-angiogenic factors

Marie Cecilie Paasche Roland

Ane Moe Holme

This thesis consists of four papers of which Paper 1 and Paper 2 are based on the STORK

study and Paper 3 and Paper 4 are based on the STORK-Placenta Study

12

In Paper 1 we studied how maternal factors were associated with birthweight and intrauterine

fetal growth For the reasons indicated above we included placental weight as a determinant

of birthweight and fetal growth

Paper 1

-parity

-BMI

-GWG

-glucose

Given the importance of placental weight on birthweight and fetal growth we then wanted to

study placental weight in Paper 2 We studied the influence of maternal factors on placental

weight and whether these associations differed with fetal sex

Paper 2

-parity

-BMI

-GWG

-glucose

13

In Paper 3 we reported initial studies of transfer of glucose across the human placenta and

how maternal and fetal glucose and insulin levels were related

Paper 3

Glucose and insulin

In Paper 4 the role of placenta in producing pathogenic factors of preeclampsia was

investigated choosing anti-angiogenic factors because of their endothelial-disturbing

properties

Paper 4

Anti-angiogenic

factors

14

12 Background

Fetal growth has implications for the newborn child both in short and long term The link

between events in early life and risk of disease in later life is now a widely recognized field of

research known as developmental programming and often called Developmental Origins of

Health and Disease Developmental programming refers to how an event at a critical or

sensitive period results in a long-term change in the structure or function of the organism

[23] Organs and systems in the human body are sensitive to the environment in certain

periods The critical periods are mainly those characterized by rapid growth and maturation

and for most organs and systems this happens to a large extent in utero

The idea of linking events in early life to later risk of disease is however not new The

association between poor living conditions in childhood and increased risk of cardiovascular

disease was observed by Anders Forsdahl who worked as a physician in Finnmark Northern

Norway in the 1970s He found a positive correlation between infant mortality which was

considered to be an index of standard of living and mortality from arteriosclerotic heart

disease as well as cholesterol values [45]

The link between early life events and later disease received more publicity when the late

David Barker introduced what is commonly referred to as the rdquoBarker hypothesisrdquo He was

probably the most acknowledged scientist in this field and established an association between

birthweight and increased risk of cardiovascular disease insulin resistance and type 2 diabetes

mellitus [6ndash8] His work has been followed by a range of publications that have not only

confirmed these associations but also provided mechanistic insight into the link between

intrauterine growth and increased risk of disease A large body of evidence have shown that

structural or functional changes that last throughout life can result from nutritional factors in

utero [2] Extensive work on animal models has demonstrated how dietary changes affect fetal

growth and lead to functional and structural changes The availability of nutrients to the fetus

is influenced not only by the motherrsquos diet during pregnancy but by maternal nutrient stores

and metabolism The placenta has multiple roles in fetal nutrition by its capacity to transport

nutrients from the maternal to the fetal circulation by its own metabolic demand for nutrients

and by producing hormones which influence fetal and maternal nutritional supply [9]

15

13 Fetal growth

Fetal growth comprises the entire process of differentiation maturation and development that

occurs between conception and birth This process starts with the fusion of two cells and ends

up with an estimated 50-100 trillion cells in the newborn child The terminology used to

describe and evaluate fetal growth is complex and the terms need to be defined First there is

a need to draw a distinction between size at birth and intrauterine growth Secondly the

difference between size which is most commonly measured as weight and body composition

must be addressed

131 Size at birth

Birthweight

Size at birth is routinely measured as birthweight (grams or kg) Birthweight is a summary

measure of fetal growth throughout pregnancy Categories based on birthweight are used both

in clinical settings and for research Low birthweight is generally defined as birthweight

lt 2500 grams whereas a definition for high birthweight (macrosomia) is more arbitrary Both

4000 4200 and 4500 grams have been used as cut-off values in various settings [1011]

Birthweight for gestational age

Birthweight as a function of gestational age gives information of size relative to expected size

for a particular gestational age Birthweight for gestational age can be given as a percentile

between 0 and 100 Birthweight for gestational age can also be categorized and the most

commonly used categories are large for gestational age (LGA) appropriate for gestational age

(AGA) and small for gestational age (SGA) The conventional cut-off percentiles for these

categories are given beneath

Population based charts for birthweight are often based on large samples including both low-

risk and high-risk pregnancies representing the underlying population On the other hand a

so-called standard chart is usually based on low-risk pregnancies with a normal outcome [12]

Furthermore customized charts have been made to accommodate for differences in eg

ethnicity parity age and BMI in individual patients Such charts have been developed for

different populations and there are electronically available charts [13]

16

Body composition

In addition to weight of the newborn baby length and head circumference give some

information about the body composition of the newborn Further evaluation of body

composition can be derived from these measurements The Ponderal Index (PI) is calculated

as a relationship between mass and height as is the body mass index (BMI) but the mass is

normalized with the third power of body height

Because it yields valid results even for very short (and very tall) persons it is more suitable

in pediatrics than BMI [14] Body composition can further be assessed by measuring

circumference of the abdomen and the extremities or by skin fold thickness measurements by

calipers to obtain an estimation of fat distribution [15] There are other methods that are either

expensive or difficult to perform on newborns Dual energy x -ray absorptiometry (DXA)

enables an estimation of bone mass fat mass and fat free (lean) mass A reasonable good

correlation between estimated fat mass by DXA and skin fold thickness measured by calipers

has been shown [16]

Categories Cut-offs

SGA lt 10 p

AGA 10-90 p

LGA gt 90 p

PI

= weight (g)

[height (cm)]3

17

132 Intrauterine growth

Fetal growth is a continuous process that starts at conception and ends at birth but is

commonly measured as just the end result which is size at birth However the distinction

between size and growth applies also to the intrauterine period Fetal size is estimated based

on a single observation or measurement whereas estimation of fetal growth requires at least

two measurements

Symphysis-fundus height

Palpation of the abdomen and measuring the symphysis-fundal height is used to estimate

intrauterine growth in low-risk pregnancies Reference curves for the symphysis-fundus

height to assess fetal growth have recently been updated in Scandinavia [17]

Ultrasound measurements

Estimation of fetal size

Estimation of fetal size by ultrasound combines measurements of the fetus and transforms

these measurements into volume and weight to estimate fetal size There are a number of

equations that use combinations of circumferences andor diameters and combinations of

measurements of head and abdominal size andor femural length to estimate fetal size The

equations differ in their ability to predict fetal size but generally perform more accurately in

predicting average fetal sizes than at the extremes of birthweight [18]

Estimation of fetal growth and fetal growth charts

To estimate fetal growth two or more measurements separated in time are needed and the rate

of growth can be assessed by using fetal growth charts There are a multitude of charts

available that are constructed by different methods and from different populations Fetal

growth charts can be derived from cross-sectional or longitudinal data In cross-sectional

charts each pregnant woman contributes with data from one observation whereas longitudinal

studies have repeated measurements from each participant The longitudinal studies provide

better references for fetal growth [12]

18

The ambiguous terminology

The lack of distinction between fetal size and fetal growth complicates the terminology Small

for gestational age (SGA) is often defined as birthweight lt 10 p The term intrauterine growth

restriction (IUGR) is often used interchangeably with SGA IUGR more strictly is used as a

term for true intrauterine growth restriction based on data that shows a decline in intrauterine

growth over time assessed by ultrasound There are however no universally accepted

definition of how much decline in fetal growth that would define IUGR although some

authors have defined IUGR as either a fall in fetometric percentiles or a combination of fall in

percentiles and low birthweight [19] On the same note accelerated fetal growth can be seen

during intrauterine life and may or may not result in a LGA newborn

Figure 1 Schematic overview of categories of fetal growth

growth

restrictionexcessive

growth

AGASGA LGA

19

14 Maternal aspects of fetal growth

141 Maternal nutritional status

Maternal nutritional status is vital for fetal growth as the fetus is dependent on nutrients being

transported from the maternal circulation across the placenta to the fetal circulation The

nutritional status of the mother is generally assessed by indirect means of which Body Mass

Index is a commonly used measurement

Body Mass Index (BMI)

BMI is calculated from a persons weight and height according to the following equation

BMI is used as a surrogate for body fat and has been shown to correlate to direct measures of

body fat such as underwater weighing and dual energy x-ray absorptiometry (DXA) [20]

Although the correlation between BMI and body fatness is fairly strong the correlation varies

by sex race and age At the same BMI women tend to have more body fat than men At the

same BMI older people tend to have more body fat than younger adults Highly trained

athletes may have a high BMI because of increased muscularity rather than increased body

fatness [21] In pregnancy the correlation between BMI and percent body fat is better in early

gestation than in late gestation [22]

The World Health Organisation (WHO) classifies BMI for adults in the following groups [23]

BMI

weight (kg)

[height (m)]2

BMI Weight Status

Below 185 Underweight

185 ndash 249 Normal

250 ndash 299 Overweight

300 and above Obese

20

For adults BMI is interpreted using standard weight status categories that are the same for all

ages and for both men and women For children and adolescents on the other hand the

interpretation of BMI is both age- and sex-specific [24]

Biological effects of high BMI

BMI is used as a surrogate for body fat which is made up of adipose tissue Adipose tissue can

be classified as white adipose tissue (WAT) and brown adipose tissue WAT is excess energy

stored as triglycerides in adipocytes which secrete a variety of substances including

hormones (eg leptin adiponectin and resistin) as well as inflammatory factors [25] Brown

adipose tissue is thought to have a function in thermo genesis Excess adipose tissue can be

estimated by anthropometric measures such as skin fold thickness measured by calipers [26]

Consequences of BMI for pregnancy and labour

Prepregnancy BMI is a major determinant of pregnancy outcome and increasing BMI is

associated with an increased risk of the majority of pregnancy complications like congenital

abnormalities miscarriages gestational diabetes preeclampsia obstructed labour and

operative deliveries [27] Low prepregnancy BMI is associated with low birthweight and

IUGR [28]

Gestational weight gain (GWG)

Gestational weight gain in pregnancy includes growth of the fetus placenta and uterus

increase in maternal plasma volume and accumulation of maternal fat mass [29] The total

amount of weight gained during pregnancy varies considerably among women and lean

women tend to accumulate more fat than obese women [30] Accumulation of fat is primarily

centrally and represents a combination of subcutaneous fat and visceral fat Visceral fat

correlates with metabolic risk factors like hypertension insulin sensitivity and plasma lipids

[31] The ideal gestational weight gain differs depending on the maternal or neonatal outcome

of interest Recommendations for gestational weight gain were revised by the Institute of

Medicine USA in 2009 and highlights both that women should be within a normal BMI range

when they conceive and gain weight within the ranges recommended The recommended

21

weight gain is based on four categories of prepregnancy BMI Higher categories of

prepregnancy BMI are recommended a lower weight gain [29]

Consequences of gestational weight gain

Gestational weight gain has consequences for both mother and child in the short and long

term Low GWG is associated with low birthweight and IUGR [32] and high GWG is

associated with macrosomia and increased neonatal fat mass [3334] High GWG is

associated with increased risk of pregnancy complications like preeclampsia and diabetes [35]

Restricted GWG in obese women with type 2 diabetes has been shown to influence fetal

growth [36] There are reports on associations between GWG and cesarean section

instrumental deliveries and low Apgar scores but it has been suggested that the effects are

mediated by high birthweight [35] The most consistent adverse outcome for mothers with

large GWG is weight retention post-partum [35]

BMI Weight Status Recommended Gestational

Weight Gain

Below 185 Underweight 13-18 kg

185 ndash 249 Normal 11-16 kg

250 ndash 299 Overweight 7-11 kg

300 and above Obese 5-9 kg

22

142 Maternal metabolism

As the fetus is dependent on nutrients from the maternal circulation not only the maternal

intake of nutrients but also the maternal metabolism plays a major role in fetal nutrition There

are adaptations to maternal metabolism that occur during pregnancy to ensure that the

increasing nutritional demands of the mother the placenta and the fetus are met Adaptations

are made in the metabolism of all major groups of nutrients

Glucose metabolism in pregnancy

The human fetus is highly dependent on glucose derived from the maternal circulation for

growth and development [2] Changes occur in the maternal glucose metabolism during

pregnancy to ensure that the increasing nutritional demands of the mother the placenta and

the fetus are met Previously published data on glucose metabolism suggested a decrease in

fasting glucose with gestation [37] Fasting glucose levels of pregnant women have been

shown to decline in early pregnancy and thereafter not decrease much further [38] In our

cohort we found fasting glucose to increase slightly with gestational age [39] There is an

increase in basal hepatic glucose production by up to 30 with increasing gestational age

[37] The insulin sensitivity shows a marked change in pregnancy Overall insulin sensitivity

decreases during pregnancy and in late pregnancy a reduction of 50-70 is estimated

compared with non-pregnant women [40] Insulin secretion increases by up to 200-250

[40]

Lipid and amino acid metabolism in pregnancy

The lipid metabolism in pregnancy is characterized by a marked hyperlipidemia Triglyceride

concentration increases and in particular very low-density lipoprotein (VLDL) triglyceride

concentration which increases 3-fold from week 14 to term Plasma cholesterol levels rise to

a lesser degree In obese women the hyperlipidemia is further exaggerated [27] There is an

overall increase in protein synthesis in pregnancy This includes maternal tissues like breasts

uterus and the liver as well as the fetus and the placenta [27]

23

143 Other maternal factors

Age and parity

Both maternal age and parity have an effect on fetal growth Young women especially

adolescents give birth to smaller newborns than older women [41] Birthweight increases with

maternal age until the 30s after which there is a decline resulting an inverse u-shaped curve

[42] Age is however closely linked to parity Birthweight increases with parity and the

largest increment of approximately 200 grams is between the first and second child [43] In

multiple models birth order exerted a greater influence on birthweight than maternal age [42]

The biological explanation behind these associations is only partly understood The effect of

parity may be partly explained by the capacity of the spiral arteries to expand which is higher

in the subsequent pregnancies than in the first pregnancy [44]

Maternal blood supply to the uterus

The uterus receives blood mainly from the uterine arteries which are branches of the internal

iliac artery The uterine arteries branch into thinner vessels first the arcuate arteries then the

radial arteries followed by the basal arteries which continue into the endometrium as the

spiral arteries The spiral arteries undergo remodeling in early pregnancy which means they

loose smooth muscle and elastic tissue from their walls This remodeling of maternal vessels

is a key aspect of early pregnancy and vital for a successful outcome Ultrasound studies have

estimated both the changes in diameters of the uterine artery and the blood flow velocity in

these vessels Several studies have reported that the diameter of the uterine artery increases

approximately 3-4 fold from non-pregnant state to term [4546] The flow velocity increases

with gestational age but reported values differ somewhat depending on whether the

measurements are made on one or both uterine arteries and the laterality of the placenta

[4546] The fraction of the cardiac output that is distributed to the uterus has been estimated

to be 35 in early pregnancy and near 12 at term [46]

24

Figure 2 Blood supply to the uterus

From Grayrsquos Anatomy 20th US edition electronically retrieved from Wikimedia commons

25

15 Placental aspects of fetal growth

151 Development structure and growth of the placenta

Normal placental development and maternal adaptation to pregnancy are crucial factors for a

successful pregnancy The placentation process and maternal adaptation are closely linked and

happen as parallel processes ensuring a healthy outcome for both mother and child Many

complications of pregnancy can be ascribed to defects in early placentation andor inadequate

maternal adaptation to pregnancy Therefore knowledge of these processes is essential in

understanding the pathophysiology of pregnancy complications

The development of the placenta begins as soon as the conceptus reaches the uterus on day 3-

4 after fertilisation By this stage the blastocyst has an outer wall and an inner cell mass The

outer wall consists of trophoblast cells which undergo transformation to either fuse into a

syncytial cell layer or form individual cytotrophoblasts Extra villous trophoblasts are named

so because of their location in the maternal endometrial (decidual) tissue and play an

important role by starting the trophoblast invasion and the adaptation of the maternal vessels

to pregnancy During this process the endometrial stromal cells differentiate into decidual

cells The extra villous trophoblasts migrate through the decidua basalis and into the inner

third of the myometrium aided by a range of proteases that degrade or remodel the maternal

extra cellular matrix

The amnion arises from the inner cell mass and makes contact with the chorion by early

second trimester Lacunae are formed within the syncytiotrophoblast and the lacunar system is

transformed into the intervillous space

The majority of the villous mass forms the placenta whereas the remainder of the villous

tissue begins to regress resulting in the chorion This remodeling ensures that rupture of

membranes and delivering of the baby can occur at birth without tearing through the placenta

This remodeling occurs at the same time as the maternal blood flow starts in the periphery of

the developing placenta

26

Figure 3 The structure of placenta

From Grayrsquos Anatomy 20th US edition electronically retrieved from Wikimedia commons

The villous mass is made up of a tree of branching villi The branches are classified according

to caliber position within the villous tree and function and goes from the larger stem villi via

intermediate villi to the thinner and distal terminal villi In a mature normal placenta stem

villi account for 20-25 intermediate villi approximately 25 and terminal villi around 40

of the total villous volume The maternal-fetal exchange takes place primarily at the

terminal villi and to some extent at the intermediate villi [47]

Figure 4 Terminal villi

Illustration by Oslashystein H Horgmo University of Oslo

27

Figure 5 Development of the placenta

Fertilized egg

blastocyst

Trophoblast

Cytotrophoblasts

Syncytiotrophoblasts

Extravillous

Villous

Inner cell mass

Fetus

Amnion

Yolk sac

-Primary villi

-Secondary villi

-Tertiary villi

-mesenchymal villi

-immature intermediate villi

-stem villi

-mature intermediate villi

-terminal villi

Matu

ratio

n

ofvilli

Angiogenesis

Transformation of

spiral arteries

Placental villi

Modified after Bernischke et al Pathology of the Human Placenta 2012

The syncytiotrophoblast layer covers a surface area of 12-14 m2

at term [48] It is covered by

microvilli which increase the surface area by a factor of five- to seven The

syncytiotrophoblast layer is comprised by two membranes the maternal-facing microvillous

membrane (MVM) and the fetal-facing basal membrane (BM) The syncytiotrophoblasts act

as an epithelium and contain high densities of transporter proteins There are transport

proteins for the major groups of nutrients Glucose transport proteins belonging to the GLUT

family transport glucose across the placenta by facilitated diffusion [49] Amino acids are

transported by transporter proteins by an active process [50] Lipids are mainly transported as

free fatty acids (FFA) by simple diffusion or by specific binding proteins [5152] Transporter

proteins for micronutrients and drug transporters involved in the transport of drugs have also

been identified [5354] The syncytiotrophoblast also transport ions and solutes to maintain

membrane potential and cell volume regulation

28

Figure 6 The syncytiothrophoblast cell

Modified by Oslashystein H Horgmo after SLager J Pregnancy 2012

Growth of the placenta

The placenta grows close to linearly throughout pregnancy [5556] Cytotrophoblast cells fuse

continuously to maintain and expand the syncytiotrophoblast layer Little is known regarding

the control of this coordinated sequence of events After around 32 weeks of gestation the

fetal capillaries and syncytiotrophoblast layer come closer as the syncytiotrophoblast becomes

thinner and free of nuclei and most organelles This thinning of the membrane separating the

maternal and fetal circulations aids gaseous exchange and the membrane is known as the

rdquovasculosyncytial membranerdquo [47] The volume of the terminal villi and hence the surface

area increases exponentially throughout pregnancy a process that appears to be dependent on

branching of the villi and angiogenesis [57] Although the villous tree undergoes continuous

growth and differentiation during pregnancy relatively little is known about the regulation of

this process Maternal factors like prepregnancy BMI and GWG have been shown to be

associated with placental growth measured both as placental weight thickness and area [58]

Little is known about fetal factors that may affect placental growth Studies in mice do

however indicate that the fetus itself influences the functional properties of placenta [59]

29

152 Placental functions

The placenta has a range of important functions to ensure a successful pregnancy outcome

including transport of nutrients and gases metabolism and endocrine and protective

functions

Transport of nutrients and gases

a Transport of gases

Oxygen provided by the maternal blood is transferred to the fetal circulation by diffusion

Carbon dioxide and other waste products are removed from the fetus and transported to the

mother by the placenta [9] Chronic exposure during pregnancy to hypoxia as seen at high

altitudes is associated with reduced fetal growth [60] However comparisons of fetal oxygen

extraction between pregnant women at high altitude (3600 m) and sea level (400 m) showed

that the fetus had the ability to adapt and to increase oxygen extraction [60] Studies on

pregnant sheep in vivo showed the O2 consumption per kg of the fetus to be twice that of an

adult and the uteroplacental tissues to consume four-fivefold that of the fetus [61]

b Transport of nutrients

Glucose

Glucose is the primary energy source for the fetus As the fetus to a very limited degree

produces its own glucose the fetus needs to obtain glucose from the maternal circulation

Glucose is transported from the maternal circulation across the syncytiotrophoblasts of the

placenta by facilitated diffusion [49] The syncytiotrophoblast is the main barrier in the human

placenta and is comprised by two cell membranes the maternal-facing microvillous

membrane (MVM) and the fetal-facing basal membrane (BM) The glucose transporters found

in the human placenta belong to the GLUT-family of which there are multiple isoforms The

GLUT 1 is the predominant transport protein in the human placenta at term and is found in

higher concentration on the microvillous membrane than the basal membrane [49] Glucose

transport across the endothelial layer is not well studied

30

The maternal-fetal glucose transfer depends on several factors

Glucose supply Glucose supply is determined by both maternal blood glucose

concentration and blood flow to the placenta

Placental glucose metabolism The placenta not only transfers glucose to the fetus but

consumes considerable amounts of glucose itself Insight into the placental glucose

transfer and metabolism is largely based on data from animal studies in particular on

pregnant sheep Placental glucose consumption is normally very high Estimates

suggest that the placenta consumes about 50 of the glucose extracted from the

maternal circulation [62] Placental glucose metabolism can be altered as a result of

alterations in the supply of other energy-generating substrates like oxygen Hypoxic

conditions has been suggested to increase glucose consumption in the placenta thus

making less glucose available to the fetus [63]

The total surface area of the membranes

Placental glucose transporter density and functions [64]

Maternal-fetal glucose gradient The maternal glucose concentration is higher than the

fetal concentration which creates a maternal-fetal gradient This gradient is thought to

be the driving force for the transfer of glucose from the mother to the fetus The

maternal and fetal glucose concentrations are closely related [65ndash67] The gradient

increases with gestation and so does the placental transport capacity Together this

ensures that placental glucose transfer to the fetus is increased which is needed to meet

the increasing needs of the growing fetus A lower fetal glucose concentration leads to

a larger maternal-fetal glucose concentration gradient which increases transfer of

glucose to the fetus In IUGR fetuses the glucose level is lower which creates a larger

gradient and hence increases the transfer of glucose [66] The regulation of fetal

glucose utilization in humans is only partially understood but has been studied in

more detail in pregnant sheep In sheep the rate of fetal glucose utilization depends on

the interaction between fetal plasma glucose and insulin concentrations and the supply

of glucose to the fetus [61] Fetal glucose uptake seems to be regulated by fetal glucose

concentration rather than maternal supply [68]

Insulin Maternal insulin is not transferred across the placenta The major glucose

transport protein in the human placenta at term is GLUT 1 which does not have

insulin receptors [64] The fetal pancreas develops in the first half of pregnancy and

31

sheep experiments have shown that by mid-gestation measurable insulin is produced

[69] Fetal insulin secretion consists of both basal secretion and glucose-stimulated

secretion Studies on pregnant sheep have revealed that both basal and glucose-

stimulated insulin secretion increases over gestation and responds to changes in fetal

glucose concentration as well as duration and pattern of change Chronic marked

hyperglycemia in sheep gave down-regulation of both glucose-stimulated and basal

insulin secretion whereas pulsatile hyperglycemia increased fetal insulin secretion

[7071] Hypoglycemia has been shown to decrease basal- and glucose-induced insulin

secretion [72] Insulin is an important growth hormone in utero and deficiency of

insulin leads to growth restriction in the fetus Fetal hyperinsulinaemia leads to

increased weight gain particularly in species with a high body fat content at birth like

the humans [73] The mechanism in which insulin stimulates fetal growth is in part

thought to be its anabolic effects on glucose and amino acid metabolism through

increased cellular uptake of glucose that maximizes the transplacental concentration

gradient for glucose and hence increases transport of glucose across the placenta

Lipids

Fatty acids are necessary for the fetus for various purposes as a source of energy as elements

of cellular membranes and for development of tissues and organs Maternal triglycerides (TG)

have been suggested as a more important source of fatty acids than nonsesterified fatty acids

(NEFAs) TG are hydrolyzed by placental lipases (lipoprotein lipase) to free fatty acids which

can diffuse freely across the placenta or be taken up by the placenta via fatty acid transport

proteins [51] Total levels of fatty acids are lower in the fetal than the maternal circulation but

the fatty acid profile is different with higher proportions of long chain polyunsaturated fatty

acids [9]

Amino acids

Fetal plasma amino acid concentrations are higher than maternal concentrations Amino acids

are taken up against a concentration gradient by secondary active transport systems in the

MVM More than 20 amino acid transport systems are expressed in the human placenta [74]

These are categorized as heterodimeric (eg system L) or monomeric (eg system A) Amino

32

acids are required by the fetus for protein synthesis but can also be metabolized by the fetus

[9] Reduced fetal plasma concentration of a number of amino acids have been reported in

studies of IUGR [75]

c Endocrine functions

The placenta metabolizes a number of substances and releases metabolic products into the

maternal andor fetal circulations The placenta thus has endocrine paracrine and autocrine

functions There are numerous hormones that are produced by the placenta in order to

maintain and regulate pregnancy [9]

Estrogen

Estrogens are produced by the syncytiotrophoblasts in large amounts during pregnancy 80-

90 of the the steroids produced in the placenta are secreted into the maternal blood The

fetus is the main source of the precursors used for production of estrogens and they are

produced in the fetal adrenal gland and the fetal liver [76] The estrogens act as specialized

growth hormones for the reproductive organs of the mother [9]

Progesterone

Progesterone is produced by the corpus luteum in the first weeks of pregnancy and later by

the trophoblasts in the placenta The plasma levels increase throughout pregnancy

Progesterone is synthesized largely from maternal plasma low density lipoprotein (LDL)

cholesterol The fetus contributes few or no precursors for progesterone synthesis In normal

pregnancy there is little de novo synthesis of progesterone in the fetus The progesterone

preferentially enter the maternal circulation and very little crosses to the fetus [76]

Progesterone inhibits uterine contractions

Human Chorionic Gonadotropin (HCG)

HCG is a glycoprotein which is structurally similar to Luteinizing Hormone (LH) Follicle

Stimulating Hormone (FSH) and Thyroid Stimulating Hormone (TSH) and is mainly

33

synthesized in the syncytiotrophoblasts HCG enters the maternal circulation at the time of

implantation and is detectable in maternal plasma and urine The concentration peeks at week

8-10 of pregnancy after which it declines The biological function is believed to be

maintenance of the corpus luteum stimulation of fetal testicular testosterone secretion and

stimulation of the maternal thyroid gland [76]

Human Placental Lactogen (HPL)

HPL is a polypeptide which is structurally similar to human growth hormone and human

prolactin It is mainly produced by the syncytiotrophoblasts It is detectable in the maternal

circulation by week 5 and rises steadily and approximately proportional to placental mass

until week 34-36 There is little HPL detectable in maternal urine or in fetal plasma HPL

participates in metabolic processes by stimulating lipolysis HPL thereby functions primarily

to ensure nutrient supply to the fetus by efficient mobilization of maternal tissue stores [76]

34

16 Sexual dimorphism in fetal growth and placental function

There are well-known sex specific differences in fetal growth Birthweight of boys is

generally higher than that of girls Body composition also differs boys being longer and

having larger head circumference than girls whereas girls have higher fat percentage than

boys [16] Fetal-placental weight ratio is greater in boys than in girls indicating a higher

placental efficiency among boys [77] Male fetuses grow faster than girls in utero and one

study reported that the difference was statistically different from week 28 onwards [78] Boys

outnumber girls at birth A study from the Norwegian Birth Registry (MBR) found a ratio of

106 among all births This ratio was higher among births in lower gestational age groups as

high as 248 in 16-19 weeks of gestation [79] Similar findings have been reported in multiple

populations [80] Perinatal mortality is generally higher in boys than in girls and in the study

from MBR of Norway it was approximately 20 higher in boys than girls across the whole

range of gestational age groups [79] Attempts have been made to explain the increased

vulnerability observed in boys by sex specific differences in the developmental environment

including possible differences in placental functions Although there are obvious differences

in fetal growth to my knowledge there are no published data on sex specific differences in

nutrient transport across the placenta However there are reports on sex specific differences

in other aspects of placental function especially related to inflammatory responses and

endocrine functions In pregnancies complicated with maternal asthma there was increased

cytokine production in male placentas compared to female placentas [81] Differences in

cytokine production have been suggested to contribute to the observed increased incidence of

preterm delivery in males [82] Glucocorticoids given as repeated doses have been shown to

reduce fetal growth [83] Data suggest that the male and female fetal-placental unit responds

to cortisol in a differential manner Among pregnant women with asthma there were similar

levels of maternal cortisol but female fetuses responded with a reduction in birthweight

whereas the growth of the male fetuses was normal [84] Data on placental properties from

male and female are generally pooled but significant findings may be lost as male placentas

might have different responses than female placentas The different strategies to cope with

the same maternal environment has been summarized by V Clifton [84] She proposed that

male responses lead to minimal placental adjustment in gene and protein expression and that

the target is to increase or continue growth resulting in a greater risk of adverse outcome

Females on the other hand have multiple adaptations in placental gene and protein expression

and minor reduction in growth resulting in increased survival

35

17 Preeclampsia

Preeclampsia is defined as new onset hypertension (blood pressure gt14090) and proteinuria

(gt03 g per 24 hours) in the second half of pregnancy [85] This pregnancy complication

affects between 3 to 5 of all pregnancies depending on the population Preeclampsia is a

leading cause of mortality and morbidity for both mother and child worldwide particularly in

the developing world Worldwide preeclampsia accounts for more than 50 000 maternal

deaths annually [86] Risk factors include genetic factors multiple pregnancies high maternal

age obesity insulin resistance preexisting hypertension diabetes mellitus and renal disease

[87] Around 70 of cases of preeclampsia occur after 37 weeks of gestation [88]

Clinical picture

The symptoms of preeclampsia are diverse reflecting the underlying syndrome The systemic

vascular involvement is reflected not only in hypertension and proteinuria but can likewise

affect the vasculature in other organs like the liver and the brain When the liver is involved

symptoms and signs include abdominal pain nausea vomiting and elevated liver enzymes In

the case of HELLP (hemolysis elevated liver enzymes and low platelets) all these are present

along with the disturbances in the coagulation system In case of brain involvement visual

disturbances and eclampsia can occur Cerebrovascular complications like stroke and cerebral

hemorrhage are other feared maternal complications The fetus of preeclamptic pregnancies

faces increased risk of oligohydramnios IUGR and prematurity [89]

Classification

Preeclampsia has both a multifactorial pathogenesis and a heterogeneous clinical presentation

which complicates classification Classifications in use are according to pathophysiological

characteristics clinical severity presence of other maternal or fetal characteristics or

gestational age at presentation Classification based on pathogenesis suggests two broad types

of preeclampsia placental and maternal preeclampsia reflecting which element is more

prominent in the pathophysiology These subtypes are more of a theoretical framework than

different biological entities as most cases will rather be represented by a combination of both

The dichotomized pathophysiological classification can briefly be described as placental

preeclampsia when there is an abnormal placentation but basically a normal maternal

36

endothelium and maternal preeclampsia when the maternal endothelium is dysfunctional and

the placentation normal Classification according to severity of disease is used by American

College of Obstetrics and Gynecology (ACOG) Severe preeclampsia is defined as

hypertension (gt160110) and proteinuria (gt5 g per 24 hours or +3 on dipstick) or

accompanying symptoms and signs like oliguria cerebral disturbances impaired liver

function thrombocytopenia or fetal growth restriction [85] Early onset preeclampsia is often

defined as presentation before 34 weeks and late onset as after 34 weeks of gestation These

subtypes have different clinical presentations with the early-onset typically exhibiting more

serious clinical featuressymptoms and fetal growth restriction than the late onset [90]

Pathophysiology

Clinical symptoms of preeclampsia arise in the second half of pregnancy which can be

considered the last stage in the development of the disorder The preceding stages include the

placentation process which involves an immunologically regulated interaction between the

placenta and the maternal endothelium Placenta is necessary for the development of

preeclampsia but preeclampsia can occur without a fetus as in hydatidiform mole The

symptoms disappear after delivery of the placenta In preeclampsia the trophoblast invasion is

restricted to the decidua and does not reach the inner third of the myometrium resulting in

inadequate remodeling of spiral arteries The normal loss of smooth muscle and enlargement

of the spiral arteries is therefore restricted

Normal placentation further requires immune tolerance for fetal and placental antigen which

might be altered in preeclampsia There is a low-grade systemic inflammatory response

present in normal pregnancy which is enhanced in preeclampsia [91] The maternal

endothelium becomes activated and eventually dysfunctional Preexisting maternal vascular

dysfunction might render the maternal endothelium more sensitive to the burden of these

factors leading to endothelial dysfunction

Disturbed endothelial maintenance

In patients with preeclampsia there is an angiogenic imbalance in the circulation resulting in

more anti-angiogenic than angiogenic factors ie more of endothelium-disturbing and less

endothelium-supportive factors The vascular endothelial growth factors (VEGF-family) are

37

involved in angiogenesis and endothelial maintenance by affecting migration and

differentiation of endothelial cells [92] The family consists of several glycoproteins

including VEGF-A and PlGF among others Both of these have pro-angiogenic effect The

VEGF receptors are present on vascular endothelial cells and include VEGFR-1 (Flt-1) and

VEGFR-2 (KDR) VEGF binds to both receptors whereas PlGF binds exclusively to VEGFR-

1 (Flt-1)

Figure 7 Angiogenic imbalance

sFlt-1

sFlt-1 is a soluble form of the VEGFR-1 produced by alternative splicing [93] Placentas from

preeclamptic pregnancies show higher expression of sFlt-1 mRNA than normal placentas [94]

How much placenta actually contributes to the circulating sFlt-1 is however not settled sFlt-1

binds free VEGF and free PlGF and thereby inhibits their beneficial actions on the vascular

endothelium sFlt-1 increases with gestational age in normal pregnancy but is significantly

higher in women destined to develop preeclampsia from approximately week 26 and peaks

around week 34 [95]

38

sEndoglin

The transforming growth factor-β (TGF- β) family of proteins is known to be involved in

angiogenesis but has diverse actions in many cells Endoglin is a TGF-β coreceptor expressed

in endothelial cells and syncytiotrophoblasts of the placenta [87] A soluble form of endoglin

(sEng) is present in sera from preeclamptic patients There is a three- five- and tenfold

increase in sEng in mild PE severe PE and HELLP syndrome respectively [96] Endoglin

mRNA expression in placentas from preeclamptic pregnancies is fourfold increased compared

to healthy pregnancies [96] But again the placental contribution to circulating sEng is

unclear sEng increases with gestational age but in women destined to develop preeclampsia

the increase is significantly higher than healthy controls from week 23 (preterm PE) and week

30 (term PE) Interestingly women destined to deliver a SGA infant had increased sEng

levels from week 10 [95]

sEng and sFlt-1 given together increased capillary permeability in the lungs liver and kidney

of mice and induced hypertension in pregnant rats [96] demonstrating a possible combined

action of sFlt-1 and sEng in the pathogenesis of PE

PlGF

Placental growth factor is one of the members of the VEGF-family which has proangiogenic

activity [92] In non-pregnant women circulating levels are low but PlGF can be produced by

the heart and lungs skeletal muscle and adipose tissue PlGF is expressed by the placenta in

particular the syncytiotrophoblasts [97] In pregnancies complicated by preeclampsia PlGF

concentrations are lower than normal pregnancies [98] In normal pregnancy PlGF can be

detected from first trimester and increases until around week 33 after which it declines

towards term PlGF binds to the VEGFR-1 (Flt-1) receptor PlGF is necessary to stimulate

angiogenesis eg after myocardial injury The function of PlGF in pregnancy is not clear but

might be to regulate maternal vascular function by displacing VEGF from the Flt-1 receptor

so that it binds to the more active Flt-2 receptor (KDR) [87]

39

Figure 8 Endothelial integrity and dysfunction

VEGF

PlGF

Flt1

(VEGFR-1)

VEGF

PlGF

Endothelial integrity

Tore Henriksen 2006

VEGF

PlGF

Flt1

(VEGFR-1)

VEGF

PlGF

Endothelial dysfunction

Tore Henriksen 2005

Treatment

There is no causal treatment besides delivery of the baby and the placenta Symptomatic

antihypertensive treatment should be given to reduce maternal complications [85]

Preeclampsia can be complicated by eclampsia stroke disseminated intravascular coagulation

(DIC) HELLP placental abruption and acute renal failure Because the only treatment is

delivery preeclampsia leads to prematurity and increased risk of perinatal mortality and

morbidity

Prevention

40

Studies assessing interventions to reduce rate or severity of preeclampsia have been

conducted There is insufficient evidence to recommend rest reduced salt intake fish-oil

supplementation and antioxidant vitamins as preventive measurements [99] A Cochrane

review concluded that low-dose aspirin had small to moderate benefits (15 risk reduction)

when used for prevention of preeclampsia but that more information is needed to assess

which women are most likely to benefit when to start treatment and at what dose [100]

Calcium supplementation reduced risk of preeclampsia and can be considered for high risk

groups in low-intake populations [101]

Prediction

Many features of preeclampsia are exaggerated responses also present in normal pregnancies

In terms of diagnosis or prediction it is difficult to draw a clear distinction between normal

and abnormal No test predictive or diagnostic can be expected to distinguish absolutely

between different degrees of features that are common to all pregnancies Many tests have

been assessed as potential predictors of preeclampsia but no single test has yet met the

clinical standards for a predictive test Combinations of tests such as ultrasound assessment of

uterine artery Doppler waveforms and serum markers have been suggested as have ratios of

antiangiogenic and proangiogenic factors However sensitivity and specificity of the markers

PlGF sFlt-1 and sEng are too poor for accurate identification of preeclampsia in clinical

practice and hence not recommended used alone for the prediction of preeclampsia [102]

Predictive tests could ideally either identify those destined to develop preeclampsia during

pregnancy or differentiate between a serious or mild form among those diagnosed with

preeclampsia The latter would be of clinical importance in handling these patients

Long-term complications

Risk of recurrent preeclampsia depends on severity and onset of preeclampsia in the previous

pregnancy but can be up to 40 for severe disease [103] Women with a history of

preeclampsia have an elevated risk of cardiovascular disease later in life According to a

meta-analysis the risk of hypertension is 3-4 times the risk for women without preeclampsia

41

and the risk of death from cardiovascular and cerebrovascular disease about twice as high as

in women without preeclampsia [104] The mechanisms for the increased risk are not yet fully

understood but shared risk factors for preeclampsia and cardiovascular disease may jointly

predispose [105] This could be the case for chronic hypertension diabetes mellitus and renal

disease

42

2 Aims of the study

Overall aim

The overall aim of this thesis was to gain insight into the associations between maternal

nutritional and metabolic factors and fetal growth and aspects of placental function in normal

and preeclamptic pregnancies

Specific aims

Paper 1

The aims were to

1) Estimate and compare the effects of maternal characteristics on birthweight and on fetal

growth in third trimester

2) Introduce placental weight as a possible determinant of birthweight and of fetal growth in

third trimester

We hypothesized that maternal factors and placental size were associated with birthweight

and fetal growth

Paper 2

Given the findings in Paper 1 the aim was to study the effects of maternal factors (parity

BMI gestational weight gain and fasting glucose) on placental weight stratified by fetal sex

We hypothesized that the maternal factors mentioned above affected placental weight Based

on emerging evidence we also hypothesized that there were differential effects between fetal

sexes

Paper 3

Based on the observations in Paper 1 and 2 the aims were to

1) Establish an in vivo model in the human

2) To use the model to study human placental transfer of glucose in vivo to describe the

glucose and insulin concentrations in the uteroplacental and umbilical circulation in healthy

43

pregnancies at term and to explore the relation between maternal and fetal glucose

concentrations

We hypothesized that maternal plasma glucose was the major determinant of the fetal venous-

arterial gradient

Paper 4

Preeclampsia is a pregnancy specific placenta dependent disorder Preeclampsia has two

prominent features maternal vascular dysfunction and placental insufficiency Using the in

vivo model the aim was to investigate factors that may link placental disturbance to maternal

vascular dysfunction For this purpose sFlt-1 and sEng were chosen

We hypothesized that both sFlt-1 and sEng originate in placenta by finding that the plasma

concentration was higher in the maternal venous than the arterial side of the uteroplacental

circulation

44

3 Materials and methods

This thesis consists of four papers based on two separate studies that differ in design

population and methodological issues and will therefore be described separately

The STORK study

The STORK study is a prospective longitudinal study performed in the period 2001-2008 A

total of 1031 healthy pregnant women who gave birth at Oslo University Hospital

Rikshospitalet Norway and their newborn infants were included in the study Inclusion

criteria were healthy women of Scandinavian heritage with singleton pregnancies Exclusion

criteria were multiple pregnancies known pregestational diabetes and any severe chronic

diseases (lung cardiac gastrointestinal or renal) as well as any malformations discovered at

the routine ultrasound examination at week 17-19

Population

Eligible women were identified by one of the three PhD candidates in the project Invitation to

participate was sent to eligible women as they were registered for obstetric care at the

beginning of pregnancy Those interested in participating confirmed by phone to a secretary

who enrolled them in the study The number of women invited to participate varied over time

due to capacity The capacity for the oral glucose tolerance test (OGTT) was the ldquorate-limiting

steprdquo The drop-out rate was very low 33 of those who were included Thirty-two women

were excluded because of twin pregnancies or malformations that were diagnosed at the

routine ultrasound scan

45

Figure 9 Flow chart showing inclusion of participants in the STORK study

Withdrawn before

inclusion

n=141

Excluded

n=32

Lost

n=37

Invited to participate

n=4122

Accepted invitation

n=1241

Included

n=1100

Followed up

n=1031

Study design

The STORK study has a longitudinal design Each pregnant woman had four antenatal visits

(visit 1-4) scheduled at weeks 14-16 22-24 30-32 and 36-38 of pregnancy The newborns

were examined shortly after birth

Data collection

Clinical data

Background data was collected at the first visit including past medical and obstetric history

Clinical examination was repeated at every visit Data on the delivery and postpartum period

were extracted from hospital records

Blood samples

Blood samples were drawn at each visit between 0730 and 0830 after an overnight fast

centrifuged and stored at -80ordm C immediately Plasma glucose was measured by Accucheck

(Roche Diagnostics Mannheim Germany)

46

Birthweight

Newborns were weighed on a calibrated scale and measured by the attending midwife or

childrenrsquos nurse within two hours after birth

Ultrasound

Ultrasound examinations were done at visit 2 - visit 4 using an Acuson Aspen machine

(Acuson Mountain View CA USA) Biometric measurements included head circumference

(HC) abdominal circumference (AC) and femur length (FL) Each measurement was made

three times and the mean value was calculated and used in the analyses Estimated fetal

weight (EFW) was calculated by Combs formula [106] Percentiles for estimated fetal weight

and the individual biometric measurements were calculated according to Norwegian charts

[107108] Fetal growth in the third trimester was calculated as the difference between

measurements made at visit 3 and visit 4 for EFW and HC AC or FL respectively

Table 1 Data collection in the STORK study

Statistical analysis

Descriptive statistics were used to characterize the study population Bivariate associations

were explored by scatter plots and correlation analyses Univariate linear regression was used

to study the associations between selected maternal characteristics and the dependent

variablesoutcome variables birthweight and several fetal growth parameters in Paper 1 and

placental weight in Paper 2 Variables with a p-value lt 01 were considered in the multiple

linear regression models Multiple linear regression models were used to study the

Visit 1

14-16 w

Visit 2

22-24 w

Visit 3

30-32 w

Visit 4

36-38 w

At birth

Clinical examination + + + + +

Anthropometric measures

(skin fold thickness)

+ + + + +

Fasting blood samples + + + +

Oral glucose tolerance test + +

Ultrasound

(evaluation of fetal growth)

+ + +

Diet questionnaire + +

Physical activity questionnaire + +

47

associations between selected maternal characteristics and the outcome variables birthweight

fetal growth and placental weight A p-value lt 05 was considered statistically significant

All analyses were done by SPSS 180

Ethical aspects

All participants signed a written consent The study was approved by The Regional

Committee for Ethics South Norway (S- 01191)

48

The STORK-Placenta study

Study design

The STORK-Placenta study was designed to serve several purposes One purpose was to

study placental aspects of fetal growth and this was done as a cross-sectional study among

healthy pregnant women Secondly the study served as a case-control study with two groups

one consisting of preeclamptic patients and one with healthy controls

Population

There are two subgroups of the STORK-Placenta study in Paper 3 and Paper 4 respectively

In Paper 3 we included 40 women Inclusion criteria were healthy non-smoking women with

uncomplicated singleton pregnancy who were scheduled for elective caesarean section

Exclusion criteria were pre-existing co-morbidity any medication and pregnancy

complications like preeclampsia or insulin-dependent gestational diabetes Women who

arrived at the delivery ward with contractions prior to scheduled caesarean section were

excluded The recruitment was done at the out-patient clinic either during the appointment

when caesarean section was decided or during scheduled preoperational information

In paper 4 we included 12 patients with preeclampsia and 7 healthy pregnant women

Inclusion criteria for the study group were the diagnosis of preeclampsia and indication for

caesarean section prior to labour The control group consisted of healthy pregnant women

scheduled for elective caesarean section

Data collection

Medical and obstetrical history was taken at inclusion Clinical data was collected at inclusion

and at the day of delivery

Blood sampling

Blood samples were drawn from both the maternal and the umbilical (fetal) circulation during

caesarean section in spinal anaesthesia Fasting maternal blood samples were obtained by the

obstetrician from the uterine vein preferable on the same side as placenta just before uterine

49

incision Simultaneously blood was drawn by the anaesthesiologist from an arterial line in the

radial artery We assumed similar blood composition in the radial and the uterine artery In

addition blood was drawn from a venous catheter in the cubital vein or dorsal vein network of

the hand Directly after delivery blood samples were obtained from the umbilical artery and

vein immediately after cord clamping Blood was drawn into SAFETY Blood Collection Set

with Luer Adapter (Vaccuette Geiner Bio-One GmbH Austria) Blood samples were

immediately transferred to ethylenediaminetetraacetic acid (EDTA) vacutainers and stored on

ice until all samples were obtained They were then centrifuged at 4-6ordmC 2500 G for 20

minutes before the supernatants were removed and aliquotted and stored at -80ordmC until

analyses were performed

Analyses of samples

Glucose and insulin

Analyses were performed according to standard laboratory methods (Department of Medical

Biochemistry Oslo University Hospital Rikshospitalet) during three consecutive days

Glucose was measured using the hexokinaseglucose-6-phosphate dehydrogenase method

(Roche) Insulin was analysed using the Elecsys insulin analysis which is an enzyme-linked

immunosorbant assay (ELISA) technique with two monoclonal antibodies (Roche)

sFlt-1 and sEng

The concentrations of sFlt-1 and sEng were measured by commercially available ELISA kits

(RampD Systems Minneapolis MN USA) Assays were conducted in duplicate and in one run

The coefficients of variance were lt 10

50

Statistical analyses

Descriptive data were reported as mean values with standard deviations (SD) or percentages

as appropriate The differences in maternal characteristics between groups were compared by

unpaired t-test (Paper 4)

Glucose values were reported as mean values (SD) Comparisons between concentrations of

glucose in maternal and fetal vessels respectively were performed by paired t-tests Due to

skewed distributions insulin concentrations were reported as median values with inter quartile

ranges (IQR) and comparisons of related samples were performed by Wilcoxon sign rank test

Correlations were reported as Pearsonrsquos correlation coefficient if one variable was normally

distributed whereas Spearmanrsquos rank correlation coefficient was used in the case of

correlation between two skewed variables

The distribution of the concentrations for sFlt-1 and sEng were not normally distributed

hence they were log transformed to obtain normal distribution in order to use parametric

methods for statistical analyses Arithmetic median levels are reported in the text and figures

The differences in concentrations between groups were compared by unpaired t-test and the

concentrations in the radial artery and uterine vein from the same individual were compared

by paired t-test However non-parametric tests on the original data gave the same results

Ethical aspects

All participants signed a written consent The study was approved by The Regional

Committee for Medical Research Ethics South Norway (S-071742011-2419)

51

4 Summary of results

Paper 1

In Paper 1 we analyzed the associations between selected maternal characteristics and

birthweight measured as z-scores adjusted for gestational age and fetal sex We found that the

following maternal characteristics were independent determinants of birthweight and

statistically significant in the multiple regression model

Parity (B 046 95 CI 033-059 plt0001)

BMI (B 0048 95 CI 003-006 plt0001)

Gestational weight gain (B 006 95 CI 004-008 plt0001)

Fasting glucose (B 033 95 CI 018-048 plt0001)

In addition placental weight was a determinant for birthweight

Placental weight (B 041 95 CI 038-044 plt0001)

Adjusting for placental weight in the multiple model left the following maternal determinants

statistically significant

Parity (B 036 95 CI 025-047 plt0001)

BMI (B 0018 95 CI 0004-003 p= 0012)

Gestational weight gain (B 0036 95 CI 002-005 plt0001)

Fasting plasma glucose (B 022 95 CI 0009-034 plt0001)

Introducing placental weight as a covariate reduced the effect estimate of the other variables

in the model by 62 for BMI 40 for weight gain 33 for glucose and 22 for parity

The magnitude of reduction was estimated by change in the regression coefficient B of the

linear regression

Fetal growth in third trimester was estimated as the difference in EFW percentiles between

visit 3 and visit 4

In the multiple model the following maternal determinants remained statistically significant

Parity (B 473 95 CI 016-807 p=0006)

BMI (B 064 95 CI 023-106 p=0002)

Gestational weight gain (B 070 95 CI 024-116 p=0003)

52

In addition placental weight was a determinant for intrauterine growth

Placental weight (B 260 95 CI 16-36 plt0001)

Adjusting for placental weight in the multiple model left the following determinants

significant

Parity (B 39 95 CI 075-70 p=0015)

BMI (B 049 95 CI 008-089 p=002)

Gestational weight gain (B 060 95 CI 015-106 p=001)

Introducing placental weight reduced the effect of BMI on intrauterine fetal growth by 23

weight gain by 17 and parity by 14

We also analyzed the associations between maternal factors and the individual biometric

measurements Results from the multiple analyses for the increase in abdominal

circumference showed statistically significant associations for

Parity (B 018 95 CI 007-029 p=0001)

BMI (B 0022 95 CI 0005-003 p=0002)

Gestational weight gain (B 0026 95 CI 0008-004 p=0001)

Fasting glucose (B 044 95 CI -008-017 p=048)

In addition placental weight was a determinant for increase in abdominal circumference

Placental weight (B 011 95 CI 008-014 plt0001)

In the multiple model adjusting for all listed variables and placental weight fasting plasma

glucose was not significant (B 0016 95 CI -011-014 p=08) BMI reached borderline

significance (B 0014 95 CI 000-0028 p=0048) as an independent determinant when

adjusted for parity weight gain and placental weight For growth of the fetal abdominal

circumference BMI showed the largest reduction in B (36 ) when placental weight was

included

53

Paper 2

Given the importance of placental weight for birthweight and fetal growth we studied the

associations between maternal factors and placental weight in Paper 2 Mean placental weight

was 711 g (SD 156)

In the multiple regression model the following maternal factors were independent

determinants of placental weight

Parity (B 292 95 CI 101-484 p=0003)

BMI (B 67 95 CI 41-93 plt0001)

Gestational weight gain (B 56 95 CI 28-84 plt0001)

Fasting glucose (B 329 95 CI 100-557 p=0005)

Boys were heavier (3667 g vs 3494 plt0001) and longer (513 cm vs 503 cm plt0001)

than girls Boys also had a higher fetal placental ratio than girls (526 g vs 508 plt0001)

When stratified by fetal sex fasting glucose was significantly associated with placental

weight in females but not in males

Paper 3

We measured glucose and insulin concentrations in the uteroplacental and umbilical

circulations and calculated arterio-venous gradients The subjects were 40 healthy women

with a mean age of 36 years (SD 32) Mean birthweight was 3571 (SD 527) g range 2680-

4955g

The highest concentration of glucose was found in the maternal arterial circulation with a

mean concentration of 471 mmoll (SD 048) The uterine vein had a lower concentration

giving an arterio-venous difference of 029 mmoll on the maternal side The maternal

concentration of glucose was higher than the fetal concentration The maternal-fetal gradient

was 122 mmoll (SD 042) The concentration in the umbilical vein was 384 mmoll (SD

041) In the umbilical artery the concentration was lower 348 mmoll (SD 045) giving a

fetal venous-arterial difference of 038 (SD 031)

54

Maternal arterial and fetal venous concentrations of glucose were highly correlated (r=086

plt0001) Maternal arterial glucose concentration was not significantly correlated to the fetal

glucose v-a difference (r=03 p=007) The maternal a-v glucose difference was neither

correlated to the level of glucose in the umbilical vein nor the fetal glucose difference The

maternal-fetal gradient was highly correlated to the fetal glucose difference (r=08 plt0001)

The maternal-fetal glucose gradient was also correlated to the glucose concentration in the

umbilical artery (r=-038 p=0017) whereas it was not correlated to the glucose concentration

in the umbilical vein Similarly the fetal glucose v-a difference was only correlated with the

glucose concentration in the umbilical artery (r=-045 p=0004) but not with the glucose

concentration in the umbilical vein

The glucose concentration in the umbilical vein was not correlated to birthweight or placental

weight whereas correlation between the fetal glucose v-a difference and birthweight just

reached borderline significance (r=032 p=0049)

We found no relation between maternal and fetal insulin values (rho=-01 p=057) Maternal

and fetal concentrations of insulin were not statistically different On the maternal side

glucose and insulin concentrations were correlated (r=052 p=0001) On the fetal side

however no such correlation was found (r=012 p=048) Fetal insulin was correlated to both

placental weight (r=046 p=0003) and birthweight (r=058 plt0001)

Paper 4

We measured the anti-angiogenic factors sFlt-1 and sEng in a group of preeclamptic patients

and in healthy controls Both factors have been suggested to be released by the placenta and

involved in the pathogenesis of preeclampsia

Preeclamptic women had

Higher concentration of sFlt-1 than healthy controls (median of 17450 pgml of sFlt-1

compared to 5055 pgml in the control group p= 0003)

Higher concentration of sEng than healthy controls (median of 687 ngml in the

preeclampsia group versus a median of 287 ngml in the control group p= 0003)

55

We compared the concentration in the blood entering the uteroplacental unit (radial artery as a

proxy for uterine artery) and the blood leaving the uteroplacental unit (uterine vein)

Preeclamptic women had

Higher concentration of sFlt-1 in the uterine vein than in the radial artery (22450 vs

17450 pgml p=0005) whereas the concentration of sEng was not statistically different

(757 vs 687 ngml p=012)

Among healthy controls

No significant differences in the concentration between the uterine vein and the radial

artery for sFlt-1 (6193 vs 5055 pgml p=039)

No significant differences in the concentration between the uterine vein and the radial

artery for sEng (307 vs 287 ngml p=059)

56

5 Discussion

51 Methodological issues STORK

511 Design

The STORK study has a longitudinal design with four antenatal visits and observations at

birth for the 1031 women and children included Longitudinal studies are well suited to study

associations between explanatory variables and outcomes but not suitable to assess causality

The associations found in our study would need to be tested in a RCT or experimental model

to assess causality

512 Validity

The word valid is derived from the Latin validus meaning strong Validity in terms of

research refers to whether the results obtained answer the questions asked in the study

Validity can further be divided into internal and external validity [109]

Internal validity

Internal validity refers to whether the conclusions reached are likely to be correct for the

circumstances of that particular study Bias undermines the internal validity and includes

selection bias information bias and confounding bias [110]

Selection bias

Selection bias can result when the selection of subjects into a study (subject selection bias) or

their likelihood of being retained in the study (loss to follow up bias) leads to a result that is

different from what you would have obtained if you had enrolled the entire target population

[110]

57

Subject selection bias

In the current study invitation to participate was sent to 4122 and 1241 accepted the invitation

The number of invitations sent per week varied according to the capacity to enroll in the study

and the limiting factor was four Oral Glucose Tolerance Tests per day There were periods of

reduced capacity like holidays when fewer invitations were sent but it is not likely that the

women invited would be any different to the ones not invited due to varying capacity

The self-selection procedure (the women themselves phoned to be enrolled) might have

resulted in selection of women that were particularly motivated to participate The opportunity

to get closer follow-up than standard antenatal care may have caused selection bias Three

evaluations of fetal well-being and fetal growth by ultrasound could theoretically have

attracted women with a previous history of fetal growth abnormalities Data on birthweight of

previous children revealed that for those who had one previous child average birthweight was

3655 g (SD599) whereas the second child on average weighed 3808 g (SD 706) The data was

normally distributed with no overrepresentation of SGA or LGA (data not shown) Thus there

was no obvious selection of women with a history of fetal growth abnormalities in our study

population

Loss to follow up bias

The number of patients lost was 37 giving a drop-out rate of only 33 The number of

patients excluded was 32 The numbers lost are small and not likely to have influenced the

results substantially All participants had birthweight and placental weight recorded

However the outcome intrauterine fetal growth could only be estimated for those who

attended both third and fourth visit 918 in total Those who gave birth prematurely (54)

were not included in this outcome Maternal characteristics were not different in this group

compared to the total group (data not shown)

The selection bias only influences the results if the women selected or lost differ in either their

characteristics or in the outcomes which does not seem to be the case in our study

Information Bias

Information bias arises if the information has not been gathered in the same way for all

participants It includes observational bias misclassification and measurement errors and can

58

occur during collection of data as well as coding and processing of the data Misclassification

includes classifying binary or discrete variables incorrectly We minimized misclassification

by using mostly continuous variables rather than categorical variables Bias might be

introduced by the observer (interviewer bias biased follow-up) by the study participants

(recall bias) or by measurement tools such as questionnaires or instruments

We might have introduced biased follow-up for at least one group of women The women

diagnosed with gestational diabetes mellitus at visit 3 were taught and encouraged to make

changes in diet and physical activity to prevent further deterioration in their glucose

metabolism This might have had an influence by reducing the outcomes birthweight and

intrauterine fetal growth in third trimester

Recall bias occurs when there are systematic differences in the way subjects remember or

report exposures or outcomes We tried to avoid recall bias by eg using measured weight and

height to calculate BMI instead of self-reported prepregnancy BMI Reviewing available data

on the relationship between self-reported and directly measured height and weight has shown

trends of under-reporting for weight and BMI and over-reporting for height [111]

Measurement errors will be discussed under data collection below

Confounding bias

A confounder is defined in epidemiological terms as a covariate that influence both the

independent and the dependent variable and can be controlled for by adding it to a multiple

regression model Confounders must be identified and then appropriately adjusted for in the

analyses [112] The statistical considerations around confounding will be discussed under

statistical issues in the discussion below

In Randomized Controlled Trials (RCT) confounding is avoided by randomly assigned groups

that differ only in the factor being studied and thereby removes the need to statistically control

for confounders In an observational study like STORK we tried to reduce the need for

adjusting for confounding factors related to comorbidities by selecting healthy women and to

avoid ethnic factors by selecting women of Scandinavian heritage

59

External validityRepresentativity

External validity or representativity refers to whether the results obtained in one study can be

generalized to other situations and to other populations [110]

To assess representativity we did two comparisons Our cohort was compared to a group of

women who delivered at Ullevaringl the largest obstetric unit in Oslo The comparison was

restricted to women of Scandinavian heritage and our cohort only differed in having fewer

smokers and single mothers (data not published)

We also compared our cohort to data from the Birth Registry of Norway Our study

population was comparable to women who gave birth in Oslo in 2009 on parameters like

maternal age parity gestational age (GA) at birth and birthweight (BW)

Figure 10 Comparison between STORK cohort and Oslo

0

10

20

30

40

50

60

Age P0 GA BW

STORK

OSLO 2009

Retrieved electronically from the Birth Registry of Norway [1]

60

513 Statistical issues

Longitudinal data

Analyzing longitudinal data with variables that are correlated over time is a statistical

challenge which can be solved by the use of mixed models However these methods are

complicated and require statistical knowledge that was not readily available to our group We

therefore chose our variables to be able to use conventional linear regression models Fetal

growth was defined as growth between visit 3 and visit 4 thereby confining fetal growth to

the third trimester The whole trajectory of fetal growth was thereby not fully explored

Similarly we only used fasting glucose concentrations at one time point as a covariate in the

multiple models instead of the change in glucose levels over time

Continuous versus categorical variables

We have chosen to use mostly continuous variables both as outcome and explanatory

variables instead of dichotomizing or creating groups This is based on both methodological

theory and published data on physiology in pregnancy Dichotomizing leads to several

problems [113] According to Altman much information is lost the statistical power is

reduced one may underestimate variation and non-linearity in the relation between variable

and outcome may be concealed [114] A large study of hyperglycemia in pregnancy (HAPO)

has shown that there is a linear relationship and no threshold value between fasting glucose

and adverse pregnancy outcomes [115] A similar relationship was seen between BMI and

adverse pregnancy outcomes [116]

Confounders mediators and colliders

A number of potential factors can influence the associations of interest These must be

identified and possibly corrected for in the regression models Whether to adjust for these

factors depend on classification of the factors into true confounders mediators and colliders

[112] Confounders should be included while colliders should no be included in regression

models to avoid introducing bias

A confounder (defined above) can be controlled for by adding it to a multiple regression

model The choice of which confounders to include in the model requires physiological

61

Independent variable Outcome

Confounder

Independent variable Outcome

Mediator

Independent variable Outcome

Collider

knowledge and requires statistical considerations when it comes to the number of observations

required [117] A mediator is considered a covariate that is on the causal pathway between the

independent and the dependent variable A collider is considered a covariate that is related to

both the independent and dependent variable in a common consequence [117] In our material

no included variables were considered to be colliders

Figure 11 Confounders mediators and colliders

62

Mediation

A mediator variable can either account for all or some of the observed relation between two

variables The effect of mediation can be assessed by judging what happens to the relation

between the independent and dependent variable when the mediator is included into the

regression model or not Full mediation would occur if inclusion of the mediation variable

removed the relation between the independent variable and dependent variable This rarely

occurs The most likely event is that the association becomes weaker yet still a significant

path with the inclusion of the mediator Partial mediation occurs when the mediating variable

accounts for some but not all of the relationship between the independent variable and

dependent variable Partial mediation implies that there is not only a significant relation

between the mediator and the dependent variable but also some direct relation between the

independent and dependent variable

One method to assess mediation was proposed by Baron and Kenny in 1986 [118] They laid

out several requirements that must be met to form true mediation relationships which are

summarized below

Step 1 Confirm that the independent variable is a significant predictor of the dependent

variable Independent Variable Dependent Variable

Y = β10 + β11 X + 1

β11 is significant

Step2 Confirm that the independent variable is a significant predictor of the mediator If the

mediator is not associated with the independent variable then it couldnrsquot possibly mediate

anything Independent Variable Mediator

Me = β20 + β21 X + 2

β21 is significant

Step 3 Confirm that the mediator is a significant predictor of the dependent variable while

controlling for the independent variable This step involves demonstrating that when the

mediator and the independent variable are used simultaneously to predict the dependent

63

variable the previously significant path between the independent and dependent variable is

now greatly reduced if not nonsignificant

Y = β30 + β31 X + β32 Me + 3

β32 is significant

β31 should be smaller in absolute value than the original mediation effect (β11 above)

Placental weight can be considered a mediator in this study Regression models are therefore

done with and without placental weight as a covariate in the model to show its role as a

possible mediator We applied the model by Baron and Kenny described above to show a

possible role of the placenta as a mediator Our results point at possible mediating pathways

involving the placenta on the causal pathway to fetal growth In order to quantify how much

of the effect that goes through the placenta we could have applied path analyses However

this method required more advanced statistical methods which were not available

64

52 Data collection STORK

521 Dependent variablesoutcomes

Birthweight

We chose to use birthweight as a summary measure of overall fetal growth It is widely used

and therefore suitable to compare our data to other publications We chose to use birthweight

as a continuous variable We wanted to report associations between maternal factors and

birthweight in the total STORK cohort as previous publications from the same cohort only

reported birthweight in sub cohorts andor using birthweight as a categorical value with a cut-

off of gt4200 g Birthweight was expressed as Z-scores adjusted for gestational age and fetal

sex

The standard score (Z-score) represents the distance between the raw score and the population

mean in units of the standard deviation Z is negative when the raw score is below the mean

positive when above The z-score is calculated as

where

x is the observed value

μ is the mean of the population

σ is the standard deviation of the population

Mean and standard deviation of the population were taken from a Norwegian reference

material [119]

Intrauterine fetal growth

There are no internationally accepted consensus on how to define and assess intrauterine fetal

growth [11] The longitudinal design of the STORK study enabled us to assess intrauterine

fetal growth We chose third trimester visit 3 to visit 4 which is the period of maximum

Z =

x - μ

σ

65

growth and a period in which maternal metabolic factors are important in terms of fetal

growth [120]

Fetal size and fetal growth were estimated by ultrasound Fetal size was expressed as both

estimated fetal weight (EFW) in grams and as EFW percentile according to Norwegian

growth charts [107] Intrauterine fetal growth was defined as the change in estimated fetal size

parameters from visit 3 to visit 4 expressed as either change in EFW (g) or change in

percentiles Combs formula was chosen as the equation to estimate fetal weight as it is the

formula in use in clinical practice at our department and the basis for the growth charts we

used as reference [106]

Errors in ultrasonographic assessment of fetal weight can be attributed to at least two factors

errors due to the equation and errors due to observer error Observer error can further be

divided into intra-observer and inter-observer error [121] Intra-observer error refers to the

variance in measurements performed by the same observer All measurements were

performed three times and we used the mean of the three values to minimize intra-observer

error Inter-observer error refers to the variance in measurements that occur because different

observers measure differently To minimize inter-observer error all measurements were done

by only three investigators and each participant was measured by the same investigator at all

visits Among errors in ultrasonographic assessment of fetal weight observer error has been

shown to be a relatively minor component compared to the larger error due to the equation

[18] To be able to assess fetal growth we compared our data to reference curves based on

data from University of Bergen Norway as that population was considered the most

comparable to our population [107] We also evaluated fetal growth as changes in each of the

three components that make up EFW according to Combs equation namely HC AC and

femur length Once again we compared our data with Norwegian reference data [108]

There are other types of fetal growth charts available Customized curves have been

developed to adjust for factors like race fetal sex parity and maternal size which are factors

known to influence birthweight and factors that differ in different populations [13] We chose

not to use customized growth charts since the aim of our study was to study the effect of

maternal factors on fetal growth In customized charts maternal factors are controlled for and

therefore unsuited to study the effect of maternal factors

Conditional growth curves take into account the estimated size measured at one point and

gives an estimation of the expected growth for a fetus of that particular size for a specified

period of time As an example a larger fetus at the 75 percentile at week 30 will be expected

to grow more during the next weeks than a smaller fetus at the 10 percentile at week 30 during

66

the same period of time Conditioning on a previous measurement gives information on

whether a particular fetus grows fast or slowly relative to other fetuses of the same size We

chose not to use conditional growth curves in the current study as preliminary analyses did not

indicate major changes in the results making use of the conceptionally more difficult variable

less justified

Placental weight

Placenta was weighed including umbilical cord and membranes by the midwife or childrenrsquos

nurse within one hour after birth The placental weight was expressed in grams The placentas

were not trimmed but there is a close correlation between trimmed and non-trimmed

placentas (r= 098) [122]

Rationale for using placental weight as a proxy for placental function

There is no single parameter that measures placental function as placenta has a range of

functions Placental weight was chosen as outcome as a surrogate for placental function

Placental weight is a measure commonly used to summarize placental growth and aspects of

placental function In normal pregnancy it is reasonable to assume that placental weight is

related to aspects of functional capacity of the placenta [123] We had no estimations of

placental weight or mass during pregnancy Placenta exhibits linear growth throughout

pregnancy [5556] making it reasonable to use placental weight after birth instead of

estimations of placental mass during pregnancy

We wanted to use a variable that reflects those aspects of placental function which are

relevant to fetal growth of which nutrient transport is an obvious factor Density or activity of

nutrient transport proteins in the placenta could have been used as an alternative measurement

of placental function but these data are not yet available in our cohort An underlying

assumption for nutrients to be transported across placenta is that the maternal or umbilical

blood flow is not impaired We performed Doppler measurements in the uterine artery and

umbilical artery In our cohort of healthy women only 35 had notching in the uterine artery

at visit 2 and 32 had a pulsatile index above 2 SD for gestational age at visit 4

(unpublished data)

67

Placental weight correlates well with surface area which is a major determinant for nutrient

transport [124] The maternal plasma level of hormones produced in the placenta are directly

related to placental weight [125]

522 Explanatory independent variables

The explanatory variables were chosen based on publications from our study [126ndash129] and

literature on fetal growth in general We selected some maternal characteristics that were

known to influence birthweight in order to study their relation to intrauterine fetal growth

Maternal factors

Maternal age was noted at the first visit in whole years Age was normally distributed

Parity was categorized into P0 and P1+ as the largest difference in birthweight is

known to be between the first child and second child and less between consecutive

children [43]

BMI was calculated based on height and weight measured at the first visit We did not

use pregestational BMI to avoid recall bias and false self-reporting

GWG was calculated as the difference in weight between visit 4 and visit 1 We did

not use weight measured at admission for delivery as there were many missing values

Fasting glucose was measured by the use of Accucheck (Roche Diagnostics

Mannheim Germany) in order to obtain the measured values immediately This

enabled us to inform the women of the result the same morning and in cases of

impaired glucose metabolism to give advice on diet and physical activity during the

consultation Analyses of glucose over the seven years of inclusion revealed that there

was an unexpected increase in fasting glucose of 06 mmolL over time We found no

accompanying increase in maternal age BMI or in insulin that could give a biological

plausible explanation for this increasing trend Thus the time trend in fasting glucose

most likely had an analytical cause The glucose values were de-trended according to

the coefficients from linear regression under the assumption of a linear increase

during the entire period and de-trending of the data removed the increasing trend

[130]

68

Placental weight

The rationale for using placental weight to reflect aspects of placental function has been

discussed above When placental weight was used as an explanatory variable in the regression

models placental weight was entered in 100 grams instead of 1 gram to avoid getting effect

estimates with too many decimals

Placental pathology

There were 55 placentas not characterized as normal which makes up 53 of the samples

Theoretically it is possible that the placental weight in these cases does not reflect function in

the same way as placentas characterized as normal Eg a placenta with infarctions has areas

of tissue that do not take part in nutrient transport Such a small percentage of pathological

placentas are not likely to have influenced the results to a significant extent

69

53 Methodological issues STORK-Placenta

Design

The STORK-Placenta study had a cross-sectional design which means the women were only

examined once which in our study was at delivery This design gives no opportunity to assess

earlier gestational ages or longitudinal changes throughout the pregnancy In Paper 3 all the

study subjects were healthy women and there was no need for a control group In paper 4 we

applied a case-control design in which the preeclampsia group was compared to a control

group of healthy pregnant women

Validity

Internal validity

Selection bias

Only women delivered by cesarean section were recruited to this study This lead to selection

bias for both the healthy women and the preeclamptic patients For the healthy women the

most common indications for cesarean section were prior cesarean section or patient request

due to traumatic previous delivery Few healthy primiparas are delivered by elective cesarean

the exception being breech presentation In Paper 3 the selection therefore resulted in age and

parity that were relatively higher than average Avoiding selection bias in a study like this was

not possible given the population eligible for participation

For the preeclamptic women the selection lead to overrepresentation of early onset

preeclampsia and cases of serious preeclampsia as late onset or less serious cases in many

cases can deliver vaginally In Paper 4 this was reflected in lower gestational age in the

preeclampsia group than the controls

Information bias

We assumed similar blood composition in the radial and the uterine artery This was done to

avoid puncturing the uterine artery as bleeding would be easier to control in the radial artery

As the blood is pumped out of the aorta it is reasonable to assume that the composition does

70

not change substantially between the blood reaching the radial artery compared to the blood

that reaches the uterine artery

External validityrepresentativity

The representativity of the results from the STORK-Placenta study is discussed in light of the

selection of the participants

Parity was higher in Paper 3 than average From our results in Paper 1 and Paper 2 we have

seen that parity was an independent variable with effect on fetal growth In Paper 3 the added

effect of parity on fetal growth could give a bias if the effect of parity also affects the glucose

transport across the placenta Hitherto the question can not be answered So far our results are

only valid for the glucose metabolism among healthy women with relatively normal BMI

Which changes that occur in the glucose metabolism in women with chronic diseases will

probably vary according to the disease Higher BMI would probably influence the glucose

metabolism both directly as higher BMI might lead to higher glucose levels in many cases

but possibly also indirectly by changes in inflammatory factors and by changes in the

transport of other nutrients as amino-acids and lipids

In Paper 4 gestational age was lower in the preeclampsia group than in controls Early-onset

and late-onset preeclampsia are by many considered two different subgroups of preeclampsia

due to the differences in risk factors pathogenesis and clinical presentation [90] Our findings

may not be valid for late-onset preeclampsia where maternal risk factors play a larger role in

the patophysiology and the endothelial dysfunction might be more prominent Therefore it is

possible that the results are valid only when the placental dysfunction is the major feature in

the pathophysiology like in early-onset preeclampsia

Statistical issues

In both papers from the STORK-Placenta study the numbers of participants were relatively

small due to the demanding logistics of the project Small numbers lead to some statistical

challenges that need to be discussed

In Paper 3 we included 40 patients which were sufficient to show significant glucose gradients

on both maternal and fetal side as well as a gradient across the placenta However the small

number restricted the possibilities to study interesting associations between maternal factors

and glucose transport or glucose transport in relation to fetal growth by the use of regression

71

models As an example we found an interesting association between maternal BMI and fetal

glucose v-a difference but the scatter plott revealed one woman with BMI 39 and analyses

showed that without that observation the association was no longer significant

In Paper 4 we found a significant difference in sFlt-1 but not in sEng across the uteroplacental

circulation among preeclamptic patients There is a possibility that lack of power influenced

this finding Possibly a larger sample could have given a significant difference for sEng in

which case our finding could represent a type 1 error (reject the hypothesis that there was a

difference even if it is true)

Both non-parametric tests on original data and parametric tests on log transformed data were

done giving the same results in terms of statistically significant differences We chose to use

the log transformed data for statistical analyses (as that seemed to be the most conventional

method used in relevant references) but presented arithmetic data in figures and tables to

make it easier for the reader

54 Data collection STORK-Placenta

Blood sampling

All procedures were standardized to minimize systematic errors Sampling was therefore done

by a small group of four trained obstetricians and handling the samples in the laboratory was

restricted to only three investigators In the few cases where sampling was inadequate it was

mostly due to failure in inserting the arterial line or in a few cases inadequate amount of blood

obtained from the umbilical artery Blood samples were kept on ice until centrifugation

Blood samples were taken in fasting condition to obtain a steady state situation This is

particularly relevant for glucose and insulin which show large post-prandial variation

Cesarean section was done under spinal anesthesia no participants received oxygen or

intravenous glucose infusion

Analyses

Glucose and insulin were analyzed at the laboratory at Oslo University Hospital The samples

were analyzed during three consecutive days

72

sFlt-1 and sEng were analyzed by commercially available ELISA kits (RampD systems) We

chose to use ELISA kits from RampD for comparison reasons as they were commonly used in

papers on preeclampsia published at the time

73

55 Interpretation of results

Paper 1 and 2

In Paper 1 and Paper 2 we have studied the associations between maternal characteristics

placental weight and fetal growth in healthy pregnant women ie these are studies of normal

physiological relations Together the results from these papers illustrate some of the interplay

between the mother the placenta and the fetus

Paper 1

Paper 1Paper 2

-parity

-BMI

-GWG

-glucose

We found largely the same determinants for both birthweight and intrauterine fetal growth in

third trimester with the exception of fasting glucose (see below) The weight of the placenta

was influenced by similar maternal metabolic and nutritional factors In summary our results

are compatible with the concept that maternal factors can influence fetal growth directly and

indirectly by promoting placental growth

We found a direct effect of maternal factors both on birthweight and intrauterine growth in the

third trimester For both birthweight and intrauterine fetal growth placental weight was an

independent determinant Hence as the placenta grows and becomes larger some of the effect

of maternal factors on fetal growth is likely to be mediated by growth of the placenta

We found independent effects of several maternal factors (parity BMI and GWG) on

intrauterine fetal growth in third trimester We did not find independent effect of age The

small variation in age (SD) might partly explain why we did not find any effect of age

74

Furthermore age has been shown to exhibit an inverse u-shaped relation to birthweight and we

only tested for linear relationships Somewhat surprisingly we did not find an independent

effect of fasting glucose on intrauterine fetal growth in third trimester The discrepancy

between the effect of glucose on birthweight and on intrauterine growth may have several

explanations One possible explanation lies in how fetal growth is assessed Fat accumulation

resulting from increased maternal glucose and subsequent increased insulin secretion in the

fetus is likely to be accumulated on extremities and truncus of the fetus as well as the

abdomen The estimation of fetal size and fetal growth used in our study included assessment

of head circumference abdominal circumference and femur length Of these only abdominal

circumference would be likely to reflect fat deposition We did not however find an

independent association between fasting glucose and change in abdominal circumference

There is no consensus on whether the diagnosis of abnormal growth should be based on EFW

or AC or both [11] Another possible explanation for the described discrepancy could be

found in the concept of conditional growth Conditional fetal growth refers to differences in

expected fetal growth depending on the size estimated at the last measurement As an

example a fetus that is large at week 30 will be expected to grow more in the remaining

weeks of the pregnancy than a fetus that is relatively smaller at week 30 Factors like impaired

glucose metabolism in early pregnancy leading to higher fasting glucose values might have

resulted in a large fetus already at week 30

Placental weight was used as a measure of placental function Introducing placental weight in

the multiple regression models gave two interesting results

First placental weight was an independent determinant of birthweight and fetal growth and

showed a positive effect on fetal growth A small placenta is commonly associated with a

growth restricted fetus hence a reduced placental function Fetalplacental ratio can be used

as an indicator of placental efficiency and includes both fetal weight and placental weight

Preliminary analyses in our material showed that the maternal factors associated with

fetalplacental ratio in the multiple model were maternal age parity and BMI Maternal

gestational weight gain was not significantly associated in the univariate model and hence not

included in the multiple model Fasting glucose was not significant in the multiple model

using fetalplacental ratio as outcome

Secondly placental weight can be viewed as a mediator in the associations between maternal

factors and fetal growth This implies that some of the effect of the maternal factors might

work through growth of the placenta There are several possible biological reasons for the

75

reduced effects of the maternal characteristics on birthweight or intrauterine fetal growth

when placental weight was included in the models The selected maternal characteristics may

exert their effects on fetal growth by affecting transplacental transport Transplacental

transport is affected by blood flow both on maternal and fetal side Furthermore the number

and efficiency of placental transport proteins may also be influenced by maternal factors The

total number of transport proteins is dependent on both the area of the syncytio-endothelial

membrane and the density of the transporting proteins In addition it can not be excluded that

placental production of growth factors may be affected

We have studied both modifiable and non-modifiable maternal factors Parity is a non-

modifiable factor present before pregnancy There is a well-known effect of parity on

birthweight We showed that this effect is evident also for intrauterine growth and placental

weight The effect of parity is relatively larger than many other maternal factors eg larger

than fasting glucose BMI and GWG Modifiable factors include BMI GWG and fasting

glucose BMI and fasting glucose may be modified before pregnancy and GWG and glucose

during pregnancy

The present study did not include data on neither fetal factors that stimulate or inhibit

placental growth function or maternal factors nor placental factors that influence maternal

metabolism Theoretically however there are possible pathways including signals from the

fetus that can stimulate placental growth and possibly placental factors that can influence

maternal metabolism

Taken together the results from Paper 1 and Paper 2 show that maternal factors influence

both placental weight and fetal growth and it is likely that some of the effect on fetal growth is

mediated through placental growth This does not exclude the possibility that an increased

fetal growth following increased maternal energy supply may lead to release of fetal growth

factors that feed back on placental growth

Clinical implications

We have only studied birthweight and intrauterine growth in third trimester which might be

too late to intervene in cases of abnormal fetal growth In order to intervene it is necessary to

know which factors influence intrauterine growth at different gestational ages As both low

76

BMI and low GWG is related to increased risk of IUGR patients with high risk of IUGR

could be advised to increase their BMI or make sure they gain sufficient weight according to

recommendations Similarly as high BMI and high GWG increase fetal growth women could

be advised to obtain a normal BMI prior to getting pregnant and not gain unnecessary weight

during pregnancy As there is a linear and continuous relation between fasting glucose and

adverse fetal outcomes including fetal growth pregnant women with fasting glucose values

just below the GDM criteria can benefit from the same advice concerning diet and physical

activity as GDM-patients receive In particular women with multiple risk factors of impaired

fetal growth should be given advice even if she does not meet the criteria of GDM or obesity

Paper 3

Glucose is the major source of energy for the fetus and the placenta and therefore has an

obvious importance in fetal nutrition Glucose transport across the placenta in humans is

interesting to study for several reasons There is a lack of human in vivo studies in contrast to

the body of evidence on mechanisms and transporter proteins etc from in vitro studies It is of

major importance to acknowledge the distinction between maternal nutrition and fetal

nutrition [2] The placenta is not just a simple conduit for gases nutrients and waste products

but has its own complex metabolism with corresponding requirements for oxygen and

nutrients

In this paper we found a close correlation between maternal and fetal glucose concentrations

which is in line with the concept that the maternal-fetal gradient is the driving force in the

transplacental transport of glucose across the placenta However the fetal v-a glucose

difference was not merely a reflection of the maternal glucose concentration or the

uteroplacental uptake of glucose but rather related to the maternal-fetal gradient and the

concentration in the umbilical artery The relation between maternal and fetal glucose

concentration has been shown in several papers Although the umbilical venous concentration

is closely related to the maternal concentration the fetal v-a difference seemed to be less

related to maternal concentrations but more to the concentration in the umbilical artery fetal

insulin placental weight and birthweight We therefore speculate that the fetus has a saying in

determining the fetal glucose consumption This might at first seem to be in conflict with the

Pedersen hypothesis which was first presented in 1952 [131] His theory was that high

maternal glucose was transferred to the fetus which responds by secreting more insulin

77

which in turn lowers the blood glucose of the newborn Compared to the 1950s pregnant

women of today are older when they get pregnant have higher prepregnancy BMI and gain

more weight in pregnancy The metabolic environment a fetus experiences today is likely to

differ from the environment some decades ago in several aspects more energy-rich altered

balance between glucose and lipids and more inflammation [132] The non-glucose factors

like lipids may have augmented their role as several factors have changed in the population

since the proposal was made by Pedersen We can only speculate as to how the relative

importance of these factors might influence the regulation of transport of nutrients to the

fetus

Our results can not explain or show the complex regulation of glucose transport and

metabolism and leaves us with some unanswered questions We only presented correlation

analyses as we did not yet have enough samples to do multivariate analyses to evaluate the

relative importance of the factors involved We were not able to do path analyses to quantify

the influence of each of these factors Do the relationships we have described work differently

in pathological pregnancies in which there is either abnormal placental function or the mother

exhibits abnormalities in her metabolism or the fetus experiences abnormal growth These

questions can hopefully be answered by future research

The amount of glucose consumed by the placenta can be changed under hypoxic conditions

[63] It is not likely that our participants were hypoxic to a large degree We only measured

oxygen in a few cases which were all normal

Clinical implications

In obstetric practice there are numerous examples of cases of abnormal fetal growth occurring

in pregnancies of healthy mothers with normal metabolism and apparently normal placental

function Placental function might still be compromised resulting in reduced fetal nutrition

Fetal under nutrition may result from compromised transplacental transfer of nutrients In the

other end of the spectrum are the fetuses that experience overgrowth despite strict glycemic

control of their diabetic mothers Some authors argue that this might be due to intermittent

hyperglycemia rather than constant hyperglycemia but another option is that hyperglycemia

is accompanied by other nutrients or other factors that increases the total energy supply to the

fetus

78

Human in vivo studies are rare and therefore valuable in terms of extrapolation to relevant

settings in clinical practice However in vivo settings include multiple factors working

together making it difficult to assess individual effects In vitro settings however can control

for one factor at a time to gain mechanistic knowledge which can hardly be drawn from in

vivo settings The clinical significance of factors operating in vitro is often difficult to assess

Paper 4

The multifactorial etiology and heterogeneous clinical presentations seen in preeclampsia

makes it an intriguing and challenging condition to study Since preeclampsia is a pregnancy

complication in which the placenta is believed to play a crucial role in the pathophysiology it

was both interesting and relevant to choose preeclampsia in order to study aspects of placental

function in pathological pregnancies Furthermore preeclampsia is still a leading cause of

mortality and morbidity worldwide Despite decades of research there is still no causal

treatment leaving timing of delivery the only intervention to balance the needs of the mother

and the fetus

In our study we found as expected that preeclamptic women had higher concentrations of sFlt-

1 and sEng than healthy controls as has been shown in numerous previous publications

Preeclamptic women further had higher concentrations of sFlt-1 in the uterine vein than the

radial artery giving a gradient across the uterus There was no gradient for sEng among

preeclamptic women and no gradients were found in the healthy controls for either of the two

factors tested The gradient across placenta is consistent with the concept that the placenta

secretes sFlt-1 into the maternal circulation The source of excess sFlt-1 and sEng in

preeclamptic patients is assumed to be the placenta based on enhanced expression of both

factors in trophoblastic tissue [133134] Enhanced expression of sFlt-1 and sEng in

trophoblastic tissue does not necessarily prove that the circulating sFlt-1 and sEng found in

preeclamptic patients originate from the placenta or that the placenta is the only source There

is a possibility that sFlt and sEng originate from circulating cells in the maternal circulation or

endothelial cells Peripheral blood mononuclear cells have been suggested to be an additional

extra-placental source of sFlt-1 [134]

Our results support the hypothesis that at least a part of the circulating sFlt-1 originates in the

placenta and is transported into the maternal circulation whereas we did not find evidence to

support that this holds for sEng The discrepancy between our results for sFlt-1 and sEng

could have several explanations

79

There might be a biological difference such that sFlt-1 only or to a larger extent than sEng is

released from the syncytiotrophoblasts in the placenta whereas sEng to a larger extent is

produced elsewhere [135] There might also be a statistical explanation suggesting that we had

inadequate power to show a statistically significant difference in sEng which would represent

a type 1 error (rejecting the hypothesis that there was a difference even if it is true)

In this paper as most studies involving preeclamptic patients and healthy controls there was a

difference in gestational age among cases and controls The difference in gestational age

raises some questions to be discussed There are publications reporting an increase in sFlt-1

and sEng with increasing gestational age both for controls and preeclamptic patients but more

so in preeclampsia [136137] Assuming this relationship for our controls we would expect to

find a lower concentration at week 30 among healthy controls than what we found near term

giving an even greater difference than we observed Thus we do not think that the difference

in gestational age can explain the observed difference in sFlt-1 and sEng between preclamptic

patients and healthy controls We did not include samples from preeclamptic patients at term

as they mostly deliver vaginally Our group of preeclamptic patients thus represents early-

onset preeclampsia In most cases preeclampsia was accompanied by a degree of intrauterine

growth restriction Whether our findings are representative for late onset preeclampsia in

which the placental dysfunction is perhaps less prominent and the endothelial dysfunction

more prominent is not clear from our study

Anti-angiogenic factors in a clinical setting

Anti-angiogenetic factors have been proposed used as diagnostic tools for preeclampsia

There is hope for a therapeutic option in treating preeclampsia in the future but whether

angiogenetic agents can be used to improve the angiogenic imbalance seen in preeclampsia is

not known At the moment the most useful implications of these types of studies is increased

knowledge on the pathogenesis including the possibility to differentiate between early- and

late-onset preeclampsia

80

6 Conclusions

In conclusion results from the first part of this thesis (Paper 1 and 2) underline the importance

of the placenta and placental functions in normal pregnancies Placenta is an important factor

to consider when studying associations between maternal factors and measures of fetal

growth birthweight intrauterine growth or body composition The effect of maternal

metabolic and nutritional factors on fetal growth is likely to go partly through growth of the

placenta There is an important distinction between maternal and fetal nutrition as one has to

consider the placenta as an active organ and not a passive conduit of nutrients and gases

In the second part of this thesis a method has been established that makes it possible to study

placental function in the human in both normal and pathological pregnancies like

preeclampsia

7 Further research

I believe the greatest challenges in the two studies that make up my thesis also reflect the

potentials for further research

In the STORK study we collected large amounts of data on a large group of women

Therefore selecting and analyzing the relevant outcomes and appropriate explanatory

variables was the greatest challenge There are large amounts of data still to be analyzed For

the STORK data my plans for a postdoc is to study in more detail the relations between

maternal metabolism and pregnancy outcomes More specifically to differentiate between

healthy and unhealthy obese pregnant women in metabolic terms and relate this to pregnancy

outcomes including fetal growth

In the STORK-Placenta study establishing the method and achieving the data collection were

the greatest challenges with demanding logistics at any time of the day There are few larger

human in vivo studies of placental nutrient transfer In particular studies of arterio-venous

differences on maternal side of placenta are scarce The main reason this kind of studies are so

limited is that such studies are logistically very requiring To our knowledge we are the only

group employing this procedure The samples obtained by this method give unique

opportunities to study concentration gradients and transplacental transfer of any nutrient

81

across placenta and how endocrine and inflammatory factors may interact with nutrient

transfer The study also includes measurements of maternal and fetal blood flow enabling us

to quantify the amounts of nutrients being transported The study has currently been

expanded to around 100 pregnancies Data collection still goes on aiming to get enough

samples to continue analyzing interesting associations linking maternal metabolism placental

functions and the fetus and extending the data to include cases of pathological pregnancies

like preeclampsia diabetes mellitus and abnormal fetal growth Samples from preeclamptic

women are currently being analyzed for Placental growth factor

The potential for further research lies in combining the data retrieved from the two studies

Ultimately I would like to be able to link preeclampsia and fetal growth in the two studies

82

8 References

Reference List

1 2009) wwwmfr-nesstaruibno Medical birth Registry Norway Available

2 Harding JE (2001) The nutritional basis of the fetal origins of adult disease Int J

Epidemiol 30 15-23

3 Barker DJ Thornburg KL (2013) The obstetric origins of health for a lifetime Clinical

Obstetrics and Gynecology 56 511-519

4 Forsdahl A (1978) Living conditions in childhood and subsequent development of risk

factors for arteriosclerotic heart disease The cardiovascular survey in Finnmark 1974-

75 J Epidemiol Community Health 32 34-37

5 Forsdahl A (1979) Are poor living conditions in childhood and adolescence and

important risk factor for arteriosclerotic heart disease Int J Rehabil Res 2 238-239

6 Barker DJ (2005) The developmental origins of insulin resistance Horm Res 64 Suppl

3 2-7

7 Barker DJ Shiell AW Barker ME Law CM (2000) Growth in utero and blood

pressure levels in the next generation J Hypertens 18 843-846

8 Barker DJ (1997) The long-term outcome of retarded fetal growth Clinical Obstetrics

and Gynecology 40 853-863

9 Gude NM Roberts CT Kalionis B King RG (2004) Growth and function of the

normal human placenta Thromb Res 114 397-407

10 Voldner N (2010) Modifiable determinants of newborn macrosomia and birth

complications [dissertation]

11 Mayer C Joseph KS (2013) Fetal growth a review of terms concepts and issues

relevant to obstetrics Ultrasound Obstet Gynecol 41 136-145

12 Zhang J Merialdi M Platt LD Kramer MS (2010) Defining normal and abnormal

fetal growth promises and challenges Am J Obstet Gynecol 202 522-528

13 Gardosi J Figueras F Clausson B Francis A (2011) The customised growth potential

an international research tool to study the epidemiology of fetal growth Paediatr

Perinat Epidemiol 25 2-10

14 Rohrer F (1921) The index of corpulence as measure of nutritional state Munchener

medizinische Wochenschrift 580-582

15 Catalano PM Thomas AJ Avallone DA Amini SB (1995) Anthropometric estimation

of neonatal body composition Am J Obstet Gynecol 173 1176-1181

16 Godang K Qvigstad E Voldner N Isaksen GA Froslie KF et al (2010) Assessing

body composition in healthy newborn infants reliability of dual-energy x-ray

absorptiometry J Clin Densitom 13 151-160

17 Pay AS Froen JF Staff AC Jacobsson B Gjessing HK (2013) A new population-

based reference curve for symphysis-fundus height Acta Obstet Gynecol Scand 92

925-933

18 Anderson NG Jolley IJ Wells JE (2007) Sonographic estimation of fetal weight

comparison of bias precision and consistency using 12 different formulae Ultrasound

Obstet Gynecol 30 173-179

19 Cetin I Alvino G (2009) Intrauterine growth restriction implications for placental

metabolism and transport A review Placenta 30 Suppl A S77-S82

20 Mei Z Grummer-Strawn LM Pietrobelli A Goulding A Goran MI et al (2002)

Validity of body mass index compared with other body-composition screening indexes

for the assessment of body fatness in children and adolescents Am J Clin Nutr 75

978-985

10

1 Introduction

11 Summary

The STORK study was initiated to address the observed increase in proportions of large

babies in Norway and the growing acknowledgement that birthweight and fetal growth have

consequences for health and disease both in short and long term In Norway the proportion of

babies with high birthweightmacrosomia (gt4000 g) increased from approximately 17 in

1990 to 22 around the year 2000 after which the proportion has returned to 17 in 2008

[1] The STORK study was designed to study maternal risk factors for macrosomia as

reflected in the acronym STORK rdquostore barn og komplikasjonerrdquo which translates into large

babies and complications The name of the study reflects the original research questions

asked when the study was planned The cohort consists of two periods referred to as STORK

1 (2001-2005) and STORK 2 (2005-2008) The cohort was extended to STORK 2 in order to

address wider research questions The outcome was expanded to include not only birthweight

but intrauterine growth and body composition at birth Placenta is central in determining the

nutritional and endocrinological conditions for fetal growth and development Virtually no

compound reaches the fetus without passing the placenta We therefore first included

placental weight in the analyses of the STORK data with an underlying assumption that

placental size to some extent reflects functional capacity During these analyses placental

weight emerged as a determinant of fetal growth parameters These observations led us to

initiate studies on functional aspects of placenta and we decided to establish an in vivo model

in the human (the STORK-Placenta study)

Two approaches were chosen in this study

1 To study nutrient transport

2 To investigate placental factors in pathological pregnancies like preeclampsia

Preeclampsia is a leading cause of mortality and morbidity in obstetrics and a condition in

which the placenta is thought to play a major pathophysiological role Importantly a

prominent feature of preeclampsia is placental insufficiency and fetal growth restriction

11

2001 2005 2008

STORK 1 STORK 2

birthweight

fetal growth

body composition ( fat)

maternal characteristics

placental aspects

Camilla M Friis

Kathrine Frey Froslashslie

Marie Cecilie Paasche Roland

Inclusion

period

Timeline for the STORK and STORK-Placenta project

STORK-Placenta

2013

Outcome

Determinants

PhD candidate

birthweight gt 4200 g

maternal characteristics

Nanna Voldner

placental functions

glucose transport across placenta

anti-angiogenic factors

Marie Cecilie Paasche Roland

Ane Moe Holme

This thesis consists of four papers of which Paper 1 and Paper 2 are based on the STORK

study and Paper 3 and Paper 4 are based on the STORK-Placenta Study

12

In Paper 1 we studied how maternal factors were associated with birthweight and intrauterine

fetal growth For the reasons indicated above we included placental weight as a determinant

of birthweight and fetal growth

Paper 1

-parity

-BMI

-GWG

-glucose

Given the importance of placental weight on birthweight and fetal growth we then wanted to

study placental weight in Paper 2 We studied the influence of maternal factors on placental

weight and whether these associations differed with fetal sex

Paper 2

-parity

-BMI

-GWG

-glucose

13

In Paper 3 we reported initial studies of transfer of glucose across the human placenta and

how maternal and fetal glucose and insulin levels were related

Paper 3

Glucose and insulin

In Paper 4 the role of placenta in producing pathogenic factors of preeclampsia was

investigated choosing anti-angiogenic factors because of their endothelial-disturbing

properties

Paper 4

Anti-angiogenic

factors

14

12 Background

Fetal growth has implications for the newborn child both in short and long term The link

between events in early life and risk of disease in later life is now a widely recognized field of

research known as developmental programming and often called Developmental Origins of

Health and Disease Developmental programming refers to how an event at a critical or

sensitive period results in a long-term change in the structure or function of the organism

[23] Organs and systems in the human body are sensitive to the environment in certain

periods The critical periods are mainly those characterized by rapid growth and maturation

and for most organs and systems this happens to a large extent in utero

The idea of linking events in early life to later risk of disease is however not new The

association between poor living conditions in childhood and increased risk of cardiovascular

disease was observed by Anders Forsdahl who worked as a physician in Finnmark Northern

Norway in the 1970s He found a positive correlation between infant mortality which was

considered to be an index of standard of living and mortality from arteriosclerotic heart

disease as well as cholesterol values [45]

The link between early life events and later disease received more publicity when the late

David Barker introduced what is commonly referred to as the rdquoBarker hypothesisrdquo He was

probably the most acknowledged scientist in this field and established an association between

birthweight and increased risk of cardiovascular disease insulin resistance and type 2 diabetes

mellitus [6ndash8] His work has been followed by a range of publications that have not only

confirmed these associations but also provided mechanistic insight into the link between

intrauterine growth and increased risk of disease A large body of evidence have shown that

structural or functional changes that last throughout life can result from nutritional factors in

utero [2] Extensive work on animal models has demonstrated how dietary changes affect fetal

growth and lead to functional and structural changes The availability of nutrients to the fetus

is influenced not only by the motherrsquos diet during pregnancy but by maternal nutrient stores

and metabolism The placenta has multiple roles in fetal nutrition by its capacity to transport

nutrients from the maternal to the fetal circulation by its own metabolic demand for nutrients

and by producing hormones which influence fetal and maternal nutritional supply [9]

15

13 Fetal growth

Fetal growth comprises the entire process of differentiation maturation and development that

occurs between conception and birth This process starts with the fusion of two cells and ends

up with an estimated 50-100 trillion cells in the newborn child The terminology used to

describe and evaluate fetal growth is complex and the terms need to be defined First there is

a need to draw a distinction between size at birth and intrauterine growth Secondly the

difference between size which is most commonly measured as weight and body composition

must be addressed

131 Size at birth

Birthweight

Size at birth is routinely measured as birthweight (grams or kg) Birthweight is a summary

measure of fetal growth throughout pregnancy Categories based on birthweight are used both

in clinical settings and for research Low birthweight is generally defined as birthweight

lt 2500 grams whereas a definition for high birthweight (macrosomia) is more arbitrary Both

4000 4200 and 4500 grams have been used as cut-off values in various settings [1011]

Birthweight for gestational age

Birthweight as a function of gestational age gives information of size relative to expected size

for a particular gestational age Birthweight for gestational age can be given as a percentile

between 0 and 100 Birthweight for gestational age can also be categorized and the most

commonly used categories are large for gestational age (LGA) appropriate for gestational age

(AGA) and small for gestational age (SGA) The conventional cut-off percentiles for these

categories are given beneath

Population based charts for birthweight are often based on large samples including both low-

risk and high-risk pregnancies representing the underlying population On the other hand a

so-called standard chart is usually based on low-risk pregnancies with a normal outcome [12]

Furthermore customized charts have been made to accommodate for differences in eg

ethnicity parity age and BMI in individual patients Such charts have been developed for

different populations and there are electronically available charts [13]

16

Body composition

In addition to weight of the newborn baby length and head circumference give some

information about the body composition of the newborn Further evaluation of body

composition can be derived from these measurements The Ponderal Index (PI) is calculated

as a relationship between mass and height as is the body mass index (BMI) but the mass is

normalized with the third power of body height

Because it yields valid results even for very short (and very tall) persons it is more suitable

in pediatrics than BMI [14] Body composition can further be assessed by measuring

circumference of the abdomen and the extremities or by skin fold thickness measurements by

calipers to obtain an estimation of fat distribution [15] There are other methods that are either

expensive or difficult to perform on newborns Dual energy x -ray absorptiometry (DXA)

enables an estimation of bone mass fat mass and fat free (lean) mass A reasonable good

correlation between estimated fat mass by DXA and skin fold thickness measured by calipers

has been shown [16]

Categories Cut-offs

SGA lt 10 p

AGA 10-90 p

LGA gt 90 p

PI

= weight (g)

[height (cm)]3

17

132 Intrauterine growth

Fetal growth is a continuous process that starts at conception and ends at birth but is

commonly measured as just the end result which is size at birth However the distinction

between size and growth applies also to the intrauterine period Fetal size is estimated based

on a single observation or measurement whereas estimation of fetal growth requires at least

two measurements

Symphysis-fundus height

Palpation of the abdomen and measuring the symphysis-fundal height is used to estimate

intrauterine growth in low-risk pregnancies Reference curves for the symphysis-fundus

height to assess fetal growth have recently been updated in Scandinavia [17]

Ultrasound measurements

Estimation of fetal size

Estimation of fetal size by ultrasound combines measurements of the fetus and transforms

these measurements into volume and weight to estimate fetal size There are a number of

equations that use combinations of circumferences andor diameters and combinations of

measurements of head and abdominal size andor femural length to estimate fetal size The

equations differ in their ability to predict fetal size but generally perform more accurately in

predicting average fetal sizes than at the extremes of birthweight [18]

Estimation of fetal growth and fetal growth charts

To estimate fetal growth two or more measurements separated in time are needed and the rate

of growth can be assessed by using fetal growth charts There are a multitude of charts

available that are constructed by different methods and from different populations Fetal

growth charts can be derived from cross-sectional or longitudinal data In cross-sectional

charts each pregnant woman contributes with data from one observation whereas longitudinal

studies have repeated measurements from each participant The longitudinal studies provide

better references for fetal growth [12]

18

The ambiguous terminology

The lack of distinction between fetal size and fetal growth complicates the terminology Small

for gestational age (SGA) is often defined as birthweight lt 10 p The term intrauterine growth

restriction (IUGR) is often used interchangeably with SGA IUGR more strictly is used as a

term for true intrauterine growth restriction based on data that shows a decline in intrauterine

growth over time assessed by ultrasound There are however no universally accepted

definition of how much decline in fetal growth that would define IUGR although some

authors have defined IUGR as either a fall in fetometric percentiles or a combination of fall in

percentiles and low birthweight [19] On the same note accelerated fetal growth can be seen

during intrauterine life and may or may not result in a LGA newborn

Figure 1 Schematic overview of categories of fetal growth

growth

restrictionexcessive

growth

AGASGA LGA

19

14 Maternal aspects of fetal growth

141 Maternal nutritional status

Maternal nutritional status is vital for fetal growth as the fetus is dependent on nutrients being

transported from the maternal circulation across the placenta to the fetal circulation The

nutritional status of the mother is generally assessed by indirect means of which Body Mass

Index is a commonly used measurement

Body Mass Index (BMI)

BMI is calculated from a persons weight and height according to the following equation

BMI is used as a surrogate for body fat and has been shown to correlate to direct measures of

body fat such as underwater weighing and dual energy x-ray absorptiometry (DXA) [20]

Although the correlation between BMI and body fatness is fairly strong the correlation varies

by sex race and age At the same BMI women tend to have more body fat than men At the

same BMI older people tend to have more body fat than younger adults Highly trained

athletes may have a high BMI because of increased muscularity rather than increased body

fatness [21] In pregnancy the correlation between BMI and percent body fat is better in early

gestation than in late gestation [22]

The World Health Organisation (WHO) classifies BMI for adults in the following groups [23]

BMI

weight (kg)

[height (m)]2

BMI Weight Status

Below 185 Underweight

185 ndash 249 Normal

250 ndash 299 Overweight

300 and above Obese

20

For adults BMI is interpreted using standard weight status categories that are the same for all

ages and for both men and women For children and adolescents on the other hand the

interpretation of BMI is both age- and sex-specific [24]

Biological effects of high BMI

BMI is used as a surrogate for body fat which is made up of adipose tissue Adipose tissue can

be classified as white adipose tissue (WAT) and brown adipose tissue WAT is excess energy

stored as triglycerides in adipocytes which secrete a variety of substances including

hormones (eg leptin adiponectin and resistin) as well as inflammatory factors [25] Brown

adipose tissue is thought to have a function in thermo genesis Excess adipose tissue can be

estimated by anthropometric measures such as skin fold thickness measured by calipers [26]

Consequences of BMI for pregnancy and labour

Prepregnancy BMI is a major determinant of pregnancy outcome and increasing BMI is

associated with an increased risk of the majority of pregnancy complications like congenital

abnormalities miscarriages gestational diabetes preeclampsia obstructed labour and

operative deliveries [27] Low prepregnancy BMI is associated with low birthweight and

IUGR [28]

Gestational weight gain (GWG)

Gestational weight gain in pregnancy includes growth of the fetus placenta and uterus

increase in maternal plasma volume and accumulation of maternal fat mass [29] The total

amount of weight gained during pregnancy varies considerably among women and lean

women tend to accumulate more fat than obese women [30] Accumulation of fat is primarily

centrally and represents a combination of subcutaneous fat and visceral fat Visceral fat

correlates with metabolic risk factors like hypertension insulin sensitivity and plasma lipids

[31] The ideal gestational weight gain differs depending on the maternal or neonatal outcome

of interest Recommendations for gestational weight gain were revised by the Institute of

Medicine USA in 2009 and highlights both that women should be within a normal BMI range

when they conceive and gain weight within the ranges recommended The recommended

21

weight gain is based on four categories of prepregnancy BMI Higher categories of

prepregnancy BMI are recommended a lower weight gain [29]

Consequences of gestational weight gain

Gestational weight gain has consequences for both mother and child in the short and long

term Low GWG is associated with low birthweight and IUGR [32] and high GWG is

associated with macrosomia and increased neonatal fat mass [3334] High GWG is

associated with increased risk of pregnancy complications like preeclampsia and diabetes [35]

Restricted GWG in obese women with type 2 diabetes has been shown to influence fetal

growth [36] There are reports on associations between GWG and cesarean section

instrumental deliveries and low Apgar scores but it has been suggested that the effects are

mediated by high birthweight [35] The most consistent adverse outcome for mothers with

large GWG is weight retention post-partum [35]

BMI Weight Status Recommended Gestational

Weight Gain

Below 185 Underweight 13-18 kg

185 ndash 249 Normal 11-16 kg

250 ndash 299 Overweight 7-11 kg

300 and above Obese 5-9 kg

22

142 Maternal metabolism

As the fetus is dependent on nutrients from the maternal circulation not only the maternal

intake of nutrients but also the maternal metabolism plays a major role in fetal nutrition There

are adaptations to maternal metabolism that occur during pregnancy to ensure that the

increasing nutritional demands of the mother the placenta and the fetus are met Adaptations

are made in the metabolism of all major groups of nutrients

Glucose metabolism in pregnancy

The human fetus is highly dependent on glucose derived from the maternal circulation for

growth and development [2] Changes occur in the maternal glucose metabolism during

pregnancy to ensure that the increasing nutritional demands of the mother the placenta and

the fetus are met Previously published data on glucose metabolism suggested a decrease in

fasting glucose with gestation [37] Fasting glucose levels of pregnant women have been

shown to decline in early pregnancy and thereafter not decrease much further [38] In our

cohort we found fasting glucose to increase slightly with gestational age [39] There is an

increase in basal hepatic glucose production by up to 30 with increasing gestational age

[37] The insulin sensitivity shows a marked change in pregnancy Overall insulin sensitivity

decreases during pregnancy and in late pregnancy a reduction of 50-70 is estimated

compared with non-pregnant women [40] Insulin secretion increases by up to 200-250

[40]

Lipid and amino acid metabolism in pregnancy

The lipid metabolism in pregnancy is characterized by a marked hyperlipidemia Triglyceride

concentration increases and in particular very low-density lipoprotein (VLDL) triglyceride

concentration which increases 3-fold from week 14 to term Plasma cholesterol levels rise to

a lesser degree In obese women the hyperlipidemia is further exaggerated [27] There is an

overall increase in protein synthesis in pregnancy This includes maternal tissues like breasts

uterus and the liver as well as the fetus and the placenta [27]

23

143 Other maternal factors

Age and parity

Both maternal age and parity have an effect on fetal growth Young women especially

adolescents give birth to smaller newborns than older women [41] Birthweight increases with

maternal age until the 30s after which there is a decline resulting an inverse u-shaped curve

[42] Age is however closely linked to parity Birthweight increases with parity and the

largest increment of approximately 200 grams is between the first and second child [43] In

multiple models birth order exerted a greater influence on birthweight than maternal age [42]

The biological explanation behind these associations is only partly understood The effect of

parity may be partly explained by the capacity of the spiral arteries to expand which is higher

in the subsequent pregnancies than in the first pregnancy [44]

Maternal blood supply to the uterus

The uterus receives blood mainly from the uterine arteries which are branches of the internal

iliac artery The uterine arteries branch into thinner vessels first the arcuate arteries then the

radial arteries followed by the basal arteries which continue into the endometrium as the

spiral arteries The spiral arteries undergo remodeling in early pregnancy which means they

loose smooth muscle and elastic tissue from their walls This remodeling of maternal vessels

is a key aspect of early pregnancy and vital for a successful outcome Ultrasound studies have

estimated both the changes in diameters of the uterine artery and the blood flow velocity in

these vessels Several studies have reported that the diameter of the uterine artery increases

approximately 3-4 fold from non-pregnant state to term [4546] The flow velocity increases

with gestational age but reported values differ somewhat depending on whether the

measurements are made on one or both uterine arteries and the laterality of the placenta

[4546] The fraction of the cardiac output that is distributed to the uterus has been estimated

to be 35 in early pregnancy and near 12 at term [46]

24

Figure 2 Blood supply to the uterus

From Grayrsquos Anatomy 20th US edition electronically retrieved from Wikimedia commons

25

15 Placental aspects of fetal growth

151 Development structure and growth of the placenta

Normal placental development and maternal adaptation to pregnancy are crucial factors for a

successful pregnancy The placentation process and maternal adaptation are closely linked and

happen as parallel processes ensuring a healthy outcome for both mother and child Many

complications of pregnancy can be ascribed to defects in early placentation andor inadequate

maternal adaptation to pregnancy Therefore knowledge of these processes is essential in

understanding the pathophysiology of pregnancy complications

The development of the placenta begins as soon as the conceptus reaches the uterus on day 3-

4 after fertilisation By this stage the blastocyst has an outer wall and an inner cell mass The

outer wall consists of trophoblast cells which undergo transformation to either fuse into a

syncytial cell layer or form individual cytotrophoblasts Extra villous trophoblasts are named

so because of their location in the maternal endometrial (decidual) tissue and play an

important role by starting the trophoblast invasion and the adaptation of the maternal vessels

to pregnancy During this process the endometrial stromal cells differentiate into decidual

cells The extra villous trophoblasts migrate through the decidua basalis and into the inner

third of the myometrium aided by a range of proteases that degrade or remodel the maternal

extra cellular matrix

The amnion arises from the inner cell mass and makes contact with the chorion by early

second trimester Lacunae are formed within the syncytiotrophoblast and the lacunar system is

transformed into the intervillous space

The majority of the villous mass forms the placenta whereas the remainder of the villous

tissue begins to regress resulting in the chorion This remodeling ensures that rupture of

membranes and delivering of the baby can occur at birth without tearing through the placenta

This remodeling occurs at the same time as the maternal blood flow starts in the periphery of

the developing placenta

26

Figure 3 The structure of placenta

From Grayrsquos Anatomy 20th US edition electronically retrieved from Wikimedia commons

The villous mass is made up of a tree of branching villi The branches are classified according

to caliber position within the villous tree and function and goes from the larger stem villi via

intermediate villi to the thinner and distal terminal villi In a mature normal placenta stem

villi account for 20-25 intermediate villi approximately 25 and terminal villi around 40

of the total villous volume The maternal-fetal exchange takes place primarily at the

terminal villi and to some extent at the intermediate villi [47]

Figure 4 Terminal villi

Illustration by Oslashystein H Horgmo University of Oslo

27

Figure 5 Development of the placenta

Fertilized egg

blastocyst

Trophoblast

Cytotrophoblasts

Syncytiotrophoblasts

Extravillous

Villous

Inner cell mass

Fetus

Amnion

Yolk sac

-Primary villi

-Secondary villi

-Tertiary villi

-mesenchymal villi

-immature intermediate villi

-stem villi

-mature intermediate villi

-terminal villi

Matu

ratio

n

ofvilli

Angiogenesis

Transformation of

spiral arteries

Placental villi

Modified after Bernischke et al Pathology of the Human Placenta 2012

The syncytiotrophoblast layer covers a surface area of 12-14 m2

at term [48] It is covered by

microvilli which increase the surface area by a factor of five- to seven The

syncytiotrophoblast layer is comprised by two membranes the maternal-facing microvillous

membrane (MVM) and the fetal-facing basal membrane (BM) The syncytiotrophoblasts act

as an epithelium and contain high densities of transporter proteins There are transport

proteins for the major groups of nutrients Glucose transport proteins belonging to the GLUT

family transport glucose across the placenta by facilitated diffusion [49] Amino acids are

transported by transporter proteins by an active process [50] Lipids are mainly transported as

free fatty acids (FFA) by simple diffusion or by specific binding proteins [5152] Transporter

proteins for micronutrients and drug transporters involved in the transport of drugs have also

been identified [5354] The syncytiotrophoblast also transport ions and solutes to maintain

membrane potential and cell volume regulation

28

Figure 6 The syncytiothrophoblast cell

Modified by Oslashystein H Horgmo after SLager J Pregnancy 2012

Growth of the placenta

The placenta grows close to linearly throughout pregnancy [5556] Cytotrophoblast cells fuse

continuously to maintain and expand the syncytiotrophoblast layer Little is known regarding

the control of this coordinated sequence of events After around 32 weeks of gestation the

fetal capillaries and syncytiotrophoblast layer come closer as the syncytiotrophoblast becomes

thinner and free of nuclei and most organelles This thinning of the membrane separating the

maternal and fetal circulations aids gaseous exchange and the membrane is known as the

rdquovasculosyncytial membranerdquo [47] The volume of the terminal villi and hence the surface

area increases exponentially throughout pregnancy a process that appears to be dependent on

branching of the villi and angiogenesis [57] Although the villous tree undergoes continuous

growth and differentiation during pregnancy relatively little is known about the regulation of

this process Maternal factors like prepregnancy BMI and GWG have been shown to be

associated with placental growth measured both as placental weight thickness and area [58]

Little is known about fetal factors that may affect placental growth Studies in mice do

however indicate that the fetus itself influences the functional properties of placenta [59]

29

152 Placental functions

The placenta has a range of important functions to ensure a successful pregnancy outcome

including transport of nutrients and gases metabolism and endocrine and protective

functions

Transport of nutrients and gases

a Transport of gases

Oxygen provided by the maternal blood is transferred to the fetal circulation by diffusion

Carbon dioxide and other waste products are removed from the fetus and transported to the

mother by the placenta [9] Chronic exposure during pregnancy to hypoxia as seen at high

altitudes is associated with reduced fetal growth [60] However comparisons of fetal oxygen

extraction between pregnant women at high altitude (3600 m) and sea level (400 m) showed

that the fetus had the ability to adapt and to increase oxygen extraction [60] Studies on

pregnant sheep in vivo showed the O2 consumption per kg of the fetus to be twice that of an

adult and the uteroplacental tissues to consume four-fivefold that of the fetus [61]

b Transport of nutrients

Glucose

Glucose is the primary energy source for the fetus As the fetus to a very limited degree

produces its own glucose the fetus needs to obtain glucose from the maternal circulation

Glucose is transported from the maternal circulation across the syncytiotrophoblasts of the

placenta by facilitated diffusion [49] The syncytiotrophoblast is the main barrier in the human

placenta and is comprised by two cell membranes the maternal-facing microvillous

membrane (MVM) and the fetal-facing basal membrane (BM) The glucose transporters found

in the human placenta belong to the GLUT-family of which there are multiple isoforms The

GLUT 1 is the predominant transport protein in the human placenta at term and is found in

higher concentration on the microvillous membrane than the basal membrane [49] Glucose

transport across the endothelial layer is not well studied

30

The maternal-fetal glucose transfer depends on several factors

Glucose supply Glucose supply is determined by both maternal blood glucose

concentration and blood flow to the placenta

Placental glucose metabolism The placenta not only transfers glucose to the fetus but

consumes considerable amounts of glucose itself Insight into the placental glucose

transfer and metabolism is largely based on data from animal studies in particular on

pregnant sheep Placental glucose consumption is normally very high Estimates

suggest that the placenta consumes about 50 of the glucose extracted from the

maternal circulation [62] Placental glucose metabolism can be altered as a result of

alterations in the supply of other energy-generating substrates like oxygen Hypoxic

conditions has been suggested to increase glucose consumption in the placenta thus

making less glucose available to the fetus [63]

The total surface area of the membranes

Placental glucose transporter density and functions [64]

Maternal-fetal glucose gradient The maternal glucose concentration is higher than the

fetal concentration which creates a maternal-fetal gradient This gradient is thought to

be the driving force for the transfer of glucose from the mother to the fetus The

maternal and fetal glucose concentrations are closely related [65ndash67] The gradient

increases with gestation and so does the placental transport capacity Together this

ensures that placental glucose transfer to the fetus is increased which is needed to meet

the increasing needs of the growing fetus A lower fetal glucose concentration leads to

a larger maternal-fetal glucose concentration gradient which increases transfer of

glucose to the fetus In IUGR fetuses the glucose level is lower which creates a larger

gradient and hence increases the transfer of glucose [66] The regulation of fetal

glucose utilization in humans is only partially understood but has been studied in

more detail in pregnant sheep In sheep the rate of fetal glucose utilization depends on

the interaction between fetal plasma glucose and insulin concentrations and the supply

of glucose to the fetus [61] Fetal glucose uptake seems to be regulated by fetal glucose

concentration rather than maternal supply [68]

Insulin Maternal insulin is not transferred across the placenta The major glucose

transport protein in the human placenta at term is GLUT 1 which does not have

insulin receptors [64] The fetal pancreas develops in the first half of pregnancy and

31

sheep experiments have shown that by mid-gestation measurable insulin is produced

[69] Fetal insulin secretion consists of both basal secretion and glucose-stimulated

secretion Studies on pregnant sheep have revealed that both basal and glucose-

stimulated insulin secretion increases over gestation and responds to changes in fetal

glucose concentration as well as duration and pattern of change Chronic marked

hyperglycemia in sheep gave down-regulation of both glucose-stimulated and basal

insulin secretion whereas pulsatile hyperglycemia increased fetal insulin secretion

[7071] Hypoglycemia has been shown to decrease basal- and glucose-induced insulin

secretion [72] Insulin is an important growth hormone in utero and deficiency of

insulin leads to growth restriction in the fetus Fetal hyperinsulinaemia leads to

increased weight gain particularly in species with a high body fat content at birth like

the humans [73] The mechanism in which insulin stimulates fetal growth is in part

thought to be its anabolic effects on glucose and amino acid metabolism through

increased cellular uptake of glucose that maximizes the transplacental concentration

gradient for glucose and hence increases transport of glucose across the placenta

Lipids

Fatty acids are necessary for the fetus for various purposes as a source of energy as elements

of cellular membranes and for development of tissues and organs Maternal triglycerides (TG)

have been suggested as a more important source of fatty acids than nonsesterified fatty acids

(NEFAs) TG are hydrolyzed by placental lipases (lipoprotein lipase) to free fatty acids which

can diffuse freely across the placenta or be taken up by the placenta via fatty acid transport

proteins [51] Total levels of fatty acids are lower in the fetal than the maternal circulation but

the fatty acid profile is different with higher proportions of long chain polyunsaturated fatty

acids [9]

Amino acids

Fetal plasma amino acid concentrations are higher than maternal concentrations Amino acids

are taken up against a concentration gradient by secondary active transport systems in the

MVM More than 20 amino acid transport systems are expressed in the human placenta [74]

These are categorized as heterodimeric (eg system L) or monomeric (eg system A) Amino

32

acids are required by the fetus for protein synthesis but can also be metabolized by the fetus

[9] Reduced fetal plasma concentration of a number of amino acids have been reported in

studies of IUGR [75]

c Endocrine functions

The placenta metabolizes a number of substances and releases metabolic products into the

maternal andor fetal circulations The placenta thus has endocrine paracrine and autocrine

functions There are numerous hormones that are produced by the placenta in order to

maintain and regulate pregnancy [9]

Estrogen

Estrogens are produced by the syncytiotrophoblasts in large amounts during pregnancy 80-

90 of the the steroids produced in the placenta are secreted into the maternal blood The

fetus is the main source of the precursors used for production of estrogens and they are

produced in the fetal adrenal gland and the fetal liver [76] The estrogens act as specialized

growth hormones for the reproductive organs of the mother [9]

Progesterone

Progesterone is produced by the corpus luteum in the first weeks of pregnancy and later by

the trophoblasts in the placenta The plasma levels increase throughout pregnancy

Progesterone is synthesized largely from maternal plasma low density lipoprotein (LDL)

cholesterol The fetus contributes few or no precursors for progesterone synthesis In normal

pregnancy there is little de novo synthesis of progesterone in the fetus The progesterone

preferentially enter the maternal circulation and very little crosses to the fetus [76]

Progesterone inhibits uterine contractions

Human Chorionic Gonadotropin (HCG)

HCG is a glycoprotein which is structurally similar to Luteinizing Hormone (LH) Follicle

Stimulating Hormone (FSH) and Thyroid Stimulating Hormone (TSH) and is mainly

33

synthesized in the syncytiotrophoblasts HCG enters the maternal circulation at the time of

implantation and is detectable in maternal plasma and urine The concentration peeks at week

8-10 of pregnancy after which it declines The biological function is believed to be

maintenance of the corpus luteum stimulation of fetal testicular testosterone secretion and

stimulation of the maternal thyroid gland [76]

Human Placental Lactogen (HPL)

HPL is a polypeptide which is structurally similar to human growth hormone and human

prolactin It is mainly produced by the syncytiotrophoblasts It is detectable in the maternal

circulation by week 5 and rises steadily and approximately proportional to placental mass

until week 34-36 There is little HPL detectable in maternal urine or in fetal plasma HPL

participates in metabolic processes by stimulating lipolysis HPL thereby functions primarily

to ensure nutrient supply to the fetus by efficient mobilization of maternal tissue stores [76]

34

16 Sexual dimorphism in fetal growth and placental function

There are well-known sex specific differences in fetal growth Birthweight of boys is

generally higher than that of girls Body composition also differs boys being longer and

having larger head circumference than girls whereas girls have higher fat percentage than

boys [16] Fetal-placental weight ratio is greater in boys than in girls indicating a higher

placental efficiency among boys [77] Male fetuses grow faster than girls in utero and one

study reported that the difference was statistically different from week 28 onwards [78] Boys

outnumber girls at birth A study from the Norwegian Birth Registry (MBR) found a ratio of

106 among all births This ratio was higher among births in lower gestational age groups as

high as 248 in 16-19 weeks of gestation [79] Similar findings have been reported in multiple

populations [80] Perinatal mortality is generally higher in boys than in girls and in the study

from MBR of Norway it was approximately 20 higher in boys than girls across the whole

range of gestational age groups [79] Attempts have been made to explain the increased

vulnerability observed in boys by sex specific differences in the developmental environment

including possible differences in placental functions Although there are obvious differences

in fetal growth to my knowledge there are no published data on sex specific differences in

nutrient transport across the placenta However there are reports on sex specific differences

in other aspects of placental function especially related to inflammatory responses and

endocrine functions In pregnancies complicated with maternal asthma there was increased

cytokine production in male placentas compared to female placentas [81] Differences in

cytokine production have been suggested to contribute to the observed increased incidence of

preterm delivery in males [82] Glucocorticoids given as repeated doses have been shown to

reduce fetal growth [83] Data suggest that the male and female fetal-placental unit responds

to cortisol in a differential manner Among pregnant women with asthma there were similar

levels of maternal cortisol but female fetuses responded with a reduction in birthweight

whereas the growth of the male fetuses was normal [84] Data on placental properties from

male and female are generally pooled but significant findings may be lost as male placentas

might have different responses than female placentas The different strategies to cope with

the same maternal environment has been summarized by V Clifton [84] She proposed that

male responses lead to minimal placental adjustment in gene and protein expression and that

the target is to increase or continue growth resulting in a greater risk of adverse outcome

Females on the other hand have multiple adaptations in placental gene and protein expression

and minor reduction in growth resulting in increased survival

35

17 Preeclampsia

Preeclampsia is defined as new onset hypertension (blood pressure gt14090) and proteinuria

(gt03 g per 24 hours) in the second half of pregnancy [85] This pregnancy complication

affects between 3 to 5 of all pregnancies depending on the population Preeclampsia is a

leading cause of mortality and morbidity for both mother and child worldwide particularly in

the developing world Worldwide preeclampsia accounts for more than 50 000 maternal

deaths annually [86] Risk factors include genetic factors multiple pregnancies high maternal

age obesity insulin resistance preexisting hypertension diabetes mellitus and renal disease

[87] Around 70 of cases of preeclampsia occur after 37 weeks of gestation [88]

Clinical picture

The symptoms of preeclampsia are diverse reflecting the underlying syndrome The systemic

vascular involvement is reflected not only in hypertension and proteinuria but can likewise

affect the vasculature in other organs like the liver and the brain When the liver is involved

symptoms and signs include abdominal pain nausea vomiting and elevated liver enzymes In

the case of HELLP (hemolysis elevated liver enzymes and low platelets) all these are present

along with the disturbances in the coagulation system In case of brain involvement visual

disturbances and eclampsia can occur Cerebrovascular complications like stroke and cerebral

hemorrhage are other feared maternal complications The fetus of preeclamptic pregnancies

faces increased risk of oligohydramnios IUGR and prematurity [89]

Classification

Preeclampsia has both a multifactorial pathogenesis and a heterogeneous clinical presentation

which complicates classification Classifications in use are according to pathophysiological

characteristics clinical severity presence of other maternal or fetal characteristics or

gestational age at presentation Classification based on pathogenesis suggests two broad types

of preeclampsia placental and maternal preeclampsia reflecting which element is more

prominent in the pathophysiology These subtypes are more of a theoretical framework than

different biological entities as most cases will rather be represented by a combination of both

The dichotomized pathophysiological classification can briefly be described as placental

preeclampsia when there is an abnormal placentation but basically a normal maternal

36

endothelium and maternal preeclampsia when the maternal endothelium is dysfunctional and

the placentation normal Classification according to severity of disease is used by American

College of Obstetrics and Gynecology (ACOG) Severe preeclampsia is defined as

hypertension (gt160110) and proteinuria (gt5 g per 24 hours or +3 on dipstick) or

accompanying symptoms and signs like oliguria cerebral disturbances impaired liver

function thrombocytopenia or fetal growth restriction [85] Early onset preeclampsia is often

defined as presentation before 34 weeks and late onset as after 34 weeks of gestation These

subtypes have different clinical presentations with the early-onset typically exhibiting more

serious clinical featuressymptoms and fetal growth restriction than the late onset [90]

Pathophysiology

Clinical symptoms of preeclampsia arise in the second half of pregnancy which can be

considered the last stage in the development of the disorder The preceding stages include the

placentation process which involves an immunologically regulated interaction between the

placenta and the maternal endothelium Placenta is necessary for the development of

preeclampsia but preeclampsia can occur without a fetus as in hydatidiform mole The

symptoms disappear after delivery of the placenta In preeclampsia the trophoblast invasion is

restricted to the decidua and does not reach the inner third of the myometrium resulting in

inadequate remodeling of spiral arteries The normal loss of smooth muscle and enlargement

of the spiral arteries is therefore restricted

Normal placentation further requires immune tolerance for fetal and placental antigen which

might be altered in preeclampsia There is a low-grade systemic inflammatory response

present in normal pregnancy which is enhanced in preeclampsia [91] The maternal

endothelium becomes activated and eventually dysfunctional Preexisting maternal vascular

dysfunction might render the maternal endothelium more sensitive to the burden of these

factors leading to endothelial dysfunction

Disturbed endothelial maintenance

In patients with preeclampsia there is an angiogenic imbalance in the circulation resulting in

more anti-angiogenic than angiogenic factors ie more of endothelium-disturbing and less

endothelium-supportive factors The vascular endothelial growth factors (VEGF-family) are

37

involved in angiogenesis and endothelial maintenance by affecting migration and

differentiation of endothelial cells [92] The family consists of several glycoproteins

including VEGF-A and PlGF among others Both of these have pro-angiogenic effect The

VEGF receptors are present on vascular endothelial cells and include VEGFR-1 (Flt-1) and

VEGFR-2 (KDR) VEGF binds to both receptors whereas PlGF binds exclusively to VEGFR-

1 (Flt-1)

Figure 7 Angiogenic imbalance

sFlt-1

sFlt-1 is a soluble form of the VEGFR-1 produced by alternative splicing [93] Placentas from

preeclamptic pregnancies show higher expression of sFlt-1 mRNA than normal placentas [94]

How much placenta actually contributes to the circulating sFlt-1 is however not settled sFlt-1

binds free VEGF and free PlGF and thereby inhibits their beneficial actions on the vascular

endothelium sFlt-1 increases with gestational age in normal pregnancy but is significantly

higher in women destined to develop preeclampsia from approximately week 26 and peaks

around week 34 [95]

38

sEndoglin

The transforming growth factor-β (TGF- β) family of proteins is known to be involved in

angiogenesis but has diverse actions in many cells Endoglin is a TGF-β coreceptor expressed

in endothelial cells and syncytiotrophoblasts of the placenta [87] A soluble form of endoglin

(sEng) is present in sera from preeclamptic patients There is a three- five- and tenfold

increase in sEng in mild PE severe PE and HELLP syndrome respectively [96] Endoglin

mRNA expression in placentas from preeclamptic pregnancies is fourfold increased compared

to healthy pregnancies [96] But again the placental contribution to circulating sEng is

unclear sEng increases with gestational age but in women destined to develop preeclampsia

the increase is significantly higher than healthy controls from week 23 (preterm PE) and week

30 (term PE) Interestingly women destined to deliver a SGA infant had increased sEng

levels from week 10 [95]

sEng and sFlt-1 given together increased capillary permeability in the lungs liver and kidney

of mice and induced hypertension in pregnant rats [96] demonstrating a possible combined

action of sFlt-1 and sEng in the pathogenesis of PE

PlGF

Placental growth factor is one of the members of the VEGF-family which has proangiogenic

activity [92] In non-pregnant women circulating levels are low but PlGF can be produced by

the heart and lungs skeletal muscle and adipose tissue PlGF is expressed by the placenta in

particular the syncytiotrophoblasts [97] In pregnancies complicated by preeclampsia PlGF

concentrations are lower than normal pregnancies [98] In normal pregnancy PlGF can be

detected from first trimester and increases until around week 33 after which it declines

towards term PlGF binds to the VEGFR-1 (Flt-1) receptor PlGF is necessary to stimulate

angiogenesis eg after myocardial injury The function of PlGF in pregnancy is not clear but

might be to regulate maternal vascular function by displacing VEGF from the Flt-1 receptor

so that it binds to the more active Flt-2 receptor (KDR) [87]

39

Figure 8 Endothelial integrity and dysfunction

VEGF

PlGF

Flt1

(VEGFR-1)

VEGF

PlGF

Endothelial integrity

Tore Henriksen 2006

VEGF

PlGF

Flt1

(VEGFR-1)

VEGF

PlGF

Endothelial dysfunction

Tore Henriksen 2005

Treatment

There is no causal treatment besides delivery of the baby and the placenta Symptomatic

antihypertensive treatment should be given to reduce maternal complications [85]

Preeclampsia can be complicated by eclampsia stroke disseminated intravascular coagulation

(DIC) HELLP placental abruption and acute renal failure Because the only treatment is

delivery preeclampsia leads to prematurity and increased risk of perinatal mortality and

morbidity

Prevention

40

Studies assessing interventions to reduce rate or severity of preeclampsia have been

conducted There is insufficient evidence to recommend rest reduced salt intake fish-oil

supplementation and antioxidant vitamins as preventive measurements [99] A Cochrane

review concluded that low-dose aspirin had small to moderate benefits (15 risk reduction)

when used for prevention of preeclampsia but that more information is needed to assess

which women are most likely to benefit when to start treatment and at what dose [100]

Calcium supplementation reduced risk of preeclampsia and can be considered for high risk

groups in low-intake populations [101]

Prediction

Many features of preeclampsia are exaggerated responses also present in normal pregnancies

In terms of diagnosis or prediction it is difficult to draw a clear distinction between normal

and abnormal No test predictive or diagnostic can be expected to distinguish absolutely

between different degrees of features that are common to all pregnancies Many tests have

been assessed as potential predictors of preeclampsia but no single test has yet met the

clinical standards for a predictive test Combinations of tests such as ultrasound assessment of

uterine artery Doppler waveforms and serum markers have been suggested as have ratios of

antiangiogenic and proangiogenic factors However sensitivity and specificity of the markers

PlGF sFlt-1 and sEng are too poor for accurate identification of preeclampsia in clinical

practice and hence not recommended used alone for the prediction of preeclampsia [102]

Predictive tests could ideally either identify those destined to develop preeclampsia during

pregnancy or differentiate between a serious or mild form among those diagnosed with

preeclampsia The latter would be of clinical importance in handling these patients

Long-term complications

Risk of recurrent preeclampsia depends on severity and onset of preeclampsia in the previous

pregnancy but can be up to 40 for severe disease [103] Women with a history of

preeclampsia have an elevated risk of cardiovascular disease later in life According to a

meta-analysis the risk of hypertension is 3-4 times the risk for women without preeclampsia

41

and the risk of death from cardiovascular and cerebrovascular disease about twice as high as

in women without preeclampsia [104] The mechanisms for the increased risk are not yet fully

understood but shared risk factors for preeclampsia and cardiovascular disease may jointly

predispose [105] This could be the case for chronic hypertension diabetes mellitus and renal

disease

42

2 Aims of the study

Overall aim

The overall aim of this thesis was to gain insight into the associations between maternal

nutritional and metabolic factors and fetal growth and aspects of placental function in normal

and preeclamptic pregnancies

Specific aims

Paper 1

The aims were to

1) Estimate and compare the effects of maternal characteristics on birthweight and on fetal

growth in third trimester

2) Introduce placental weight as a possible determinant of birthweight and of fetal growth in

third trimester

We hypothesized that maternal factors and placental size were associated with birthweight

and fetal growth

Paper 2

Given the findings in Paper 1 the aim was to study the effects of maternal factors (parity

BMI gestational weight gain and fasting glucose) on placental weight stratified by fetal sex

We hypothesized that the maternal factors mentioned above affected placental weight Based

on emerging evidence we also hypothesized that there were differential effects between fetal

sexes

Paper 3

Based on the observations in Paper 1 and 2 the aims were to

1) Establish an in vivo model in the human

2) To use the model to study human placental transfer of glucose in vivo to describe the

glucose and insulin concentrations in the uteroplacental and umbilical circulation in healthy

43

pregnancies at term and to explore the relation between maternal and fetal glucose

concentrations

We hypothesized that maternal plasma glucose was the major determinant of the fetal venous-

arterial gradient

Paper 4

Preeclampsia is a pregnancy specific placenta dependent disorder Preeclampsia has two

prominent features maternal vascular dysfunction and placental insufficiency Using the in

vivo model the aim was to investigate factors that may link placental disturbance to maternal

vascular dysfunction For this purpose sFlt-1 and sEng were chosen

We hypothesized that both sFlt-1 and sEng originate in placenta by finding that the plasma

concentration was higher in the maternal venous than the arterial side of the uteroplacental

circulation

44

3 Materials and methods

This thesis consists of four papers based on two separate studies that differ in design

population and methodological issues and will therefore be described separately

The STORK study

The STORK study is a prospective longitudinal study performed in the period 2001-2008 A

total of 1031 healthy pregnant women who gave birth at Oslo University Hospital

Rikshospitalet Norway and their newborn infants were included in the study Inclusion

criteria were healthy women of Scandinavian heritage with singleton pregnancies Exclusion

criteria were multiple pregnancies known pregestational diabetes and any severe chronic

diseases (lung cardiac gastrointestinal or renal) as well as any malformations discovered at

the routine ultrasound examination at week 17-19

Population

Eligible women were identified by one of the three PhD candidates in the project Invitation to

participate was sent to eligible women as they were registered for obstetric care at the

beginning of pregnancy Those interested in participating confirmed by phone to a secretary

who enrolled them in the study The number of women invited to participate varied over time

due to capacity The capacity for the oral glucose tolerance test (OGTT) was the ldquorate-limiting

steprdquo The drop-out rate was very low 33 of those who were included Thirty-two women

were excluded because of twin pregnancies or malformations that were diagnosed at the

routine ultrasound scan

45

Figure 9 Flow chart showing inclusion of participants in the STORK study

Withdrawn before

inclusion

n=141

Excluded

n=32

Lost

n=37

Invited to participate

n=4122

Accepted invitation

n=1241

Included

n=1100

Followed up

n=1031

Study design

The STORK study has a longitudinal design Each pregnant woman had four antenatal visits

(visit 1-4) scheduled at weeks 14-16 22-24 30-32 and 36-38 of pregnancy The newborns

were examined shortly after birth

Data collection

Clinical data

Background data was collected at the first visit including past medical and obstetric history

Clinical examination was repeated at every visit Data on the delivery and postpartum period

were extracted from hospital records

Blood samples

Blood samples were drawn at each visit between 0730 and 0830 after an overnight fast

centrifuged and stored at -80ordm C immediately Plasma glucose was measured by Accucheck

(Roche Diagnostics Mannheim Germany)

46

Birthweight

Newborns were weighed on a calibrated scale and measured by the attending midwife or

childrenrsquos nurse within two hours after birth

Ultrasound

Ultrasound examinations were done at visit 2 - visit 4 using an Acuson Aspen machine

(Acuson Mountain View CA USA) Biometric measurements included head circumference

(HC) abdominal circumference (AC) and femur length (FL) Each measurement was made

three times and the mean value was calculated and used in the analyses Estimated fetal

weight (EFW) was calculated by Combs formula [106] Percentiles for estimated fetal weight

and the individual biometric measurements were calculated according to Norwegian charts

[107108] Fetal growth in the third trimester was calculated as the difference between

measurements made at visit 3 and visit 4 for EFW and HC AC or FL respectively

Table 1 Data collection in the STORK study

Statistical analysis

Descriptive statistics were used to characterize the study population Bivariate associations

were explored by scatter plots and correlation analyses Univariate linear regression was used

to study the associations between selected maternal characteristics and the dependent

variablesoutcome variables birthweight and several fetal growth parameters in Paper 1 and

placental weight in Paper 2 Variables with a p-value lt 01 were considered in the multiple

linear regression models Multiple linear regression models were used to study the

Visit 1

14-16 w

Visit 2

22-24 w

Visit 3

30-32 w

Visit 4

36-38 w

At birth

Clinical examination + + + + +

Anthropometric measures

(skin fold thickness)

+ + + + +

Fasting blood samples + + + +

Oral glucose tolerance test + +

Ultrasound

(evaluation of fetal growth)

+ + +

Diet questionnaire + +

Physical activity questionnaire + +

47

associations between selected maternal characteristics and the outcome variables birthweight

fetal growth and placental weight A p-value lt 05 was considered statistically significant

All analyses were done by SPSS 180

Ethical aspects

All participants signed a written consent The study was approved by The Regional

Committee for Ethics South Norway (S- 01191)

48

The STORK-Placenta study

Study design

The STORK-Placenta study was designed to serve several purposes One purpose was to

study placental aspects of fetal growth and this was done as a cross-sectional study among

healthy pregnant women Secondly the study served as a case-control study with two groups

one consisting of preeclamptic patients and one with healthy controls

Population

There are two subgroups of the STORK-Placenta study in Paper 3 and Paper 4 respectively

In Paper 3 we included 40 women Inclusion criteria were healthy non-smoking women with

uncomplicated singleton pregnancy who were scheduled for elective caesarean section

Exclusion criteria were pre-existing co-morbidity any medication and pregnancy

complications like preeclampsia or insulin-dependent gestational diabetes Women who

arrived at the delivery ward with contractions prior to scheduled caesarean section were

excluded The recruitment was done at the out-patient clinic either during the appointment

when caesarean section was decided or during scheduled preoperational information

In paper 4 we included 12 patients with preeclampsia and 7 healthy pregnant women

Inclusion criteria for the study group were the diagnosis of preeclampsia and indication for

caesarean section prior to labour The control group consisted of healthy pregnant women

scheduled for elective caesarean section

Data collection

Medical and obstetrical history was taken at inclusion Clinical data was collected at inclusion

and at the day of delivery

Blood sampling

Blood samples were drawn from both the maternal and the umbilical (fetal) circulation during

caesarean section in spinal anaesthesia Fasting maternal blood samples were obtained by the

obstetrician from the uterine vein preferable on the same side as placenta just before uterine

49

incision Simultaneously blood was drawn by the anaesthesiologist from an arterial line in the

radial artery We assumed similar blood composition in the radial and the uterine artery In

addition blood was drawn from a venous catheter in the cubital vein or dorsal vein network of

the hand Directly after delivery blood samples were obtained from the umbilical artery and

vein immediately after cord clamping Blood was drawn into SAFETY Blood Collection Set

with Luer Adapter (Vaccuette Geiner Bio-One GmbH Austria) Blood samples were

immediately transferred to ethylenediaminetetraacetic acid (EDTA) vacutainers and stored on

ice until all samples were obtained They were then centrifuged at 4-6ordmC 2500 G for 20

minutes before the supernatants were removed and aliquotted and stored at -80ordmC until

analyses were performed

Analyses of samples

Glucose and insulin

Analyses were performed according to standard laboratory methods (Department of Medical

Biochemistry Oslo University Hospital Rikshospitalet) during three consecutive days

Glucose was measured using the hexokinaseglucose-6-phosphate dehydrogenase method

(Roche) Insulin was analysed using the Elecsys insulin analysis which is an enzyme-linked

immunosorbant assay (ELISA) technique with two monoclonal antibodies (Roche)

sFlt-1 and sEng

The concentrations of sFlt-1 and sEng were measured by commercially available ELISA kits

(RampD Systems Minneapolis MN USA) Assays were conducted in duplicate and in one run

The coefficients of variance were lt 10

50

Statistical analyses

Descriptive data were reported as mean values with standard deviations (SD) or percentages

as appropriate The differences in maternal characteristics between groups were compared by

unpaired t-test (Paper 4)

Glucose values were reported as mean values (SD) Comparisons between concentrations of

glucose in maternal and fetal vessels respectively were performed by paired t-tests Due to

skewed distributions insulin concentrations were reported as median values with inter quartile

ranges (IQR) and comparisons of related samples were performed by Wilcoxon sign rank test

Correlations were reported as Pearsonrsquos correlation coefficient if one variable was normally

distributed whereas Spearmanrsquos rank correlation coefficient was used in the case of

correlation between two skewed variables

The distribution of the concentrations for sFlt-1 and sEng were not normally distributed

hence they were log transformed to obtain normal distribution in order to use parametric

methods for statistical analyses Arithmetic median levels are reported in the text and figures

The differences in concentrations between groups were compared by unpaired t-test and the

concentrations in the radial artery and uterine vein from the same individual were compared

by paired t-test However non-parametric tests on the original data gave the same results

Ethical aspects

All participants signed a written consent The study was approved by The Regional

Committee for Medical Research Ethics South Norway (S-071742011-2419)

51

4 Summary of results

Paper 1

In Paper 1 we analyzed the associations between selected maternal characteristics and

birthweight measured as z-scores adjusted for gestational age and fetal sex We found that the

following maternal characteristics were independent determinants of birthweight and

statistically significant in the multiple regression model

Parity (B 046 95 CI 033-059 plt0001)

BMI (B 0048 95 CI 003-006 plt0001)

Gestational weight gain (B 006 95 CI 004-008 plt0001)

Fasting glucose (B 033 95 CI 018-048 plt0001)

In addition placental weight was a determinant for birthweight

Placental weight (B 041 95 CI 038-044 plt0001)

Adjusting for placental weight in the multiple model left the following maternal determinants

statistically significant

Parity (B 036 95 CI 025-047 plt0001)

BMI (B 0018 95 CI 0004-003 p= 0012)

Gestational weight gain (B 0036 95 CI 002-005 plt0001)

Fasting plasma glucose (B 022 95 CI 0009-034 plt0001)

Introducing placental weight as a covariate reduced the effect estimate of the other variables

in the model by 62 for BMI 40 for weight gain 33 for glucose and 22 for parity

The magnitude of reduction was estimated by change in the regression coefficient B of the

linear regression

Fetal growth in third trimester was estimated as the difference in EFW percentiles between

visit 3 and visit 4

In the multiple model the following maternal determinants remained statistically significant

Parity (B 473 95 CI 016-807 p=0006)

BMI (B 064 95 CI 023-106 p=0002)

Gestational weight gain (B 070 95 CI 024-116 p=0003)

52

In addition placental weight was a determinant for intrauterine growth

Placental weight (B 260 95 CI 16-36 plt0001)

Adjusting for placental weight in the multiple model left the following determinants

significant

Parity (B 39 95 CI 075-70 p=0015)

BMI (B 049 95 CI 008-089 p=002)

Gestational weight gain (B 060 95 CI 015-106 p=001)

Introducing placental weight reduced the effect of BMI on intrauterine fetal growth by 23

weight gain by 17 and parity by 14

We also analyzed the associations between maternal factors and the individual biometric

measurements Results from the multiple analyses for the increase in abdominal

circumference showed statistically significant associations for

Parity (B 018 95 CI 007-029 p=0001)

BMI (B 0022 95 CI 0005-003 p=0002)

Gestational weight gain (B 0026 95 CI 0008-004 p=0001)

Fasting glucose (B 044 95 CI -008-017 p=048)

In addition placental weight was a determinant for increase in abdominal circumference

Placental weight (B 011 95 CI 008-014 plt0001)

In the multiple model adjusting for all listed variables and placental weight fasting plasma

glucose was not significant (B 0016 95 CI -011-014 p=08) BMI reached borderline

significance (B 0014 95 CI 000-0028 p=0048) as an independent determinant when

adjusted for parity weight gain and placental weight For growth of the fetal abdominal

circumference BMI showed the largest reduction in B (36 ) when placental weight was

included

53

Paper 2

Given the importance of placental weight for birthweight and fetal growth we studied the

associations between maternal factors and placental weight in Paper 2 Mean placental weight

was 711 g (SD 156)

In the multiple regression model the following maternal factors were independent

determinants of placental weight

Parity (B 292 95 CI 101-484 p=0003)

BMI (B 67 95 CI 41-93 plt0001)

Gestational weight gain (B 56 95 CI 28-84 plt0001)

Fasting glucose (B 329 95 CI 100-557 p=0005)

Boys were heavier (3667 g vs 3494 plt0001) and longer (513 cm vs 503 cm plt0001)

than girls Boys also had a higher fetal placental ratio than girls (526 g vs 508 plt0001)

When stratified by fetal sex fasting glucose was significantly associated with placental

weight in females but not in males

Paper 3

We measured glucose and insulin concentrations in the uteroplacental and umbilical

circulations and calculated arterio-venous gradients The subjects were 40 healthy women

with a mean age of 36 years (SD 32) Mean birthweight was 3571 (SD 527) g range 2680-

4955g

The highest concentration of glucose was found in the maternal arterial circulation with a

mean concentration of 471 mmoll (SD 048) The uterine vein had a lower concentration

giving an arterio-venous difference of 029 mmoll on the maternal side The maternal

concentration of glucose was higher than the fetal concentration The maternal-fetal gradient

was 122 mmoll (SD 042) The concentration in the umbilical vein was 384 mmoll (SD

041) In the umbilical artery the concentration was lower 348 mmoll (SD 045) giving a

fetal venous-arterial difference of 038 (SD 031)

54

Maternal arterial and fetal venous concentrations of glucose were highly correlated (r=086

plt0001) Maternal arterial glucose concentration was not significantly correlated to the fetal

glucose v-a difference (r=03 p=007) The maternal a-v glucose difference was neither

correlated to the level of glucose in the umbilical vein nor the fetal glucose difference The

maternal-fetal gradient was highly correlated to the fetal glucose difference (r=08 plt0001)

The maternal-fetal glucose gradient was also correlated to the glucose concentration in the

umbilical artery (r=-038 p=0017) whereas it was not correlated to the glucose concentration

in the umbilical vein Similarly the fetal glucose v-a difference was only correlated with the

glucose concentration in the umbilical artery (r=-045 p=0004) but not with the glucose

concentration in the umbilical vein

The glucose concentration in the umbilical vein was not correlated to birthweight or placental

weight whereas correlation between the fetal glucose v-a difference and birthweight just

reached borderline significance (r=032 p=0049)

We found no relation between maternal and fetal insulin values (rho=-01 p=057) Maternal

and fetal concentrations of insulin were not statistically different On the maternal side

glucose and insulin concentrations were correlated (r=052 p=0001) On the fetal side

however no such correlation was found (r=012 p=048) Fetal insulin was correlated to both

placental weight (r=046 p=0003) and birthweight (r=058 plt0001)

Paper 4

We measured the anti-angiogenic factors sFlt-1 and sEng in a group of preeclamptic patients

and in healthy controls Both factors have been suggested to be released by the placenta and

involved in the pathogenesis of preeclampsia

Preeclamptic women had

Higher concentration of sFlt-1 than healthy controls (median of 17450 pgml of sFlt-1

compared to 5055 pgml in the control group p= 0003)

Higher concentration of sEng than healthy controls (median of 687 ngml in the

preeclampsia group versus a median of 287 ngml in the control group p= 0003)

55

We compared the concentration in the blood entering the uteroplacental unit (radial artery as a

proxy for uterine artery) and the blood leaving the uteroplacental unit (uterine vein)

Preeclamptic women had

Higher concentration of sFlt-1 in the uterine vein than in the radial artery (22450 vs

17450 pgml p=0005) whereas the concentration of sEng was not statistically different

(757 vs 687 ngml p=012)

Among healthy controls

No significant differences in the concentration between the uterine vein and the radial

artery for sFlt-1 (6193 vs 5055 pgml p=039)

No significant differences in the concentration between the uterine vein and the radial

artery for sEng (307 vs 287 ngml p=059)

56

5 Discussion

51 Methodological issues STORK

511 Design

The STORK study has a longitudinal design with four antenatal visits and observations at

birth for the 1031 women and children included Longitudinal studies are well suited to study

associations between explanatory variables and outcomes but not suitable to assess causality

The associations found in our study would need to be tested in a RCT or experimental model

to assess causality

512 Validity

The word valid is derived from the Latin validus meaning strong Validity in terms of

research refers to whether the results obtained answer the questions asked in the study

Validity can further be divided into internal and external validity [109]

Internal validity

Internal validity refers to whether the conclusions reached are likely to be correct for the

circumstances of that particular study Bias undermines the internal validity and includes

selection bias information bias and confounding bias [110]

Selection bias

Selection bias can result when the selection of subjects into a study (subject selection bias) or

their likelihood of being retained in the study (loss to follow up bias) leads to a result that is

different from what you would have obtained if you had enrolled the entire target population

[110]

57

Subject selection bias

In the current study invitation to participate was sent to 4122 and 1241 accepted the invitation

The number of invitations sent per week varied according to the capacity to enroll in the study

and the limiting factor was four Oral Glucose Tolerance Tests per day There were periods of

reduced capacity like holidays when fewer invitations were sent but it is not likely that the

women invited would be any different to the ones not invited due to varying capacity

The self-selection procedure (the women themselves phoned to be enrolled) might have

resulted in selection of women that were particularly motivated to participate The opportunity

to get closer follow-up than standard antenatal care may have caused selection bias Three

evaluations of fetal well-being and fetal growth by ultrasound could theoretically have

attracted women with a previous history of fetal growth abnormalities Data on birthweight of

previous children revealed that for those who had one previous child average birthweight was

3655 g (SD599) whereas the second child on average weighed 3808 g (SD 706) The data was

normally distributed with no overrepresentation of SGA or LGA (data not shown) Thus there

was no obvious selection of women with a history of fetal growth abnormalities in our study

population

Loss to follow up bias

The number of patients lost was 37 giving a drop-out rate of only 33 The number of

patients excluded was 32 The numbers lost are small and not likely to have influenced the

results substantially All participants had birthweight and placental weight recorded

However the outcome intrauterine fetal growth could only be estimated for those who

attended both third and fourth visit 918 in total Those who gave birth prematurely (54)

were not included in this outcome Maternal characteristics were not different in this group

compared to the total group (data not shown)

The selection bias only influences the results if the women selected or lost differ in either their

characteristics or in the outcomes which does not seem to be the case in our study

Information Bias

Information bias arises if the information has not been gathered in the same way for all

participants It includes observational bias misclassification and measurement errors and can

58

occur during collection of data as well as coding and processing of the data Misclassification

includes classifying binary or discrete variables incorrectly We minimized misclassification

by using mostly continuous variables rather than categorical variables Bias might be

introduced by the observer (interviewer bias biased follow-up) by the study participants

(recall bias) or by measurement tools such as questionnaires or instruments

We might have introduced biased follow-up for at least one group of women The women

diagnosed with gestational diabetes mellitus at visit 3 were taught and encouraged to make

changes in diet and physical activity to prevent further deterioration in their glucose

metabolism This might have had an influence by reducing the outcomes birthweight and

intrauterine fetal growth in third trimester

Recall bias occurs when there are systematic differences in the way subjects remember or

report exposures or outcomes We tried to avoid recall bias by eg using measured weight and

height to calculate BMI instead of self-reported prepregnancy BMI Reviewing available data

on the relationship between self-reported and directly measured height and weight has shown

trends of under-reporting for weight and BMI and over-reporting for height [111]

Measurement errors will be discussed under data collection below

Confounding bias

A confounder is defined in epidemiological terms as a covariate that influence both the

independent and the dependent variable and can be controlled for by adding it to a multiple

regression model Confounders must be identified and then appropriately adjusted for in the

analyses [112] The statistical considerations around confounding will be discussed under

statistical issues in the discussion below

In Randomized Controlled Trials (RCT) confounding is avoided by randomly assigned groups

that differ only in the factor being studied and thereby removes the need to statistically control

for confounders In an observational study like STORK we tried to reduce the need for

adjusting for confounding factors related to comorbidities by selecting healthy women and to

avoid ethnic factors by selecting women of Scandinavian heritage

59

External validityRepresentativity

External validity or representativity refers to whether the results obtained in one study can be

generalized to other situations and to other populations [110]

To assess representativity we did two comparisons Our cohort was compared to a group of

women who delivered at Ullevaringl the largest obstetric unit in Oslo The comparison was

restricted to women of Scandinavian heritage and our cohort only differed in having fewer

smokers and single mothers (data not published)

We also compared our cohort to data from the Birth Registry of Norway Our study

population was comparable to women who gave birth in Oslo in 2009 on parameters like

maternal age parity gestational age (GA) at birth and birthweight (BW)

Figure 10 Comparison between STORK cohort and Oslo

0

10

20

30

40

50

60

Age P0 GA BW

STORK

OSLO 2009

Retrieved electronically from the Birth Registry of Norway [1]

60

513 Statistical issues

Longitudinal data

Analyzing longitudinal data with variables that are correlated over time is a statistical

challenge which can be solved by the use of mixed models However these methods are

complicated and require statistical knowledge that was not readily available to our group We

therefore chose our variables to be able to use conventional linear regression models Fetal

growth was defined as growth between visit 3 and visit 4 thereby confining fetal growth to

the third trimester The whole trajectory of fetal growth was thereby not fully explored

Similarly we only used fasting glucose concentrations at one time point as a covariate in the

multiple models instead of the change in glucose levels over time

Continuous versus categorical variables

We have chosen to use mostly continuous variables both as outcome and explanatory

variables instead of dichotomizing or creating groups This is based on both methodological

theory and published data on physiology in pregnancy Dichotomizing leads to several

problems [113] According to Altman much information is lost the statistical power is

reduced one may underestimate variation and non-linearity in the relation between variable

and outcome may be concealed [114] A large study of hyperglycemia in pregnancy (HAPO)

has shown that there is a linear relationship and no threshold value between fasting glucose

and adverse pregnancy outcomes [115] A similar relationship was seen between BMI and

adverse pregnancy outcomes [116]

Confounders mediators and colliders

A number of potential factors can influence the associations of interest These must be

identified and possibly corrected for in the regression models Whether to adjust for these

factors depend on classification of the factors into true confounders mediators and colliders

[112] Confounders should be included while colliders should no be included in regression

models to avoid introducing bias

A confounder (defined above) can be controlled for by adding it to a multiple regression

model The choice of which confounders to include in the model requires physiological

61

Independent variable Outcome

Confounder

Independent variable Outcome

Mediator

Independent variable Outcome

Collider

knowledge and requires statistical considerations when it comes to the number of observations

required [117] A mediator is considered a covariate that is on the causal pathway between the

independent and the dependent variable A collider is considered a covariate that is related to

both the independent and dependent variable in a common consequence [117] In our material

no included variables were considered to be colliders

Figure 11 Confounders mediators and colliders

62

Mediation

A mediator variable can either account for all or some of the observed relation between two

variables The effect of mediation can be assessed by judging what happens to the relation

between the independent and dependent variable when the mediator is included into the

regression model or not Full mediation would occur if inclusion of the mediation variable

removed the relation between the independent variable and dependent variable This rarely

occurs The most likely event is that the association becomes weaker yet still a significant

path with the inclusion of the mediator Partial mediation occurs when the mediating variable

accounts for some but not all of the relationship between the independent variable and

dependent variable Partial mediation implies that there is not only a significant relation

between the mediator and the dependent variable but also some direct relation between the

independent and dependent variable

One method to assess mediation was proposed by Baron and Kenny in 1986 [118] They laid

out several requirements that must be met to form true mediation relationships which are

summarized below

Step 1 Confirm that the independent variable is a significant predictor of the dependent

variable Independent Variable Dependent Variable

Y = β10 + β11 X + 1

β11 is significant

Step2 Confirm that the independent variable is a significant predictor of the mediator If the

mediator is not associated with the independent variable then it couldnrsquot possibly mediate

anything Independent Variable Mediator

Me = β20 + β21 X + 2

β21 is significant

Step 3 Confirm that the mediator is a significant predictor of the dependent variable while

controlling for the independent variable This step involves demonstrating that when the

mediator and the independent variable are used simultaneously to predict the dependent

63

variable the previously significant path between the independent and dependent variable is

now greatly reduced if not nonsignificant

Y = β30 + β31 X + β32 Me + 3

β32 is significant

β31 should be smaller in absolute value than the original mediation effect (β11 above)

Placental weight can be considered a mediator in this study Regression models are therefore

done with and without placental weight as a covariate in the model to show its role as a

possible mediator We applied the model by Baron and Kenny described above to show a

possible role of the placenta as a mediator Our results point at possible mediating pathways

involving the placenta on the causal pathway to fetal growth In order to quantify how much

of the effect that goes through the placenta we could have applied path analyses However

this method required more advanced statistical methods which were not available

64

52 Data collection STORK

521 Dependent variablesoutcomes

Birthweight

We chose to use birthweight as a summary measure of overall fetal growth It is widely used

and therefore suitable to compare our data to other publications We chose to use birthweight

as a continuous variable We wanted to report associations between maternal factors and

birthweight in the total STORK cohort as previous publications from the same cohort only

reported birthweight in sub cohorts andor using birthweight as a categorical value with a cut-

off of gt4200 g Birthweight was expressed as Z-scores adjusted for gestational age and fetal

sex

The standard score (Z-score) represents the distance between the raw score and the population

mean in units of the standard deviation Z is negative when the raw score is below the mean

positive when above The z-score is calculated as

where

x is the observed value

μ is the mean of the population

σ is the standard deviation of the population

Mean and standard deviation of the population were taken from a Norwegian reference

material [119]

Intrauterine fetal growth

There are no internationally accepted consensus on how to define and assess intrauterine fetal

growth [11] The longitudinal design of the STORK study enabled us to assess intrauterine

fetal growth We chose third trimester visit 3 to visit 4 which is the period of maximum

Z =

x - μ

σ

65

growth and a period in which maternal metabolic factors are important in terms of fetal

growth [120]

Fetal size and fetal growth were estimated by ultrasound Fetal size was expressed as both

estimated fetal weight (EFW) in grams and as EFW percentile according to Norwegian

growth charts [107] Intrauterine fetal growth was defined as the change in estimated fetal size

parameters from visit 3 to visit 4 expressed as either change in EFW (g) or change in

percentiles Combs formula was chosen as the equation to estimate fetal weight as it is the

formula in use in clinical practice at our department and the basis for the growth charts we

used as reference [106]

Errors in ultrasonographic assessment of fetal weight can be attributed to at least two factors

errors due to the equation and errors due to observer error Observer error can further be

divided into intra-observer and inter-observer error [121] Intra-observer error refers to the

variance in measurements performed by the same observer All measurements were

performed three times and we used the mean of the three values to minimize intra-observer

error Inter-observer error refers to the variance in measurements that occur because different

observers measure differently To minimize inter-observer error all measurements were done

by only three investigators and each participant was measured by the same investigator at all

visits Among errors in ultrasonographic assessment of fetal weight observer error has been

shown to be a relatively minor component compared to the larger error due to the equation

[18] To be able to assess fetal growth we compared our data to reference curves based on

data from University of Bergen Norway as that population was considered the most

comparable to our population [107] We also evaluated fetal growth as changes in each of the

three components that make up EFW according to Combs equation namely HC AC and

femur length Once again we compared our data with Norwegian reference data [108]

There are other types of fetal growth charts available Customized curves have been

developed to adjust for factors like race fetal sex parity and maternal size which are factors

known to influence birthweight and factors that differ in different populations [13] We chose

not to use customized growth charts since the aim of our study was to study the effect of

maternal factors on fetal growth In customized charts maternal factors are controlled for and

therefore unsuited to study the effect of maternal factors

Conditional growth curves take into account the estimated size measured at one point and

gives an estimation of the expected growth for a fetus of that particular size for a specified

period of time As an example a larger fetus at the 75 percentile at week 30 will be expected

to grow more during the next weeks than a smaller fetus at the 10 percentile at week 30 during

66

the same period of time Conditioning on a previous measurement gives information on

whether a particular fetus grows fast or slowly relative to other fetuses of the same size We

chose not to use conditional growth curves in the current study as preliminary analyses did not

indicate major changes in the results making use of the conceptionally more difficult variable

less justified

Placental weight

Placenta was weighed including umbilical cord and membranes by the midwife or childrenrsquos

nurse within one hour after birth The placental weight was expressed in grams The placentas

were not trimmed but there is a close correlation between trimmed and non-trimmed

placentas (r= 098) [122]

Rationale for using placental weight as a proxy for placental function

There is no single parameter that measures placental function as placenta has a range of

functions Placental weight was chosen as outcome as a surrogate for placental function

Placental weight is a measure commonly used to summarize placental growth and aspects of

placental function In normal pregnancy it is reasonable to assume that placental weight is

related to aspects of functional capacity of the placenta [123] We had no estimations of

placental weight or mass during pregnancy Placenta exhibits linear growth throughout

pregnancy [5556] making it reasonable to use placental weight after birth instead of

estimations of placental mass during pregnancy

We wanted to use a variable that reflects those aspects of placental function which are

relevant to fetal growth of which nutrient transport is an obvious factor Density or activity of

nutrient transport proteins in the placenta could have been used as an alternative measurement

of placental function but these data are not yet available in our cohort An underlying

assumption for nutrients to be transported across placenta is that the maternal or umbilical

blood flow is not impaired We performed Doppler measurements in the uterine artery and

umbilical artery In our cohort of healthy women only 35 had notching in the uterine artery

at visit 2 and 32 had a pulsatile index above 2 SD for gestational age at visit 4

(unpublished data)

67

Placental weight correlates well with surface area which is a major determinant for nutrient

transport [124] The maternal plasma level of hormones produced in the placenta are directly

related to placental weight [125]

522 Explanatory independent variables

The explanatory variables were chosen based on publications from our study [126ndash129] and

literature on fetal growth in general We selected some maternal characteristics that were

known to influence birthweight in order to study their relation to intrauterine fetal growth

Maternal factors

Maternal age was noted at the first visit in whole years Age was normally distributed

Parity was categorized into P0 and P1+ as the largest difference in birthweight is

known to be between the first child and second child and less between consecutive

children [43]

BMI was calculated based on height and weight measured at the first visit We did not

use pregestational BMI to avoid recall bias and false self-reporting

GWG was calculated as the difference in weight between visit 4 and visit 1 We did

not use weight measured at admission for delivery as there were many missing values

Fasting glucose was measured by the use of Accucheck (Roche Diagnostics

Mannheim Germany) in order to obtain the measured values immediately This

enabled us to inform the women of the result the same morning and in cases of

impaired glucose metabolism to give advice on diet and physical activity during the

consultation Analyses of glucose over the seven years of inclusion revealed that there

was an unexpected increase in fasting glucose of 06 mmolL over time We found no

accompanying increase in maternal age BMI or in insulin that could give a biological

plausible explanation for this increasing trend Thus the time trend in fasting glucose

most likely had an analytical cause The glucose values were de-trended according to

the coefficients from linear regression under the assumption of a linear increase

during the entire period and de-trending of the data removed the increasing trend

[130]

68

Placental weight

The rationale for using placental weight to reflect aspects of placental function has been

discussed above When placental weight was used as an explanatory variable in the regression

models placental weight was entered in 100 grams instead of 1 gram to avoid getting effect

estimates with too many decimals

Placental pathology

There were 55 placentas not characterized as normal which makes up 53 of the samples

Theoretically it is possible that the placental weight in these cases does not reflect function in

the same way as placentas characterized as normal Eg a placenta with infarctions has areas

of tissue that do not take part in nutrient transport Such a small percentage of pathological

placentas are not likely to have influenced the results to a significant extent

69

53 Methodological issues STORK-Placenta

Design

The STORK-Placenta study had a cross-sectional design which means the women were only

examined once which in our study was at delivery This design gives no opportunity to assess

earlier gestational ages or longitudinal changes throughout the pregnancy In Paper 3 all the

study subjects were healthy women and there was no need for a control group In paper 4 we

applied a case-control design in which the preeclampsia group was compared to a control

group of healthy pregnant women

Validity

Internal validity

Selection bias

Only women delivered by cesarean section were recruited to this study This lead to selection

bias for both the healthy women and the preeclamptic patients For the healthy women the

most common indications for cesarean section were prior cesarean section or patient request

due to traumatic previous delivery Few healthy primiparas are delivered by elective cesarean

the exception being breech presentation In Paper 3 the selection therefore resulted in age and

parity that were relatively higher than average Avoiding selection bias in a study like this was

not possible given the population eligible for participation

For the preeclamptic women the selection lead to overrepresentation of early onset

preeclampsia and cases of serious preeclampsia as late onset or less serious cases in many

cases can deliver vaginally In Paper 4 this was reflected in lower gestational age in the

preeclampsia group than the controls

Information bias

We assumed similar blood composition in the radial and the uterine artery This was done to

avoid puncturing the uterine artery as bleeding would be easier to control in the radial artery

As the blood is pumped out of the aorta it is reasonable to assume that the composition does

70

not change substantially between the blood reaching the radial artery compared to the blood

that reaches the uterine artery

External validityrepresentativity

The representativity of the results from the STORK-Placenta study is discussed in light of the

selection of the participants

Parity was higher in Paper 3 than average From our results in Paper 1 and Paper 2 we have

seen that parity was an independent variable with effect on fetal growth In Paper 3 the added

effect of parity on fetal growth could give a bias if the effect of parity also affects the glucose

transport across the placenta Hitherto the question can not be answered So far our results are

only valid for the glucose metabolism among healthy women with relatively normal BMI

Which changes that occur in the glucose metabolism in women with chronic diseases will

probably vary according to the disease Higher BMI would probably influence the glucose

metabolism both directly as higher BMI might lead to higher glucose levels in many cases

but possibly also indirectly by changes in inflammatory factors and by changes in the

transport of other nutrients as amino-acids and lipids

In Paper 4 gestational age was lower in the preeclampsia group than in controls Early-onset

and late-onset preeclampsia are by many considered two different subgroups of preeclampsia

due to the differences in risk factors pathogenesis and clinical presentation [90] Our findings

may not be valid for late-onset preeclampsia where maternal risk factors play a larger role in

the patophysiology and the endothelial dysfunction might be more prominent Therefore it is

possible that the results are valid only when the placental dysfunction is the major feature in

the pathophysiology like in early-onset preeclampsia

Statistical issues

In both papers from the STORK-Placenta study the numbers of participants were relatively

small due to the demanding logistics of the project Small numbers lead to some statistical

challenges that need to be discussed

In Paper 3 we included 40 patients which were sufficient to show significant glucose gradients

on both maternal and fetal side as well as a gradient across the placenta However the small

number restricted the possibilities to study interesting associations between maternal factors

and glucose transport or glucose transport in relation to fetal growth by the use of regression

71

models As an example we found an interesting association between maternal BMI and fetal

glucose v-a difference but the scatter plott revealed one woman with BMI 39 and analyses

showed that without that observation the association was no longer significant

In Paper 4 we found a significant difference in sFlt-1 but not in sEng across the uteroplacental

circulation among preeclamptic patients There is a possibility that lack of power influenced

this finding Possibly a larger sample could have given a significant difference for sEng in

which case our finding could represent a type 1 error (reject the hypothesis that there was a

difference even if it is true)

Both non-parametric tests on original data and parametric tests on log transformed data were

done giving the same results in terms of statistically significant differences We chose to use

the log transformed data for statistical analyses (as that seemed to be the most conventional

method used in relevant references) but presented arithmetic data in figures and tables to

make it easier for the reader

54 Data collection STORK-Placenta

Blood sampling

All procedures were standardized to minimize systematic errors Sampling was therefore done

by a small group of four trained obstetricians and handling the samples in the laboratory was

restricted to only three investigators In the few cases where sampling was inadequate it was

mostly due to failure in inserting the arterial line or in a few cases inadequate amount of blood

obtained from the umbilical artery Blood samples were kept on ice until centrifugation

Blood samples were taken in fasting condition to obtain a steady state situation This is

particularly relevant for glucose and insulin which show large post-prandial variation

Cesarean section was done under spinal anesthesia no participants received oxygen or

intravenous glucose infusion

Analyses

Glucose and insulin were analyzed at the laboratory at Oslo University Hospital The samples

were analyzed during three consecutive days

72

sFlt-1 and sEng were analyzed by commercially available ELISA kits (RampD systems) We

chose to use ELISA kits from RampD for comparison reasons as they were commonly used in

papers on preeclampsia published at the time

73

55 Interpretation of results

Paper 1 and 2

In Paper 1 and Paper 2 we have studied the associations between maternal characteristics

placental weight and fetal growth in healthy pregnant women ie these are studies of normal

physiological relations Together the results from these papers illustrate some of the interplay

between the mother the placenta and the fetus

Paper 1

Paper 1Paper 2

-parity

-BMI

-GWG

-glucose

We found largely the same determinants for both birthweight and intrauterine fetal growth in

third trimester with the exception of fasting glucose (see below) The weight of the placenta

was influenced by similar maternal metabolic and nutritional factors In summary our results

are compatible with the concept that maternal factors can influence fetal growth directly and

indirectly by promoting placental growth

We found a direct effect of maternal factors both on birthweight and intrauterine growth in the

third trimester For both birthweight and intrauterine fetal growth placental weight was an

independent determinant Hence as the placenta grows and becomes larger some of the effect

of maternal factors on fetal growth is likely to be mediated by growth of the placenta

We found independent effects of several maternal factors (parity BMI and GWG) on

intrauterine fetal growth in third trimester We did not find independent effect of age The

small variation in age (SD) might partly explain why we did not find any effect of age

74

Furthermore age has been shown to exhibit an inverse u-shaped relation to birthweight and we

only tested for linear relationships Somewhat surprisingly we did not find an independent

effect of fasting glucose on intrauterine fetal growth in third trimester The discrepancy

between the effect of glucose on birthweight and on intrauterine growth may have several

explanations One possible explanation lies in how fetal growth is assessed Fat accumulation

resulting from increased maternal glucose and subsequent increased insulin secretion in the

fetus is likely to be accumulated on extremities and truncus of the fetus as well as the

abdomen The estimation of fetal size and fetal growth used in our study included assessment

of head circumference abdominal circumference and femur length Of these only abdominal

circumference would be likely to reflect fat deposition We did not however find an

independent association between fasting glucose and change in abdominal circumference

There is no consensus on whether the diagnosis of abnormal growth should be based on EFW

or AC or both [11] Another possible explanation for the described discrepancy could be

found in the concept of conditional growth Conditional fetal growth refers to differences in

expected fetal growth depending on the size estimated at the last measurement As an

example a fetus that is large at week 30 will be expected to grow more in the remaining

weeks of the pregnancy than a fetus that is relatively smaller at week 30 Factors like impaired

glucose metabolism in early pregnancy leading to higher fasting glucose values might have

resulted in a large fetus already at week 30

Placental weight was used as a measure of placental function Introducing placental weight in

the multiple regression models gave two interesting results

First placental weight was an independent determinant of birthweight and fetal growth and

showed a positive effect on fetal growth A small placenta is commonly associated with a

growth restricted fetus hence a reduced placental function Fetalplacental ratio can be used

as an indicator of placental efficiency and includes both fetal weight and placental weight

Preliminary analyses in our material showed that the maternal factors associated with

fetalplacental ratio in the multiple model were maternal age parity and BMI Maternal

gestational weight gain was not significantly associated in the univariate model and hence not

included in the multiple model Fasting glucose was not significant in the multiple model

using fetalplacental ratio as outcome

Secondly placental weight can be viewed as a mediator in the associations between maternal

factors and fetal growth This implies that some of the effect of the maternal factors might

work through growth of the placenta There are several possible biological reasons for the

75

reduced effects of the maternal characteristics on birthweight or intrauterine fetal growth

when placental weight was included in the models The selected maternal characteristics may

exert their effects on fetal growth by affecting transplacental transport Transplacental

transport is affected by blood flow both on maternal and fetal side Furthermore the number

and efficiency of placental transport proteins may also be influenced by maternal factors The

total number of transport proteins is dependent on both the area of the syncytio-endothelial

membrane and the density of the transporting proteins In addition it can not be excluded that

placental production of growth factors may be affected

We have studied both modifiable and non-modifiable maternal factors Parity is a non-

modifiable factor present before pregnancy There is a well-known effect of parity on

birthweight We showed that this effect is evident also for intrauterine growth and placental

weight The effect of parity is relatively larger than many other maternal factors eg larger

than fasting glucose BMI and GWG Modifiable factors include BMI GWG and fasting

glucose BMI and fasting glucose may be modified before pregnancy and GWG and glucose

during pregnancy

The present study did not include data on neither fetal factors that stimulate or inhibit

placental growth function or maternal factors nor placental factors that influence maternal

metabolism Theoretically however there are possible pathways including signals from the

fetus that can stimulate placental growth and possibly placental factors that can influence

maternal metabolism

Taken together the results from Paper 1 and Paper 2 show that maternal factors influence

both placental weight and fetal growth and it is likely that some of the effect on fetal growth is

mediated through placental growth This does not exclude the possibility that an increased

fetal growth following increased maternal energy supply may lead to release of fetal growth

factors that feed back on placental growth

Clinical implications

We have only studied birthweight and intrauterine growth in third trimester which might be

too late to intervene in cases of abnormal fetal growth In order to intervene it is necessary to

know which factors influence intrauterine growth at different gestational ages As both low

76

BMI and low GWG is related to increased risk of IUGR patients with high risk of IUGR

could be advised to increase their BMI or make sure they gain sufficient weight according to

recommendations Similarly as high BMI and high GWG increase fetal growth women could

be advised to obtain a normal BMI prior to getting pregnant and not gain unnecessary weight

during pregnancy As there is a linear and continuous relation between fasting glucose and

adverse fetal outcomes including fetal growth pregnant women with fasting glucose values

just below the GDM criteria can benefit from the same advice concerning diet and physical

activity as GDM-patients receive In particular women with multiple risk factors of impaired

fetal growth should be given advice even if she does not meet the criteria of GDM or obesity

Paper 3

Glucose is the major source of energy for the fetus and the placenta and therefore has an

obvious importance in fetal nutrition Glucose transport across the placenta in humans is

interesting to study for several reasons There is a lack of human in vivo studies in contrast to

the body of evidence on mechanisms and transporter proteins etc from in vitro studies It is of

major importance to acknowledge the distinction between maternal nutrition and fetal

nutrition [2] The placenta is not just a simple conduit for gases nutrients and waste products

but has its own complex metabolism with corresponding requirements for oxygen and

nutrients

In this paper we found a close correlation between maternal and fetal glucose concentrations

which is in line with the concept that the maternal-fetal gradient is the driving force in the

transplacental transport of glucose across the placenta However the fetal v-a glucose

difference was not merely a reflection of the maternal glucose concentration or the

uteroplacental uptake of glucose but rather related to the maternal-fetal gradient and the

concentration in the umbilical artery The relation between maternal and fetal glucose

concentration has been shown in several papers Although the umbilical venous concentration

is closely related to the maternal concentration the fetal v-a difference seemed to be less

related to maternal concentrations but more to the concentration in the umbilical artery fetal

insulin placental weight and birthweight We therefore speculate that the fetus has a saying in

determining the fetal glucose consumption This might at first seem to be in conflict with the

Pedersen hypothesis which was first presented in 1952 [131] His theory was that high

maternal glucose was transferred to the fetus which responds by secreting more insulin

77

which in turn lowers the blood glucose of the newborn Compared to the 1950s pregnant

women of today are older when they get pregnant have higher prepregnancy BMI and gain

more weight in pregnancy The metabolic environment a fetus experiences today is likely to

differ from the environment some decades ago in several aspects more energy-rich altered

balance between glucose and lipids and more inflammation [132] The non-glucose factors

like lipids may have augmented their role as several factors have changed in the population

since the proposal was made by Pedersen We can only speculate as to how the relative

importance of these factors might influence the regulation of transport of nutrients to the

fetus

Our results can not explain or show the complex regulation of glucose transport and

metabolism and leaves us with some unanswered questions We only presented correlation

analyses as we did not yet have enough samples to do multivariate analyses to evaluate the

relative importance of the factors involved We were not able to do path analyses to quantify

the influence of each of these factors Do the relationships we have described work differently

in pathological pregnancies in which there is either abnormal placental function or the mother

exhibits abnormalities in her metabolism or the fetus experiences abnormal growth These

questions can hopefully be answered by future research

The amount of glucose consumed by the placenta can be changed under hypoxic conditions

[63] It is not likely that our participants were hypoxic to a large degree We only measured

oxygen in a few cases which were all normal

Clinical implications

In obstetric practice there are numerous examples of cases of abnormal fetal growth occurring

in pregnancies of healthy mothers with normal metabolism and apparently normal placental

function Placental function might still be compromised resulting in reduced fetal nutrition

Fetal under nutrition may result from compromised transplacental transfer of nutrients In the

other end of the spectrum are the fetuses that experience overgrowth despite strict glycemic

control of their diabetic mothers Some authors argue that this might be due to intermittent

hyperglycemia rather than constant hyperglycemia but another option is that hyperglycemia

is accompanied by other nutrients or other factors that increases the total energy supply to the

fetus

78

Human in vivo studies are rare and therefore valuable in terms of extrapolation to relevant

settings in clinical practice However in vivo settings include multiple factors working

together making it difficult to assess individual effects In vitro settings however can control

for one factor at a time to gain mechanistic knowledge which can hardly be drawn from in

vivo settings The clinical significance of factors operating in vitro is often difficult to assess

Paper 4

The multifactorial etiology and heterogeneous clinical presentations seen in preeclampsia

makes it an intriguing and challenging condition to study Since preeclampsia is a pregnancy

complication in which the placenta is believed to play a crucial role in the pathophysiology it

was both interesting and relevant to choose preeclampsia in order to study aspects of placental

function in pathological pregnancies Furthermore preeclampsia is still a leading cause of

mortality and morbidity worldwide Despite decades of research there is still no causal

treatment leaving timing of delivery the only intervention to balance the needs of the mother

and the fetus

In our study we found as expected that preeclamptic women had higher concentrations of sFlt-

1 and sEng than healthy controls as has been shown in numerous previous publications

Preeclamptic women further had higher concentrations of sFlt-1 in the uterine vein than the

radial artery giving a gradient across the uterus There was no gradient for sEng among

preeclamptic women and no gradients were found in the healthy controls for either of the two

factors tested The gradient across placenta is consistent with the concept that the placenta

secretes sFlt-1 into the maternal circulation The source of excess sFlt-1 and sEng in

preeclamptic patients is assumed to be the placenta based on enhanced expression of both

factors in trophoblastic tissue [133134] Enhanced expression of sFlt-1 and sEng in

trophoblastic tissue does not necessarily prove that the circulating sFlt-1 and sEng found in

preeclamptic patients originate from the placenta or that the placenta is the only source There

is a possibility that sFlt and sEng originate from circulating cells in the maternal circulation or

endothelial cells Peripheral blood mononuclear cells have been suggested to be an additional

extra-placental source of sFlt-1 [134]

Our results support the hypothesis that at least a part of the circulating sFlt-1 originates in the

placenta and is transported into the maternal circulation whereas we did not find evidence to

support that this holds for sEng The discrepancy between our results for sFlt-1 and sEng

could have several explanations

79

There might be a biological difference such that sFlt-1 only or to a larger extent than sEng is

released from the syncytiotrophoblasts in the placenta whereas sEng to a larger extent is

produced elsewhere [135] There might also be a statistical explanation suggesting that we had

inadequate power to show a statistically significant difference in sEng which would represent

a type 1 error (rejecting the hypothesis that there was a difference even if it is true)

In this paper as most studies involving preeclamptic patients and healthy controls there was a

difference in gestational age among cases and controls The difference in gestational age

raises some questions to be discussed There are publications reporting an increase in sFlt-1

and sEng with increasing gestational age both for controls and preeclamptic patients but more

so in preeclampsia [136137] Assuming this relationship for our controls we would expect to

find a lower concentration at week 30 among healthy controls than what we found near term

giving an even greater difference than we observed Thus we do not think that the difference

in gestational age can explain the observed difference in sFlt-1 and sEng between preclamptic

patients and healthy controls We did not include samples from preeclamptic patients at term

as they mostly deliver vaginally Our group of preeclamptic patients thus represents early-

onset preeclampsia In most cases preeclampsia was accompanied by a degree of intrauterine

growth restriction Whether our findings are representative for late onset preeclampsia in

which the placental dysfunction is perhaps less prominent and the endothelial dysfunction

more prominent is not clear from our study

Anti-angiogenic factors in a clinical setting

Anti-angiogenetic factors have been proposed used as diagnostic tools for preeclampsia

There is hope for a therapeutic option in treating preeclampsia in the future but whether

angiogenetic agents can be used to improve the angiogenic imbalance seen in preeclampsia is

not known At the moment the most useful implications of these types of studies is increased

knowledge on the pathogenesis including the possibility to differentiate between early- and

late-onset preeclampsia

80

6 Conclusions

In conclusion results from the first part of this thesis (Paper 1 and 2) underline the importance

of the placenta and placental functions in normal pregnancies Placenta is an important factor

to consider when studying associations between maternal factors and measures of fetal

growth birthweight intrauterine growth or body composition The effect of maternal

metabolic and nutritional factors on fetal growth is likely to go partly through growth of the

placenta There is an important distinction between maternal and fetal nutrition as one has to

consider the placenta as an active organ and not a passive conduit of nutrients and gases

In the second part of this thesis a method has been established that makes it possible to study

placental function in the human in both normal and pathological pregnancies like

preeclampsia

7 Further research

I believe the greatest challenges in the two studies that make up my thesis also reflect the

potentials for further research

In the STORK study we collected large amounts of data on a large group of women

Therefore selecting and analyzing the relevant outcomes and appropriate explanatory

variables was the greatest challenge There are large amounts of data still to be analyzed For

the STORK data my plans for a postdoc is to study in more detail the relations between

maternal metabolism and pregnancy outcomes More specifically to differentiate between

healthy and unhealthy obese pregnant women in metabolic terms and relate this to pregnancy

outcomes including fetal growth

In the STORK-Placenta study establishing the method and achieving the data collection were

the greatest challenges with demanding logistics at any time of the day There are few larger

human in vivo studies of placental nutrient transfer In particular studies of arterio-venous

differences on maternal side of placenta are scarce The main reason this kind of studies are so

limited is that such studies are logistically very requiring To our knowledge we are the only

group employing this procedure The samples obtained by this method give unique

opportunities to study concentration gradients and transplacental transfer of any nutrient

81

across placenta and how endocrine and inflammatory factors may interact with nutrient

transfer The study also includes measurements of maternal and fetal blood flow enabling us

to quantify the amounts of nutrients being transported The study has currently been

expanded to around 100 pregnancies Data collection still goes on aiming to get enough

samples to continue analyzing interesting associations linking maternal metabolism placental

functions and the fetus and extending the data to include cases of pathological pregnancies

like preeclampsia diabetes mellitus and abnormal fetal growth Samples from preeclamptic

women are currently being analyzed for Placental growth factor

The potential for further research lies in combining the data retrieved from the two studies

Ultimately I would like to be able to link preeclampsia and fetal growth in the two studies

82

8 References

Reference List

1 2009) wwwmfr-nesstaruibno Medical birth Registry Norway Available

2 Harding JE (2001) The nutritional basis of the fetal origins of adult disease Int J

Epidemiol 30 15-23

3 Barker DJ Thornburg KL (2013) The obstetric origins of health for a lifetime Clinical

Obstetrics and Gynecology 56 511-519

4 Forsdahl A (1978) Living conditions in childhood and subsequent development of risk

factors for arteriosclerotic heart disease The cardiovascular survey in Finnmark 1974-

75 J Epidemiol Community Health 32 34-37

5 Forsdahl A (1979) Are poor living conditions in childhood and adolescence and

important risk factor for arteriosclerotic heart disease Int J Rehabil Res 2 238-239

6 Barker DJ (2005) The developmental origins of insulin resistance Horm Res 64 Suppl

3 2-7

7 Barker DJ Shiell AW Barker ME Law CM (2000) Growth in utero and blood

pressure levels in the next generation J Hypertens 18 843-846

8 Barker DJ (1997) The long-term outcome of retarded fetal growth Clinical Obstetrics

and Gynecology 40 853-863

9 Gude NM Roberts CT Kalionis B King RG (2004) Growth and function of the

normal human placenta Thromb Res 114 397-407

10 Voldner N (2010) Modifiable determinants of newborn macrosomia and birth

complications [dissertation]

11 Mayer C Joseph KS (2013) Fetal growth a review of terms concepts and issues

relevant to obstetrics Ultrasound Obstet Gynecol 41 136-145

12 Zhang J Merialdi M Platt LD Kramer MS (2010) Defining normal and abnormal

fetal growth promises and challenges Am J Obstet Gynecol 202 522-528

13 Gardosi J Figueras F Clausson B Francis A (2011) The customised growth potential

an international research tool to study the epidemiology of fetal growth Paediatr

Perinat Epidemiol 25 2-10

14 Rohrer F (1921) The index of corpulence as measure of nutritional state Munchener

medizinische Wochenschrift 580-582

15 Catalano PM Thomas AJ Avallone DA Amini SB (1995) Anthropometric estimation

of neonatal body composition Am J Obstet Gynecol 173 1176-1181

16 Godang K Qvigstad E Voldner N Isaksen GA Froslie KF et al (2010) Assessing

body composition in healthy newborn infants reliability of dual-energy x-ray

absorptiometry J Clin Densitom 13 151-160

17 Pay AS Froen JF Staff AC Jacobsson B Gjessing HK (2013) A new population-

based reference curve for symphysis-fundus height Acta Obstet Gynecol Scand 92

925-933

18 Anderson NG Jolley IJ Wells JE (2007) Sonographic estimation of fetal weight

comparison of bias precision and consistency using 12 different formulae Ultrasound

Obstet Gynecol 30 173-179

19 Cetin I Alvino G (2009) Intrauterine growth restriction implications for placental

metabolism and transport A review Placenta 30 Suppl A S77-S82

20 Mei Z Grummer-Strawn LM Pietrobelli A Goulding A Goran MI et al (2002)

Validity of body mass index compared with other body-composition screening indexes

for the assessment of body fatness in children and adolescents Am J Clin Nutr 75

978-985

11

2001 2005 2008

STORK 1 STORK 2

birthweight

fetal growth

body composition ( fat)

maternal characteristics

placental aspects

Camilla M Friis

Kathrine Frey Froslashslie

Marie Cecilie Paasche Roland

Inclusion

period

Timeline for the STORK and STORK-Placenta project

STORK-Placenta

2013

Outcome

Determinants

PhD candidate

birthweight gt 4200 g

maternal characteristics

Nanna Voldner

placental functions

glucose transport across placenta

anti-angiogenic factors

Marie Cecilie Paasche Roland

Ane Moe Holme

This thesis consists of four papers of which Paper 1 and Paper 2 are based on the STORK

study and Paper 3 and Paper 4 are based on the STORK-Placenta Study

12

In Paper 1 we studied how maternal factors were associated with birthweight and intrauterine

fetal growth For the reasons indicated above we included placental weight as a determinant

of birthweight and fetal growth

Paper 1

-parity

-BMI

-GWG

-glucose

Given the importance of placental weight on birthweight and fetal growth we then wanted to

study placental weight in Paper 2 We studied the influence of maternal factors on placental

weight and whether these associations differed with fetal sex

Paper 2

-parity

-BMI

-GWG

-glucose

13

In Paper 3 we reported initial studies of transfer of glucose across the human placenta and

how maternal and fetal glucose and insulin levels were related

Paper 3

Glucose and insulin

In Paper 4 the role of placenta in producing pathogenic factors of preeclampsia was

investigated choosing anti-angiogenic factors because of their endothelial-disturbing

properties

Paper 4

Anti-angiogenic

factors

14

12 Background

Fetal growth has implications for the newborn child both in short and long term The link

between events in early life and risk of disease in later life is now a widely recognized field of

research known as developmental programming and often called Developmental Origins of

Health and Disease Developmental programming refers to how an event at a critical or

sensitive period results in a long-term change in the structure or function of the organism

[23] Organs and systems in the human body are sensitive to the environment in certain

periods The critical periods are mainly those characterized by rapid growth and maturation

and for most organs and systems this happens to a large extent in utero

The idea of linking events in early life to later risk of disease is however not new The

association between poor living conditions in childhood and increased risk of cardiovascular

disease was observed by Anders Forsdahl who worked as a physician in Finnmark Northern

Norway in the 1970s He found a positive correlation between infant mortality which was

considered to be an index of standard of living and mortality from arteriosclerotic heart

disease as well as cholesterol values [45]

The link between early life events and later disease received more publicity when the late

David Barker introduced what is commonly referred to as the rdquoBarker hypothesisrdquo He was

probably the most acknowledged scientist in this field and established an association between

birthweight and increased risk of cardiovascular disease insulin resistance and type 2 diabetes

mellitus [6ndash8] His work has been followed by a range of publications that have not only

confirmed these associations but also provided mechanistic insight into the link between

intrauterine growth and increased risk of disease A large body of evidence have shown that

structural or functional changes that last throughout life can result from nutritional factors in

utero [2] Extensive work on animal models has demonstrated how dietary changes affect fetal

growth and lead to functional and structural changes The availability of nutrients to the fetus

is influenced not only by the motherrsquos diet during pregnancy but by maternal nutrient stores

and metabolism The placenta has multiple roles in fetal nutrition by its capacity to transport

nutrients from the maternal to the fetal circulation by its own metabolic demand for nutrients

and by producing hormones which influence fetal and maternal nutritional supply [9]

15

13 Fetal growth

Fetal growth comprises the entire process of differentiation maturation and development that

occurs between conception and birth This process starts with the fusion of two cells and ends

up with an estimated 50-100 trillion cells in the newborn child The terminology used to

describe and evaluate fetal growth is complex and the terms need to be defined First there is

a need to draw a distinction between size at birth and intrauterine growth Secondly the

difference between size which is most commonly measured as weight and body composition

must be addressed

131 Size at birth

Birthweight

Size at birth is routinely measured as birthweight (grams or kg) Birthweight is a summary

measure of fetal growth throughout pregnancy Categories based on birthweight are used both

in clinical settings and for research Low birthweight is generally defined as birthweight

lt 2500 grams whereas a definition for high birthweight (macrosomia) is more arbitrary Both

4000 4200 and 4500 grams have been used as cut-off values in various settings [1011]

Birthweight for gestational age

Birthweight as a function of gestational age gives information of size relative to expected size

for a particular gestational age Birthweight for gestational age can be given as a percentile

between 0 and 100 Birthweight for gestational age can also be categorized and the most

commonly used categories are large for gestational age (LGA) appropriate for gestational age

(AGA) and small for gestational age (SGA) The conventional cut-off percentiles for these

categories are given beneath

Population based charts for birthweight are often based on large samples including both low-

risk and high-risk pregnancies representing the underlying population On the other hand a

so-called standard chart is usually based on low-risk pregnancies with a normal outcome [12]

Furthermore customized charts have been made to accommodate for differences in eg

ethnicity parity age and BMI in individual patients Such charts have been developed for

different populations and there are electronically available charts [13]

16

Body composition

In addition to weight of the newborn baby length and head circumference give some

information about the body composition of the newborn Further evaluation of body

composition can be derived from these measurements The Ponderal Index (PI) is calculated

as a relationship between mass and height as is the body mass index (BMI) but the mass is

normalized with the third power of body height

Because it yields valid results even for very short (and very tall) persons it is more suitable

in pediatrics than BMI [14] Body composition can further be assessed by measuring

circumference of the abdomen and the extremities or by skin fold thickness measurements by

calipers to obtain an estimation of fat distribution [15] There are other methods that are either

expensive or difficult to perform on newborns Dual energy x -ray absorptiometry (DXA)

enables an estimation of bone mass fat mass and fat free (lean) mass A reasonable good

correlation between estimated fat mass by DXA and skin fold thickness measured by calipers

has been shown [16]

Categories Cut-offs

SGA lt 10 p

AGA 10-90 p

LGA gt 90 p

PI

= weight (g)

[height (cm)]3

17

132 Intrauterine growth

Fetal growth is a continuous process that starts at conception and ends at birth but is

commonly measured as just the end result which is size at birth However the distinction

between size and growth applies also to the intrauterine period Fetal size is estimated based

on a single observation or measurement whereas estimation of fetal growth requires at least

two measurements

Symphysis-fundus height

Palpation of the abdomen and measuring the symphysis-fundal height is used to estimate

intrauterine growth in low-risk pregnancies Reference curves for the symphysis-fundus

height to assess fetal growth have recently been updated in Scandinavia [17]

Ultrasound measurements

Estimation of fetal size

Estimation of fetal size by ultrasound combines measurements of the fetus and transforms

these measurements into volume and weight to estimate fetal size There are a number of

equations that use combinations of circumferences andor diameters and combinations of

measurements of head and abdominal size andor femural length to estimate fetal size The

equations differ in their ability to predict fetal size but generally perform more accurately in

predicting average fetal sizes than at the extremes of birthweight [18]

Estimation of fetal growth and fetal growth charts

To estimate fetal growth two or more measurements separated in time are needed and the rate

of growth can be assessed by using fetal growth charts There are a multitude of charts

available that are constructed by different methods and from different populations Fetal

growth charts can be derived from cross-sectional or longitudinal data In cross-sectional

charts each pregnant woman contributes with data from one observation whereas longitudinal

studies have repeated measurements from each participant The longitudinal studies provide

better references for fetal growth [12]

18

The ambiguous terminology

The lack of distinction between fetal size and fetal growth complicates the terminology Small

for gestational age (SGA) is often defined as birthweight lt 10 p The term intrauterine growth

restriction (IUGR) is often used interchangeably with SGA IUGR more strictly is used as a

term for true intrauterine growth restriction based on data that shows a decline in intrauterine

growth over time assessed by ultrasound There are however no universally accepted

definition of how much decline in fetal growth that would define IUGR although some

authors have defined IUGR as either a fall in fetometric percentiles or a combination of fall in

percentiles and low birthweight [19] On the same note accelerated fetal growth can be seen

during intrauterine life and may or may not result in a LGA newborn

Figure 1 Schematic overview of categories of fetal growth

growth

restrictionexcessive

growth

AGASGA LGA

19

14 Maternal aspects of fetal growth

141 Maternal nutritional status

Maternal nutritional status is vital for fetal growth as the fetus is dependent on nutrients being

transported from the maternal circulation across the placenta to the fetal circulation The

nutritional status of the mother is generally assessed by indirect means of which Body Mass

Index is a commonly used measurement

Body Mass Index (BMI)

BMI is calculated from a persons weight and height according to the following equation

BMI is used as a surrogate for body fat and has been shown to correlate to direct measures of

body fat such as underwater weighing and dual energy x-ray absorptiometry (DXA) [20]

Although the correlation between BMI and body fatness is fairly strong the correlation varies

by sex race and age At the same BMI women tend to have more body fat than men At the

same BMI older people tend to have more body fat than younger adults Highly trained

athletes may have a high BMI because of increased muscularity rather than increased body

fatness [21] In pregnancy the correlation between BMI and percent body fat is better in early

gestation than in late gestation [22]

The World Health Organisation (WHO) classifies BMI for adults in the following groups [23]

BMI

weight (kg)

[height (m)]2

BMI Weight Status

Below 185 Underweight

185 ndash 249 Normal

250 ndash 299 Overweight

300 and above Obese

20

For adults BMI is interpreted using standard weight status categories that are the same for all

ages and for both men and women For children and adolescents on the other hand the

interpretation of BMI is both age- and sex-specific [24]

Biological effects of high BMI

BMI is used as a surrogate for body fat which is made up of adipose tissue Adipose tissue can

be classified as white adipose tissue (WAT) and brown adipose tissue WAT is excess energy

stored as triglycerides in adipocytes which secrete a variety of substances including

hormones (eg leptin adiponectin and resistin) as well as inflammatory factors [25] Brown

adipose tissue is thought to have a function in thermo genesis Excess adipose tissue can be

estimated by anthropometric measures such as skin fold thickness measured by calipers [26]

Consequences of BMI for pregnancy and labour

Prepregnancy BMI is a major determinant of pregnancy outcome and increasing BMI is

associated with an increased risk of the majority of pregnancy complications like congenital

abnormalities miscarriages gestational diabetes preeclampsia obstructed labour and

operative deliveries [27] Low prepregnancy BMI is associated with low birthweight and

IUGR [28]

Gestational weight gain (GWG)

Gestational weight gain in pregnancy includes growth of the fetus placenta and uterus

increase in maternal plasma volume and accumulation of maternal fat mass [29] The total

amount of weight gained during pregnancy varies considerably among women and lean

women tend to accumulate more fat than obese women [30] Accumulation of fat is primarily

centrally and represents a combination of subcutaneous fat and visceral fat Visceral fat

correlates with metabolic risk factors like hypertension insulin sensitivity and plasma lipids

[31] The ideal gestational weight gain differs depending on the maternal or neonatal outcome

of interest Recommendations for gestational weight gain were revised by the Institute of

Medicine USA in 2009 and highlights both that women should be within a normal BMI range

when they conceive and gain weight within the ranges recommended The recommended

21

weight gain is based on four categories of prepregnancy BMI Higher categories of

prepregnancy BMI are recommended a lower weight gain [29]

Consequences of gestational weight gain

Gestational weight gain has consequences for both mother and child in the short and long

term Low GWG is associated with low birthweight and IUGR [32] and high GWG is

associated with macrosomia and increased neonatal fat mass [3334] High GWG is

associated with increased risk of pregnancy complications like preeclampsia and diabetes [35]

Restricted GWG in obese women with type 2 diabetes has been shown to influence fetal

growth [36] There are reports on associations between GWG and cesarean section

instrumental deliveries and low Apgar scores but it has been suggested that the effects are

mediated by high birthweight [35] The most consistent adverse outcome for mothers with

large GWG is weight retention post-partum [35]

BMI Weight Status Recommended Gestational

Weight Gain

Below 185 Underweight 13-18 kg

185 ndash 249 Normal 11-16 kg

250 ndash 299 Overweight 7-11 kg

300 and above Obese 5-9 kg

22

142 Maternal metabolism

As the fetus is dependent on nutrients from the maternal circulation not only the maternal

intake of nutrients but also the maternal metabolism plays a major role in fetal nutrition There

are adaptations to maternal metabolism that occur during pregnancy to ensure that the

increasing nutritional demands of the mother the placenta and the fetus are met Adaptations

are made in the metabolism of all major groups of nutrients

Glucose metabolism in pregnancy

The human fetus is highly dependent on glucose derived from the maternal circulation for

growth and development [2] Changes occur in the maternal glucose metabolism during

pregnancy to ensure that the increasing nutritional demands of the mother the placenta and

the fetus are met Previously published data on glucose metabolism suggested a decrease in

fasting glucose with gestation [37] Fasting glucose levels of pregnant women have been

shown to decline in early pregnancy and thereafter not decrease much further [38] In our

cohort we found fasting glucose to increase slightly with gestational age [39] There is an

increase in basal hepatic glucose production by up to 30 with increasing gestational age

[37] The insulin sensitivity shows a marked change in pregnancy Overall insulin sensitivity

decreases during pregnancy and in late pregnancy a reduction of 50-70 is estimated

compared with non-pregnant women [40] Insulin secretion increases by up to 200-250

[40]

Lipid and amino acid metabolism in pregnancy

The lipid metabolism in pregnancy is characterized by a marked hyperlipidemia Triglyceride

concentration increases and in particular very low-density lipoprotein (VLDL) triglyceride

concentration which increases 3-fold from week 14 to term Plasma cholesterol levels rise to

a lesser degree In obese women the hyperlipidemia is further exaggerated [27] There is an

overall increase in protein synthesis in pregnancy This includes maternal tissues like breasts

uterus and the liver as well as the fetus and the placenta [27]

23

143 Other maternal factors

Age and parity

Both maternal age and parity have an effect on fetal growth Young women especially

adolescents give birth to smaller newborns than older women [41] Birthweight increases with

maternal age until the 30s after which there is a decline resulting an inverse u-shaped curve

[42] Age is however closely linked to parity Birthweight increases with parity and the

largest increment of approximately 200 grams is between the first and second child [43] In

multiple models birth order exerted a greater influence on birthweight than maternal age [42]

The biological explanation behind these associations is only partly understood The effect of

parity may be partly explained by the capacity of the spiral arteries to expand which is higher

in the subsequent pregnancies than in the first pregnancy [44]

Maternal blood supply to the uterus

The uterus receives blood mainly from the uterine arteries which are branches of the internal

iliac artery The uterine arteries branch into thinner vessels first the arcuate arteries then the

radial arteries followed by the basal arteries which continue into the endometrium as the

spiral arteries The spiral arteries undergo remodeling in early pregnancy which means they

loose smooth muscle and elastic tissue from their walls This remodeling of maternal vessels

is a key aspect of early pregnancy and vital for a successful outcome Ultrasound studies have

estimated both the changes in diameters of the uterine artery and the blood flow velocity in

these vessels Several studies have reported that the diameter of the uterine artery increases

approximately 3-4 fold from non-pregnant state to term [4546] The flow velocity increases

with gestational age but reported values differ somewhat depending on whether the

measurements are made on one or both uterine arteries and the laterality of the placenta

[4546] The fraction of the cardiac output that is distributed to the uterus has been estimated

to be 35 in early pregnancy and near 12 at term [46]

24

Figure 2 Blood supply to the uterus

From Grayrsquos Anatomy 20th US edition electronically retrieved from Wikimedia commons

25

15 Placental aspects of fetal growth

151 Development structure and growth of the placenta

Normal placental development and maternal adaptation to pregnancy are crucial factors for a

successful pregnancy The placentation process and maternal adaptation are closely linked and

happen as parallel processes ensuring a healthy outcome for both mother and child Many

complications of pregnancy can be ascribed to defects in early placentation andor inadequate

maternal adaptation to pregnancy Therefore knowledge of these processes is essential in

understanding the pathophysiology of pregnancy complications

The development of the placenta begins as soon as the conceptus reaches the uterus on day 3-

4 after fertilisation By this stage the blastocyst has an outer wall and an inner cell mass The

outer wall consists of trophoblast cells which undergo transformation to either fuse into a

syncytial cell layer or form individual cytotrophoblasts Extra villous trophoblasts are named

so because of their location in the maternal endometrial (decidual) tissue and play an

important role by starting the trophoblast invasion and the adaptation of the maternal vessels

to pregnancy During this process the endometrial stromal cells differentiate into decidual

cells The extra villous trophoblasts migrate through the decidua basalis and into the inner

third of the myometrium aided by a range of proteases that degrade or remodel the maternal

extra cellular matrix

The amnion arises from the inner cell mass and makes contact with the chorion by early

second trimester Lacunae are formed within the syncytiotrophoblast and the lacunar system is

transformed into the intervillous space

The majority of the villous mass forms the placenta whereas the remainder of the villous

tissue begins to regress resulting in the chorion This remodeling ensures that rupture of

membranes and delivering of the baby can occur at birth without tearing through the placenta

This remodeling occurs at the same time as the maternal blood flow starts in the periphery of

the developing placenta

26

Figure 3 The structure of placenta

From Grayrsquos Anatomy 20th US edition electronically retrieved from Wikimedia commons

The villous mass is made up of a tree of branching villi The branches are classified according

to caliber position within the villous tree and function and goes from the larger stem villi via

intermediate villi to the thinner and distal terminal villi In a mature normal placenta stem

villi account for 20-25 intermediate villi approximately 25 and terminal villi around 40

of the total villous volume The maternal-fetal exchange takes place primarily at the

terminal villi and to some extent at the intermediate villi [47]

Figure 4 Terminal villi

Illustration by Oslashystein H Horgmo University of Oslo

27

Figure 5 Development of the placenta

Fertilized egg

blastocyst

Trophoblast

Cytotrophoblasts

Syncytiotrophoblasts

Extravillous

Villous

Inner cell mass

Fetus

Amnion

Yolk sac

-Primary villi

-Secondary villi

-Tertiary villi

-mesenchymal villi

-immature intermediate villi

-stem villi

-mature intermediate villi

-terminal villi

Matu

ratio

n

ofvilli

Angiogenesis

Transformation of

spiral arteries

Placental villi

Modified after Bernischke et al Pathology of the Human Placenta 2012

The syncytiotrophoblast layer covers a surface area of 12-14 m2

at term [48] It is covered by

microvilli which increase the surface area by a factor of five- to seven The

syncytiotrophoblast layer is comprised by two membranes the maternal-facing microvillous

membrane (MVM) and the fetal-facing basal membrane (BM) The syncytiotrophoblasts act

as an epithelium and contain high densities of transporter proteins There are transport

proteins for the major groups of nutrients Glucose transport proteins belonging to the GLUT

family transport glucose across the placenta by facilitated diffusion [49] Amino acids are

transported by transporter proteins by an active process [50] Lipids are mainly transported as

free fatty acids (FFA) by simple diffusion or by specific binding proteins [5152] Transporter

proteins for micronutrients and drug transporters involved in the transport of drugs have also

been identified [5354] The syncytiotrophoblast also transport ions and solutes to maintain

membrane potential and cell volume regulation

28

Figure 6 The syncytiothrophoblast cell

Modified by Oslashystein H Horgmo after SLager J Pregnancy 2012

Growth of the placenta

The placenta grows close to linearly throughout pregnancy [5556] Cytotrophoblast cells fuse

continuously to maintain and expand the syncytiotrophoblast layer Little is known regarding

the control of this coordinated sequence of events After around 32 weeks of gestation the

fetal capillaries and syncytiotrophoblast layer come closer as the syncytiotrophoblast becomes

thinner and free of nuclei and most organelles This thinning of the membrane separating the

maternal and fetal circulations aids gaseous exchange and the membrane is known as the

rdquovasculosyncytial membranerdquo [47] The volume of the terminal villi and hence the surface

area increases exponentially throughout pregnancy a process that appears to be dependent on

branching of the villi and angiogenesis [57] Although the villous tree undergoes continuous

growth and differentiation during pregnancy relatively little is known about the regulation of

this process Maternal factors like prepregnancy BMI and GWG have been shown to be

associated with placental growth measured both as placental weight thickness and area [58]

Little is known about fetal factors that may affect placental growth Studies in mice do

however indicate that the fetus itself influences the functional properties of placenta [59]

29

152 Placental functions

The placenta has a range of important functions to ensure a successful pregnancy outcome

including transport of nutrients and gases metabolism and endocrine and protective

functions

Transport of nutrients and gases

a Transport of gases

Oxygen provided by the maternal blood is transferred to the fetal circulation by diffusion

Carbon dioxide and other waste products are removed from the fetus and transported to the

mother by the placenta [9] Chronic exposure during pregnancy to hypoxia as seen at high

altitudes is associated with reduced fetal growth [60] However comparisons of fetal oxygen

extraction between pregnant women at high altitude (3600 m) and sea level (400 m) showed

that the fetus had the ability to adapt and to increase oxygen extraction [60] Studies on

pregnant sheep in vivo showed the O2 consumption per kg of the fetus to be twice that of an

adult and the uteroplacental tissues to consume four-fivefold that of the fetus [61]

b Transport of nutrients

Glucose

Glucose is the primary energy source for the fetus As the fetus to a very limited degree

produces its own glucose the fetus needs to obtain glucose from the maternal circulation

Glucose is transported from the maternal circulation across the syncytiotrophoblasts of the

placenta by facilitated diffusion [49] The syncytiotrophoblast is the main barrier in the human

placenta and is comprised by two cell membranes the maternal-facing microvillous

membrane (MVM) and the fetal-facing basal membrane (BM) The glucose transporters found

in the human placenta belong to the GLUT-family of which there are multiple isoforms The

GLUT 1 is the predominant transport protein in the human placenta at term and is found in

higher concentration on the microvillous membrane than the basal membrane [49] Glucose

transport across the endothelial layer is not well studied

30

The maternal-fetal glucose transfer depends on several factors

Glucose supply Glucose supply is determined by both maternal blood glucose

concentration and blood flow to the placenta

Placental glucose metabolism The placenta not only transfers glucose to the fetus but

consumes considerable amounts of glucose itself Insight into the placental glucose

transfer and metabolism is largely based on data from animal studies in particular on

pregnant sheep Placental glucose consumption is normally very high Estimates

suggest that the placenta consumes about 50 of the glucose extracted from the

maternal circulation [62] Placental glucose metabolism can be altered as a result of

alterations in the supply of other energy-generating substrates like oxygen Hypoxic

conditions has been suggested to increase glucose consumption in the placenta thus

making less glucose available to the fetus [63]

The total surface area of the membranes

Placental glucose transporter density and functions [64]

Maternal-fetal glucose gradient The maternal glucose concentration is higher than the

fetal concentration which creates a maternal-fetal gradient This gradient is thought to

be the driving force for the transfer of glucose from the mother to the fetus The

maternal and fetal glucose concentrations are closely related [65ndash67] The gradient

increases with gestation and so does the placental transport capacity Together this

ensures that placental glucose transfer to the fetus is increased which is needed to meet

the increasing needs of the growing fetus A lower fetal glucose concentration leads to

a larger maternal-fetal glucose concentration gradient which increases transfer of

glucose to the fetus In IUGR fetuses the glucose level is lower which creates a larger

gradient and hence increases the transfer of glucose [66] The regulation of fetal

glucose utilization in humans is only partially understood but has been studied in

more detail in pregnant sheep In sheep the rate of fetal glucose utilization depends on

the interaction between fetal plasma glucose and insulin concentrations and the supply

of glucose to the fetus [61] Fetal glucose uptake seems to be regulated by fetal glucose

concentration rather than maternal supply [68]

Insulin Maternal insulin is not transferred across the placenta The major glucose

transport protein in the human placenta at term is GLUT 1 which does not have

insulin receptors [64] The fetal pancreas develops in the first half of pregnancy and

31

sheep experiments have shown that by mid-gestation measurable insulin is produced

[69] Fetal insulin secretion consists of both basal secretion and glucose-stimulated

secretion Studies on pregnant sheep have revealed that both basal and glucose-

stimulated insulin secretion increases over gestation and responds to changes in fetal

glucose concentration as well as duration and pattern of change Chronic marked

hyperglycemia in sheep gave down-regulation of both glucose-stimulated and basal

insulin secretion whereas pulsatile hyperglycemia increased fetal insulin secretion

[7071] Hypoglycemia has been shown to decrease basal- and glucose-induced insulin

secretion [72] Insulin is an important growth hormone in utero and deficiency of

insulin leads to growth restriction in the fetus Fetal hyperinsulinaemia leads to

increased weight gain particularly in species with a high body fat content at birth like

the humans [73] The mechanism in which insulin stimulates fetal growth is in part

thought to be its anabolic effects on glucose and amino acid metabolism through

increased cellular uptake of glucose that maximizes the transplacental concentration

gradient for glucose and hence increases transport of glucose across the placenta

Lipids

Fatty acids are necessary for the fetus for various purposes as a source of energy as elements

of cellular membranes and for development of tissues and organs Maternal triglycerides (TG)

have been suggested as a more important source of fatty acids than nonsesterified fatty acids

(NEFAs) TG are hydrolyzed by placental lipases (lipoprotein lipase) to free fatty acids which

can diffuse freely across the placenta or be taken up by the placenta via fatty acid transport

proteins [51] Total levels of fatty acids are lower in the fetal than the maternal circulation but

the fatty acid profile is different with higher proportions of long chain polyunsaturated fatty

acids [9]

Amino acids

Fetal plasma amino acid concentrations are higher than maternal concentrations Amino acids

are taken up against a concentration gradient by secondary active transport systems in the

MVM More than 20 amino acid transport systems are expressed in the human placenta [74]

These are categorized as heterodimeric (eg system L) or monomeric (eg system A) Amino

32

acids are required by the fetus for protein synthesis but can also be metabolized by the fetus

[9] Reduced fetal plasma concentration of a number of amino acids have been reported in

studies of IUGR [75]

c Endocrine functions

The placenta metabolizes a number of substances and releases metabolic products into the

maternal andor fetal circulations The placenta thus has endocrine paracrine and autocrine

functions There are numerous hormones that are produced by the placenta in order to

maintain and regulate pregnancy [9]

Estrogen

Estrogens are produced by the syncytiotrophoblasts in large amounts during pregnancy 80-

90 of the the steroids produced in the placenta are secreted into the maternal blood The

fetus is the main source of the precursors used for production of estrogens and they are

produced in the fetal adrenal gland and the fetal liver [76] The estrogens act as specialized

growth hormones for the reproductive organs of the mother [9]

Progesterone

Progesterone is produced by the corpus luteum in the first weeks of pregnancy and later by

the trophoblasts in the placenta The plasma levels increase throughout pregnancy

Progesterone is synthesized largely from maternal plasma low density lipoprotein (LDL)

cholesterol The fetus contributes few or no precursors for progesterone synthesis In normal

pregnancy there is little de novo synthesis of progesterone in the fetus The progesterone

preferentially enter the maternal circulation and very little crosses to the fetus [76]

Progesterone inhibits uterine contractions

Human Chorionic Gonadotropin (HCG)

HCG is a glycoprotein which is structurally similar to Luteinizing Hormone (LH) Follicle

Stimulating Hormone (FSH) and Thyroid Stimulating Hormone (TSH) and is mainly

33

synthesized in the syncytiotrophoblasts HCG enters the maternal circulation at the time of

implantation and is detectable in maternal plasma and urine The concentration peeks at week

8-10 of pregnancy after which it declines The biological function is believed to be

maintenance of the corpus luteum stimulation of fetal testicular testosterone secretion and

stimulation of the maternal thyroid gland [76]

Human Placental Lactogen (HPL)

HPL is a polypeptide which is structurally similar to human growth hormone and human

prolactin It is mainly produced by the syncytiotrophoblasts It is detectable in the maternal

circulation by week 5 and rises steadily and approximately proportional to placental mass

until week 34-36 There is little HPL detectable in maternal urine or in fetal plasma HPL

participates in metabolic processes by stimulating lipolysis HPL thereby functions primarily

to ensure nutrient supply to the fetus by efficient mobilization of maternal tissue stores [76]

34

16 Sexual dimorphism in fetal growth and placental function

There are well-known sex specific differences in fetal growth Birthweight of boys is

generally higher than that of girls Body composition also differs boys being longer and

having larger head circumference than girls whereas girls have higher fat percentage than

boys [16] Fetal-placental weight ratio is greater in boys than in girls indicating a higher

placental efficiency among boys [77] Male fetuses grow faster than girls in utero and one

study reported that the difference was statistically different from week 28 onwards [78] Boys

outnumber girls at birth A study from the Norwegian Birth Registry (MBR) found a ratio of

106 among all births This ratio was higher among births in lower gestational age groups as

high as 248 in 16-19 weeks of gestation [79] Similar findings have been reported in multiple

populations [80] Perinatal mortality is generally higher in boys than in girls and in the study

from MBR of Norway it was approximately 20 higher in boys than girls across the whole

range of gestational age groups [79] Attempts have been made to explain the increased

vulnerability observed in boys by sex specific differences in the developmental environment

including possible differences in placental functions Although there are obvious differences

in fetal growth to my knowledge there are no published data on sex specific differences in

nutrient transport across the placenta However there are reports on sex specific differences

in other aspects of placental function especially related to inflammatory responses and

endocrine functions In pregnancies complicated with maternal asthma there was increased

cytokine production in male placentas compared to female placentas [81] Differences in

cytokine production have been suggested to contribute to the observed increased incidence of

preterm delivery in males [82] Glucocorticoids given as repeated doses have been shown to

reduce fetal growth [83] Data suggest that the male and female fetal-placental unit responds

to cortisol in a differential manner Among pregnant women with asthma there were similar

levels of maternal cortisol but female fetuses responded with a reduction in birthweight

whereas the growth of the male fetuses was normal [84] Data on placental properties from

male and female are generally pooled but significant findings may be lost as male placentas

might have different responses than female placentas The different strategies to cope with

the same maternal environment has been summarized by V Clifton [84] She proposed that

male responses lead to minimal placental adjustment in gene and protein expression and that

the target is to increase or continue growth resulting in a greater risk of adverse outcome

Females on the other hand have multiple adaptations in placental gene and protein expression

and minor reduction in growth resulting in increased survival

35

17 Preeclampsia

Preeclampsia is defined as new onset hypertension (blood pressure gt14090) and proteinuria

(gt03 g per 24 hours) in the second half of pregnancy [85] This pregnancy complication

affects between 3 to 5 of all pregnancies depending on the population Preeclampsia is a

leading cause of mortality and morbidity for both mother and child worldwide particularly in

the developing world Worldwide preeclampsia accounts for more than 50 000 maternal

deaths annually [86] Risk factors include genetic factors multiple pregnancies high maternal

age obesity insulin resistance preexisting hypertension diabetes mellitus and renal disease

[87] Around 70 of cases of preeclampsia occur after 37 weeks of gestation [88]

Clinical picture

The symptoms of preeclampsia are diverse reflecting the underlying syndrome The systemic

vascular involvement is reflected not only in hypertension and proteinuria but can likewise

affect the vasculature in other organs like the liver and the brain When the liver is involved

symptoms and signs include abdominal pain nausea vomiting and elevated liver enzymes In

the case of HELLP (hemolysis elevated liver enzymes and low platelets) all these are present

along with the disturbances in the coagulation system In case of brain involvement visual

disturbances and eclampsia can occur Cerebrovascular complications like stroke and cerebral

hemorrhage are other feared maternal complications The fetus of preeclamptic pregnancies

faces increased risk of oligohydramnios IUGR and prematurity [89]

Classification

Preeclampsia has both a multifactorial pathogenesis and a heterogeneous clinical presentation

which complicates classification Classifications in use are according to pathophysiological

characteristics clinical severity presence of other maternal or fetal characteristics or

gestational age at presentation Classification based on pathogenesis suggests two broad types

of preeclampsia placental and maternal preeclampsia reflecting which element is more

prominent in the pathophysiology These subtypes are more of a theoretical framework than

different biological entities as most cases will rather be represented by a combination of both

The dichotomized pathophysiological classification can briefly be described as placental

preeclampsia when there is an abnormal placentation but basically a normal maternal

36

endothelium and maternal preeclampsia when the maternal endothelium is dysfunctional and

the placentation normal Classification according to severity of disease is used by American

College of Obstetrics and Gynecology (ACOG) Severe preeclampsia is defined as

hypertension (gt160110) and proteinuria (gt5 g per 24 hours or +3 on dipstick) or

accompanying symptoms and signs like oliguria cerebral disturbances impaired liver

function thrombocytopenia or fetal growth restriction [85] Early onset preeclampsia is often

defined as presentation before 34 weeks and late onset as after 34 weeks of gestation These

subtypes have different clinical presentations with the early-onset typically exhibiting more

serious clinical featuressymptoms and fetal growth restriction than the late onset [90]

Pathophysiology

Clinical symptoms of preeclampsia arise in the second half of pregnancy which can be

considered the last stage in the development of the disorder The preceding stages include the

placentation process which involves an immunologically regulated interaction between the

placenta and the maternal endothelium Placenta is necessary for the development of

preeclampsia but preeclampsia can occur without a fetus as in hydatidiform mole The

symptoms disappear after delivery of the placenta In preeclampsia the trophoblast invasion is

restricted to the decidua and does not reach the inner third of the myometrium resulting in

inadequate remodeling of spiral arteries The normal loss of smooth muscle and enlargement

of the spiral arteries is therefore restricted

Normal placentation further requires immune tolerance for fetal and placental antigen which

might be altered in preeclampsia There is a low-grade systemic inflammatory response

present in normal pregnancy which is enhanced in preeclampsia [91] The maternal

endothelium becomes activated and eventually dysfunctional Preexisting maternal vascular

dysfunction might render the maternal endothelium more sensitive to the burden of these

factors leading to endothelial dysfunction

Disturbed endothelial maintenance

In patients with preeclampsia there is an angiogenic imbalance in the circulation resulting in

more anti-angiogenic than angiogenic factors ie more of endothelium-disturbing and less

endothelium-supportive factors The vascular endothelial growth factors (VEGF-family) are

37

involved in angiogenesis and endothelial maintenance by affecting migration and

differentiation of endothelial cells [92] The family consists of several glycoproteins

including VEGF-A and PlGF among others Both of these have pro-angiogenic effect The

VEGF receptors are present on vascular endothelial cells and include VEGFR-1 (Flt-1) and

VEGFR-2 (KDR) VEGF binds to both receptors whereas PlGF binds exclusively to VEGFR-

1 (Flt-1)

Figure 7 Angiogenic imbalance

sFlt-1

sFlt-1 is a soluble form of the VEGFR-1 produced by alternative splicing [93] Placentas from

preeclamptic pregnancies show higher expression of sFlt-1 mRNA than normal placentas [94]

How much placenta actually contributes to the circulating sFlt-1 is however not settled sFlt-1

binds free VEGF and free PlGF and thereby inhibits their beneficial actions on the vascular

endothelium sFlt-1 increases with gestational age in normal pregnancy but is significantly

higher in women destined to develop preeclampsia from approximately week 26 and peaks

around week 34 [95]

38

sEndoglin

The transforming growth factor-β (TGF- β) family of proteins is known to be involved in

angiogenesis but has diverse actions in many cells Endoglin is a TGF-β coreceptor expressed

in endothelial cells and syncytiotrophoblasts of the placenta [87] A soluble form of endoglin

(sEng) is present in sera from preeclamptic patients There is a three- five- and tenfold

increase in sEng in mild PE severe PE and HELLP syndrome respectively [96] Endoglin

mRNA expression in placentas from preeclamptic pregnancies is fourfold increased compared

to healthy pregnancies [96] But again the placental contribution to circulating sEng is

unclear sEng increases with gestational age but in women destined to develop preeclampsia

the increase is significantly higher than healthy controls from week 23 (preterm PE) and week

30 (term PE) Interestingly women destined to deliver a SGA infant had increased sEng

levels from week 10 [95]

sEng and sFlt-1 given together increased capillary permeability in the lungs liver and kidney

of mice and induced hypertension in pregnant rats [96] demonstrating a possible combined

action of sFlt-1 and sEng in the pathogenesis of PE

PlGF

Placental growth factor is one of the members of the VEGF-family which has proangiogenic

activity [92] In non-pregnant women circulating levels are low but PlGF can be produced by

the heart and lungs skeletal muscle and adipose tissue PlGF is expressed by the placenta in

particular the syncytiotrophoblasts [97] In pregnancies complicated by preeclampsia PlGF

concentrations are lower than normal pregnancies [98] In normal pregnancy PlGF can be

detected from first trimester and increases until around week 33 after which it declines

towards term PlGF binds to the VEGFR-1 (Flt-1) receptor PlGF is necessary to stimulate

angiogenesis eg after myocardial injury The function of PlGF in pregnancy is not clear but

might be to regulate maternal vascular function by displacing VEGF from the Flt-1 receptor

so that it binds to the more active Flt-2 receptor (KDR) [87]

39

Figure 8 Endothelial integrity and dysfunction

VEGF

PlGF

Flt1

(VEGFR-1)

VEGF

PlGF

Endothelial integrity

Tore Henriksen 2006

VEGF

PlGF

Flt1

(VEGFR-1)

VEGF

PlGF

Endothelial dysfunction

Tore Henriksen 2005

Treatment

There is no causal treatment besides delivery of the baby and the placenta Symptomatic

antihypertensive treatment should be given to reduce maternal complications [85]

Preeclampsia can be complicated by eclampsia stroke disseminated intravascular coagulation

(DIC) HELLP placental abruption and acute renal failure Because the only treatment is

delivery preeclampsia leads to prematurity and increased risk of perinatal mortality and

morbidity

Prevention

40

Studies assessing interventions to reduce rate or severity of preeclampsia have been

conducted There is insufficient evidence to recommend rest reduced salt intake fish-oil

supplementation and antioxidant vitamins as preventive measurements [99] A Cochrane

review concluded that low-dose aspirin had small to moderate benefits (15 risk reduction)

when used for prevention of preeclampsia but that more information is needed to assess

which women are most likely to benefit when to start treatment and at what dose [100]

Calcium supplementation reduced risk of preeclampsia and can be considered for high risk

groups in low-intake populations [101]

Prediction

Many features of preeclampsia are exaggerated responses also present in normal pregnancies

In terms of diagnosis or prediction it is difficult to draw a clear distinction between normal

and abnormal No test predictive or diagnostic can be expected to distinguish absolutely

between different degrees of features that are common to all pregnancies Many tests have

been assessed as potential predictors of preeclampsia but no single test has yet met the

clinical standards for a predictive test Combinations of tests such as ultrasound assessment of

uterine artery Doppler waveforms and serum markers have been suggested as have ratios of

antiangiogenic and proangiogenic factors However sensitivity and specificity of the markers

PlGF sFlt-1 and sEng are too poor for accurate identification of preeclampsia in clinical

practice and hence not recommended used alone for the prediction of preeclampsia [102]

Predictive tests could ideally either identify those destined to develop preeclampsia during

pregnancy or differentiate between a serious or mild form among those diagnosed with

preeclampsia The latter would be of clinical importance in handling these patients

Long-term complications

Risk of recurrent preeclampsia depends on severity and onset of preeclampsia in the previous

pregnancy but can be up to 40 for severe disease [103] Women with a history of

preeclampsia have an elevated risk of cardiovascular disease later in life According to a

meta-analysis the risk of hypertension is 3-4 times the risk for women without preeclampsia

41

and the risk of death from cardiovascular and cerebrovascular disease about twice as high as

in women without preeclampsia [104] The mechanisms for the increased risk are not yet fully

understood but shared risk factors for preeclampsia and cardiovascular disease may jointly

predispose [105] This could be the case for chronic hypertension diabetes mellitus and renal

disease

42

2 Aims of the study

Overall aim

The overall aim of this thesis was to gain insight into the associations between maternal

nutritional and metabolic factors and fetal growth and aspects of placental function in normal

and preeclamptic pregnancies

Specific aims

Paper 1

The aims were to

1) Estimate and compare the effects of maternal characteristics on birthweight and on fetal

growth in third trimester

2) Introduce placental weight as a possible determinant of birthweight and of fetal growth in

third trimester

We hypothesized that maternal factors and placental size were associated with birthweight

and fetal growth

Paper 2

Given the findings in Paper 1 the aim was to study the effects of maternal factors (parity

BMI gestational weight gain and fasting glucose) on placental weight stratified by fetal sex

We hypothesized that the maternal factors mentioned above affected placental weight Based

on emerging evidence we also hypothesized that there were differential effects between fetal

sexes

Paper 3

Based on the observations in Paper 1 and 2 the aims were to

1) Establish an in vivo model in the human

2) To use the model to study human placental transfer of glucose in vivo to describe the

glucose and insulin concentrations in the uteroplacental and umbilical circulation in healthy

43

pregnancies at term and to explore the relation between maternal and fetal glucose

concentrations

We hypothesized that maternal plasma glucose was the major determinant of the fetal venous-

arterial gradient

Paper 4

Preeclampsia is a pregnancy specific placenta dependent disorder Preeclampsia has two

prominent features maternal vascular dysfunction and placental insufficiency Using the in

vivo model the aim was to investigate factors that may link placental disturbance to maternal

vascular dysfunction For this purpose sFlt-1 and sEng were chosen

We hypothesized that both sFlt-1 and sEng originate in placenta by finding that the plasma

concentration was higher in the maternal venous than the arterial side of the uteroplacental

circulation

44

3 Materials and methods

This thesis consists of four papers based on two separate studies that differ in design

population and methodological issues and will therefore be described separately

The STORK study

The STORK study is a prospective longitudinal study performed in the period 2001-2008 A

total of 1031 healthy pregnant women who gave birth at Oslo University Hospital

Rikshospitalet Norway and their newborn infants were included in the study Inclusion

criteria were healthy women of Scandinavian heritage with singleton pregnancies Exclusion

criteria were multiple pregnancies known pregestational diabetes and any severe chronic

diseases (lung cardiac gastrointestinal or renal) as well as any malformations discovered at

the routine ultrasound examination at week 17-19

Population

Eligible women were identified by one of the three PhD candidates in the project Invitation to

participate was sent to eligible women as they were registered for obstetric care at the

beginning of pregnancy Those interested in participating confirmed by phone to a secretary

who enrolled them in the study The number of women invited to participate varied over time

due to capacity The capacity for the oral glucose tolerance test (OGTT) was the ldquorate-limiting

steprdquo The drop-out rate was very low 33 of those who were included Thirty-two women

were excluded because of twin pregnancies or malformations that were diagnosed at the

routine ultrasound scan

45

Figure 9 Flow chart showing inclusion of participants in the STORK study

Withdrawn before

inclusion

n=141

Excluded

n=32

Lost

n=37

Invited to participate

n=4122

Accepted invitation

n=1241

Included

n=1100

Followed up

n=1031

Study design

The STORK study has a longitudinal design Each pregnant woman had four antenatal visits

(visit 1-4) scheduled at weeks 14-16 22-24 30-32 and 36-38 of pregnancy The newborns

were examined shortly after birth

Data collection

Clinical data

Background data was collected at the first visit including past medical and obstetric history

Clinical examination was repeated at every visit Data on the delivery and postpartum period

were extracted from hospital records

Blood samples

Blood samples were drawn at each visit between 0730 and 0830 after an overnight fast

centrifuged and stored at -80ordm C immediately Plasma glucose was measured by Accucheck

(Roche Diagnostics Mannheim Germany)

46

Birthweight

Newborns were weighed on a calibrated scale and measured by the attending midwife or

childrenrsquos nurse within two hours after birth

Ultrasound

Ultrasound examinations were done at visit 2 - visit 4 using an Acuson Aspen machine

(Acuson Mountain View CA USA) Biometric measurements included head circumference

(HC) abdominal circumference (AC) and femur length (FL) Each measurement was made

three times and the mean value was calculated and used in the analyses Estimated fetal

weight (EFW) was calculated by Combs formula [106] Percentiles for estimated fetal weight

and the individual biometric measurements were calculated according to Norwegian charts

[107108] Fetal growth in the third trimester was calculated as the difference between

measurements made at visit 3 and visit 4 for EFW and HC AC or FL respectively

Table 1 Data collection in the STORK study

Statistical analysis

Descriptive statistics were used to characterize the study population Bivariate associations

were explored by scatter plots and correlation analyses Univariate linear regression was used

to study the associations between selected maternal characteristics and the dependent

variablesoutcome variables birthweight and several fetal growth parameters in Paper 1 and

placental weight in Paper 2 Variables with a p-value lt 01 were considered in the multiple

linear regression models Multiple linear regression models were used to study the

Visit 1

14-16 w

Visit 2

22-24 w

Visit 3

30-32 w

Visit 4

36-38 w

At birth

Clinical examination + + + + +

Anthropometric measures

(skin fold thickness)

+ + + + +

Fasting blood samples + + + +

Oral glucose tolerance test + +

Ultrasound

(evaluation of fetal growth)

+ + +

Diet questionnaire + +

Physical activity questionnaire + +

47

associations between selected maternal characteristics and the outcome variables birthweight

fetal growth and placental weight A p-value lt 05 was considered statistically significant

All analyses were done by SPSS 180

Ethical aspects

All participants signed a written consent The study was approved by The Regional

Committee for Ethics South Norway (S- 01191)

48

The STORK-Placenta study

Study design

The STORK-Placenta study was designed to serve several purposes One purpose was to

study placental aspects of fetal growth and this was done as a cross-sectional study among

healthy pregnant women Secondly the study served as a case-control study with two groups

one consisting of preeclamptic patients and one with healthy controls

Population

There are two subgroups of the STORK-Placenta study in Paper 3 and Paper 4 respectively

In Paper 3 we included 40 women Inclusion criteria were healthy non-smoking women with

uncomplicated singleton pregnancy who were scheduled for elective caesarean section

Exclusion criteria were pre-existing co-morbidity any medication and pregnancy

complications like preeclampsia or insulin-dependent gestational diabetes Women who

arrived at the delivery ward with contractions prior to scheduled caesarean section were

excluded The recruitment was done at the out-patient clinic either during the appointment

when caesarean section was decided or during scheduled preoperational information

In paper 4 we included 12 patients with preeclampsia and 7 healthy pregnant women

Inclusion criteria for the study group were the diagnosis of preeclampsia and indication for

caesarean section prior to labour The control group consisted of healthy pregnant women

scheduled for elective caesarean section

Data collection

Medical and obstetrical history was taken at inclusion Clinical data was collected at inclusion

and at the day of delivery

Blood sampling

Blood samples were drawn from both the maternal and the umbilical (fetal) circulation during

caesarean section in spinal anaesthesia Fasting maternal blood samples were obtained by the

obstetrician from the uterine vein preferable on the same side as placenta just before uterine

49

incision Simultaneously blood was drawn by the anaesthesiologist from an arterial line in the

radial artery We assumed similar blood composition in the radial and the uterine artery In

addition blood was drawn from a venous catheter in the cubital vein or dorsal vein network of

the hand Directly after delivery blood samples were obtained from the umbilical artery and

vein immediately after cord clamping Blood was drawn into SAFETY Blood Collection Set

with Luer Adapter (Vaccuette Geiner Bio-One GmbH Austria) Blood samples were

immediately transferred to ethylenediaminetetraacetic acid (EDTA) vacutainers and stored on

ice until all samples were obtained They were then centrifuged at 4-6ordmC 2500 G for 20

minutes before the supernatants were removed and aliquotted and stored at -80ordmC until

analyses were performed

Analyses of samples

Glucose and insulin

Analyses were performed according to standard laboratory methods (Department of Medical

Biochemistry Oslo University Hospital Rikshospitalet) during three consecutive days

Glucose was measured using the hexokinaseglucose-6-phosphate dehydrogenase method

(Roche) Insulin was analysed using the Elecsys insulin analysis which is an enzyme-linked

immunosorbant assay (ELISA) technique with two monoclonal antibodies (Roche)

sFlt-1 and sEng

The concentrations of sFlt-1 and sEng were measured by commercially available ELISA kits

(RampD Systems Minneapolis MN USA) Assays were conducted in duplicate and in one run

The coefficients of variance were lt 10

50

Statistical analyses

Descriptive data were reported as mean values with standard deviations (SD) or percentages

as appropriate The differences in maternal characteristics between groups were compared by

unpaired t-test (Paper 4)

Glucose values were reported as mean values (SD) Comparisons between concentrations of

glucose in maternal and fetal vessels respectively were performed by paired t-tests Due to

skewed distributions insulin concentrations were reported as median values with inter quartile

ranges (IQR) and comparisons of related samples were performed by Wilcoxon sign rank test

Correlations were reported as Pearsonrsquos correlation coefficient if one variable was normally

distributed whereas Spearmanrsquos rank correlation coefficient was used in the case of

correlation between two skewed variables

The distribution of the concentrations for sFlt-1 and sEng were not normally distributed

hence they were log transformed to obtain normal distribution in order to use parametric

methods for statistical analyses Arithmetic median levels are reported in the text and figures

The differences in concentrations between groups were compared by unpaired t-test and the

concentrations in the radial artery and uterine vein from the same individual were compared

by paired t-test However non-parametric tests on the original data gave the same results

Ethical aspects

All participants signed a written consent The study was approved by The Regional

Committee for Medical Research Ethics South Norway (S-071742011-2419)

51

4 Summary of results

Paper 1

In Paper 1 we analyzed the associations between selected maternal characteristics and

birthweight measured as z-scores adjusted for gestational age and fetal sex We found that the

following maternal characteristics were independent determinants of birthweight and

statistically significant in the multiple regression model

Parity (B 046 95 CI 033-059 plt0001)

BMI (B 0048 95 CI 003-006 plt0001)

Gestational weight gain (B 006 95 CI 004-008 plt0001)

Fasting glucose (B 033 95 CI 018-048 plt0001)

In addition placental weight was a determinant for birthweight

Placental weight (B 041 95 CI 038-044 plt0001)

Adjusting for placental weight in the multiple model left the following maternal determinants

statistically significant

Parity (B 036 95 CI 025-047 plt0001)

BMI (B 0018 95 CI 0004-003 p= 0012)

Gestational weight gain (B 0036 95 CI 002-005 plt0001)

Fasting plasma glucose (B 022 95 CI 0009-034 plt0001)

Introducing placental weight as a covariate reduced the effect estimate of the other variables

in the model by 62 for BMI 40 for weight gain 33 for glucose and 22 for parity

The magnitude of reduction was estimated by change in the regression coefficient B of the

linear regression

Fetal growth in third trimester was estimated as the difference in EFW percentiles between

visit 3 and visit 4

In the multiple model the following maternal determinants remained statistically significant

Parity (B 473 95 CI 016-807 p=0006)

BMI (B 064 95 CI 023-106 p=0002)

Gestational weight gain (B 070 95 CI 024-116 p=0003)

52

In addition placental weight was a determinant for intrauterine growth

Placental weight (B 260 95 CI 16-36 plt0001)

Adjusting for placental weight in the multiple model left the following determinants

significant

Parity (B 39 95 CI 075-70 p=0015)

BMI (B 049 95 CI 008-089 p=002)

Gestational weight gain (B 060 95 CI 015-106 p=001)

Introducing placental weight reduced the effect of BMI on intrauterine fetal growth by 23

weight gain by 17 and parity by 14

We also analyzed the associations between maternal factors and the individual biometric

measurements Results from the multiple analyses for the increase in abdominal

circumference showed statistically significant associations for

Parity (B 018 95 CI 007-029 p=0001)

BMI (B 0022 95 CI 0005-003 p=0002)

Gestational weight gain (B 0026 95 CI 0008-004 p=0001)

Fasting glucose (B 044 95 CI -008-017 p=048)

In addition placental weight was a determinant for increase in abdominal circumference

Placental weight (B 011 95 CI 008-014 plt0001)

In the multiple model adjusting for all listed variables and placental weight fasting plasma

glucose was not significant (B 0016 95 CI -011-014 p=08) BMI reached borderline

significance (B 0014 95 CI 000-0028 p=0048) as an independent determinant when

adjusted for parity weight gain and placental weight For growth of the fetal abdominal

circumference BMI showed the largest reduction in B (36 ) when placental weight was

included

53

Paper 2

Given the importance of placental weight for birthweight and fetal growth we studied the

associations between maternal factors and placental weight in Paper 2 Mean placental weight

was 711 g (SD 156)

In the multiple regression model the following maternal factors were independent

determinants of placental weight

Parity (B 292 95 CI 101-484 p=0003)

BMI (B 67 95 CI 41-93 plt0001)

Gestational weight gain (B 56 95 CI 28-84 plt0001)

Fasting glucose (B 329 95 CI 100-557 p=0005)

Boys were heavier (3667 g vs 3494 plt0001) and longer (513 cm vs 503 cm plt0001)

than girls Boys also had a higher fetal placental ratio than girls (526 g vs 508 plt0001)

When stratified by fetal sex fasting glucose was significantly associated with placental

weight in females but not in males

Paper 3

We measured glucose and insulin concentrations in the uteroplacental and umbilical

circulations and calculated arterio-venous gradients The subjects were 40 healthy women

with a mean age of 36 years (SD 32) Mean birthweight was 3571 (SD 527) g range 2680-

4955g

The highest concentration of glucose was found in the maternal arterial circulation with a

mean concentration of 471 mmoll (SD 048) The uterine vein had a lower concentration

giving an arterio-venous difference of 029 mmoll on the maternal side The maternal

concentration of glucose was higher than the fetal concentration The maternal-fetal gradient

was 122 mmoll (SD 042) The concentration in the umbilical vein was 384 mmoll (SD

041) In the umbilical artery the concentration was lower 348 mmoll (SD 045) giving a

fetal venous-arterial difference of 038 (SD 031)

54

Maternal arterial and fetal venous concentrations of glucose were highly correlated (r=086

plt0001) Maternal arterial glucose concentration was not significantly correlated to the fetal

glucose v-a difference (r=03 p=007) The maternal a-v glucose difference was neither

correlated to the level of glucose in the umbilical vein nor the fetal glucose difference The

maternal-fetal gradient was highly correlated to the fetal glucose difference (r=08 plt0001)

The maternal-fetal glucose gradient was also correlated to the glucose concentration in the

umbilical artery (r=-038 p=0017) whereas it was not correlated to the glucose concentration

in the umbilical vein Similarly the fetal glucose v-a difference was only correlated with the

glucose concentration in the umbilical artery (r=-045 p=0004) but not with the glucose

concentration in the umbilical vein

The glucose concentration in the umbilical vein was not correlated to birthweight or placental

weight whereas correlation between the fetal glucose v-a difference and birthweight just

reached borderline significance (r=032 p=0049)

We found no relation between maternal and fetal insulin values (rho=-01 p=057) Maternal

and fetal concentrations of insulin were not statistically different On the maternal side

glucose and insulin concentrations were correlated (r=052 p=0001) On the fetal side

however no such correlation was found (r=012 p=048) Fetal insulin was correlated to both

placental weight (r=046 p=0003) and birthweight (r=058 plt0001)

Paper 4

We measured the anti-angiogenic factors sFlt-1 and sEng in a group of preeclamptic patients

and in healthy controls Both factors have been suggested to be released by the placenta and

involved in the pathogenesis of preeclampsia

Preeclamptic women had

Higher concentration of sFlt-1 than healthy controls (median of 17450 pgml of sFlt-1

compared to 5055 pgml in the control group p= 0003)

Higher concentration of sEng than healthy controls (median of 687 ngml in the

preeclampsia group versus a median of 287 ngml in the control group p= 0003)

55

We compared the concentration in the blood entering the uteroplacental unit (radial artery as a

proxy for uterine artery) and the blood leaving the uteroplacental unit (uterine vein)

Preeclamptic women had

Higher concentration of sFlt-1 in the uterine vein than in the radial artery (22450 vs

17450 pgml p=0005) whereas the concentration of sEng was not statistically different

(757 vs 687 ngml p=012)

Among healthy controls

No significant differences in the concentration between the uterine vein and the radial

artery for sFlt-1 (6193 vs 5055 pgml p=039)

No significant differences in the concentration between the uterine vein and the radial

artery for sEng (307 vs 287 ngml p=059)

56

5 Discussion

51 Methodological issues STORK

511 Design

The STORK study has a longitudinal design with four antenatal visits and observations at

birth for the 1031 women and children included Longitudinal studies are well suited to study

associations between explanatory variables and outcomes but not suitable to assess causality

The associations found in our study would need to be tested in a RCT or experimental model

to assess causality

512 Validity

The word valid is derived from the Latin validus meaning strong Validity in terms of

research refers to whether the results obtained answer the questions asked in the study

Validity can further be divided into internal and external validity [109]

Internal validity

Internal validity refers to whether the conclusions reached are likely to be correct for the

circumstances of that particular study Bias undermines the internal validity and includes

selection bias information bias and confounding bias [110]

Selection bias

Selection bias can result when the selection of subjects into a study (subject selection bias) or

their likelihood of being retained in the study (loss to follow up bias) leads to a result that is

different from what you would have obtained if you had enrolled the entire target population

[110]

57

Subject selection bias

In the current study invitation to participate was sent to 4122 and 1241 accepted the invitation

The number of invitations sent per week varied according to the capacity to enroll in the study

and the limiting factor was four Oral Glucose Tolerance Tests per day There were periods of

reduced capacity like holidays when fewer invitations were sent but it is not likely that the

women invited would be any different to the ones not invited due to varying capacity

The self-selection procedure (the women themselves phoned to be enrolled) might have

resulted in selection of women that were particularly motivated to participate The opportunity

to get closer follow-up than standard antenatal care may have caused selection bias Three

evaluations of fetal well-being and fetal growth by ultrasound could theoretically have

attracted women with a previous history of fetal growth abnormalities Data on birthweight of

previous children revealed that for those who had one previous child average birthweight was

3655 g (SD599) whereas the second child on average weighed 3808 g (SD 706) The data was

normally distributed with no overrepresentation of SGA or LGA (data not shown) Thus there

was no obvious selection of women with a history of fetal growth abnormalities in our study

population

Loss to follow up bias

The number of patients lost was 37 giving a drop-out rate of only 33 The number of

patients excluded was 32 The numbers lost are small and not likely to have influenced the

results substantially All participants had birthweight and placental weight recorded

However the outcome intrauterine fetal growth could only be estimated for those who

attended both third and fourth visit 918 in total Those who gave birth prematurely (54)

were not included in this outcome Maternal characteristics were not different in this group

compared to the total group (data not shown)

The selection bias only influences the results if the women selected or lost differ in either their

characteristics or in the outcomes which does not seem to be the case in our study

Information Bias

Information bias arises if the information has not been gathered in the same way for all

participants It includes observational bias misclassification and measurement errors and can

58

occur during collection of data as well as coding and processing of the data Misclassification

includes classifying binary or discrete variables incorrectly We minimized misclassification

by using mostly continuous variables rather than categorical variables Bias might be

introduced by the observer (interviewer bias biased follow-up) by the study participants

(recall bias) or by measurement tools such as questionnaires or instruments

We might have introduced biased follow-up for at least one group of women The women

diagnosed with gestational diabetes mellitus at visit 3 were taught and encouraged to make

changes in diet and physical activity to prevent further deterioration in their glucose

metabolism This might have had an influence by reducing the outcomes birthweight and

intrauterine fetal growth in third trimester

Recall bias occurs when there are systematic differences in the way subjects remember or

report exposures or outcomes We tried to avoid recall bias by eg using measured weight and

height to calculate BMI instead of self-reported prepregnancy BMI Reviewing available data

on the relationship between self-reported and directly measured height and weight has shown

trends of under-reporting for weight and BMI and over-reporting for height [111]

Measurement errors will be discussed under data collection below

Confounding bias

A confounder is defined in epidemiological terms as a covariate that influence both the

independent and the dependent variable and can be controlled for by adding it to a multiple

regression model Confounders must be identified and then appropriately adjusted for in the

analyses [112] The statistical considerations around confounding will be discussed under

statistical issues in the discussion below

In Randomized Controlled Trials (RCT) confounding is avoided by randomly assigned groups

that differ only in the factor being studied and thereby removes the need to statistically control

for confounders In an observational study like STORK we tried to reduce the need for

adjusting for confounding factors related to comorbidities by selecting healthy women and to

avoid ethnic factors by selecting women of Scandinavian heritage

59

External validityRepresentativity

External validity or representativity refers to whether the results obtained in one study can be

generalized to other situations and to other populations [110]

To assess representativity we did two comparisons Our cohort was compared to a group of

women who delivered at Ullevaringl the largest obstetric unit in Oslo The comparison was

restricted to women of Scandinavian heritage and our cohort only differed in having fewer

smokers and single mothers (data not published)

We also compared our cohort to data from the Birth Registry of Norway Our study

population was comparable to women who gave birth in Oslo in 2009 on parameters like

maternal age parity gestational age (GA) at birth and birthweight (BW)

Figure 10 Comparison between STORK cohort and Oslo

0

10

20

30

40

50

60

Age P0 GA BW

STORK

OSLO 2009

Retrieved electronically from the Birth Registry of Norway [1]

60

513 Statistical issues

Longitudinal data

Analyzing longitudinal data with variables that are correlated over time is a statistical

challenge which can be solved by the use of mixed models However these methods are

complicated and require statistical knowledge that was not readily available to our group We

therefore chose our variables to be able to use conventional linear regression models Fetal

growth was defined as growth between visit 3 and visit 4 thereby confining fetal growth to

the third trimester The whole trajectory of fetal growth was thereby not fully explored

Similarly we only used fasting glucose concentrations at one time point as a covariate in the

multiple models instead of the change in glucose levels over time

Continuous versus categorical variables

We have chosen to use mostly continuous variables both as outcome and explanatory

variables instead of dichotomizing or creating groups This is based on both methodological

theory and published data on physiology in pregnancy Dichotomizing leads to several

problems [113] According to Altman much information is lost the statistical power is

reduced one may underestimate variation and non-linearity in the relation between variable

and outcome may be concealed [114] A large study of hyperglycemia in pregnancy (HAPO)

has shown that there is a linear relationship and no threshold value between fasting glucose

and adverse pregnancy outcomes [115] A similar relationship was seen between BMI and

adverse pregnancy outcomes [116]

Confounders mediators and colliders

A number of potential factors can influence the associations of interest These must be

identified and possibly corrected for in the regression models Whether to adjust for these

factors depend on classification of the factors into true confounders mediators and colliders

[112] Confounders should be included while colliders should no be included in regression

models to avoid introducing bias

A confounder (defined above) can be controlled for by adding it to a multiple regression

model The choice of which confounders to include in the model requires physiological

61

Independent variable Outcome

Confounder

Independent variable Outcome

Mediator

Independent variable Outcome

Collider

knowledge and requires statistical considerations when it comes to the number of observations

required [117] A mediator is considered a covariate that is on the causal pathway between the

independent and the dependent variable A collider is considered a covariate that is related to

both the independent and dependent variable in a common consequence [117] In our material

no included variables were considered to be colliders

Figure 11 Confounders mediators and colliders

62

Mediation

A mediator variable can either account for all or some of the observed relation between two

variables The effect of mediation can be assessed by judging what happens to the relation

between the independent and dependent variable when the mediator is included into the

regression model or not Full mediation would occur if inclusion of the mediation variable

removed the relation between the independent variable and dependent variable This rarely

occurs The most likely event is that the association becomes weaker yet still a significant

path with the inclusion of the mediator Partial mediation occurs when the mediating variable

accounts for some but not all of the relationship between the independent variable and

dependent variable Partial mediation implies that there is not only a significant relation

between the mediator and the dependent variable but also some direct relation between the

independent and dependent variable

One method to assess mediation was proposed by Baron and Kenny in 1986 [118] They laid

out several requirements that must be met to form true mediation relationships which are

summarized below

Step 1 Confirm that the independent variable is a significant predictor of the dependent

variable Independent Variable Dependent Variable

Y = β10 + β11 X + 1

β11 is significant

Step2 Confirm that the independent variable is a significant predictor of the mediator If the

mediator is not associated with the independent variable then it couldnrsquot possibly mediate

anything Independent Variable Mediator

Me = β20 + β21 X + 2

β21 is significant

Step 3 Confirm that the mediator is a significant predictor of the dependent variable while

controlling for the independent variable This step involves demonstrating that when the

mediator and the independent variable are used simultaneously to predict the dependent

63

variable the previously significant path between the independent and dependent variable is

now greatly reduced if not nonsignificant

Y = β30 + β31 X + β32 Me + 3

β32 is significant

β31 should be smaller in absolute value than the original mediation effect (β11 above)

Placental weight can be considered a mediator in this study Regression models are therefore

done with and without placental weight as a covariate in the model to show its role as a

possible mediator We applied the model by Baron and Kenny described above to show a

possible role of the placenta as a mediator Our results point at possible mediating pathways

involving the placenta on the causal pathway to fetal growth In order to quantify how much

of the effect that goes through the placenta we could have applied path analyses However

this method required more advanced statistical methods which were not available

64

52 Data collection STORK

521 Dependent variablesoutcomes

Birthweight

We chose to use birthweight as a summary measure of overall fetal growth It is widely used

and therefore suitable to compare our data to other publications We chose to use birthweight

as a continuous variable We wanted to report associations between maternal factors and

birthweight in the total STORK cohort as previous publications from the same cohort only

reported birthweight in sub cohorts andor using birthweight as a categorical value with a cut-

off of gt4200 g Birthweight was expressed as Z-scores adjusted for gestational age and fetal

sex

The standard score (Z-score) represents the distance between the raw score and the population

mean in units of the standard deviation Z is negative when the raw score is below the mean

positive when above The z-score is calculated as

where

x is the observed value

μ is the mean of the population

σ is the standard deviation of the population

Mean and standard deviation of the population were taken from a Norwegian reference

material [119]

Intrauterine fetal growth

There are no internationally accepted consensus on how to define and assess intrauterine fetal

growth [11] The longitudinal design of the STORK study enabled us to assess intrauterine

fetal growth We chose third trimester visit 3 to visit 4 which is the period of maximum

Z =

x - μ

σ

65

growth and a period in which maternal metabolic factors are important in terms of fetal

growth [120]

Fetal size and fetal growth were estimated by ultrasound Fetal size was expressed as both

estimated fetal weight (EFW) in grams and as EFW percentile according to Norwegian

growth charts [107] Intrauterine fetal growth was defined as the change in estimated fetal size

parameters from visit 3 to visit 4 expressed as either change in EFW (g) or change in

percentiles Combs formula was chosen as the equation to estimate fetal weight as it is the

formula in use in clinical practice at our department and the basis for the growth charts we

used as reference [106]

Errors in ultrasonographic assessment of fetal weight can be attributed to at least two factors

errors due to the equation and errors due to observer error Observer error can further be

divided into intra-observer and inter-observer error [121] Intra-observer error refers to the

variance in measurements performed by the same observer All measurements were

performed three times and we used the mean of the three values to minimize intra-observer

error Inter-observer error refers to the variance in measurements that occur because different

observers measure differently To minimize inter-observer error all measurements were done

by only three investigators and each participant was measured by the same investigator at all

visits Among errors in ultrasonographic assessment of fetal weight observer error has been

shown to be a relatively minor component compared to the larger error due to the equation

[18] To be able to assess fetal growth we compared our data to reference curves based on

data from University of Bergen Norway as that population was considered the most

comparable to our population [107] We also evaluated fetal growth as changes in each of the

three components that make up EFW according to Combs equation namely HC AC and

femur length Once again we compared our data with Norwegian reference data [108]

There are other types of fetal growth charts available Customized curves have been

developed to adjust for factors like race fetal sex parity and maternal size which are factors

known to influence birthweight and factors that differ in different populations [13] We chose

not to use customized growth charts since the aim of our study was to study the effect of

maternal factors on fetal growth In customized charts maternal factors are controlled for and

therefore unsuited to study the effect of maternal factors

Conditional growth curves take into account the estimated size measured at one point and

gives an estimation of the expected growth for a fetus of that particular size for a specified

period of time As an example a larger fetus at the 75 percentile at week 30 will be expected

to grow more during the next weeks than a smaller fetus at the 10 percentile at week 30 during

66

the same period of time Conditioning on a previous measurement gives information on

whether a particular fetus grows fast or slowly relative to other fetuses of the same size We

chose not to use conditional growth curves in the current study as preliminary analyses did not

indicate major changes in the results making use of the conceptionally more difficult variable

less justified

Placental weight

Placenta was weighed including umbilical cord and membranes by the midwife or childrenrsquos

nurse within one hour after birth The placental weight was expressed in grams The placentas

were not trimmed but there is a close correlation between trimmed and non-trimmed

placentas (r= 098) [122]

Rationale for using placental weight as a proxy for placental function

There is no single parameter that measures placental function as placenta has a range of

functions Placental weight was chosen as outcome as a surrogate for placental function

Placental weight is a measure commonly used to summarize placental growth and aspects of

placental function In normal pregnancy it is reasonable to assume that placental weight is

related to aspects of functional capacity of the placenta [123] We had no estimations of

placental weight or mass during pregnancy Placenta exhibits linear growth throughout

pregnancy [5556] making it reasonable to use placental weight after birth instead of

estimations of placental mass during pregnancy

We wanted to use a variable that reflects those aspects of placental function which are

relevant to fetal growth of which nutrient transport is an obvious factor Density or activity of

nutrient transport proteins in the placenta could have been used as an alternative measurement

of placental function but these data are not yet available in our cohort An underlying

assumption for nutrients to be transported across placenta is that the maternal or umbilical

blood flow is not impaired We performed Doppler measurements in the uterine artery and

umbilical artery In our cohort of healthy women only 35 had notching in the uterine artery

at visit 2 and 32 had a pulsatile index above 2 SD for gestational age at visit 4

(unpublished data)

67

Placental weight correlates well with surface area which is a major determinant for nutrient

transport [124] The maternal plasma level of hormones produced in the placenta are directly

related to placental weight [125]

522 Explanatory independent variables

The explanatory variables were chosen based on publications from our study [126ndash129] and

literature on fetal growth in general We selected some maternal characteristics that were

known to influence birthweight in order to study their relation to intrauterine fetal growth

Maternal factors

Maternal age was noted at the first visit in whole years Age was normally distributed

Parity was categorized into P0 and P1+ as the largest difference in birthweight is

known to be between the first child and second child and less between consecutive

children [43]

BMI was calculated based on height and weight measured at the first visit We did not

use pregestational BMI to avoid recall bias and false self-reporting

GWG was calculated as the difference in weight between visit 4 and visit 1 We did

not use weight measured at admission for delivery as there were many missing values

Fasting glucose was measured by the use of Accucheck (Roche Diagnostics

Mannheim Germany) in order to obtain the measured values immediately This

enabled us to inform the women of the result the same morning and in cases of

impaired glucose metabolism to give advice on diet and physical activity during the

consultation Analyses of glucose over the seven years of inclusion revealed that there

was an unexpected increase in fasting glucose of 06 mmolL over time We found no

accompanying increase in maternal age BMI or in insulin that could give a biological

plausible explanation for this increasing trend Thus the time trend in fasting glucose

most likely had an analytical cause The glucose values were de-trended according to

the coefficients from linear regression under the assumption of a linear increase

during the entire period and de-trending of the data removed the increasing trend

[130]

68

Placental weight

The rationale for using placental weight to reflect aspects of placental function has been

discussed above When placental weight was used as an explanatory variable in the regression

models placental weight was entered in 100 grams instead of 1 gram to avoid getting effect

estimates with too many decimals

Placental pathology

There were 55 placentas not characterized as normal which makes up 53 of the samples

Theoretically it is possible that the placental weight in these cases does not reflect function in

the same way as placentas characterized as normal Eg a placenta with infarctions has areas

of tissue that do not take part in nutrient transport Such a small percentage of pathological

placentas are not likely to have influenced the results to a significant extent

69

53 Methodological issues STORK-Placenta

Design

The STORK-Placenta study had a cross-sectional design which means the women were only

examined once which in our study was at delivery This design gives no opportunity to assess

earlier gestational ages or longitudinal changes throughout the pregnancy In Paper 3 all the

study subjects were healthy women and there was no need for a control group In paper 4 we

applied a case-control design in which the preeclampsia group was compared to a control

group of healthy pregnant women

Validity

Internal validity

Selection bias

Only women delivered by cesarean section were recruited to this study This lead to selection

bias for both the healthy women and the preeclamptic patients For the healthy women the

most common indications for cesarean section were prior cesarean section or patient request

due to traumatic previous delivery Few healthy primiparas are delivered by elective cesarean

the exception being breech presentation In Paper 3 the selection therefore resulted in age and

parity that were relatively higher than average Avoiding selection bias in a study like this was

not possible given the population eligible for participation

For the preeclamptic women the selection lead to overrepresentation of early onset

preeclampsia and cases of serious preeclampsia as late onset or less serious cases in many

cases can deliver vaginally In Paper 4 this was reflected in lower gestational age in the

preeclampsia group than the controls

Information bias

We assumed similar blood composition in the radial and the uterine artery This was done to

avoid puncturing the uterine artery as bleeding would be easier to control in the radial artery

As the blood is pumped out of the aorta it is reasonable to assume that the composition does

70

not change substantially between the blood reaching the radial artery compared to the blood

that reaches the uterine artery

External validityrepresentativity

The representativity of the results from the STORK-Placenta study is discussed in light of the

selection of the participants

Parity was higher in Paper 3 than average From our results in Paper 1 and Paper 2 we have

seen that parity was an independent variable with effect on fetal growth In Paper 3 the added

effect of parity on fetal growth could give a bias if the effect of parity also affects the glucose

transport across the placenta Hitherto the question can not be answered So far our results are

only valid for the glucose metabolism among healthy women with relatively normal BMI

Which changes that occur in the glucose metabolism in women with chronic diseases will

probably vary according to the disease Higher BMI would probably influence the glucose

metabolism both directly as higher BMI might lead to higher glucose levels in many cases

but possibly also indirectly by changes in inflammatory factors and by changes in the

transport of other nutrients as amino-acids and lipids

In Paper 4 gestational age was lower in the preeclampsia group than in controls Early-onset

and late-onset preeclampsia are by many considered two different subgroups of preeclampsia

due to the differences in risk factors pathogenesis and clinical presentation [90] Our findings

may not be valid for late-onset preeclampsia where maternal risk factors play a larger role in

the patophysiology and the endothelial dysfunction might be more prominent Therefore it is

possible that the results are valid only when the placental dysfunction is the major feature in

the pathophysiology like in early-onset preeclampsia

Statistical issues

In both papers from the STORK-Placenta study the numbers of participants were relatively

small due to the demanding logistics of the project Small numbers lead to some statistical

challenges that need to be discussed

In Paper 3 we included 40 patients which were sufficient to show significant glucose gradients

on both maternal and fetal side as well as a gradient across the placenta However the small

number restricted the possibilities to study interesting associations between maternal factors

and glucose transport or glucose transport in relation to fetal growth by the use of regression

71

models As an example we found an interesting association between maternal BMI and fetal

glucose v-a difference but the scatter plott revealed one woman with BMI 39 and analyses

showed that without that observation the association was no longer significant

In Paper 4 we found a significant difference in sFlt-1 but not in sEng across the uteroplacental

circulation among preeclamptic patients There is a possibility that lack of power influenced

this finding Possibly a larger sample could have given a significant difference for sEng in

which case our finding could represent a type 1 error (reject the hypothesis that there was a

difference even if it is true)

Both non-parametric tests on original data and parametric tests on log transformed data were

done giving the same results in terms of statistically significant differences We chose to use

the log transformed data for statistical analyses (as that seemed to be the most conventional

method used in relevant references) but presented arithmetic data in figures and tables to

make it easier for the reader

54 Data collection STORK-Placenta

Blood sampling

All procedures were standardized to minimize systematic errors Sampling was therefore done

by a small group of four trained obstetricians and handling the samples in the laboratory was

restricted to only three investigators In the few cases where sampling was inadequate it was

mostly due to failure in inserting the arterial line or in a few cases inadequate amount of blood

obtained from the umbilical artery Blood samples were kept on ice until centrifugation

Blood samples were taken in fasting condition to obtain a steady state situation This is

particularly relevant for glucose and insulin which show large post-prandial variation

Cesarean section was done under spinal anesthesia no participants received oxygen or

intravenous glucose infusion

Analyses

Glucose and insulin were analyzed at the laboratory at Oslo University Hospital The samples

were analyzed during three consecutive days

72

sFlt-1 and sEng were analyzed by commercially available ELISA kits (RampD systems) We

chose to use ELISA kits from RampD for comparison reasons as they were commonly used in

papers on preeclampsia published at the time

73

55 Interpretation of results

Paper 1 and 2

In Paper 1 and Paper 2 we have studied the associations between maternal characteristics

placental weight and fetal growth in healthy pregnant women ie these are studies of normal

physiological relations Together the results from these papers illustrate some of the interplay

between the mother the placenta and the fetus

Paper 1

Paper 1Paper 2

-parity

-BMI

-GWG

-glucose

We found largely the same determinants for both birthweight and intrauterine fetal growth in

third trimester with the exception of fasting glucose (see below) The weight of the placenta

was influenced by similar maternal metabolic and nutritional factors In summary our results

are compatible with the concept that maternal factors can influence fetal growth directly and

indirectly by promoting placental growth

We found a direct effect of maternal factors both on birthweight and intrauterine growth in the

third trimester For both birthweight and intrauterine fetal growth placental weight was an

independent determinant Hence as the placenta grows and becomes larger some of the effect

of maternal factors on fetal growth is likely to be mediated by growth of the placenta

We found independent effects of several maternal factors (parity BMI and GWG) on

intrauterine fetal growth in third trimester We did not find independent effect of age The

small variation in age (SD) might partly explain why we did not find any effect of age

74

Furthermore age has been shown to exhibit an inverse u-shaped relation to birthweight and we

only tested for linear relationships Somewhat surprisingly we did not find an independent

effect of fasting glucose on intrauterine fetal growth in third trimester The discrepancy

between the effect of glucose on birthweight and on intrauterine growth may have several

explanations One possible explanation lies in how fetal growth is assessed Fat accumulation

resulting from increased maternal glucose and subsequent increased insulin secretion in the

fetus is likely to be accumulated on extremities and truncus of the fetus as well as the

abdomen The estimation of fetal size and fetal growth used in our study included assessment

of head circumference abdominal circumference and femur length Of these only abdominal

circumference would be likely to reflect fat deposition We did not however find an

independent association between fasting glucose and change in abdominal circumference

There is no consensus on whether the diagnosis of abnormal growth should be based on EFW

or AC or both [11] Another possible explanation for the described discrepancy could be

found in the concept of conditional growth Conditional fetal growth refers to differences in

expected fetal growth depending on the size estimated at the last measurement As an

example a fetus that is large at week 30 will be expected to grow more in the remaining

weeks of the pregnancy than a fetus that is relatively smaller at week 30 Factors like impaired

glucose metabolism in early pregnancy leading to higher fasting glucose values might have

resulted in a large fetus already at week 30

Placental weight was used as a measure of placental function Introducing placental weight in

the multiple regression models gave two interesting results

First placental weight was an independent determinant of birthweight and fetal growth and

showed a positive effect on fetal growth A small placenta is commonly associated with a

growth restricted fetus hence a reduced placental function Fetalplacental ratio can be used

as an indicator of placental efficiency and includes both fetal weight and placental weight

Preliminary analyses in our material showed that the maternal factors associated with

fetalplacental ratio in the multiple model were maternal age parity and BMI Maternal

gestational weight gain was not significantly associated in the univariate model and hence not

included in the multiple model Fasting glucose was not significant in the multiple model

using fetalplacental ratio as outcome

Secondly placental weight can be viewed as a mediator in the associations between maternal

factors and fetal growth This implies that some of the effect of the maternal factors might

work through growth of the placenta There are several possible biological reasons for the

75

reduced effects of the maternal characteristics on birthweight or intrauterine fetal growth

when placental weight was included in the models The selected maternal characteristics may

exert their effects on fetal growth by affecting transplacental transport Transplacental

transport is affected by blood flow both on maternal and fetal side Furthermore the number

and efficiency of placental transport proteins may also be influenced by maternal factors The

total number of transport proteins is dependent on both the area of the syncytio-endothelial

membrane and the density of the transporting proteins In addition it can not be excluded that

placental production of growth factors may be affected

We have studied both modifiable and non-modifiable maternal factors Parity is a non-

modifiable factor present before pregnancy There is a well-known effect of parity on

birthweight We showed that this effect is evident also for intrauterine growth and placental

weight The effect of parity is relatively larger than many other maternal factors eg larger

than fasting glucose BMI and GWG Modifiable factors include BMI GWG and fasting

glucose BMI and fasting glucose may be modified before pregnancy and GWG and glucose

during pregnancy

The present study did not include data on neither fetal factors that stimulate or inhibit

placental growth function or maternal factors nor placental factors that influence maternal

metabolism Theoretically however there are possible pathways including signals from the

fetus that can stimulate placental growth and possibly placental factors that can influence

maternal metabolism

Taken together the results from Paper 1 and Paper 2 show that maternal factors influence

both placental weight and fetal growth and it is likely that some of the effect on fetal growth is

mediated through placental growth This does not exclude the possibility that an increased

fetal growth following increased maternal energy supply may lead to release of fetal growth

factors that feed back on placental growth

Clinical implications

We have only studied birthweight and intrauterine growth in third trimester which might be

too late to intervene in cases of abnormal fetal growth In order to intervene it is necessary to

know which factors influence intrauterine growth at different gestational ages As both low

76

BMI and low GWG is related to increased risk of IUGR patients with high risk of IUGR

could be advised to increase their BMI or make sure they gain sufficient weight according to

recommendations Similarly as high BMI and high GWG increase fetal growth women could

be advised to obtain a normal BMI prior to getting pregnant and not gain unnecessary weight

during pregnancy As there is a linear and continuous relation between fasting glucose and

adverse fetal outcomes including fetal growth pregnant women with fasting glucose values

just below the GDM criteria can benefit from the same advice concerning diet and physical

activity as GDM-patients receive In particular women with multiple risk factors of impaired

fetal growth should be given advice even if she does not meet the criteria of GDM or obesity

Paper 3

Glucose is the major source of energy for the fetus and the placenta and therefore has an

obvious importance in fetal nutrition Glucose transport across the placenta in humans is

interesting to study for several reasons There is a lack of human in vivo studies in contrast to

the body of evidence on mechanisms and transporter proteins etc from in vitro studies It is of

major importance to acknowledge the distinction between maternal nutrition and fetal

nutrition [2] The placenta is not just a simple conduit for gases nutrients and waste products

but has its own complex metabolism with corresponding requirements for oxygen and

nutrients

In this paper we found a close correlation between maternal and fetal glucose concentrations

which is in line with the concept that the maternal-fetal gradient is the driving force in the

transplacental transport of glucose across the placenta However the fetal v-a glucose

difference was not merely a reflection of the maternal glucose concentration or the

uteroplacental uptake of glucose but rather related to the maternal-fetal gradient and the

concentration in the umbilical artery The relation between maternal and fetal glucose

concentration has been shown in several papers Although the umbilical venous concentration

is closely related to the maternal concentration the fetal v-a difference seemed to be less

related to maternal concentrations but more to the concentration in the umbilical artery fetal

insulin placental weight and birthweight We therefore speculate that the fetus has a saying in

determining the fetal glucose consumption This might at first seem to be in conflict with the

Pedersen hypothesis which was first presented in 1952 [131] His theory was that high

maternal glucose was transferred to the fetus which responds by secreting more insulin

77

which in turn lowers the blood glucose of the newborn Compared to the 1950s pregnant

women of today are older when they get pregnant have higher prepregnancy BMI and gain

more weight in pregnancy The metabolic environment a fetus experiences today is likely to

differ from the environment some decades ago in several aspects more energy-rich altered

balance between glucose and lipids and more inflammation [132] The non-glucose factors

like lipids may have augmented their role as several factors have changed in the population

since the proposal was made by Pedersen We can only speculate as to how the relative

importance of these factors might influence the regulation of transport of nutrients to the

fetus

Our results can not explain or show the complex regulation of glucose transport and

metabolism and leaves us with some unanswered questions We only presented correlation

analyses as we did not yet have enough samples to do multivariate analyses to evaluate the

relative importance of the factors involved We were not able to do path analyses to quantify

the influence of each of these factors Do the relationships we have described work differently

in pathological pregnancies in which there is either abnormal placental function or the mother

exhibits abnormalities in her metabolism or the fetus experiences abnormal growth These

questions can hopefully be answered by future research

The amount of glucose consumed by the placenta can be changed under hypoxic conditions

[63] It is not likely that our participants were hypoxic to a large degree We only measured

oxygen in a few cases which were all normal

Clinical implications

In obstetric practice there are numerous examples of cases of abnormal fetal growth occurring

in pregnancies of healthy mothers with normal metabolism and apparently normal placental

function Placental function might still be compromised resulting in reduced fetal nutrition

Fetal under nutrition may result from compromised transplacental transfer of nutrients In the

other end of the spectrum are the fetuses that experience overgrowth despite strict glycemic

control of their diabetic mothers Some authors argue that this might be due to intermittent

hyperglycemia rather than constant hyperglycemia but another option is that hyperglycemia

is accompanied by other nutrients or other factors that increases the total energy supply to the

fetus

78

Human in vivo studies are rare and therefore valuable in terms of extrapolation to relevant

settings in clinical practice However in vivo settings include multiple factors working

together making it difficult to assess individual effects In vitro settings however can control

for one factor at a time to gain mechanistic knowledge which can hardly be drawn from in

vivo settings The clinical significance of factors operating in vitro is often difficult to assess

Paper 4

The multifactorial etiology and heterogeneous clinical presentations seen in preeclampsia

makes it an intriguing and challenging condition to study Since preeclampsia is a pregnancy

complication in which the placenta is believed to play a crucial role in the pathophysiology it

was both interesting and relevant to choose preeclampsia in order to study aspects of placental

function in pathological pregnancies Furthermore preeclampsia is still a leading cause of

mortality and morbidity worldwide Despite decades of research there is still no causal

treatment leaving timing of delivery the only intervention to balance the needs of the mother

and the fetus

In our study we found as expected that preeclamptic women had higher concentrations of sFlt-

1 and sEng than healthy controls as has been shown in numerous previous publications

Preeclamptic women further had higher concentrations of sFlt-1 in the uterine vein than the

radial artery giving a gradient across the uterus There was no gradient for sEng among

preeclamptic women and no gradients were found in the healthy controls for either of the two

factors tested The gradient across placenta is consistent with the concept that the placenta

secretes sFlt-1 into the maternal circulation The source of excess sFlt-1 and sEng in

preeclamptic patients is assumed to be the placenta based on enhanced expression of both

factors in trophoblastic tissue [133134] Enhanced expression of sFlt-1 and sEng in

trophoblastic tissue does not necessarily prove that the circulating sFlt-1 and sEng found in

preeclamptic patients originate from the placenta or that the placenta is the only source There

is a possibility that sFlt and sEng originate from circulating cells in the maternal circulation or

endothelial cells Peripheral blood mononuclear cells have been suggested to be an additional

extra-placental source of sFlt-1 [134]

Our results support the hypothesis that at least a part of the circulating sFlt-1 originates in the

placenta and is transported into the maternal circulation whereas we did not find evidence to

support that this holds for sEng The discrepancy between our results for sFlt-1 and sEng

could have several explanations

79

There might be a biological difference such that sFlt-1 only or to a larger extent than sEng is

released from the syncytiotrophoblasts in the placenta whereas sEng to a larger extent is

produced elsewhere [135] There might also be a statistical explanation suggesting that we had

inadequate power to show a statistically significant difference in sEng which would represent

a type 1 error (rejecting the hypothesis that there was a difference even if it is true)

In this paper as most studies involving preeclamptic patients and healthy controls there was a

difference in gestational age among cases and controls The difference in gestational age

raises some questions to be discussed There are publications reporting an increase in sFlt-1

and sEng with increasing gestational age both for controls and preeclamptic patients but more

so in preeclampsia [136137] Assuming this relationship for our controls we would expect to

find a lower concentration at week 30 among healthy controls than what we found near term

giving an even greater difference than we observed Thus we do not think that the difference

in gestational age can explain the observed difference in sFlt-1 and sEng between preclamptic

patients and healthy controls We did not include samples from preeclamptic patients at term

as they mostly deliver vaginally Our group of preeclamptic patients thus represents early-

onset preeclampsia In most cases preeclampsia was accompanied by a degree of intrauterine

growth restriction Whether our findings are representative for late onset preeclampsia in

which the placental dysfunction is perhaps less prominent and the endothelial dysfunction

more prominent is not clear from our study

Anti-angiogenic factors in a clinical setting

Anti-angiogenetic factors have been proposed used as diagnostic tools for preeclampsia

There is hope for a therapeutic option in treating preeclampsia in the future but whether

angiogenetic agents can be used to improve the angiogenic imbalance seen in preeclampsia is

not known At the moment the most useful implications of these types of studies is increased

knowledge on the pathogenesis including the possibility to differentiate between early- and

late-onset preeclampsia

80

6 Conclusions

In conclusion results from the first part of this thesis (Paper 1 and 2) underline the importance

of the placenta and placental functions in normal pregnancies Placenta is an important factor

to consider when studying associations between maternal factors and measures of fetal

growth birthweight intrauterine growth or body composition The effect of maternal

metabolic and nutritional factors on fetal growth is likely to go partly through growth of the

placenta There is an important distinction between maternal and fetal nutrition as one has to

consider the placenta as an active organ and not a passive conduit of nutrients and gases

In the second part of this thesis a method has been established that makes it possible to study

placental function in the human in both normal and pathological pregnancies like

preeclampsia

7 Further research

I believe the greatest challenges in the two studies that make up my thesis also reflect the

potentials for further research

In the STORK study we collected large amounts of data on a large group of women

Therefore selecting and analyzing the relevant outcomes and appropriate explanatory

variables was the greatest challenge There are large amounts of data still to be analyzed For

the STORK data my plans for a postdoc is to study in more detail the relations between

maternal metabolism and pregnancy outcomes More specifically to differentiate between

healthy and unhealthy obese pregnant women in metabolic terms and relate this to pregnancy

outcomes including fetal growth

In the STORK-Placenta study establishing the method and achieving the data collection were

the greatest challenges with demanding logistics at any time of the day There are few larger

human in vivo studies of placental nutrient transfer In particular studies of arterio-venous

differences on maternal side of placenta are scarce The main reason this kind of studies are so

limited is that such studies are logistically very requiring To our knowledge we are the only

group employing this procedure The samples obtained by this method give unique

opportunities to study concentration gradients and transplacental transfer of any nutrient

81

across placenta and how endocrine and inflammatory factors may interact with nutrient

transfer The study also includes measurements of maternal and fetal blood flow enabling us

to quantify the amounts of nutrients being transported The study has currently been

expanded to around 100 pregnancies Data collection still goes on aiming to get enough

samples to continue analyzing interesting associations linking maternal metabolism placental

functions and the fetus and extending the data to include cases of pathological pregnancies

like preeclampsia diabetes mellitus and abnormal fetal growth Samples from preeclamptic

women are currently being analyzed for Placental growth factor

The potential for further research lies in combining the data retrieved from the two studies

Ultimately I would like to be able to link preeclampsia and fetal growth in the two studies

82

8 References

Reference List

1 2009) wwwmfr-nesstaruibno Medical birth Registry Norway Available

2 Harding JE (2001) The nutritional basis of the fetal origins of adult disease Int J

Epidemiol 30 15-23

3 Barker DJ Thornburg KL (2013) The obstetric origins of health for a lifetime Clinical

Obstetrics and Gynecology 56 511-519

4 Forsdahl A (1978) Living conditions in childhood and subsequent development of risk

factors for arteriosclerotic heart disease The cardiovascular survey in Finnmark 1974-

75 J Epidemiol Community Health 32 34-37

5 Forsdahl A (1979) Are poor living conditions in childhood and adolescence and

important risk factor for arteriosclerotic heart disease Int J Rehabil Res 2 238-239

6 Barker DJ (2005) The developmental origins of insulin resistance Horm Res 64 Suppl

3 2-7

7 Barker DJ Shiell AW Barker ME Law CM (2000) Growth in utero and blood

pressure levels in the next generation J Hypertens 18 843-846

8 Barker DJ (1997) The long-term outcome of retarded fetal growth Clinical Obstetrics

and Gynecology 40 853-863

9 Gude NM Roberts CT Kalionis B King RG (2004) Growth and function of the

normal human placenta Thromb Res 114 397-407

10 Voldner N (2010) Modifiable determinants of newborn macrosomia and birth

complications [dissertation]

11 Mayer C Joseph KS (2013) Fetal growth a review of terms concepts and issues

relevant to obstetrics Ultrasound Obstet Gynecol 41 136-145

12 Zhang J Merialdi M Platt LD Kramer MS (2010) Defining normal and abnormal

fetal growth promises and challenges Am J Obstet Gynecol 202 522-528

13 Gardosi J Figueras F Clausson B Francis A (2011) The customised growth potential

an international research tool to study the epidemiology of fetal growth Paediatr

Perinat Epidemiol 25 2-10

14 Rohrer F (1921) The index of corpulence as measure of nutritional state Munchener

medizinische Wochenschrift 580-582

15 Catalano PM Thomas AJ Avallone DA Amini SB (1995) Anthropometric estimation

of neonatal body composition Am J Obstet Gynecol 173 1176-1181

16 Godang K Qvigstad E Voldner N Isaksen GA Froslie KF et al (2010) Assessing

body composition in healthy newborn infants reliability of dual-energy x-ray

absorptiometry J Clin Densitom 13 151-160

17 Pay AS Froen JF Staff AC Jacobsson B Gjessing HK (2013) A new population-

based reference curve for symphysis-fundus height Acta Obstet Gynecol Scand 92

925-933

18 Anderson NG Jolley IJ Wells JE (2007) Sonographic estimation of fetal weight

comparison of bias precision and consistency using 12 different formulae Ultrasound

Obstet Gynecol 30 173-179

19 Cetin I Alvino G (2009) Intrauterine growth restriction implications for placental

metabolism and transport A review Placenta 30 Suppl A S77-S82

20 Mei Z Grummer-Strawn LM Pietrobelli A Goulding A Goran MI et al (2002)

Validity of body mass index compared with other body-composition screening indexes

for the assessment of body fatness in children and adolescents Am J Clin Nutr 75

978-985

12

In Paper 1 we studied how maternal factors were associated with birthweight and intrauterine

fetal growth For the reasons indicated above we included placental weight as a determinant

of birthweight and fetal growth

Paper 1

-parity

-BMI

-GWG

-glucose

Given the importance of placental weight on birthweight and fetal growth we then wanted to

study placental weight in Paper 2 We studied the influence of maternal factors on placental

weight and whether these associations differed with fetal sex

Paper 2

-parity

-BMI

-GWG

-glucose

13

In Paper 3 we reported initial studies of transfer of glucose across the human placenta and

how maternal and fetal glucose and insulin levels were related

Paper 3

Glucose and insulin

In Paper 4 the role of placenta in producing pathogenic factors of preeclampsia was

investigated choosing anti-angiogenic factors because of their endothelial-disturbing

properties

Paper 4

Anti-angiogenic

factors

14

12 Background

Fetal growth has implications for the newborn child both in short and long term The link

between events in early life and risk of disease in later life is now a widely recognized field of

research known as developmental programming and often called Developmental Origins of

Health and Disease Developmental programming refers to how an event at a critical or

sensitive period results in a long-term change in the structure or function of the organism

[23] Organs and systems in the human body are sensitive to the environment in certain

periods The critical periods are mainly those characterized by rapid growth and maturation

and for most organs and systems this happens to a large extent in utero

The idea of linking events in early life to later risk of disease is however not new The

association between poor living conditions in childhood and increased risk of cardiovascular

disease was observed by Anders Forsdahl who worked as a physician in Finnmark Northern

Norway in the 1970s He found a positive correlation between infant mortality which was

considered to be an index of standard of living and mortality from arteriosclerotic heart

disease as well as cholesterol values [45]

The link between early life events and later disease received more publicity when the late

David Barker introduced what is commonly referred to as the rdquoBarker hypothesisrdquo He was

probably the most acknowledged scientist in this field and established an association between

birthweight and increased risk of cardiovascular disease insulin resistance and type 2 diabetes

mellitus [6ndash8] His work has been followed by a range of publications that have not only

confirmed these associations but also provided mechanistic insight into the link between

intrauterine growth and increased risk of disease A large body of evidence have shown that

structural or functional changes that last throughout life can result from nutritional factors in

utero [2] Extensive work on animal models has demonstrated how dietary changes affect fetal

growth and lead to functional and structural changes The availability of nutrients to the fetus

is influenced not only by the motherrsquos diet during pregnancy but by maternal nutrient stores

and metabolism The placenta has multiple roles in fetal nutrition by its capacity to transport

nutrients from the maternal to the fetal circulation by its own metabolic demand for nutrients

and by producing hormones which influence fetal and maternal nutritional supply [9]

15

13 Fetal growth

Fetal growth comprises the entire process of differentiation maturation and development that

occurs between conception and birth This process starts with the fusion of two cells and ends

up with an estimated 50-100 trillion cells in the newborn child The terminology used to

describe and evaluate fetal growth is complex and the terms need to be defined First there is

a need to draw a distinction between size at birth and intrauterine growth Secondly the

difference between size which is most commonly measured as weight and body composition

must be addressed

131 Size at birth

Birthweight

Size at birth is routinely measured as birthweight (grams or kg) Birthweight is a summary

measure of fetal growth throughout pregnancy Categories based on birthweight are used both

in clinical settings and for research Low birthweight is generally defined as birthweight

lt 2500 grams whereas a definition for high birthweight (macrosomia) is more arbitrary Both

4000 4200 and 4500 grams have been used as cut-off values in various settings [1011]

Birthweight for gestational age

Birthweight as a function of gestational age gives information of size relative to expected size

for a particular gestational age Birthweight for gestational age can be given as a percentile

between 0 and 100 Birthweight for gestational age can also be categorized and the most

commonly used categories are large for gestational age (LGA) appropriate for gestational age

(AGA) and small for gestational age (SGA) The conventional cut-off percentiles for these

categories are given beneath

Population based charts for birthweight are often based on large samples including both low-

risk and high-risk pregnancies representing the underlying population On the other hand a

so-called standard chart is usually based on low-risk pregnancies with a normal outcome [12]

Furthermore customized charts have been made to accommodate for differences in eg

ethnicity parity age and BMI in individual patients Such charts have been developed for

different populations and there are electronically available charts [13]

16

Body composition

In addition to weight of the newborn baby length and head circumference give some

information about the body composition of the newborn Further evaluation of body

composition can be derived from these measurements The Ponderal Index (PI) is calculated

as a relationship between mass and height as is the body mass index (BMI) but the mass is

normalized with the third power of body height

Because it yields valid results even for very short (and very tall) persons it is more suitable

in pediatrics than BMI [14] Body composition can further be assessed by measuring

circumference of the abdomen and the extremities or by skin fold thickness measurements by

calipers to obtain an estimation of fat distribution [15] There are other methods that are either

expensive or difficult to perform on newborns Dual energy x -ray absorptiometry (DXA)

enables an estimation of bone mass fat mass and fat free (lean) mass A reasonable good

correlation between estimated fat mass by DXA and skin fold thickness measured by calipers

has been shown [16]

Categories Cut-offs

SGA lt 10 p

AGA 10-90 p

LGA gt 90 p

PI

= weight (g)

[height (cm)]3

17

132 Intrauterine growth

Fetal growth is a continuous process that starts at conception and ends at birth but is

commonly measured as just the end result which is size at birth However the distinction

between size and growth applies also to the intrauterine period Fetal size is estimated based

on a single observation or measurement whereas estimation of fetal growth requires at least

two measurements

Symphysis-fundus height

Palpation of the abdomen and measuring the symphysis-fundal height is used to estimate

intrauterine growth in low-risk pregnancies Reference curves for the symphysis-fundus

height to assess fetal growth have recently been updated in Scandinavia [17]

Ultrasound measurements

Estimation of fetal size

Estimation of fetal size by ultrasound combines measurements of the fetus and transforms

these measurements into volume and weight to estimate fetal size There are a number of

equations that use combinations of circumferences andor diameters and combinations of

measurements of head and abdominal size andor femural length to estimate fetal size The

equations differ in their ability to predict fetal size but generally perform more accurately in

predicting average fetal sizes than at the extremes of birthweight [18]

Estimation of fetal growth and fetal growth charts

To estimate fetal growth two or more measurements separated in time are needed and the rate

of growth can be assessed by using fetal growth charts There are a multitude of charts

available that are constructed by different methods and from different populations Fetal

growth charts can be derived from cross-sectional or longitudinal data In cross-sectional

charts each pregnant woman contributes with data from one observation whereas longitudinal

studies have repeated measurements from each participant The longitudinal studies provide

better references for fetal growth [12]

18

The ambiguous terminology

The lack of distinction between fetal size and fetal growth complicates the terminology Small

for gestational age (SGA) is often defined as birthweight lt 10 p The term intrauterine growth

restriction (IUGR) is often used interchangeably with SGA IUGR more strictly is used as a

term for true intrauterine growth restriction based on data that shows a decline in intrauterine

growth over time assessed by ultrasound There are however no universally accepted

definition of how much decline in fetal growth that would define IUGR although some

authors have defined IUGR as either a fall in fetometric percentiles or a combination of fall in

percentiles and low birthweight [19] On the same note accelerated fetal growth can be seen

during intrauterine life and may or may not result in a LGA newborn

Figure 1 Schematic overview of categories of fetal growth

growth

restrictionexcessive

growth

AGASGA LGA

19

14 Maternal aspects of fetal growth

141 Maternal nutritional status

Maternal nutritional status is vital for fetal growth as the fetus is dependent on nutrients being

transported from the maternal circulation across the placenta to the fetal circulation The

nutritional status of the mother is generally assessed by indirect means of which Body Mass

Index is a commonly used measurement

Body Mass Index (BMI)

BMI is calculated from a persons weight and height according to the following equation

BMI is used as a surrogate for body fat and has been shown to correlate to direct measures of

body fat such as underwater weighing and dual energy x-ray absorptiometry (DXA) [20]

Although the correlation between BMI and body fatness is fairly strong the correlation varies

by sex race and age At the same BMI women tend to have more body fat than men At the

same BMI older people tend to have more body fat than younger adults Highly trained

athletes may have a high BMI because of increased muscularity rather than increased body

fatness [21] In pregnancy the correlation between BMI and percent body fat is better in early

gestation than in late gestation [22]

The World Health Organisation (WHO) classifies BMI for adults in the following groups [23]

BMI

weight (kg)

[height (m)]2

BMI Weight Status

Below 185 Underweight

185 ndash 249 Normal

250 ndash 299 Overweight

300 and above Obese

20

For adults BMI is interpreted using standard weight status categories that are the same for all

ages and for both men and women For children and adolescents on the other hand the

interpretation of BMI is both age- and sex-specific [24]

Biological effects of high BMI

BMI is used as a surrogate for body fat which is made up of adipose tissue Adipose tissue can

be classified as white adipose tissue (WAT) and brown adipose tissue WAT is excess energy

stored as triglycerides in adipocytes which secrete a variety of substances including

hormones (eg leptin adiponectin and resistin) as well as inflammatory factors [25] Brown

adipose tissue is thought to have a function in thermo genesis Excess adipose tissue can be

estimated by anthropometric measures such as skin fold thickness measured by calipers [26]

Consequences of BMI for pregnancy and labour

Prepregnancy BMI is a major determinant of pregnancy outcome and increasing BMI is

associated with an increased risk of the majority of pregnancy complications like congenital

abnormalities miscarriages gestational diabetes preeclampsia obstructed labour and

operative deliveries [27] Low prepregnancy BMI is associated with low birthweight and

IUGR [28]

Gestational weight gain (GWG)

Gestational weight gain in pregnancy includes growth of the fetus placenta and uterus

increase in maternal plasma volume and accumulation of maternal fat mass [29] The total

amount of weight gained during pregnancy varies considerably among women and lean

women tend to accumulate more fat than obese women [30] Accumulation of fat is primarily

centrally and represents a combination of subcutaneous fat and visceral fat Visceral fat

correlates with metabolic risk factors like hypertension insulin sensitivity and plasma lipids

[31] The ideal gestational weight gain differs depending on the maternal or neonatal outcome

of interest Recommendations for gestational weight gain were revised by the Institute of

Medicine USA in 2009 and highlights both that women should be within a normal BMI range

when they conceive and gain weight within the ranges recommended The recommended

21

weight gain is based on four categories of prepregnancy BMI Higher categories of

prepregnancy BMI are recommended a lower weight gain [29]

Consequences of gestational weight gain

Gestational weight gain has consequences for both mother and child in the short and long

term Low GWG is associated with low birthweight and IUGR [32] and high GWG is

associated with macrosomia and increased neonatal fat mass [3334] High GWG is

associated with increased risk of pregnancy complications like preeclampsia and diabetes [35]

Restricted GWG in obese women with type 2 diabetes has been shown to influence fetal

growth [36] There are reports on associations between GWG and cesarean section

instrumental deliveries and low Apgar scores but it has been suggested that the effects are

mediated by high birthweight [35] The most consistent adverse outcome for mothers with

large GWG is weight retention post-partum [35]

BMI Weight Status Recommended Gestational

Weight Gain

Below 185 Underweight 13-18 kg

185 ndash 249 Normal 11-16 kg

250 ndash 299 Overweight 7-11 kg

300 and above Obese 5-9 kg

22

142 Maternal metabolism

As the fetus is dependent on nutrients from the maternal circulation not only the maternal

intake of nutrients but also the maternal metabolism plays a major role in fetal nutrition There

are adaptations to maternal metabolism that occur during pregnancy to ensure that the

increasing nutritional demands of the mother the placenta and the fetus are met Adaptations

are made in the metabolism of all major groups of nutrients

Glucose metabolism in pregnancy

The human fetus is highly dependent on glucose derived from the maternal circulation for

growth and development [2] Changes occur in the maternal glucose metabolism during

pregnancy to ensure that the increasing nutritional demands of the mother the placenta and

the fetus are met Previously published data on glucose metabolism suggested a decrease in

fasting glucose with gestation [37] Fasting glucose levels of pregnant women have been

shown to decline in early pregnancy and thereafter not decrease much further [38] In our

cohort we found fasting glucose to increase slightly with gestational age [39] There is an

increase in basal hepatic glucose production by up to 30 with increasing gestational age

[37] The insulin sensitivity shows a marked change in pregnancy Overall insulin sensitivity

decreases during pregnancy and in late pregnancy a reduction of 50-70 is estimated

compared with non-pregnant women [40] Insulin secretion increases by up to 200-250

[40]

Lipid and amino acid metabolism in pregnancy

The lipid metabolism in pregnancy is characterized by a marked hyperlipidemia Triglyceride

concentration increases and in particular very low-density lipoprotein (VLDL) triglyceride

concentration which increases 3-fold from week 14 to term Plasma cholesterol levels rise to

a lesser degree In obese women the hyperlipidemia is further exaggerated [27] There is an

overall increase in protein synthesis in pregnancy This includes maternal tissues like breasts

uterus and the liver as well as the fetus and the placenta [27]

23

143 Other maternal factors

Age and parity

Both maternal age and parity have an effect on fetal growth Young women especially

adolescents give birth to smaller newborns than older women [41] Birthweight increases with

maternal age until the 30s after which there is a decline resulting an inverse u-shaped curve

[42] Age is however closely linked to parity Birthweight increases with parity and the

largest increment of approximately 200 grams is between the first and second child [43] In

multiple models birth order exerted a greater influence on birthweight than maternal age [42]

The biological explanation behind these associations is only partly understood The effect of

parity may be partly explained by the capacity of the spiral arteries to expand which is higher

in the subsequent pregnancies than in the first pregnancy [44]

Maternal blood supply to the uterus

The uterus receives blood mainly from the uterine arteries which are branches of the internal

iliac artery The uterine arteries branch into thinner vessels first the arcuate arteries then the

radial arteries followed by the basal arteries which continue into the endometrium as the

spiral arteries The spiral arteries undergo remodeling in early pregnancy which means they

loose smooth muscle and elastic tissue from their walls This remodeling of maternal vessels

is a key aspect of early pregnancy and vital for a successful outcome Ultrasound studies have

estimated both the changes in diameters of the uterine artery and the blood flow velocity in

these vessels Several studies have reported that the diameter of the uterine artery increases

approximately 3-4 fold from non-pregnant state to term [4546] The flow velocity increases

with gestational age but reported values differ somewhat depending on whether the

measurements are made on one or both uterine arteries and the laterality of the placenta

[4546] The fraction of the cardiac output that is distributed to the uterus has been estimated

to be 35 in early pregnancy and near 12 at term [46]

24

Figure 2 Blood supply to the uterus

From Grayrsquos Anatomy 20th US edition electronically retrieved from Wikimedia commons

25

15 Placental aspects of fetal growth

151 Development structure and growth of the placenta

Normal placental development and maternal adaptation to pregnancy are crucial factors for a

successful pregnancy The placentation process and maternal adaptation are closely linked and

happen as parallel processes ensuring a healthy outcome for both mother and child Many

complications of pregnancy can be ascribed to defects in early placentation andor inadequate

maternal adaptation to pregnancy Therefore knowledge of these processes is essential in

understanding the pathophysiology of pregnancy complications

The development of the placenta begins as soon as the conceptus reaches the uterus on day 3-

4 after fertilisation By this stage the blastocyst has an outer wall and an inner cell mass The

outer wall consists of trophoblast cells which undergo transformation to either fuse into a

syncytial cell layer or form individual cytotrophoblasts Extra villous trophoblasts are named

so because of their location in the maternal endometrial (decidual) tissue and play an

important role by starting the trophoblast invasion and the adaptation of the maternal vessels

to pregnancy During this process the endometrial stromal cells differentiate into decidual

cells The extra villous trophoblasts migrate through the decidua basalis and into the inner

third of the myometrium aided by a range of proteases that degrade or remodel the maternal

extra cellular matrix

The amnion arises from the inner cell mass and makes contact with the chorion by early

second trimester Lacunae are formed within the syncytiotrophoblast and the lacunar system is

transformed into the intervillous space

The majority of the villous mass forms the placenta whereas the remainder of the villous

tissue begins to regress resulting in the chorion This remodeling ensures that rupture of

membranes and delivering of the baby can occur at birth without tearing through the placenta

This remodeling occurs at the same time as the maternal blood flow starts in the periphery of

the developing placenta

26

Figure 3 The structure of placenta

From Grayrsquos Anatomy 20th US edition electronically retrieved from Wikimedia commons

The villous mass is made up of a tree of branching villi The branches are classified according

to caliber position within the villous tree and function and goes from the larger stem villi via

intermediate villi to the thinner and distal terminal villi In a mature normal placenta stem

villi account for 20-25 intermediate villi approximately 25 and terminal villi around 40

of the total villous volume The maternal-fetal exchange takes place primarily at the

terminal villi and to some extent at the intermediate villi [47]

Figure 4 Terminal villi

Illustration by Oslashystein H Horgmo University of Oslo

27

Figure 5 Development of the placenta

Fertilized egg

blastocyst

Trophoblast

Cytotrophoblasts

Syncytiotrophoblasts

Extravillous

Villous

Inner cell mass

Fetus

Amnion

Yolk sac

-Primary villi

-Secondary villi

-Tertiary villi

-mesenchymal villi

-immature intermediate villi

-stem villi

-mature intermediate villi

-terminal villi

Matu

ratio

n

ofvilli

Angiogenesis

Transformation of

spiral arteries

Placental villi

Modified after Bernischke et al Pathology of the Human Placenta 2012

The syncytiotrophoblast layer covers a surface area of 12-14 m2

at term [48] It is covered by

microvilli which increase the surface area by a factor of five- to seven The

syncytiotrophoblast layer is comprised by two membranes the maternal-facing microvillous

membrane (MVM) and the fetal-facing basal membrane (BM) The syncytiotrophoblasts act

as an epithelium and contain high densities of transporter proteins There are transport

proteins for the major groups of nutrients Glucose transport proteins belonging to the GLUT

family transport glucose across the placenta by facilitated diffusion [49] Amino acids are

transported by transporter proteins by an active process [50] Lipids are mainly transported as

free fatty acids (FFA) by simple diffusion or by specific binding proteins [5152] Transporter

proteins for micronutrients and drug transporters involved in the transport of drugs have also

been identified [5354] The syncytiotrophoblast also transport ions and solutes to maintain

membrane potential and cell volume regulation

28

Figure 6 The syncytiothrophoblast cell

Modified by Oslashystein H Horgmo after SLager J Pregnancy 2012

Growth of the placenta

The placenta grows close to linearly throughout pregnancy [5556] Cytotrophoblast cells fuse

continuously to maintain and expand the syncytiotrophoblast layer Little is known regarding

the control of this coordinated sequence of events After around 32 weeks of gestation the

fetal capillaries and syncytiotrophoblast layer come closer as the syncytiotrophoblast becomes

thinner and free of nuclei and most organelles This thinning of the membrane separating the

maternal and fetal circulations aids gaseous exchange and the membrane is known as the

rdquovasculosyncytial membranerdquo [47] The volume of the terminal villi and hence the surface

area increases exponentially throughout pregnancy a process that appears to be dependent on

branching of the villi and angiogenesis [57] Although the villous tree undergoes continuous

growth and differentiation during pregnancy relatively little is known about the regulation of

this process Maternal factors like prepregnancy BMI and GWG have been shown to be

associated with placental growth measured both as placental weight thickness and area [58]

Little is known about fetal factors that may affect placental growth Studies in mice do

however indicate that the fetus itself influences the functional properties of placenta [59]

29

152 Placental functions

The placenta has a range of important functions to ensure a successful pregnancy outcome

including transport of nutrients and gases metabolism and endocrine and protective

functions

Transport of nutrients and gases

a Transport of gases

Oxygen provided by the maternal blood is transferred to the fetal circulation by diffusion

Carbon dioxide and other waste products are removed from the fetus and transported to the

mother by the placenta [9] Chronic exposure during pregnancy to hypoxia as seen at high

altitudes is associated with reduced fetal growth [60] However comparisons of fetal oxygen

extraction between pregnant women at high altitude (3600 m) and sea level (400 m) showed

that the fetus had the ability to adapt and to increase oxygen extraction [60] Studies on

pregnant sheep in vivo showed the O2 consumption per kg of the fetus to be twice that of an

adult and the uteroplacental tissues to consume four-fivefold that of the fetus [61]

b Transport of nutrients

Glucose

Glucose is the primary energy source for the fetus As the fetus to a very limited degree

produces its own glucose the fetus needs to obtain glucose from the maternal circulation

Glucose is transported from the maternal circulation across the syncytiotrophoblasts of the

placenta by facilitated diffusion [49] The syncytiotrophoblast is the main barrier in the human

placenta and is comprised by two cell membranes the maternal-facing microvillous

membrane (MVM) and the fetal-facing basal membrane (BM) The glucose transporters found

in the human placenta belong to the GLUT-family of which there are multiple isoforms The

GLUT 1 is the predominant transport protein in the human placenta at term and is found in

higher concentration on the microvillous membrane than the basal membrane [49] Glucose

transport across the endothelial layer is not well studied

30

The maternal-fetal glucose transfer depends on several factors

Glucose supply Glucose supply is determined by both maternal blood glucose

concentration and blood flow to the placenta

Placental glucose metabolism The placenta not only transfers glucose to the fetus but

consumes considerable amounts of glucose itself Insight into the placental glucose

transfer and metabolism is largely based on data from animal studies in particular on

pregnant sheep Placental glucose consumption is normally very high Estimates

suggest that the placenta consumes about 50 of the glucose extracted from the

maternal circulation [62] Placental glucose metabolism can be altered as a result of

alterations in the supply of other energy-generating substrates like oxygen Hypoxic

conditions has been suggested to increase glucose consumption in the placenta thus

making less glucose available to the fetus [63]

The total surface area of the membranes

Placental glucose transporter density and functions [64]

Maternal-fetal glucose gradient The maternal glucose concentration is higher than the

fetal concentration which creates a maternal-fetal gradient This gradient is thought to

be the driving force for the transfer of glucose from the mother to the fetus The

maternal and fetal glucose concentrations are closely related [65ndash67] The gradient

increases with gestation and so does the placental transport capacity Together this

ensures that placental glucose transfer to the fetus is increased which is needed to meet

the increasing needs of the growing fetus A lower fetal glucose concentration leads to

a larger maternal-fetal glucose concentration gradient which increases transfer of

glucose to the fetus In IUGR fetuses the glucose level is lower which creates a larger

gradient and hence increases the transfer of glucose [66] The regulation of fetal

glucose utilization in humans is only partially understood but has been studied in

more detail in pregnant sheep In sheep the rate of fetal glucose utilization depends on

the interaction between fetal plasma glucose and insulin concentrations and the supply

of glucose to the fetus [61] Fetal glucose uptake seems to be regulated by fetal glucose

concentration rather than maternal supply [68]

Insulin Maternal insulin is not transferred across the placenta The major glucose

transport protein in the human placenta at term is GLUT 1 which does not have

insulin receptors [64] The fetal pancreas develops in the first half of pregnancy and

31

sheep experiments have shown that by mid-gestation measurable insulin is produced

[69] Fetal insulin secretion consists of both basal secretion and glucose-stimulated

secretion Studies on pregnant sheep have revealed that both basal and glucose-

stimulated insulin secretion increases over gestation and responds to changes in fetal

glucose concentration as well as duration and pattern of change Chronic marked

hyperglycemia in sheep gave down-regulation of both glucose-stimulated and basal

insulin secretion whereas pulsatile hyperglycemia increased fetal insulin secretion

[7071] Hypoglycemia has been shown to decrease basal- and glucose-induced insulin

secretion [72] Insulin is an important growth hormone in utero and deficiency of

insulin leads to growth restriction in the fetus Fetal hyperinsulinaemia leads to

increased weight gain particularly in species with a high body fat content at birth like

the humans [73] The mechanism in which insulin stimulates fetal growth is in part

thought to be its anabolic effects on glucose and amino acid metabolism through

increased cellular uptake of glucose that maximizes the transplacental concentration

gradient for glucose and hence increases transport of glucose across the placenta

Lipids

Fatty acids are necessary for the fetus for various purposes as a source of energy as elements

of cellular membranes and for development of tissues and organs Maternal triglycerides (TG)

have been suggested as a more important source of fatty acids than nonsesterified fatty acids

(NEFAs) TG are hydrolyzed by placental lipases (lipoprotein lipase) to free fatty acids which

can diffuse freely across the placenta or be taken up by the placenta via fatty acid transport

proteins [51] Total levels of fatty acids are lower in the fetal than the maternal circulation but

the fatty acid profile is different with higher proportions of long chain polyunsaturated fatty

acids [9]

Amino acids

Fetal plasma amino acid concentrations are higher than maternal concentrations Amino acids

are taken up against a concentration gradient by secondary active transport systems in the

MVM More than 20 amino acid transport systems are expressed in the human placenta [74]

These are categorized as heterodimeric (eg system L) or monomeric (eg system A) Amino

32

acids are required by the fetus for protein synthesis but can also be metabolized by the fetus

[9] Reduced fetal plasma concentration of a number of amino acids have been reported in

studies of IUGR [75]

c Endocrine functions

The placenta metabolizes a number of substances and releases metabolic products into the

maternal andor fetal circulations The placenta thus has endocrine paracrine and autocrine

functions There are numerous hormones that are produced by the placenta in order to

maintain and regulate pregnancy [9]

Estrogen

Estrogens are produced by the syncytiotrophoblasts in large amounts during pregnancy 80-

90 of the the steroids produced in the placenta are secreted into the maternal blood The

fetus is the main source of the precursors used for production of estrogens and they are

produced in the fetal adrenal gland and the fetal liver [76] The estrogens act as specialized

growth hormones for the reproductive organs of the mother [9]

Progesterone

Progesterone is produced by the corpus luteum in the first weeks of pregnancy and later by

the trophoblasts in the placenta The plasma levels increase throughout pregnancy

Progesterone is synthesized largely from maternal plasma low density lipoprotein (LDL)

cholesterol The fetus contributes few or no precursors for progesterone synthesis In normal

pregnancy there is little de novo synthesis of progesterone in the fetus The progesterone

preferentially enter the maternal circulation and very little crosses to the fetus [76]

Progesterone inhibits uterine contractions

Human Chorionic Gonadotropin (HCG)

HCG is a glycoprotein which is structurally similar to Luteinizing Hormone (LH) Follicle

Stimulating Hormone (FSH) and Thyroid Stimulating Hormone (TSH) and is mainly

33

synthesized in the syncytiotrophoblasts HCG enters the maternal circulation at the time of

implantation and is detectable in maternal plasma and urine The concentration peeks at week

8-10 of pregnancy after which it declines The biological function is believed to be

maintenance of the corpus luteum stimulation of fetal testicular testosterone secretion and

stimulation of the maternal thyroid gland [76]

Human Placental Lactogen (HPL)

HPL is a polypeptide which is structurally similar to human growth hormone and human

prolactin It is mainly produced by the syncytiotrophoblasts It is detectable in the maternal

circulation by week 5 and rises steadily and approximately proportional to placental mass

until week 34-36 There is little HPL detectable in maternal urine or in fetal plasma HPL

participates in metabolic processes by stimulating lipolysis HPL thereby functions primarily

to ensure nutrient supply to the fetus by efficient mobilization of maternal tissue stores [76]

34

16 Sexual dimorphism in fetal growth and placental function

There are well-known sex specific differences in fetal growth Birthweight of boys is

generally higher than that of girls Body composition also differs boys being longer and

having larger head circumference than girls whereas girls have higher fat percentage than

boys [16] Fetal-placental weight ratio is greater in boys than in girls indicating a higher

placental efficiency among boys [77] Male fetuses grow faster than girls in utero and one

study reported that the difference was statistically different from week 28 onwards [78] Boys

outnumber girls at birth A study from the Norwegian Birth Registry (MBR) found a ratio of

106 among all births This ratio was higher among births in lower gestational age groups as

high as 248 in 16-19 weeks of gestation [79] Similar findings have been reported in multiple

populations [80] Perinatal mortality is generally higher in boys than in girls and in the study

from MBR of Norway it was approximately 20 higher in boys than girls across the whole

range of gestational age groups [79] Attempts have been made to explain the increased

vulnerability observed in boys by sex specific differences in the developmental environment

including possible differences in placental functions Although there are obvious differences

in fetal growth to my knowledge there are no published data on sex specific differences in

nutrient transport across the placenta However there are reports on sex specific differences

in other aspects of placental function especially related to inflammatory responses and

endocrine functions In pregnancies complicated with maternal asthma there was increased

cytokine production in male placentas compared to female placentas [81] Differences in

cytokine production have been suggested to contribute to the observed increased incidence of

preterm delivery in males [82] Glucocorticoids given as repeated doses have been shown to

reduce fetal growth [83] Data suggest that the male and female fetal-placental unit responds

to cortisol in a differential manner Among pregnant women with asthma there were similar

levels of maternal cortisol but female fetuses responded with a reduction in birthweight

whereas the growth of the male fetuses was normal [84] Data on placental properties from

male and female are generally pooled but significant findings may be lost as male placentas

might have different responses than female placentas The different strategies to cope with

the same maternal environment has been summarized by V Clifton [84] She proposed that

male responses lead to minimal placental adjustment in gene and protein expression and that

the target is to increase or continue growth resulting in a greater risk of adverse outcome

Females on the other hand have multiple adaptations in placental gene and protein expression

and minor reduction in growth resulting in increased survival

35

17 Preeclampsia

Preeclampsia is defined as new onset hypertension (blood pressure gt14090) and proteinuria

(gt03 g per 24 hours) in the second half of pregnancy [85] This pregnancy complication

affects between 3 to 5 of all pregnancies depending on the population Preeclampsia is a

leading cause of mortality and morbidity for both mother and child worldwide particularly in

the developing world Worldwide preeclampsia accounts for more than 50 000 maternal

deaths annually [86] Risk factors include genetic factors multiple pregnancies high maternal

age obesity insulin resistance preexisting hypertension diabetes mellitus and renal disease

[87] Around 70 of cases of preeclampsia occur after 37 weeks of gestation [88]

Clinical picture

The symptoms of preeclampsia are diverse reflecting the underlying syndrome The systemic

vascular involvement is reflected not only in hypertension and proteinuria but can likewise

affect the vasculature in other organs like the liver and the brain When the liver is involved

symptoms and signs include abdominal pain nausea vomiting and elevated liver enzymes In

the case of HELLP (hemolysis elevated liver enzymes and low platelets) all these are present

along with the disturbances in the coagulation system In case of brain involvement visual

disturbances and eclampsia can occur Cerebrovascular complications like stroke and cerebral

hemorrhage are other feared maternal complications The fetus of preeclamptic pregnancies

faces increased risk of oligohydramnios IUGR and prematurity [89]

Classification

Preeclampsia has both a multifactorial pathogenesis and a heterogeneous clinical presentation

which complicates classification Classifications in use are according to pathophysiological

characteristics clinical severity presence of other maternal or fetal characteristics or

gestational age at presentation Classification based on pathogenesis suggests two broad types

of preeclampsia placental and maternal preeclampsia reflecting which element is more

prominent in the pathophysiology These subtypes are more of a theoretical framework than

different biological entities as most cases will rather be represented by a combination of both

The dichotomized pathophysiological classification can briefly be described as placental

preeclampsia when there is an abnormal placentation but basically a normal maternal

36

endothelium and maternal preeclampsia when the maternal endothelium is dysfunctional and

the placentation normal Classification according to severity of disease is used by American

College of Obstetrics and Gynecology (ACOG) Severe preeclampsia is defined as

hypertension (gt160110) and proteinuria (gt5 g per 24 hours or +3 on dipstick) or

accompanying symptoms and signs like oliguria cerebral disturbances impaired liver

function thrombocytopenia or fetal growth restriction [85] Early onset preeclampsia is often

defined as presentation before 34 weeks and late onset as after 34 weeks of gestation These

subtypes have different clinical presentations with the early-onset typically exhibiting more

serious clinical featuressymptoms and fetal growth restriction than the late onset [90]

Pathophysiology

Clinical symptoms of preeclampsia arise in the second half of pregnancy which can be

considered the last stage in the development of the disorder The preceding stages include the

placentation process which involves an immunologically regulated interaction between the

placenta and the maternal endothelium Placenta is necessary for the development of

preeclampsia but preeclampsia can occur without a fetus as in hydatidiform mole The

symptoms disappear after delivery of the placenta In preeclampsia the trophoblast invasion is

restricted to the decidua and does not reach the inner third of the myometrium resulting in

inadequate remodeling of spiral arteries The normal loss of smooth muscle and enlargement

of the spiral arteries is therefore restricted

Normal placentation further requires immune tolerance for fetal and placental antigen which

might be altered in preeclampsia There is a low-grade systemic inflammatory response

present in normal pregnancy which is enhanced in preeclampsia [91] The maternal

endothelium becomes activated and eventually dysfunctional Preexisting maternal vascular

dysfunction might render the maternal endothelium more sensitive to the burden of these

factors leading to endothelial dysfunction

Disturbed endothelial maintenance

In patients with preeclampsia there is an angiogenic imbalance in the circulation resulting in

more anti-angiogenic than angiogenic factors ie more of endothelium-disturbing and less

endothelium-supportive factors The vascular endothelial growth factors (VEGF-family) are

37

involved in angiogenesis and endothelial maintenance by affecting migration and

differentiation of endothelial cells [92] The family consists of several glycoproteins

including VEGF-A and PlGF among others Both of these have pro-angiogenic effect The

VEGF receptors are present on vascular endothelial cells and include VEGFR-1 (Flt-1) and

VEGFR-2 (KDR) VEGF binds to both receptors whereas PlGF binds exclusively to VEGFR-

1 (Flt-1)

Figure 7 Angiogenic imbalance

sFlt-1

sFlt-1 is a soluble form of the VEGFR-1 produced by alternative splicing [93] Placentas from

preeclamptic pregnancies show higher expression of sFlt-1 mRNA than normal placentas [94]

How much placenta actually contributes to the circulating sFlt-1 is however not settled sFlt-1

binds free VEGF and free PlGF and thereby inhibits their beneficial actions on the vascular

endothelium sFlt-1 increases with gestational age in normal pregnancy but is significantly

higher in women destined to develop preeclampsia from approximately week 26 and peaks

around week 34 [95]

38

sEndoglin

The transforming growth factor-β (TGF- β) family of proteins is known to be involved in

angiogenesis but has diverse actions in many cells Endoglin is a TGF-β coreceptor expressed

in endothelial cells and syncytiotrophoblasts of the placenta [87] A soluble form of endoglin

(sEng) is present in sera from preeclamptic patients There is a three- five- and tenfold

increase in sEng in mild PE severe PE and HELLP syndrome respectively [96] Endoglin

mRNA expression in placentas from preeclamptic pregnancies is fourfold increased compared

to healthy pregnancies [96] But again the placental contribution to circulating sEng is

unclear sEng increases with gestational age but in women destined to develop preeclampsia

the increase is significantly higher than healthy controls from week 23 (preterm PE) and week

30 (term PE) Interestingly women destined to deliver a SGA infant had increased sEng

levels from week 10 [95]

sEng and sFlt-1 given together increased capillary permeability in the lungs liver and kidney

of mice and induced hypertension in pregnant rats [96] demonstrating a possible combined

action of sFlt-1 and sEng in the pathogenesis of PE

PlGF

Placental growth factor is one of the members of the VEGF-family which has proangiogenic

activity [92] In non-pregnant women circulating levels are low but PlGF can be produced by

the heart and lungs skeletal muscle and adipose tissue PlGF is expressed by the placenta in

particular the syncytiotrophoblasts [97] In pregnancies complicated by preeclampsia PlGF

concentrations are lower than normal pregnancies [98] In normal pregnancy PlGF can be

detected from first trimester and increases until around week 33 after which it declines

towards term PlGF binds to the VEGFR-1 (Flt-1) receptor PlGF is necessary to stimulate

angiogenesis eg after myocardial injury The function of PlGF in pregnancy is not clear but

might be to regulate maternal vascular function by displacing VEGF from the Flt-1 receptor

so that it binds to the more active Flt-2 receptor (KDR) [87]

39

Figure 8 Endothelial integrity and dysfunction

VEGF

PlGF

Flt1

(VEGFR-1)

VEGF

PlGF

Endothelial integrity

Tore Henriksen 2006

VEGF

PlGF

Flt1

(VEGFR-1)

VEGF

PlGF

Endothelial dysfunction

Tore Henriksen 2005

Treatment

There is no causal treatment besides delivery of the baby and the placenta Symptomatic

antihypertensive treatment should be given to reduce maternal complications [85]

Preeclampsia can be complicated by eclampsia stroke disseminated intravascular coagulation

(DIC) HELLP placental abruption and acute renal failure Because the only treatment is

delivery preeclampsia leads to prematurity and increased risk of perinatal mortality and

morbidity

Prevention

40

Studies assessing interventions to reduce rate or severity of preeclampsia have been

conducted There is insufficient evidence to recommend rest reduced salt intake fish-oil

supplementation and antioxidant vitamins as preventive measurements [99] A Cochrane

review concluded that low-dose aspirin had small to moderate benefits (15 risk reduction)

when used for prevention of preeclampsia but that more information is needed to assess

which women are most likely to benefit when to start treatment and at what dose [100]

Calcium supplementation reduced risk of preeclampsia and can be considered for high risk

groups in low-intake populations [101]

Prediction

Many features of preeclampsia are exaggerated responses also present in normal pregnancies

In terms of diagnosis or prediction it is difficult to draw a clear distinction between normal

and abnormal No test predictive or diagnostic can be expected to distinguish absolutely

between different degrees of features that are common to all pregnancies Many tests have

been assessed as potential predictors of preeclampsia but no single test has yet met the

clinical standards for a predictive test Combinations of tests such as ultrasound assessment of

uterine artery Doppler waveforms and serum markers have been suggested as have ratios of

antiangiogenic and proangiogenic factors However sensitivity and specificity of the markers

PlGF sFlt-1 and sEng are too poor for accurate identification of preeclampsia in clinical

practice and hence not recommended used alone for the prediction of preeclampsia [102]

Predictive tests could ideally either identify those destined to develop preeclampsia during

pregnancy or differentiate between a serious or mild form among those diagnosed with

preeclampsia The latter would be of clinical importance in handling these patients

Long-term complications

Risk of recurrent preeclampsia depends on severity and onset of preeclampsia in the previous

pregnancy but can be up to 40 for severe disease [103] Women with a history of

preeclampsia have an elevated risk of cardiovascular disease later in life According to a

meta-analysis the risk of hypertension is 3-4 times the risk for women without preeclampsia

41

and the risk of death from cardiovascular and cerebrovascular disease about twice as high as

in women without preeclampsia [104] The mechanisms for the increased risk are not yet fully

understood but shared risk factors for preeclampsia and cardiovascular disease may jointly

predispose [105] This could be the case for chronic hypertension diabetes mellitus and renal

disease

42

2 Aims of the study

Overall aim

The overall aim of this thesis was to gain insight into the associations between maternal

nutritional and metabolic factors and fetal growth and aspects of placental function in normal

and preeclamptic pregnancies

Specific aims

Paper 1

The aims were to

1) Estimate and compare the effects of maternal characteristics on birthweight and on fetal

growth in third trimester

2) Introduce placental weight as a possible determinant of birthweight and of fetal growth in

third trimester

We hypothesized that maternal factors and placental size were associated with birthweight

and fetal growth

Paper 2

Given the findings in Paper 1 the aim was to study the effects of maternal factors (parity

BMI gestational weight gain and fasting glucose) on placental weight stratified by fetal sex

We hypothesized that the maternal factors mentioned above affected placental weight Based

on emerging evidence we also hypothesized that there were differential effects between fetal

sexes

Paper 3

Based on the observations in Paper 1 and 2 the aims were to

1) Establish an in vivo model in the human

2) To use the model to study human placental transfer of glucose in vivo to describe the

glucose and insulin concentrations in the uteroplacental and umbilical circulation in healthy

43

pregnancies at term and to explore the relation between maternal and fetal glucose

concentrations

We hypothesized that maternal plasma glucose was the major determinant of the fetal venous-

arterial gradient

Paper 4

Preeclampsia is a pregnancy specific placenta dependent disorder Preeclampsia has two

prominent features maternal vascular dysfunction and placental insufficiency Using the in

vivo model the aim was to investigate factors that may link placental disturbance to maternal

vascular dysfunction For this purpose sFlt-1 and sEng were chosen

We hypothesized that both sFlt-1 and sEng originate in placenta by finding that the plasma

concentration was higher in the maternal venous than the arterial side of the uteroplacental

circulation

44

3 Materials and methods

This thesis consists of four papers based on two separate studies that differ in design

population and methodological issues and will therefore be described separately

The STORK study

The STORK study is a prospective longitudinal study performed in the period 2001-2008 A

total of 1031 healthy pregnant women who gave birth at Oslo University Hospital

Rikshospitalet Norway and their newborn infants were included in the study Inclusion

criteria were healthy women of Scandinavian heritage with singleton pregnancies Exclusion

criteria were multiple pregnancies known pregestational diabetes and any severe chronic

diseases (lung cardiac gastrointestinal or renal) as well as any malformations discovered at

the routine ultrasound examination at week 17-19

Population

Eligible women were identified by one of the three PhD candidates in the project Invitation to

participate was sent to eligible women as they were registered for obstetric care at the

beginning of pregnancy Those interested in participating confirmed by phone to a secretary

who enrolled them in the study The number of women invited to participate varied over time

due to capacity The capacity for the oral glucose tolerance test (OGTT) was the ldquorate-limiting

steprdquo The drop-out rate was very low 33 of those who were included Thirty-two women

were excluded because of twin pregnancies or malformations that were diagnosed at the

routine ultrasound scan

45

Figure 9 Flow chart showing inclusion of participants in the STORK study

Withdrawn before

inclusion

n=141

Excluded

n=32

Lost

n=37

Invited to participate

n=4122

Accepted invitation

n=1241

Included

n=1100

Followed up

n=1031

Study design

The STORK study has a longitudinal design Each pregnant woman had four antenatal visits

(visit 1-4) scheduled at weeks 14-16 22-24 30-32 and 36-38 of pregnancy The newborns

were examined shortly after birth

Data collection

Clinical data

Background data was collected at the first visit including past medical and obstetric history

Clinical examination was repeated at every visit Data on the delivery and postpartum period

were extracted from hospital records

Blood samples

Blood samples were drawn at each visit between 0730 and 0830 after an overnight fast

centrifuged and stored at -80ordm C immediately Plasma glucose was measured by Accucheck

(Roche Diagnostics Mannheim Germany)

46

Birthweight

Newborns were weighed on a calibrated scale and measured by the attending midwife or

childrenrsquos nurse within two hours after birth

Ultrasound

Ultrasound examinations were done at visit 2 - visit 4 using an Acuson Aspen machine

(Acuson Mountain View CA USA) Biometric measurements included head circumference

(HC) abdominal circumference (AC) and femur length (FL) Each measurement was made

three times and the mean value was calculated and used in the analyses Estimated fetal

weight (EFW) was calculated by Combs formula [106] Percentiles for estimated fetal weight

and the individual biometric measurements were calculated according to Norwegian charts

[107108] Fetal growth in the third trimester was calculated as the difference between

measurements made at visit 3 and visit 4 for EFW and HC AC or FL respectively

Table 1 Data collection in the STORK study

Statistical analysis

Descriptive statistics were used to characterize the study population Bivariate associations

were explored by scatter plots and correlation analyses Univariate linear regression was used

to study the associations between selected maternal characteristics and the dependent

variablesoutcome variables birthweight and several fetal growth parameters in Paper 1 and

placental weight in Paper 2 Variables with a p-value lt 01 were considered in the multiple

linear regression models Multiple linear regression models were used to study the

Visit 1

14-16 w

Visit 2

22-24 w

Visit 3

30-32 w

Visit 4

36-38 w

At birth

Clinical examination + + + + +

Anthropometric measures

(skin fold thickness)

+ + + + +

Fasting blood samples + + + +

Oral glucose tolerance test + +

Ultrasound

(evaluation of fetal growth)

+ + +

Diet questionnaire + +

Physical activity questionnaire + +

47

associations between selected maternal characteristics and the outcome variables birthweight

fetal growth and placental weight A p-value lt 05 was considered statistically significant

All analyses were done by SPSS 180

Ethical aspects

All participants signed a written consent The study was approved by The Regional

Committee for Ethics South Norway (S- 01191)

48

The STORK-Placenta study

Study design

The STORK-Placenta study was designed to serve several purposes One purpose was to

study placental aspects of fetal growth and this was done as a cross-sectional study among

healthy pregnant women Secondly the study served as a case-control study with two groups

one consisting of preeclamptic patients and one with healthy controls

Population

There are two subgroups of the STORK-Placenta study in Paper 3 and Paper 4 respectively

In Paper 3 we included 40 women Inclusion criteria were healthy non-smoking women with

uncomplicated singleton pregnancy who were scheduled for elective caesarean section

Exclusion criteria were pre-existing co-morbidity any medication and pregnancy

complications like preeclampsia or insulin-dependent gestational diabetes Women who

arrived at the delivery ward with contractions prior to scheduled caesarean section were

excluded The recruitment was done at the out-patient clinic either during the appointment

when caesarean section was decided or during scheduled preoperational information

In paper 4 we included 12 patients with preeclampsia and 7 healthy pregnant women

Inclusion criteria for the study group were the diagnosis of preeclampsia and indication for

caesarean section prior to labour The control group consisted of healthy pregnant women

scheduled for elective caesarean section

Data collection

Medical and obstetrical history was taken at inclusion Clinical data was collected at inclusion

and at the day of delivery

Blood sampling

Blood samples were drawn from both the maternal and the umbilical (fetal) circulation during

caesarean section in spinal anaesthesia Fasting maternal blood samples were obtained by the

obstetrician from the uterine vein preferable on the same side as placenta just before uterine

49

incision Simultaneously blood was drawn by the anaesthesiologist from an arterial line in the

radial artery We assumed similar blood composition in the radial and the uterine artery In

addition blood was drawn from a venous catheter in the cubital vein or dorsal vein network of

the hand Directly after delivery blood samples were obtained from the umbilical artery and

vein immediately after cord clamping Blood was drawn into SAFETY Blood Collection Set

with Luer Adapter (Vaccuette Geiner Bio-One GmbH Austria) Blood samples were

immediately transferred to ethylenediaminetetraacetic acid (EDTA) vacutainers and stored on

ice until all samples were obtained They were then centrifuged at 4-6ordmC 2500 G for 20

minutes before the supernatants were removed and aliquotted and stored at -80ordmC until

analyses were performed

Analyses of samples

Glucose and insulin

Analyses were performed according to standard laboratory methods (Department of Medical

Biochemistry Oslo University Hospital Rikshospitalet) during three consecutive days

Glucose was measured using the hexokinaseglucose-6-phosphate dehydrogenase method

(Roche) Insulin was analysed using the Elecsys insulin analysis which is an enzyme-linked

immunosorbant assay (ELISA) technique with two monoclonal antibodies (Roche)

sFlt-1 and sEng

The concentrations of sFlt-1 and sEng were measured by commercially available ELISA kits

(RampD Systems Minneapolis MN USA) Assays were conducted in duplicate and in one run

The coefficients of variance were lt 10

50

Statistical analyses

Descriptive data were reported as mean values with standard deviations (SD) or percentages

as appropriate The differences in maternal characteristics between groups were compared by

unpaired t-test (Paper 4)

Glucose values were reported as mean values (SD) Comparisons between concentrations of

glucose in maternal and fetal vessels respectively were performed by paired t-tests Due to

skewed distributions insulin concentrations were reported as median values with inter quartile

ranges (IQR) and comparisons of related samples were performed by Wilcoxon sign rank test

Correlations were reported as Pearsonrsquos correlation coefficient if one variable was normally

distributed whereas Spearmanrsquos rank correlation coefficient was used in the case of

correlation between two skewed variables

The distribution of the concentrations for sFlt-1 and sEng were not normally distributed

hence they were log transformed to obtain normal distribution in order to use parametric

methods for statistical analyses Arithmetic median levels are reported in the text and figures

The differences in concentrations between groups were compared by unpaired t-test and the

concentrations in the radial artery and uterine vein from the same individual were compared

by paired t-test However non-parametric tests on the original data gave the same results

Ethical aspects

All participants signed a written consent The study was approved by The Regional

Committee for Medical Research Ethics South Norway (S-071742011-2419)

51

4 Summary of results

Paper 1

In Paper 1 we analyzed the associations between selected maternal characteristics and

birthweight measured as z-scores adjusted for gestational age and fetal sex We found that the

following maternal characteristics were independent determinants of birthweight and

statistically significant in the multiple regression model

Parity (B 046 95 CI 033-059 plt0001)

BMI (B 0048 95 CI 003-006 plt0001)

Gestational weight gain (B 006 95 CI 004-008 plt0001)

Fasting glucose (B 033 95 CI 018-048 plt0001)

In addition placental weight was a determinant for birthweight

Placental weight (B 041 95 CI 038-044 plt0001)

Adjusting for placental weight in the multiple model left the following maternal determinants

statistically significant

Parity (B 036 95 CI 025-047 plt0001)

BMI (B 0018 95 CI 0004-003 p= 0012)

Gestational weight gain (B 0036 95 CI 002-005 plt0001)

Fasting plasma glucose (B 022 95 CI 0009-034 plt0001)

Introducing placental weight as a covariate reduced the effect estimate of the other variables

in the model by 62 for BMI 40 for weight gain 33 for glucose and 22 for parity

The magnitude of reduction was estimated by change in the regression coefficient B of the

linear regression

Fetal growth in third trimester was estimated as the difference in EFW percentiles between

visit 3 and visit 4

In the multiple model the following maternal determinants remained statistically significant

Parity (B 473 95 CI 016-807 p=0006)

BMI (B 064 95 CI 023-106 p=0002)

Gestational weight gain (B 070 95 CI 024-116 p=0003)

52

In addition placental weight was a determinant for intrauterine growth

Placental weight (B 260 95 CI 16-36 plt0001)

Adjusting for placental weight in the multiple model left the following determinants

significant

Parity (B 39 95 CI 075-70 p=0015)

BMI (B 049 95 CI 008-089 p=002)

Gestational weight gain (B 060 95 CI 015-106 p=001)

Introducing placental weight reduced the effect of BMI on intrauterine fetal growth by 23

weight gain by 17 and parity by 14

We also analyzed the associations between maternal factors and the individual biometric

measurements Results from the multiple analyses for the increase in abdominal

circumference showed statistically significant associations for

Parity (B 018 95 CI 007-029 p=0001)

BMI (B 0022 95 CI 0005-003 p=0002)

Gestational weight gain (B 0026 95 CI 0008-004 p=0001)

Fasting glucose (B 044 95 CI -008-017 p=048)

In addition placental weight was a determinant for increase in abdominal circumference

Placental weight (B 011 95 CI 008-014 plt0001)

In the multiple model adjusting for all listed variables and placental weight fasting plasma

glucose was not significant (B 0016 95 CI -011-014 p=08) BMI reached borderline

significance (B 0014 95 CI 000-0028 p=0048) as an independent determinant when

adjusted for parity weight gain and placental weight For growth of the fetal abdominal

circumference BMI showed the largest reduction in B (36 ) when placental weight was

included

53

Paper 2

Given the importance of placental weight for birthweight and fetal growth we studied the

associations between maternal factors and placental weight in Paper 2 Mean placental weight

was 711 g (SD 156)

In the multiple regression model the following maternal factors were independent

determinants of placental weight

Parity (B 292 95 CI 101-484 p=0003)

BMI (B 67 95 CI 41-93 plt0001)

Gestational weight gain (B 56 95 CI 28-84 plt0001)

Fasting glucose (B 329 95 CI 100-557 p=0005)

Boys were heavier (3667 g vs 3494 plt0001) and longer (513 cm vs 503 cm plt0001)

than girls Boys also had a higher fetal placental ratio than girls (526 g vs 508 plt0001)

When stratified by fetal sex fasting glucose was significantly associated with placental

weight in females but not in males

Paper 3

We measured glucose and insulin concentrations in the uteroplacental and umbilical

circulations and calculated arterio-venous gradients The subjects were 40 healthy women

with a mean age of 36 years (SD 32) Mean birthweight was 3571 (SD 527) g range 2680-

4955g

The highest concentration of glucose was found in the maternal arterial circulation with a

mean concentration of 471 mmoll (SD 048) The uterine vein had a lower concentration

giving an arterio-venous difference of 029 mmoll on the maternal side The maternal

concentration of glucose was higher than the fetal concentration The maternal-fetal gradient

was 122 mmoll (SD 042) The concentration in the umbilical vein was 384 mmoll (SD

041) In the umbilical artery the concentration was lower 348 mmoll (SD 045) giving a

fetal venous-arterial difference of 038 (SD 031)

54

Maternal arterial and fetal venous concentrations of glucose were highly correlated (r=086

plt0001) Maternal arterial glucose concentration was not significantly correlated to the fetal

glucose v-a difference (r=03 p=007) The maternal a-v glucose difference was neither

correlated to the level of glucose in the umbilical vein nor the fetal glucose difference The

maternal-fetal gradient was highly correlated to the fetal glucose difference (r=08 plt0001)

The maternal-fetal glucose gradient was also correlated to the glucose concentration in the

umbilical artery (r=-038 p=0017) whereas it was not correlated to the glucose concentration

in the umbilical vein Similarly the fetal glucose v-a difference was only correlated with the

glucose concentration in the umbilical artery (r=-045 p=0004) but not with the glucose

concentration in the umbilical vein

The glucose concentration in the umbilical vein was not correlated to birthweight or placental

weight whereas correlation between the fetal glucose v-a difference and birthweight just

reached borderline significance (r=032 p=0049)

We found no relation between maternal and fetal insulin values (rho=-01 p=057) Maternal

and fetal concentrations of insulin were not statistically different On the maternal side

glucose and insulin concentrations were correlated (r=052 p=0001) On the fetal side

however no such correlation was found (r=012 p=048) Fetal insulin was correlated to both

placental weight (r=046 p=0003) and birthweight (r=058 plt0001)

Paper 4

We measured the anti-angiogenic factors sFlt-1 and sEng in a group of preeclamptic patients

and in healthy controls Both factors have been suggested to be released by the placenta and

involved in the pathogenesis of preeclampsia

Preeclamptic women had

Higher concentration of sFlt-1 than healthy controls (median of 17450 pgml of sFlt-1

compared to 5055 pgml in the control group p= 0003)

Higher concentration of sEng than healthy controls (median of 687 ngml in the

preeclampsia group versus a median of 287 ngml in the control group p= 0003)

55

We compared the concentration in the blood entering the uteroplacental unit (radial artery as a

proxy for uterine artery) and the blood leaving the uteroplacental unit (uterine vein)

Preeclamptic women had

Higher concentration of sFlt-1 in the uterine vein than in the radial artery (22450 vs

17450 pgml p=0005) whereas the concentration of sEng was not statistically different

(757 vs 687 ngml p=012)

Among healthy controls

No significant differences in the concentration between the uterine vein and the radial

artery for sFlt-1 (6193 vs 5055 pgml p=039)

No significant differences in the concentration between the uterine vein and the radial

artery for sEng (307 vs 287 ngml p=059)

56

5 Discussion

51 Methodological issues STORK

511 Design

The STORK study has a longitudinal design with four antenatal visits and observations at

birth for the 1031 women and children included Longitudinal studies are well suited to study

associations between explanatory variables and outcomes but not suitable to assess causality

The associations found in our study would need to be tested in a RCT or experimental model

to assess causality

512 Validity

The word valid is derived from the Latin validus meaning strong Validity in terms of

research refers to whether the results obtained answer the questions asked in the study

Validity can further be divided into internal and external validity [109]

Internal validity

Internal validity refers to whether the conclusions reached are likely to be correct for the

circumstances of that particular study Bias undermines the internal validity and includes

selection bias information bias and confounding bias [110]

Selection bias

Selection bias can result when the selection of subjects into a study (subject selection bias) or

their likelihood of being retained in the study (loss to follow up bias) leads to a result that is

different from what you would have obtained if you had enrolled the entire target population

[110]

57

Subject selection bias

In the current study invitation to participate was sent to 4122 and 1241 accepted the invitation

The number of invitations sent per week varied according to the capacity to enroll in the study

and the limiting factor was four Oral Glucose Tolerance Tests per day There were periods of

reduced capacity like holidays when fewer invitations were sent but it is not likely that the

women invited would be any different to the ones not invited due to varying capacity

The self-selection procedure (the women themselves phoned to be enrolled) might have

resulted in selection of women that were particularly motivated to participate The opportunity

to get closer follow-up than standard antenatal care may have caused selection bias Three

evaluations of fetal well-being and fetal growth by ultrasound could theoretically have

attracted women with a previous history of fetal growth abnormalities Data on birthweight of

previous children revealed that for those who had one previous child average birthweight was

3655 g (SD599) whereas the second child on average weighed 3808 g (SD 706) The data was

normally distributed with no overrepresentation of SGA or LGA (data not shown) Thus there

was no obvious selection of women with a history of fetal growth abnormalities in our study

population

Loss to follow up bias

The number of patients lost was 37 giving a drop-out rate of only 33 The number of

patients excluded was 32 The numbers lost are small and not likely to have influenced the

results substantially All participants had birthweight and placental weight recorded

However the outcome intrauterine fetal growth could only be estimated for those who

attended both third and fourth visit 918 in total Those who gave birth prematurely (54)

were not included in this outcome Maternal characteristics were not different in this group

compared to the total group (data not shown)

The selection bias only influences the results if the women selected or lost differ in either their

characteristics or in the outcomes which does not seem to be the case in our study

Information Bias

Information bias arises if the information has not been gathered in the same way for all

participants It includes observational bias misclassification and measurement errors and can

58

occur during collection of data as well as coding and processing of the data Misclassification

includes classifying binary or discrete variables incorrectly We minimized misclassification

by using mostly continuous variables rather than categorical variables Bias might be

introduced by the observer (interviewer bias biased follow-up) by the study participants

(recall bias) or by measurement tools such as questionnaires or instruments

We might have introduced biased follow-up for at least one group of women The women

diagnosed with gestational diabetes mellitus at visit 3 were taught and encouraged to make

changes in diet and physical activity to prevent further deterioration in their glucose

metabolism This might have had an influence by reducing the outcomes birthweight and

intrauterine fetal growth in third trimester

Recall bias occurs when there are systematic differences in the way subjects remember or

report exposures or outcomes We tried to avoid recall bias by eg using measured weight and

height to calculate BMI instead of self-reported prepregnancy BMI Reviewing available data

on the relationship between self-reported and directly measured height and weight has shown

trends of under-reporting for weight and BMI and over-reporting for height [111]

Measurement errors will be discussed under data collection below

Confounding bias

A confounder is defined in epidemiological terms as a covariate that influence both the

independent and the dependent variable and can be controlled for by adding it to a multiple

regression model Confounders must be identified and then appropriately adjusted for in the

analyses [112] The statistical considerations around confounding will be discussed under

statistical issues in the discussion below

In Randomized Controlled Trials (RCT) confounding is avoided by randomly assigned groups

that differ only in the factor being studied and thereby removes the need to statistically control

for confounders In an observational study like STORK we tried to reduce the need for

adjusting for confounding factors related to comorbidities by selecting healthy women and to

avoid ethnic factors by selecting women of Scandinavian heritage

59

External validityRepresentativity

External validity or representativity refers to whether the results obtained in one study can be

generalized to other situations and to other populations [110]

To assess representativity we did two comparisons Our cohort was compared to a group of

women who delivered at Ullevaringl the largest obstetric unit in Oslo The comparison was

restricted to women of Scandinavian heritage and our cohort only differed in having fewer

smokers and single mothers (data not published)

We also compared our cohort to data from the Birth Registry of Norway Our study

population was comparable to women who gave birth in Oslo in 2009 on parameters like

maternal age parity gestational age (GA) at birth and birthweight (BW)

Figure 10 Comparison between STORK cohort and Oslo

0

10

20

30

40

50

60

Age P0 GA BW

STORK

OSLO 2009

Retrieved electronically from the Birth Registry of Norway [1]

60

513 Statistical issues

Longitudinal data

Analyzing longitudinal data with variables that are correlated over time is a statistical

challenge which can be solved by the use of mixed models However these methods are

complicated and require statistical knowledge that was not readily available to our group We

therefore chose our variables to be able to use conventional linear regression models Fetal

growth was defined as growth between visit 3 and visit 4 thereby confining fetal growth to

the third trimester The whole trajectory of fetal growth was thereby not fully explored

Similarly we only used fasting glucose concentrations at one time point as a covariate in the

multiple models instead of the change in glucose levels over time

Continuous versus categorical variables

We have chosen to use mostly continuous variables both as outcome and explanatory

variables instead of dichotomizing or creating groups This is based on both methodological

theory and published data on physiology in pregnancy Dichotomizing leads to several

problems [113] According to Altman much information is lost the statistical power is

reduced one may underestimate variation and non-linearity in the relation between variable

and outcome may be concealed [114] A large study of hyperglycemia in pregnancy (HAPO)

has shown that there is a linear relationship and no threshold value between fasting glucose

and adverse pregnancy outcomes [115] A similar relationship was seen between BMI and

adverse pregnancy outcomes [116]

Confounders mediators and colliders

A number of potential factors can influence the associations of interest These must be

identified and possibly corrected for in the regression models Whether to adjust for these

factors depend on classification of the factors into true confounders mediators and colliders

[112] Confounders should be included while colliders should no be included in regression

models to avoid introducing bias

A confounder (defined above) can be controlled for by adding it to a multiple regression

model The choice of which confounders to include in the model requires physiological

61

Independent variable Outcome

Confounder

Independent variable Outcome

Mediator

Independent variable Outcome

Collider

knowledge and requires statistical considerations when it comes to the number of observations

required [117] A mediator is considered a covariate that is on the causal pathway between the

independent and the dependent variable A collider is considered a covariate that is related to

both the independent and dependent variable in a common consequence [117] In our material

no included variables were considered to be colliders

Figure 11 Confounders mediators and colliders

62

Mediation

A mediator variable can either account for all or some of the observed relation between two

variables The effect of mediation can be assessed by judging what happens to the relation

between the independent and dependent variable when the mediator is included into the

regression model or not Full mediation would occur if inclusion of the mediation variable

removed the relation between the independent variable and dependent variable This rarely

occurs The most likely event is that the association becomes weaker yet still a significant

path with the inclusion of the mediator Partial mediation occurs when the mediating variable

accounts for some but not all of the relationship between the independent variable and

dependent variable Partial mediation implies that there is not only a significant relation

between the mediator and the dependent variable but also some direct relation between the

independent and dependent variable

One method to assess mediation was proposed by Baron and Kenny in 1986 [118] They laid

out several requirements that must be met to form true mediation relationships which are

summarized below

Step 1 Confirm that the independent variable is a significant predictor of the dependent

variable Independent Variable Dependent Variable

Y = β10 + β11 X + 1

β11 is significant

Step2 Confirm that the independent variable is a significant predictor of the mediator If the

mediator is not associated with the independent variable then it couldnrsquot possibly mediate

anything Independent Variable Mediator

Me = β20 + β21 X + 2

β21 is significant

Step 3 Confirm that the mediator is a significant predictor of the dependent variable while

controlling for the independent variable This step involves demonstrating that when the

mediator and the independent variable are used simultaneously to predict the dependent

63

variable the previously significant path between the independent and dependent variable is

now greatly reduced if not nonsignificant

Y = β30 + β31 X + β32 Me + 3

β32 is significant

β31 should be smaller in absolute value than the original mediation effect (β11 above)

Placental weight can be considered a mediator in this study Regression models are therefore

done with and without placental weight as a covariate in the model to show its role as a

possible mediator We applied the model by Baron and Kenny described above to show a

possible role of the placenta as a mediator Our results point at possible mediating pathways

involving the placenta on the causal pathway to fetal growth In order to quantify how much

of the effect that goes through the placenta we could have applied path analyses However

this method required more advanced statistical methods which were not available

64

52 Data collection STORK

521 Dependent variablesoutcomes

Birthweight

We chose to use birthweight as a summary measure of overall fetal growth It is widely used

and therefore suitable to compare our data to other publications We chose to use birthweight

as a continuous variable We wanted to report associations between maternal factors and

birthweight in the total STORK cohort as previous publications from the same cohort only

reported birthweight in sub cohorts andor using birthweight as a categorical value with a cut-

off of gt4200 g Birthweight was expressed as Z-scores adjusted for gestational age and fetal

sex

The standard score (Z-score) represents the distance between the raw score and the population

mean in units of the standard deviation Z is negative when the raw score is below the mean

positive when above The z-score is calculated as

where

x is the observed value

μ is the mean of the population

σ is the standard deviation of the population

Mean and standard deviation of the population were taken from a Norwegian reference

material [119]

Intrauterine fetal growth

There are no internationally accepted consensus on how to define and assess intrauterine fetal

growth [11] The longitudinal design of the STORK study enabled us to assess intrauterine

fetal growth We chose third trimester visit 3 to visit 4 which is the period of maximum

Z =

x - μ

σ

65

growth and a period in which maternal metabolic factors are important in terms of fetal

growth [120]

Fetal size and fetal growth were estimated by ultrasound Fetal size was expressed as both

estimated fetal weight (EFW) in grams and as EFW percentile according to Norwegian

growth charts [107] Intrauterine fetal growth was defined as the change in estimated fetal size

parameters from visit 3 to visit 4 expressed as either change in EFW (g) or change in

percentiles Combs formula was chosen as the equation to estimate fetal weight as it is the

formula in use in clinical practice at our department and the basis for the growth charts we

used as reference [106]

Errors in ultrasonographic assessment of fetal weight can be attributed to at least two factors

errors due to the equation and errors due to observer error Observer error can further be

divided into intra-observer and inter-observer error [121] Intra-observer error refers to the

variance in measurements performed by the same observer All measurements were

performed three times and we used the mean of the three values to minimize intra-observer

error Inter-observer error refers to the variance in measurements that occur because different

observers measure differently To minimize inter-observer error all measurements were done

by only three investigators and each participant was measured by the same investigator at all

visits Among errors in ultrasonographic assessment of fetal weight observer error has been

shown to be a relatively minor component compared to the larger error due to the equation

[18] To be able to assess fetal growth we compared our data to reference curves based on

data from University of Bergen Norway as that population was considered the most

comparable to our population [107] We also evaluated fetal growth as changes in each of the

three components that make up EFW according to Combs equation namely HC AC and

femur length Once again we compared our data with Norwegian reference data [108]

There are other types of fetal growth charts available Customized curves have been

developed to adjust for factors like race fetal sex parity and maternal size which are factors

known to influence birthweight and factors that differ in different populations [13] We chose

not to use customized growth charts since the aim of our study was to study the effect of

maternal factors on fetal growth In customized charts maternal factors are controlled for and

therefore unsuited to study the effect of maternal factors

Conditional growth curves take into account the estimated size measured at one point and

gives an estimation of the expected growth for a fetus of that particular size for a specified

period of time As an example a larger fetus at the 75 percentile at week 30 will be expected

to grow more during the next weeks than a smaller fetus at the 10 percentile at week 30 during

66

the same period of time Conditioning on a previous measurement gives information on

whether a particular fetus grows fast or slowly relative to other fetuses of the same size We

chose not to use conditional growth curves in the current study as preliminary analyses did not

indicate major changes in the results making use of the conceptionally more difficult variable

less justified

Placental weight

Placenta was weighed including umbilical cord and membranes by the midwife or childrenrsquos

nurse within one hour after birth The placental weight was expressed in grams The placentas

were not trimmed but there is a close correlation between trimmed and non-trimmed

placentas (r= 098) [122]

Rationale for using placental weight as a proxy for placental function

There is no single parameter that measures placental function as placenta has a range of

functions Placental weight was chosen as outcome as a surrogate for placental function

Placental weight is a measure commonly used to summarize placental growth and aspects of

placental function In normal pregnancy it is reasonable to assume that placental weight is

related to aspects of functional capacity of the placenta [123] We had no estimations of

placental weight or mass during pregnancy Placenta exhibits linear growth throughout

pregnancy [5556] making it reasonable to use placental weight after birth instead of

estimations of placental mass during pregnancy

We wanted to use a variable that reflects those aspects of placental function which are

relevant to fetal growth of which nutrient transport is an obvious factor Density or activity of

nutrient transport proteins in the placenta could have been used as an alternative measurement

of placental function but these data are not yet available in our cohort An underlying

assumption for nutrients to be transported across placenta is that the maternal or umbilical

blood flow is not impaired We performed Doppler measurements in the uterine artery and

umbilical artery In our cohort of healthy women only 35 had notching in the uterine artery

at visit 2 and 32 had a pulsatile index above 2 SD for gestational age at visit 4

(unpublished data)

67

Placental weight correlates well with surface area which is a major determinant for nutrient

transport [124] The maternal plasma level of hormones produced in the placenta are directly

related to placental weight [125]

522 Explanatory independent variables

The explanatory variables were chosen based on publications from our study [126ndash129] and

literature on fetal growth in general We selected some maternal characteristics that were

known to influence birthweight in order to study their relation to intrauterine fetal growth

Maternal factors

Maternal age was noted at the first visit in whole years Age was normally distributed

Parity was categorized into P0 and P1+ as the largest difference in birthweight is

known to be between the first child and second child and less between consecutive

children [43]

BMI was calculated based on height and weight measured at the first visit We did not

use pregestational BMI to avoid recall bias and false self-reporting

GWG was calculated as the difference in weight between visit 4 and visit 1 We did

not use weight measured at admission for delivery as there were many missing values

Fasting glucose was measured by the use of Accucheck (Roche Diagnostics

Mannheim Germany) in order to obtain the measured values immediately This

enabled us to inform the women of the result the same morning and in cases of

impaired glucose metabolism to give advice on diet and physical activity during the

consultation Analyses of glucose over the seven years of inclusion revealed that there

was an unexpected increase in fasting glucose of 06 mmolL over time We found no

accompanying increase in maternal age BMI or in insulin that could give a biological

plausible explanation for this increasing trend Thus the time trend in fasting glucose

most likely had an analytical cause The glucose values were de-trended according to

the coefficients from linear regression under the assumption of a linear increase

during the entire period and de-trending of the data removed the increasing trend

[130]

68

Placental weight

The rationale for using placental weight to reflect aspects of placental function has been

discussed above When placental weight was used as an explanatory variable in the regression

models placental weight was entered in 100 grams instead of 1 gram to avoid getting effect

estimates with too many decimals

Placental pathology

There were 55 placentas not characterized as normal which makes up 53 of the samples

Theoretically it is possible that the placental weight in these cases does not reflect function in

the same way as placentas characterized as normal Eg a placenta with infarctions has areas

of tissue that do not take part in nutrient transport Such a small percentage of pathological

placentas are not likely to have influenced the results to a significant extent

69

53 Methodological issues STORK-Placenta

Design

The STORK-Placenta study had a cross-sectional design which means the women were only

examined once which in our study was at delivery This design gives no opportunity to assess

earlier gestational ages or longitudinal changes throughout the pregnancy In Paper 3 all the

study subjects were healthy women and there was no need for a control group In paper 4 we

applied a case-control design in which the preeclampsia group was compared to a control

group of healthy pregnant women

Validity

Internal validity

Selection bias

Only women delivered by cesarean section were recruited to this study This lead to selection

bias for both the healthy women and the preeclamptic patients For the healthy women the

most common indications for cesarean section were prior cesarean section or patient request

due to traumatic previous delivery Few healthy primiparas are delivered by elective cesarean

the exception being breech presentation In Paper 3 the selection therefore resulted in age and

parity that were relatively higher than average Avoiding selection bias in a study like this was

not possible given the population eligible for participation

For the preeclamptic women the selection lead to overrepresentation of early onset

preeclampsia and cases of serious preeclampsia as late onset or less serious cases in many

cases can deliver vaginally In Paper 4 this was reflected in lower gestational age in the

preeclampsia group than the controls

Information bias

We assumed similar blood composition in the radial and the uterine artery This was done to

avoid puncturing the uterine artery as bleeding would be easier to control in the radial artery

As the blood is pumped out of the aorta it is reasonable to assume that the composition does

70

not change substantially between the blood reaching the radial artery compared to the blood

that reaches the uterine artery

External validityrepresentativity

The representativity of the results from the STORK-Placenta study is discussed in light of the

selection of the participants

Parity was higher in Paper 3 than average From our results in Paper 1 and Paper 2 we have

seen that parity was an independent variable with effect on fetal growth In Paper 3 the added

effect of parity on fetal growth could give a bias if the effect of parity also affects the glucose

transport across the placenta Hitherto the question can not be answered So far our results are

only valid for the glucose metabolism among healthy women with relatively normal BMI

Which changes that occur in the glucose metabolism in women with chronic diseases will

probably vary according to the disease Higher BMI would probably influence the glucose

metabolism both directly as higher BMI might lead to higher glucose levels in many cases

but possibly also indirectly by changes in inflammatory factors and by changes in the

transport of other nutrients as amino-acids and lipids

In Paper 4 gestational age was lower in the preeclampsia group than in controls Early-onset

and late-onset preeclampsia are by many considered two different subgroups of preeclampsia

due to the differences in risk factors pathogenesis and clinical presentation [90] Our findings

may not be valid for late-onset preeclampsia where maternal risk factors play a larger role in

the patophysiology and the endothelial dysfunction might be more prominent Therefore it is

possible that the results are valid only when the placental dysfunction is the major feature in

the pathophysiology like in early-onset preeclampsia

Statistical issues

In both papers from the STORK-Placenta study the numbers of participants were relatively

small due to the demanding logistics of the project Small numbers lead to some statistical

challenges that need to be discussed

In Paper 3 we included 40 patients which were sufficient to show significant glucose gradients

on both maternal and fetal side as well as a gradient across the placenta However the small

number restricted the possibilities to study interesting associations between maternal factors

and glucose transport or glucose transport in relation to fetal growth by the use of regression

71

models As an example we found an interesting association between maternal BMI and fetal

glucose v-a difference but the scatter plott revealed one woman with BMI 39 and analyses

showed that without that observation the association was no longer significant

In Paper 4 we found a significant difference in sFlt-1 but not in sEng across the uteroplacental

circulation among preeclamptic patients There is a possibility that lack of power influenced

this finding Possibly a larger sample could have given a significant difference for sEng in

which case our finding could represent a type 1 error (reject the hypothesis that there was a

difference even if it is true)

Both non-parametric tests on original data and parametric tests on log transformed data were

done giving the same results in terms of statistically significant differences We chose to use

the log transformed data for statistical analyses (as that seemed to be the most conventional

method used in relevant references) but presented arithmetic data in figures and tables to

make it easier for the reader

54 Data collection STORK-Placenta

Blood sampling

All procedures were standardized to minimize systematic errors Sampling was therefore done

by a small group of four trained obstetricians and handling the samples in the laboratory was

restricted to only three investigators In the few cases where sampling was inadequate it was

mostly due to failure in inserting the arterial line or in a few cases inadequate amount of blood

obtained from the umbilical artery Blood samples were kept on ice until centrifugation

Blood samples were taken in fasting condition to obtain a steady state situation This is

particularly relevant for glucose and insulin which show large post-prandial variation

Cesarean section was done under spinal anesthesia no participants received oxygen or

intravenous glucose infusion

Analyses

Glucose and insulin were analyzed at the laboratory at Oslo University Hospital The samples

were analyzed during three consecutive days

72

sFlt-1 and sEng were analyzed by commercially available ELISA kits (RampD systems) We

chose to use ELISA kits from RampD for comparison reasons as they were commonly used in

papers on preeclampsia published at the time

73

55 Interpretation of results

Paper 1 and 2

In Paper 1 and Paper 2 we have studied the associations between maternal characteristics

placental weight and fetal growth in healthy pregnant women ie these are studies of normal

physiological relations Together the results from these papers illustrate some of the interplay

between the mother the placenta and the fetus

Paper 1

Paper 1Paper 2

-parity

-BMI

-GWG

-glucose

We found largely the same determinants for both birthweight and intrauterine fetal growth in

third trimester with the exception of fasting glucose (see below) The weight of the placenta

was influenced by similar maternal metabolic and nutritional factors In summary our results

are compatible with the concept that maternal factors can influence fetal growth directly and

indirectly by promoting placental growth

We found a direct effect of maternal factors both on birthweight and intrauterine growth in the

third trimester For both birthweight and intrauterine fetal growth placental weight was an

independent determinant Hence as the placenta grows and becomes larger some of the effect

of maternal factors on fetal growth is likely to be mediated by growth of the placenta

We found independent effects of several maternal factors (parity BMI and GWG) on

intrauterine fetal growth in third trimester We did not find independent effect of age The

small variation in age (SD) might partly explain why we did not find any effect of age

74

Furthermore age has been shown to exhibit an inverse u-shaped relation to birthweight and we

only tested for linear relationships Somewhat surprisingly we did not find an independent

effect of fasting glucose on intrauterine fetal growth in third trimester The discrepancy

between the effect of glucose on birthweight and on intrauterine growth may have several

explanations One possible explanation lies in how fetal growth is assessed Fat accumulation

resulting from increased maternal glucose and subsequent increased insulin secretion in the

fetus is likely to be accumulated on extremities and truncus of the fetus as well as the

abdomen The estimation of fetal size and fetal growth used in our study included assessment

of head circumference abdominal circumference and femur length Of these only abdominal

circumference would be likely to reflect fat deposition We did not however find an

independent association between fasting glucose and change in abdominal circumference

There is no consensus on whether the diagnosis of abnormal growth should be based on EFW

or AC or both [11] Another possible explanation for the described discrepancy could be

found in the concept of conditional growth Conditional fetal growth refers to differences in

expected fetal growth depending on the size estimated at the last measurement As an

example a fetus that is large at week 30 will be expected to grow more in the remaining

weeks of the pregnancy than a fetus that is relatively smaller at week 30 Factors like impaired

glucose metabolism in early pregnancy leading to higher fasting glucose values might have

resulted in a large fetus already at week 30

Placental weight was used as a measure of placental function Introducing placental weight in

the multiple regression models gave two interesting results

First placental weight was an independent determinant of birthweight and fetal growth and

showed a positive effect on fetal growth A small placenta is commonly associated with a

growth restricted fetus hence a reduced placental function Fetalplacental ratio can be used

as an indicator of placental efficiency and includes both fetal weight and placental weight

Preliminary analyses in our material showed that the maternal factors associated with

fetalplacental ratio in the multiple model were maternal age parity and BMI Maternal

gestational weight gain was not significantly associated in the univariate model and hence not

included in the multiple model Fasting glucose was not significant in the multiple model

using fetalplacental ratio as outcome

Secondly placental weight can be viewed as a mediator in the associations between maternal

factors and fetal growth This implies that some of the effect of the maternal factors might

work through growth of the placenta There are several possible biological reasons for the

75

reduced effects of the maternal characteristics on birthweight or intrauterine fetal growth

when placental weight was included in the models The selected maternal characteristics may

exert their effects on fetal growth by affecting transplacental transport Transplacental

transport is affected by blood flow both on maternal and fetal side Furthermore the number

and efficiency of placental transport proteins may also be influenced by maternal factors The

total number of transport proteins is dependent on both the area of the syncytio-endothelial

membrane and the density of the transporting proteins In addition it can not be excluded that

placental production of growth factors may be affected

We have studied both modifiable and non-modifiable maternal factors Parity is a non-

modifiable factor present before pregnancy There is a well-known effect of parity on

birthweight We showed that this effect is evident also for intrauterine growth and placental

weight The effect of parity is relatively larger than many other maternal factors eg larger

than fasting glucose BMI and GWG Modifiable factors include BMI GWG and fasting

glucose BMI and fasting glucose may be modified before pregnancy and GWG and glucose

during pregnancy

The present study did not include data on neither fetal factors that stimulate or inhibit

placental growth function or maternal factors nor placental factors that influence maternal

metabolism Theoretically however there are possible pathways including signals from the

fetus that can stimulate placental growth and possibly placental factors that can influence

maternal metabolism

Taken together the results from Paper 1 and Paper 2 show that maternal factors influence

both placental weight and fetal growth and it is likely that some of the effect on fetal growth is

mediated through placental growth This does not exclude the possibility that an increased

fetal growth following increased maternal energy supply may lead to release of fetal growth

factors that feed back on placental growth

Clinical implications

We have only studied birthweight and intrauterine growth in third trimester which might be

too late to intervene in cases of abnormal fetal growth In order to intervene it is necessary to

know which factors influence intrauterine growth at different gestational ages As both low

76

BMI and low GWG is related to increased risk of IUGR patients with high risk of IUGR

could be advised to increase their BMI or make sure they gain sufficient weight according to

recommendations Similarly as high BMI and high GWG increase fetal growth women could

be advised to obtain a normal BMI prior to getting pregnant and not gain unnecessary weight

during pregnancy As there is a linear and continuous relation between fasting glucose and

adverse fetal outcomes including fetal growth pregnant women with fasting glucose values

just below the GDM criteria can benefit from the same advice concerning diet and physical

activity as GDM-patients receive In particular women with multiple risk factors of impaired

fetal growth should be given advice even if she does not meet the criteria of GDM or obesity

Paper 3

Glucose is the major source of energy for the fetus and the placenta and therefore has an

obvious importance in fetal nutrition Glucose transport across the placenta in humans is

interesting to study for several reasons There is a lack of human in vivo studies in contrast to

the body of evidence on mechanisms and transporter proteins etc from in vitro studies It is of

major importance to acknowledge the distinction between maternal nutrition and fetal

nutrition [2] The placenta is not just a simple conduit for gases nutrients and waste products

but has its own complex metabolism with corresponding requirements for oxygen and

nutrients

In this paper we found a close correlation between maternal and fetal glucose concentrations

which is in line with the concept that the maternal-fetal gradient is the driving force in the

transplacental transport of glucose across the placenta However the fetal v-a glucose

difference was not merely a reflection of the maternal glucose concentration or the

uteroplacental uptake of glucose but rather related to the maternal-fetal gradient and the

concentration in the umbilical artery The relation between maternal and fetal glucose

concentration has been shown in several papers Although the umbilical venous concentration

is closely related to the maternal concentration the fetal v-a difference seemed to be less

related to maternal concentrations but more to the concentration in the umbilical artery fetal

insulin placental weight and birthweight We therefore speculate that the fetus has a saying in

determining the fetal glucose consumption This might at first seem to be in conflict with the

Pedersen hypothesis which was first presented in 1952 [131] His theory was that high

maternal glucose was transferred to the fetus which responds by secreting more insulin

77

which in turn lowers the blood glucose of the newborn Compared to the 1950s pregnant

women of today are older when they get pregnant have higher prepregnancy BMI and gain

more weight in pregnancy The metabolic environment a fetus experiences today is likely to

differ from the environment some decades ago in several aspects more energy-rich altered

balance between glucose and lipids and more inflammation [132] The non-glucose factors

like lipids may have augmented their role as several factors have changed in the population

since the proposal was made by Pedersen We can only speculate as to how the relative

importance of these factors might influence the regulation of transport of nutrients to the

fetus

Our results can not explain or show the complex regulation of glucose transport and

metabolism and leaves us with some unanswered questions We only presented correlation

analyses as we did not yet have enough samples to do multivariate analyses to evaluate the

relative importance of the factors involved We were not able to do path analyses to quantify

the influence of each of these factors Do the relationships we have described work differently

in pathological pregnancies in which there is either abnormal placental function or the mother

exhibits abnormalities in her metabolism or the fetus experiences abnormal growth These

questions can hopefully be answered by future research

The amount of glucose consumed by the placenta can be changed under hypoxic conditions

[63] It is not likely that our participants were hypoxic to a large degree We only measured

oxygen in a few cases which were all normal

Clinical implications

In obstetric practice there are numerous examples of cases of abnormal fetal growth occurring

in pregnancies of healthy mothers with normal metabolism and apparently normal placental

function Placental function might still be compromised resulting in reduced fetal nutrition

Fetal under nutrition may result from compromised transplacental transfer of nutrients In the

other end of the spectrum are the fetuses that experience overgrowth despite strict glycemic

control of their diabetic mothers Some authors argue that this might be due to intermittent

hyperglycemia rather than constant hyperglycemia but another option is that hyperglycemia

is accompanied by other nutrients or other factors that increases the total energy supply to the

fetus

78

Human in vivo studies are rare and therefore valuable in terms of extrapolation to relevant

settings in clinical practice However in vivo settings include multiple factors working

together making it difficult to assess individual effects In vitro settings however can control

for one factor at a time to gain mechanistic knowledge which can hardly be drawn from in

vivo settings The clinical significance of factors operating in vitro is often difficult to assess

Paper 4

The multifactorial etiology and heterogeneous clinical presentations seen in preeclampsia

makes it an intriguing and challenging condition to study Since preeclampsia is a pregnancy

complication in which the placenta is believed to play a crucial role in the pathophysiology it

was both interesting and relevant to choose preeclampsia in order to study aspects of placental

function in pathological pregnancies Furthermore preeclampsia is still a leading cause of

mortality and morbidity worldwide Despite decades of research there is still no causal

treatment leaving timing of delivery the only intervention to balance the needs of the mother

and the fetus

In our study we found as expected that preeclamptic women had higher concentrations of sFlt-

1 and sEng than healthy controls as has been shown in numerous previous publications

Preeclamptic women further had higher concentrations of sFlt-1 in the uterine vein than the

radial artery giving a gradient across the uterus There was no gradient for sEng among

preeclamptic women and no gradients were found in the healthy controls for either of the two

factors tested The gradient across placenta is consistent with the concept that the placenta

secretes sFlt-1 into the maternal circulation The source of excess sFlt-1 and sEng in

preeclamptic patients is assumed to be the placenta based on enhanced expression of both

factors in trophoblastic tissue [133134] Enhanced expression of sFlt-1 and sEng in

trophoblastic tissue does not necessarily prove that the circulating sFlt-1 and sEng found in

preeclamptic patients originate from the placenta or that the placenta is the only source There

is a possibility that sFlt and sEng originate from circulating cells in the maternal circulation or

endothelial cells Peripheral blood mononuclear cells have been suggested to be an additional

extra-placental source of sFlt-1 [134]

Our results support the hypothesis that at least a part of the circulating sFlt-1 originates in the

placenta and is transported into the maternal circulation whereas we did not find evidence to

support that this holds for sEng The discrepancy between our results for sFlt-1 and sEng

could have several explanations

79

There might be a biological difference such that sFlt-1 only or to a larger extent than sEng is

released from the syncytiotrophoblasts in the placenta whereas sEng to a larger extent is

produced elsewhere [135] There might also be a statistical explanation suggesting that we had

inadequate power to show a statistically significant difference in sEng which would represent

a type 1 error (rejecting the hypothesis that there was a difference even if it is true)

In this paper as most studies involving preeclamptic patients and healthy controls there was a

difference in gestational age among cases and controls The difference in gestational age

raises some questions to be discussed There are publications reporting an increase in sFlt-1

and sEng with increasing gestational age both for controls and preeclamptic patients but more

so in preeclampsia [136137] Assuming this relationship for our controls we would expect to

find a lower concentration at week 30 among healthy controls than what we found near term

giving an even greater difference than we observed Thus we do not think that the difference

in gestational age can explain the observed difference in sFlt-1 and sEng between preclamptic

patients and healthy controls We did not include samples from preeclamptic patients at term

as they mostly deliver vaginally Our group of preeclamptic patients thus represents early-

onset preeclampsia In most cases preeclampsia was accompanied by a degree of intrauterine

growth restriction Whether our findings are representative for late onset preeclampsia in

which the placental dysfunction is perhaps less prominent and the endothelial dysfunction

more prominent is not clear from our study

Anti-angiogenic factors in a clinical setting

Anti-angiogenetic factors have been proposed used as diagnostic tools for preeclampsia

There is hope for a therapeutic option in treating preeclampsia in the future but whether

angiogenetic agents can be used to improve the angiogenic imbalance seen in preeclampsia is

not known At the moment the most useful implications of these types of studies is increased

knowledge on the pathogenesis including the possibility to differentiate between early- and

late-onset preeclampsia

80

6 Conclusions

In conclusion results from the first part of this thesis (Paper 1 and 2) underline the importance

of the placenta and placental functions in normal pregnancies Placenta is an important factor

to consider when studying associations between maternal factors and measures of fetal

growth birthweight intrauterine growth or body composition The effect of maternal

metabolic and nutritional factors on fetal growth is likely to go partly through growth of the

placenta There is an important distinction between maternal and fetal nutrition as one has to

consider the placenta as an active organ and not a passive conduit of nutrients and gases

In the second part of this thesis a method has been established that makes it possible to study

placental function in the human in both normal and pathological pregnancies like

preeclampsia

7 Further research

I believe the greatest challenges in the two studies that make up my thesis also reflect the

potentials for further research

In the STORK study we collected large amounts of data on a large group of women

Therefore selecting and analyzing the relevant outcomes and appropriate explanatory

variables was the greatest challenge There are large amounts of data still to be analyzed For

the STORK data my plans for a postdoc is to study in more detail the relations between

maternal metabolism and pregnancy outcomes More specifically to differentiate between

healthy and unhealthy obese pregnant women in metabolic terms and relate this to pregnancy

outcomes including fetal growth

In the STORK-Placenta study establishing the method and achieving the data collection were

the greatest challenges with demanding logistics at any time of the day There are few larger

human in vivo studies of placental nutrient transfer In particular studies of arterio-venous

differences on maternal side of placenta are scarce The main reason this kind of studies are so

limited is that such studies are logistically very requiring To our knowledge we are the only

group employing this procedure The samples obtained by this method give unique

opportunities to study concentration gradients and transplacental transfer of any nutrient

81

across placenta and how endocrine and inflammatory factors may interact with nutrient

transfer The study also includes measurements of maternal and fetal blood flow enabling us

to quantify the amounts of nutrients being transported The study has currently been

expanded to around 100 pregnancies Data collection still goes on aiming to get enough

samples to continue analyzing interesting associations linking maternal metabolism placental

functions and the fetus and extending the data to include cases of pathological pregnancies

like preeclampsia diabetes mellitus and abnormal fetal growth Samples from preeclamptic

women are currently being analyzed for Placental growth factor

The potential for further research lies in combining the data retrieved from the two studies

Ultimately I would like to be able to link preeclampsia and fetal growth in the two studies

82

8 References

Reference List

1 2009) wwwmfr-nesstaruibno Medical birth Registry Norway Available

2 Harding JE (2001) The nutritional basis of the fetal origins of adult disease Int J

Epidemiol 30 15-23

3 Barker DJ Thornburg KL (2013) The obstetric origins of health for a lifetime Clinical

Obstetrics and Gynecology 56 511-519

4 Forsdahl A (1978) Living conditions in childhood and subsequent development of risk

factors for arteriosclerotic heart disease The cardiovascular survey in Finnmark 1974-

75 J Epidemiol Community Health 32 34-37

5 Forsdahl A (1979) Are poor living conditions in childhood and adolescence and

important risk factor for arteriosclerotic heart disease Int J Rehabil Res 2 238-239

6 Barker DJ (2005) The developmental origins of insulin resistance Horm Res 64 Suppl

3 2-7

7 Barker DJ Shiell AW Barker ME Law CM (2000) Growth in utero and blood

pressure levels in the next generation J Hypertens 18 843-846

8 Barker DJ (1997) The long-term outcome of retarded fetal growth Clinical Obstetrics

and Gynecology 40 853-863

9 Gude NM Roberts CT Kalionis B King RG (2004) Growth and function of the

normal human placenta Thromb Res 114 397-407

10 Voldner N (2010) Modifiable determinants of newborn macrosomia and birth

complications [dissertation]

11 Mayer C Joseph KS (2013) Fetal growth a review of terms concepts and issues

relevant to obstetrics Ultrasound Obstet Gynecol 41 136-145

12 Zhang J Merialdi M Platt LD Kramer MS (2010) Defining normal and abnormal

fetal growth promises and challenges Am J Obstet Gynecol 202 522-528

13 Gardosi J Figueras F Clausson B Francis A (2011) The customised growth potential

an international research tool to study the epidemiology of fetal growth Paediatr

Perinat Epidemiol 25 2-10

14 Rohrer F (1921) The index of corpulence as measure of nutritional state Munchener

medizinische Wochenschrift 580-582

15 Catalano PM Thomas AJ Avallone DA Amini SB (1995) Anthropometric estimation

of neonatal body composition Am J Obstet Gynecol 173 1176-1181

16 Godang K Qvigstad E Voldner N Isaksen GA Froslie KF et al (2010) Assessing

body composition in healthy newborn infants reliability of dual-energy x-ray

absorptiometry J Clin Densitom 13 151-160

17 Pay AS Froen JF Staff AC Jacobsson B Gjessing HK (2013) A new population-

based reference curve for symphysis-fundus height Acta Obstet Gynecol Scand 92

925-933

18 Anderson NG Jolley IJ Wells JE (2007) Sonographic estimation of fetal weight

comparison of bias precision and consistency using 12 different formulae Ultrasound

Obstet Gynecol 30 173-179

19 Cetin I Alvino G (2009) Intrauterine growth restriction implications for placental

metabolism and transport A review Placenta 30 Suppl A S77-S82

20 Mei Z Grummer-Strawn LM Pietrobelli A Goulding A Goran MI et al (2002)

Validity of body mass index compared with other body-composition screening indexes

for the assessment of body fatness in children and adolescents Am J Clin Nutr 75

978-985

13

In Paper 3 we reported initial studies of transfer of glucose across the human placenta and

how maternal and fetal glucose and insulin levels were related

Paper 3

Glucose and insulin

In Paper 4 the role of placenta in producing pathogenic factors of preeclampsia was

investigated choosing anti-angiogenic factors because of their endothelial-disturbing

properties

Paper 4

Anti-angiogenic

factors

14

12 Background

Fetal growth has implications for the newborn child both in short and long term The link

between events in early life and risk of disease in later life is now a widely recognized field of

research known as developmental programming and often called Developmental Origins of

Health and Disease Developmental programming refers to how an event at a critical or

sensitive period results in a long-term change in the structure or function of the organism

[23] Organs and systems in the human body are sensitive to the environment in certain

periods The critical periods are mainly those characterized by rapid growth and maturation

and for most organs and systems this happens to a large extent in utero

The idea of linking events in early life to later risk of disease is however not new The

association between poor living conditions in childhood and increased risk of cardiovascular

disease was observed by Anders Forsdahl who worked as a physician in Finnmark Northern

Norway in the 1970s He found a positive correlation between infant mortality which was

considered to be an index of standard of living and mortality from arteriosclerotic heart

disease as well as cholesterol values [45]

The link between early life events and later disease received more publicity when the late

David Barker introduced what is commonly referred to as the rdquoBarker hypothesisrdquo He was

probably the most acknowledged scientist in this field and established an association between

birthweight and increased risk of cardiovascular disease insulin resistance and type 2 diabetes

mellitus [6ndash8] His work has been followed by a range of publications that have not only

confirmed these associations but also provided mechanistic insight into the link between

intrauterine growth and increased risk of disease A large body of evidence have shown that

structural or functional changes that last throughout life can result from nutritional factors in

utero [2] Extensive work on animal models has demonstrated how dietary changes affect fetal

growth and lead to functional and structural changes The availability of nutrients to the fetus

is influenced not only by the motherrsquos diet during pregnancy but by maternal nutrient stores

and metabolism The placenta has multiple roles in fetal nutrition by its capacity to transport

nutrients from the maternal to the fetal circulation by its own metabolic demand for nutrients

and by producing hormones which influence fetal and maternal nutritional supply [9]

15

13 Fetal growth

Fetal growth comprises the entire process of differentiation maturation and development that

occurs between conception and birth This process starts with the fusion of two cells and ends

up with an estimated 50-100 trillion cells in the newborn child The terminology used to

describe and evaluate fetal growth is complex and the terms need to be defined First there is

a need to draw a distinction between size at birth and intrauterine growth Secondly the

difference between size which is most commonly measured as weight and body composition

must be addressed

131 Size at birth

Birthweight

Size at birth is routinely measured as birthweight (grams or kg) Birthweight is a summary

measure of fetal growth throughout pregnancy Categories based on birthweight are used both

in clinical settings and for research Low birthweight is generally defined as birthweight

lt 2500 grams whereas a definition for high birthweight (macrosomia) is more arbitrary Both

4000 4200 and 4500 grams have been used as cut-off values in various settings [1011]

Birthweight for gestational age

Birthweight as a function of gestational age gives information of size relative to expected size

for a particular gestational age Birthweight for gestational age can be given as a percentile

between 0 and 100 Birthweight for gestational age can also be categorized and the most

commonly used categories are large for gestational age (LGA) appropriate for gestational age

(AGA) and small for gestational age (SGA) The conventional cut-off percentiles for these

categories are given beneath

Population based charts for birthweight are often based on large samples including both low-

risk and high-risk pregnancies representing the underlying population On the other hand a

so-called standard chart is usually based on low-risk pregnancies with a normal outcome [12]

Furthermore customized charts have been made to accommodate for differences in eg

ethnicity parity age and BMI in individual patients Such charts have been developed for

different populations and there are electronically available charts [13]

16

Body composition

In addition to weight of the newborn baby length and head circumference give some

information about the body composition of the newborn Further evaluation of body

composition can be derived from these measurements The Ponderal Index (PI) is calculated

as a relationship between mass and height as is the body mass index (BMI) but the mass is

normalized with the third power of body height

Because it yields valid results even for very short (and very tall) persons it is more suitable

in pediatrics than BMI [14] Body composition can further be assessed by measuring

circumference of the abdomen and the extremities or by skin fold thickness measurements by

calipers to obtain an estimation of fat distribution [15] There are other methods that are either

expensive or difficult to perform on newborns Dual energy x -ray absorptiometry (DXA)

enables an estimation of bone mass fat mass and fat free (lean) mass A reasonable good

correlation between estimated fat mass by DXA and skin fold thickness measured by calipers

has been shown [16]

Categories Cut-offs

SGA lt 10 p

AGA 10-90 p

LGA gt 90 p

PI

= weight (g)

[height (cm)]3

17

132 Intrauterine growth

Fetal growth is a continuous process that starts at conception and ends at birth but is

commonly measured as just the end result which is size at birth However the distinction

between size and growth applies also to the intrauterine period Fetal size is estimated based

on a single observation or measurement whereas estimation of fetal growth requires at least

two measurements

Symphysis-fundus height

Palpation of the abdomen and measuring the symphysis-fundal height is used to estimate

intrauterine growth in low-risk pregnancies Reference curves for the symphysis-fundus

height to assess fetal growth have recently been updated in Scandinavia [17]

Ultrasound measurements

Estimation of fetal size

Estimation of fetal size by ultrasound combines measurements of the fetus and transforms

these measurements into volume and weight to estimate fetal size There are a number of

equations that use combinations of circumferences andor diameters and combinations of

measurements of head and abdominal size andor femural length to estimate fetal size The

equations differ in their ability to predict fetal size but generally perform more accurately in

predicting average fetal sizes than at the extremes of birthweight [18]

Estimation of fetal growth and fetal growth charts

To estimate fetal growth two or more measurements separated in time are needed and the rate

of growth can be assessed by using fetal growth charts There are a multitude of charts

available that are constructed by different methods and from different populations Fetal

growth charts can be derived from cross-sectional or longitudinal data In cross-sectional

charts each pregnant woman contributes with data from one observation whereas longitudinal

studies have repeated measurements from each participant The longitudinal studies provide

better references for fetal growth [12]

18

The ambiguous terminology

The lack of distinction between fetal size and fetal growth complicates the terminology Small

for gestational age (SGA) is often defined as birthweight lt 10 p The term intrauterine growth

restriction (IUGR) is often used interchangeably with SGA IUGR more strictly is used as a

term for true intrauterine growth restriction based on data that shows a decline in intrauterine

growth over time assessed by ultrasound There are however no universally accepted

definition of how much decline in fetal growth that would define IUGR although some

authors have defined IUGR as either a fall in fetometric percentiles or a combination of fall in

percentiles and low birthweight [19] On the same note accelerated fetal growth can be seen

during intrauterine life and may or may not result in a LGA newborn

Figure 1 Schematic overview of categories of fetal growth

growth

restrictionexcessive

growth

AGASGA LGA

19

14 Maternal aspects of fetal growth

141 Maternal nutritional status

Maternal nutritional status is vital for fetal growth as the fetus is dependent on nutrients being

transported from the maternal circulation across the placenta to the fetal circulation The

nutritional status of the mother is generally assessed by indirect means of which Body Mass

Index is a commonly used measurement

Body Mass Index (BMI)

BMI is calculated from a persons weight and height according to the following equation

BMI is used as a surrogate for body fat and has been shown to correlate to direct measures of

body fat such as underwater weighing and dual energy x-ray absorptiometry (DXA) [20]

Although the correlation between BMI and body fatness is fairly strong the correlation varies

by sex race and age At the same BMI women tend to have more body fat than men At the

same BMI older people tend to have more body fat than younger adults Highly trained

athletes may have a high BMI because of increased muscularity rather than increased body

fatness [21] In pregnancy the correlation between BMI and percent body fat is better in early

gestation than in late gestation [22]

The World Health Organisation (WHO) classifies BMI for adults in the following groups [23]

BMI

weight (kg)

[height (m)]2

BMI Weight Status

Below 185 Underweight

185 ndash 249 Normal

250 ndash 299 Overweight

300 and above Obese

20

For adults BMI is interpreted using standard weight status categories that are the same for all

ages and for both men and women For children and adolescents on the other hand the

interpretation of BMI is both age- and sex-specific [24]

Biological effects of high BMI

BMI is used as a surrogate for body fat which is made up of adipose tissue Adipose tissue can

be classified as white adipose tissue (WAT) and brown adipose tissue WAT is excess energy

stored as triglycerides in adipocytes which secrete a variety of substances including

hormones (eg leptin adiponectin and resistin) as well as inflammatory factors [25] Brown

adipose tissue is thought to have a function in thermo genesis Excess adipose tissue can be

estimated by anthropometric measures such as skin fold thickness measured by calipers [26]

Consequences of BMI for pregnancy and labour

Prepregnancy BMI is a major determinant of pregnancy outcome and increasing BMI is

associated with an increased risk of the majority of pregnancy complications like congenital

abnormalities miscarriages gestational diabetes preeclampsia obstructed labour and

operative deliveries [27] Low prepregnancy BMI is associated with low birthweight and

IUGR [28]

Gestational weight gain (GWG)

Gestational weight gain in pregnancy includes growth of the fetus placenta and uterus

increase in maternal plasma volume and accumulation of maternal fat mass [29] The total

amount of weight gained during pregnancy varies considerably among women and lean

women tend to accumulate more fat than obese women [30] Accumulation of fat is primarily

centrally and represents a combination of subcutaneous fat and visceral fat Visceral fat

correlates with metabolic risk factors like hypertension insulin sensitivity and plasma lipids

[31] The ideal gestational weight gain differs depending on the maternal or neonatal outcome

of interest Recommendations for gestational weight gain were revised by the Institute of

Medicine USA in 2009 and highlights both that women should be within a normal BMI range

when they conceive and gain weight within the ranges recommended The recommended

21

weight gain is based on four categories of prepregnancy BMI Higher categories of

prepregnancy BMI are recommended a lower weight gain [29]

Consequences of gestational weight gain

Gestational weight gain has consequences for both mother and child in the short and long

term Low GWG is associated with low birthweight and IUGR [32] and high GWG is

associated with macrosomia and increased neonatal fat mass [3334] High GWG is

associated with increased risk of pregnancy complications like preeclampsia and diabetes [35]

Restricted GWG in obese women with type 2 diabetes has been shown to influence fetal

growth [36] There are reports on associations between GWG and cesarean section

instrumental deliveries and low Apgar scores but it has been suggested that the effects are

mediated by high birthweight [35] The most consistent adverse outcome for mothers with

large GWG is weight retention post-partum [35]

BMI Weight Status Recommended Gestational

Weight Gain

Below 185 Underweight 13-18 kg

185 ndash 249 Normal 11-16 kg

250 ndash 299 Overweight 7-11 kg

300 and above Obese 5-9 kg

22

142 Maternal metabolism

As the fetus is dependent on nutrients from the maternal circulation not only the maternal

intake of nutrients but also the maternal metabolism plays a major role in fetal nutrition There

are adaptations to maternal metabolism that occur during pregnancy to ensure that the

increasing nutritional demands of the mother the placenta and the fetus are met Adaptations

are made in the metabolism of all major groups of nutrients

Glucose metabolism in pregnancy

The human fetus is highly dependent on glucose derived from the maternal circulation for

growth and development [2] Changes occur in the maternal glucose metabolism during

pregnancy to ensure that the increasing nutritional demands of the mother the placenta and

the fetus are met Previously published data on glucose metabolism suggested a decrease in

fasting glucose with gestation [37] Fasting glucose levels of pregnant women have been

shown to decline in early pregnancy and thereafter not decrease much further [38] In our

cohort we found fasting glucose to increase slightly with gestational age [39] There is an

increase in basal hepatic glucose production by up to 30 with increasing gestational age

[37] The insulin sensitivity shows a marked change in pregnancy Overall insulin sensitivity

decreases during pregnancy and in late pregnancy a reduction of 50-70 is estimated

compared with non-pregnant women [40] Insulin secretion increases by up to 200-250

[40]

Lipid and amino acid metabolism in pregnancy

The lipid metabolism in pregnancy is characterized by a marked hyperlipidemia Triglyceride

concentration increases and in particular very low-density lipoprotein (VLDL) triglyceride

concentration which increases 3-fold from week 14 to term Plasma cholesterol levels rise to

a lesser degree In obese women the hyperlipidemia is further exaggerated [27] There is an

overall increase in protein synthesis in pregnancy This includes maternal tissues like breasts

uterus and the liver as well as the fetus and the placenta [27]

23

143 Other maternal factors

Age and parity

Both maternal age and parity have an effect on fetal growth Young women especially

adolescents give birth to smaller newborns than older women [41] Birthweight increases with

maternal age until the 30s after which there is a decline resulting an inverse u-shaped curve

[42] Age is however closely linked to parity Birthweight increases with parity and the

largest increment of approximately 200 grams is between the first and second child [43] In

multiple models birth order exerted a greater influence on birthweight than maternal age [42]

The biological explanation behind these associations is only partly understood The effect of

parity may be partly explained by the capacity of the spiral arteries to expand which is higher

in the subsequent pregnancies than in the first pregnancy [44]

Maternal blood supply to the uterus

The uterus receives blood mainly from the uterine arteries which are branches of the internal

iliac artery The uterine arteries branch into thinner vessels first the arcuate arteries then the

radial arteries followed by the basal arteries which continue into the endometrium as the

spiral arteries The spiral arteries undergo remodeling in early pregnancy which means they

loose smooth muscle and elastic tissue from their walls This remodeling of maternal vessels

is a key aspect of early pregnancy and vital for a successful outcome Ultrasound studies have

estimated both the changes in diameters of the uterine artery and the blood flow velocity in

these vessels Several studies have reported that the diameter of the uterine artery increases

approximately 3-4 fold from non-pregnant state to term [4546] The flow velocity increases

with gestational age but reported values differ somewhat depending on whether the

measurements are made on one or both uterine arteries and the laterality of the placenta

[4546] The fraction of the cardiac output that is distributed to the uterus has been estimated

to be 35 in early pregnancy and near 12 at term [46]

24

Figure 2 Blood supply to the uterus

From Grayrsquos Anatomy 20th US edition electronically retrieved from Wikimedia commons

25

15 Placental aspects of fetal growth

151 Development structure and growth of the placenta

Normal placental development and maternal adaptation to pregnancy are crucial factors for a

successful pregnancy The placentation process and maternal adaptation are closely linked and

happen as parallel processes ensuring a healthy outcome for both mother and child Many

complications of pregnancy can be ascribed to defects in early placentation andor inadequate

maternal adaptation to pregnancy Therefore knowledge of these processes is essential in

understanding the pathophysiology of pregnancy complications

The development of the placenta begins as soon as the conceptus reaches the uterus on day 3-

4 after fertilisation By this stage the blastocyst has an outer wall and an inner cell mass The

outer wall consists of trophoblast cells which undergo transformation to either fuse into a

syncytial cell layer or form individual cytotrophoblasts Extra villous trophoblasts are named

so because of their location in the maternal endometrial (decidual) tissue and play an

important role by starting the trophoblast invasion and the adaptation of the maternal vessels

to pregnancy During this process the endometrial stromal cells differentiate into decidual

cells The extra villous trophoblasts migrate through the decidua basalis and into the inner

third of the myometrium aided by a range of proteases that degrade or remodel the maternal

extra cellular matrix

The amnion arises from the inner cell mass and makes contact with the chorion by early

second trimester Lacunae are formed within the syncytiotrophoblast and the lacunar system is

transformed into the intervillous space

The majority of the villous mass forms the placenta whereas the remainder of the villous

tissue begins to regress resulting in the chorion This remodeling ensures that rupture of

membranes and delivering of the baby can occur at birth without tearing through the placenta

This remodeling occurs at the same time as the maternal blood flow starts in the periphery of

the developing placenta

26

Figure 3 The structure of placenta

From Grayrsquos Anatomy 20th US edition electronically retrieved from Wikimedia commons

The villous mass is made up of a tree of branching villi The branches are classified according

to caliber position within the villous tree and function and goes from the larger stem villi via

intermediate villi to the thinner and distal terminal villi In a mature normal placenta stem

villi account for 20-25 intermediate villi approximately 25 and terminal villi around 40

of the total villous volume The maternal-fetal exchange takes place primarily at the

terminal villi and to some extent at the intermediate villi [47]

Figure 4 Terminal villi

Illustration by Oslashystein H Horgmo University of Oslo

27

Figure 5 Development of the placenta

Fertilized egg

blastocyst

Trophoblast

Cytotrophoblasts

Syncytiotrophoblasts

Extravillous

Villous

Inner cell mass

Fetus

Amnion

Yolk sac

-Primary villi

-Secondary villi

-Tertiary villi

-mesenchymal villi

-immature intermediate villi

-stem villi

-mature intermediate villi

-terminal villi

Matu

ratio

n

ofvilli

Angiogenesis

Transformation of

spiral arteries

Placental villi

Modified after Bernischke et al Pathology of the Human Placenta 2012

The syncytiotrophoblast layer covers a surface area of 12-14 m2

at term [48] It is covered by

microvilli which increase the surface area by a factor of five- to seven The

syncytiotrophoblast layer is comprised by two membranes the maternal-facing microvillous

membrane (MVM) and the fetal-facing basal membrane (BM) The syncytiotrophoblasts act

as an epithelium and contain high densities of transporter proteins There are transport

proteins for the major groups of nutrients Glucose transport proteins belonging to the GLUT

family transport glucose across the placenta by facilitated diffusion [49] Amino acids are

transported by transporter proteins by an active process [50] Lipids are mainly transported as

free fatty acids (FFA) by simple diffusion or by specific binding proteins [5152] Transporter

proteins for micronutrients and drug transporters involved in the transport of drugs have also

been identified [5354] The syncytiotrophoblast also transport ions and solutes to maintain

membrane potential and cell volume regulation

28

Figure 6 The syncytiothrophoblast cell

Modified by Oslashystein H Horgmo after SLager J Pregnancy 2012

Growth of the placenta

The placenta grows close to linearly throughout pregnancy [5556] Cytotrophoblast cells fuse

continuously to maintain and expand the syncytiotrophoblast layer Little is known regarding

the control of this coordinated sequence of events After around 32 weeks of gestation the

fetal capillaries and syncytiotrophoblast layer come closer as the syncytiotrophoblast becomes

thinner and free of nuclei and most organelles This thinning of the membrane separating the

maternal and fetal circulations aids gaseous exchange and the membrane is known as the

rdquovasculosyncytial membranerdquo [47] The volume of the terminal villi and hence the surface

area increases exponentially throughout pregnancy a process that appears to be dependent on

branching of the villi and angiogenesis [57] Although the villous tree undergoes continuous

growth and differentiation during pregnancy relatively little is known about the regulation of

this process Maternal factors like prepregnancy BMI and GWG have been shown to be

associated with placental growth measured both as placental weight thickness and area [58]

Little is known about fetal factors that may affect placental growth Studies in mice do

however indicate that the fetus itself influences the functional properties of placenta [59]

29

152 Placental functions

The placenta has a range of important functions to ensure a successful pregnancy outcome

including transport of nutrients and gases metabolism and endocrine and protective

functions

Transport of nutrients and gases

a Transport of gases

Oxygen provided by the maternal blood is transferred to the fetal circulation by diffusion

Carbon dioxide and other waste products are removed from the fetus and transported to the

mother by the placenta [9] Chronic exposure during pregnancy to hypoxia as seen at high

altitudes is associated with reduced fetal growth [60] However comparisons of fetal oxygen

extraction between pregnant women at high altitude (3600 m) and sea level (400 m) showed

that the fetus had the ability to adapt and to increase oxygen extraction [60] Studies on

pregnant sheep in vivo showed the O2 consumption per kg of the fetus to be twice that of an

adult and the uteroplacental tissues to consume four-fivefold that of the fetus [61]

b Transport of nutrients

Glucose

Glucose is the primary energy source for the fetus As the fetus to a very limited degree

produces its own glucose the fetus needs to obtain glucose from the maternal circulation

Glucose is transported from the maternal circulation across the syncytiotrophoblasts of the

placenta by facilitated diffusion [49] The syncytiotrophoblast is the main barrier in the human

placenta and is comprised by two cell membranes the maternal-facing microvillous

membrane (MVM) and the fetal-facing basal membrane (BM) The glucose transporters found

in the human placenta belong to the GLUT-family of which there are multiple isoforms The

GLUT 1 is the predominant transport protein in the human placenta at term and is found in

higher concentration on the microvillous membrane than the basal membrane [49] Glucose

transport across the endothelial layer is not well studied

30

The maternal-fetal glucose transfer depends on several factors

Glucose supply Glucose supply is determined by both maternal blood glucose

concentration and blood flow to the placenta

Placental glucose metabolism The placenta not only transfers glucose to the fetus but

consumes considerable amounts of glucose itself Insight into the placental glucose

transfer and metabolism is largely based on data from animal studies in particular on

pregnant sheep Placental glucose consumption is normally very high Estimates

suggest that the placenta consumes about 50 of the glucose extracted from the

maternal circulation [62] Placental glucose metabolism can be altered as a result of

alterations in the supply of other energy-generating substrates like oxygen Hypoxic

conditions has been suggested to increase glucose consumption in the placenta thus

making less glucose available to the fetus [63]

The total surface area of the membranes

Placental glucose transporter density and functions [64]

Maternal-fetal glucose gradient The maternal glucose concentration is higher than the

fetal concentration which creates a maternal-fetal gradient This gradient is thought to

be the driving force for the transfer of glucose from the mother to the fetus The

maternal and fetal glucose concentrations are closely related [65ndash67] The gradient

increases with gestation and so does the placental transport capacity Together this

ensures that placental glucose transfer to the fetus is increased which is needed to meet

the increasing needs of the growing fetus A lower fetal glucose concentration leads to

a larger maternal-fetal glucose concentration gradient which increases transfer of

glucose to the fetus In IUGR fetuses the glucose level is lower which creates a larger

gradient and hence increases the transfer of glucose [66] The regulation of fetal

glucose utilization in humans is only partially understood but has been studied in

more detail in pregnant sheep In sheep the rate of fetal glucose utilization depends on

the interaction between fetal plasma glucose and insulin concentrations and the supply

of glucose to the fetus [61] Fetal glucose uptake seems to be regulated by fetal glucose

concentration rather than maternal supply [68]

Insulin Maternal insulin is not transferred across the placenta The major glucose

transport protein in the human placenta at term is GLUT 1 which does not have

insulin receptors [64] The fetal pancreas develops in the first half of pregnancy and

31

sheep experiments have shown that by mid-gestation measurable insulin is produced

[69] Fetal insulin secretion consists of both basal secretion and glucose-stimulated

secretion Studies on pregnant sheep have revealed that both basal and glucose-

stimulated insulin secretion increases over gestation and responds to changes in fetal

glucose concentration as well as duration and pattern of change Chronic marked

hyperglycemia in sheep gave down-regulation of both glucose-stimulated and basal

insulin secretion whereas pulsatile hyperglycemia increased fetal insulin secretion

[7071] Hypoglycemia has been shown to decrease basal- and glucose-induced insulin

secretion [72] Insulin is an important growth hormone in utero and deficiency of

insulin leads to growth restriction in the fetus Fetal hyperinsulinaemia leads to

increased weight gain particularly in species with a high body fat content at birth like

the humans [73] The mechanism in which insulin stimulates fetal growth is in part

thought to be its anabolic effects on glucose and amino acid metabolism through

increased cellular uptake of glucose that maximizes the transplacental concentration

gradient for glucose and hence increases transport of glucose across the placenta

Lipids

Fatty acids are necessary for the fetus for various purposes as a source of energy as elements

of cellular membranes and for development of tissues and organs Maternal triglycerides (TG)

have been suggested as a more important source of fatty acids than nonsesterified fatty acids

(NEFAs) TG are hydrolyzed by placental lipases (lipoprotein lipase) to free fatty acids which

can diffuse freely across the placenta or be taken up by the placenta via fatty acid transport

proteins [51] Total levels of fatty acids are lower in the fetal than the maternal circulation but

the fatty acid profile is different with higher proportions of long chain polyunsaturated fatty

acids [9]

Amino acids

Fetal plasma amino acid concentrations are higher than maternal concentrations Amino acids

are taken up against a concentration gradient by secondary active transport systems in the

MVM More than 20 amino acid transport systems are expressed in the human placenta [74]

These are categorized as heterodimeric (eg system L) or monomeric (eg system A) Amino

32

acids are required by the fetus for protein synthesis but can also be metabolized by the fetus

[9] Reduced fetal plasma concentration of a number of amino acids have been reported in

studies of IUGR [75]

c Endocrine functions

The placenta metabolizes a number of substances and releases metabolic products into the

maternal andor fetal circulations The placenta thus has endocrine paracrine and autocrine

functions There are numerous hormones that are produced by the placenta in order to

maintain and regulate pregnancy [9]

Estrogen

Estrogens are produced by the syncytiotrophoblasts in large amounts during pregnancy 80-

90 of the the steroids produced in the placenta are secreted into the maternal blood The

fetus is the main source of the precursors used for production of estrogens and they are

produced in the fetal adrenal gland and the fetal liver [76] The estrogens act as specialized

growth hormones for the reproductive organs of the mother [9]

Progesterone

Progesterone is produced by the corpus luteum in the first weeks of pregnancy and later by

the trophoblasts in the placenta The plasma levels increase throughout pregnancy

Progesterone is synthesized largely from maternal plasma low density lipoprotein (LDL)

cholesterol The fetus contributes few or no precursors for progesterone synthesis In normal

pregnancy there is little de novo synthesis of progesterone in the fetus The progesterone

preferentially enter the maternal circulation and very little crosses to the fetus [76]

Progesterone inhibits uterine contractions

Human Chorionic Gonadotropin (HCG)

HCG is a glycoprotein which is structurally similar to Luteinizing Hormone (LH) Follicle

Stimulating Hormone (FSH) and Thyroid Stimulating Hormone (TSH) and is mainly

33

synthesized in the syncytiotrophoblasts HCG enters the maternal circulation at the time of

implantation and is detectable in maternal plasma and urine The concentration peeks at week

8-10 of pregnancy after which it declines The biological function is believed to be

maintenance of the corpus luteum stimulation of fetal testicular testosterone secretion and

stimulation of the maternal thyroid gland [76]

Human Placental Lactogen (HPL)

HPL is a polypeptide which is structurally similar to human growth hormone and human

prolactin It is mainly produced by the syncytiotrophoblasts It is detectable in the maternal

circulation by week 5 and rises steadily and approximately proportional to placental mass

until week 34-36 There is little HPL detectable in maternal urine or in fetal plasma HPL

participates in metabolic processes by stimulating lipolysis HPL thereby functions primarily

to ensure nutrient supply to the fetus by efficient mobilization of maternal tissue stores [76]

34

16 Sexual dimorphism in fetal growth and placental function

There are well-known sex specific differences in fetal growth Birthweight of boys is

generally higher than that of girls Body composition also differs boys being longer and

having larger head circumference than girls whereas girls have higher fat percentage than

boys [16] Fetal-placental weight ratio is greater in boys than in girls indicating a higher

placental efficiency among boys [77] Male fetuses grow faster than girls in utero and one

study reported that the difference was statistically different from week 28 onwards [78] Boys

outnumber girls at birth A study from the Norwegian Birth Registry (MBR) found a ratio of

106 among all births This ratio was higher among births in lower gestational age groups as

high as 248 in 16-19 weeks of gestation [79] Similar findings have been reported in multiple

populations [80] Perinatal mortality is generally higher in boys than in girls and in the study

from MBR of Norway it was approximately 20 higher in boys than girls across the whole

range of gestational age groups [79] Attempts have been made to explain the increased

vulnerability observed in boys by sex specific differences in the developmental environment

including possible differences in placental functions Although there are obvious differences

in fetal growth to my knowledge there are no published data on sex specific differences in

nutrient transport across the placenta However there are reports on sex specific differences

in other aspects of placental function especially related to inflammatory responses and

endocrine functions In pregnancies complicated with maternal asthma there was increased

cytokine production in male placentas compared to female placentas [81] Differences in

cytokine production have been suggested to contribute to the observed increased incidence of

preterm delivery in males [82] Glucocorticoids given as repeated doses have been shown to

reduce fetal growth [83] Data suggest that the male and female fetal-placental unit responds

to cortisol in a differential manner Among pregnant women with asthma there were similar

levels of maternal cortisol but female fetuses responded with a reduction in birthweight

whereas the growth of the male fetuses was normal [84] Data on placental properties from

male and female are generally pooled but significant findings may be lost as male placentas

might have different responses than female placentas The different strategies to cope with

the same maternal environment has been summarized by V Clifton [84] She proposed that

male responses lead to minimal placental adjustment in gene and protein expression and that

the target is to increase or continue growth resulting in a greater risk of adverse outcome

Females on the other hand have multiple adaptations in placental gene and protein expression

and minor reduction in growth resulting in increased survival

35

17 Preeclampsia

Preeclampsia is defined as new onset hypertension (blood pressure gt14090) and proteinuria

(gt03 g per 24 hours) in the second half of pregnancy [85] This pregnancy complication

affects between 3 to 5 of all pregnancies depending on the population Preeclampsia is a

leading cause of mortality and morbidity for both mother and child worldwide particularly in

the developing world Worldwide preeclampsia accounts for more than 50 000 maternal

deaths annually [86] Risk factors include genetic factors multiple pregnancies high maternal

age obesity insulin resistance preexisting hypertension diabetes mellitus and renal disease

[87] Around 70 of cases of preeclampsia occur after 37 weeks of gestation [88]

Clinical picture

The symptoms of preeclampsia are diverse reflecting the underlying syndrome The systemic

vascular involvement is reflected not only in hypertension and proteinuria but can likewise

affect the vasculature in other organs like the liver and the brain When the liver is involved

symptoms and signs include abdominal pain nausea vomiting and elevated liver enzymes In

the case of HELLP (hemolysis elevated liver enzymes and low platelets) all these are present

along with the disturbances in the coagulation system In case of brain involvement visual

disturbances and eclampsia can occur Cerebrovascular complications like stroke and cerebral

hemorrhage are other feared maternal complications The fetus of preeclamptic pregnancies

faces increased risk of oligohydramnios IUGR and prematurity [89]

Classification

Preeclampsia has both a multifactorial pathogenesis and a heterogeneous clinical presentation

which complicates classification Classifications in use are according to pathophysiological

characteristics clinical severity presence of other maternal or fetal characteristics or

gestational age at presentation Classification based on pathogenesis suggests two broad types

of preeclampsia placental and maternal preeclampsia reflecting which element is more

prominent in the pathophysiology These subtypes are more of a theoretical framework than

different biological entities as most cases will rather be represented by a combination of both

The dichotomized pathophysiological classification can briefly be described as placental

preeclampsia when there is an abnormal placentation but basically a normal maternal

36

endothelium and maternal preeclampsia when the maternal endothelium is dysfunctional and

the placentation normal Classification according to severity of disease is used by American

College of Obstetrics and Gynecology (ACOG) Severe preeclampsia is defined as

hypertension (gt160110) and proteinuria (gt5 g per 24 hours or +3 on dipstick) or

accompanying symptoms and signs like oliguria cerebral disturbances impaired liver

function thrombocytopenia or fetal growth restriction [85] Early onset preeclampsia is often

defined as presentation before 34 weeks and late onset as after 34 weeks of gestation These

subtypes have different clinical presentations with the early-onset typically exhibiting more

serious clinical featuressymptoms and fetal growth restriction than the late onset [90]

Pathophysiology

Clinical symptoms of preeclampsia arise in the second half of pregnancy which can be

considered the last stage in the development of the disorder The preceding stages include the

placentation process which involves an immunologically regulated interaction between the

placenta and the maternal endothelium Placenta is necessary for the development of

preeclampsia but preeclampsia can occur without a fetus as in hydatidiform mole The

symptoms disappear after delivery of the placenta In preeclampsia the trophoblast invasion is

restricted to the decidua and does not reach the inner third of the myometrium resulting in

inadequate remodeling of spiral arteries The normal loss of smooth muscle and enlargement

of the spiral arteries is therefore restricted

Normal placentation further requires immune tolerance for fetal and placental antigen which

might be altered in preeclampsia There is a low-grade systemic inflammatory response

present in normal pregnancy which is enhanced in preeclampsia [91] The maternal

endothelium becomes activated and eventually dysfunctional Preexisting maternal vascular

dysfunction might render the maternal endothelium more sensitive to the burden of these

factors leading to endothelial dysfunction

Disturbed endothelial maintenance

In patients with preeclampsia there is an angiogenic imbalance in the circulation resulting in

more anti-angiogenic than angiogenic factors ie more of endothelium-disturbing and less

endothelium-supportive factors The vascular endothelial growth factors (VEGF-family) are

37

involved in angiogenesis and endothelial maintenance by affecting migration and

differentiation of endothelial cells [92] The family consists of several glycoproteins

including VEGF-A and PlGF among others Both of these have pro-angiogenic effect The

VEGF receptors are present on vascular endothelial cells and include VEGFR-1 (Flt-1) and

VEGFR-2 (KDR) VEGF binds to both receptors whereas PlGF binds exclusively to VEGFR-

1 (Flt-1)

Figure 7 Angiogenic imbalance

sFlt-1

sFlt-1 is a soluble form of the VEGFR-1 produced by alternative splicing [93] Placentas from

preeclamptic pregnancies show higher expression of sFlt-1 mRNA than normal placentas [94]

How much placenta actually contributes to the circulating sFlt-1 is however not settled sFlt-1

binds free VEGF and free PlGF and thereby inhibits their beneficial actions on the vascular

endothelium sFlt-1 increases with gestational age in normal pregnancy but is significantly

higher in women destined to develop preeclampsia from approximately week 26 and peaks

around week 34 [95]

38

sEndoglin

The transforming growth factor-β (TGF- β) family of proteins is known to be involved in

angiogenesis but has diverse actions in many cells Endoglin is a TGF-β coreceptor expressed

in endothelial cells and syncytiotrophoblasts of the placenta [87] A soluble form of endoglin

(sEng) is present in sera from preeclamptic patients There is a three- five- and tenfold

increase in sEng in mild PE severe PE and HELLP syndrome respectively [96] Endoglin

mRNA expression in placentas from preeclamptic pregnancies is fourfold increased compared

to healthy pregnancies [96] But again the placental contribution to circulating sEng is

unclear sEng increases with gestational age but in women destined to develop preeclampsia

the increase is significantly higher than healthy controls from week 23 (preterm PE) and week

30 (term PE) Interestingly women destined to deliver a SGA infant had increased sEng

levels from week 10 [95]

sEng and sFlt-1 given together increased capillary permeability in the lungs liver and kidney

of mice and induced hypertension in pregnant rats [96] demonstrating a possible combined

action of sFlt-1 and sEng in the pathogenesis of PE

PlGF

Placental growth factor is one of the members of the VEGF-family which has proangiogenic

activity [92] In non-pregnant women circulating levels are low but PlGF can be produced by

the heart and lungs skeletal muscle and adipose tissue PlGF is expressed by the placenta in

particular the syncytiotrophoblasts [97] In pregnancies complicated by preeclampsia PlGF

concentrations are lower than normal pregnancies [98] In normal pregnancy PlGF can be

detected from first trimester and increases until around week 33 after which it declines

towards term PlGF binds to the VEGFR-1 (Flt-1) receptor PlGF is necessary to stimulate

angiogenesis eg after myocardial injury The function of PlGF in pregnancy is not clear but

might be to regulate maternal vascular function by displacing VEGF from the Flt-1 receptor

so that it binds to the more active Flt-2 receptor (KDR) [87]

39

Figure 8 Endothelial integrity and dysfunction

VEGF

PlGF

Flt1

(VEGFR-1)

VEGF

PlGF

Endothelial integrity

Tore Henriksen 2006

VEGF

PlGF

Flt1

(VEGFR-1)

VEGF

PlGF

Endothelial dysfunction

Tore Henriksen 2005

Treatment

There is no causal treatment besides delivery of the baby and the placenta Symptomatic

antihypertensive treatment should be given to reduce maternal complications [85]

Preeclampsia can be complicated by eclampsia stroke disseminated intravascular coagulation

(DIC) HELLP placental abruption and acute renal failure Because the only treatment is

delivery preeclampsia leads to prematurity and increased risk of perinatal mortality and

morbidity

Prevention

40

Studies assessing interventions to reduce rate or severity of preeclampsia have been

conducted There is insufficient evidence to recommend rest reduced salt intake fish-oil

supplementation and antioxidant vitamins as preventive measurements [99] A Cochrane

review concluded that low-dose aspirin had small to moderate benefits (15 risk reduction)

when used for prevention of preeclampsia but that more information is needed to assess

which women are most likely to benefit when to start treatment and at what dose [100]

Calcium supplementation reduced risk of preeclampsia and can be considered for high risk

groups in low-intake populations [101]

Prediction

Many features of preeclampsia are exaggerated responses also present in normal pregnancies

In terms of diagnosis or prediction it is difficult to draw a clear distinction between normal

and abnormal No test predictive or diagnostic can be expected to distinguish absolutely

between different degrees of features that are common to all pregnancies Many tests have

been assessed as potential predictors of preeclampsia but no single test has yet met the

clinical standards for a predictive test Combinations of tests such as ultrasound assessment of

uterine artery Doppler waveforms and serum markers have been suggested as have ratios of

antiangiogenic and proangiogenic factors However sensitivity and specificity of the markers

PlGF sFlt-1 and sEng are too poor for accurate identification of preeclampsia in clinical

practice and hence not recommended used alone for the prediction of preeclampsia [102]

Predictive tests could ideally either identify those destined to develop preeclampsia during

pregnancy or differentiate between a serious or mild form among those diagnosed with

preeclampsia The latter would be of clinical importance in handling these patients

Long-term complications

Risk of recurrent preeclampsia depends on severity and onset of preeclampsia in the previous

pregnancy but can be up to 40 for severe disease [103] Women with a history of

preeclampsia have an elevated risk of cardiovascular disease later in life According to a

meta-analysis the risk of hypertension is 3-4 times the risk for women without preeclampsia

41

and the risk of death from cardiovascular and cerebrovascular disease about twice as high as

in women without preeclampsia [104] The mechanisms for the increased risk are not yet fully

understood but shared risk factors for preeclampsia and cardiovascular disease may jointly

predispose [105] This could be the case for chronic hypertension diabetes mellitus and renal

disease

42

2 Aims of the study

Overall aim

The overall aim of this thesis was to gain insight into the associations between maternal

nutritional and metabolic factors and fetal growth and aspects of placental function in normal

and preeclamptic pregnancies

Specific aims

Paper 1

The aims were to

1) Estimate and compare the effects of maternal characteristics on birthweight and on fetal

growth in third trimester

2) Introduce placental weight as a possible determinant of birthweight and of fetal growth in

third trimester

We hypothesized that maternal factors and placental size were associated with birthweight

and fetal growth

Paper 2

Given the findings in Paper 1 the aim was to study the effects of maternal factors (parity

BMI gestational weight gain and fasting glucose) on placental weight stratified by fetal sex

We hypothesized that the maternal factors mentioned above affected placental weight Based

on emerging evidence we also hypothesized that there were differential effects between fetal

sexes

Paper 3

Based on the observations in Paper 1 and 2 the aims were to

1) Establish an in vivo model in the human

2) To use the model to study human placental transfer of glucose in vivo to describe the

glucose and insulin concentrations in the uteroplacental and umbilical circulation in healthy

43

pregnancies at term and to explore the relation between maternal and fetal glucose

concentrations

We hypothesized that maternal plasma glucose was the major determinant of the fetal venous-

arterial gradient

Paper 4

Preeclampsia is a pregnancy specific placenta dependent disorder Preeclampsia has two

prominent features maternal vascular dysfunction and placental insufficiency Using the in

vivo model the aim was to investigate factors that may link placental disturbance to maternal

vascular dysfunction For this purpose sFlt-1 and sEng were chosen

We hypothesized that both sFlt-1 and sEng originate in placenta by finding that the plasma

concentration was higher in the maternal venous than the arterial side of the uteroplacental

circulation

44

3 Materials and methods

This thesis consists of four papers based on two separate studies that differ in design

population and methodological issues and will therefore be described separately

The STORK study

The STORK study is a prospective longitudinal study performed in the period 2001-2008 A

total of 1031 healthy pregnant women who gave birth at Oslo University Hospital

Rikshospitalet Norway and their newborn infants were included in the study Inclusion

criteria were healthy women of Scandinavian heritage with singleton pregnancies Exclusion

criteria were multiple pregnancies known pregestational diabetes and any severe chronic

diseases (lung cardiac gastrointestinal or renal) as well as any malformations discovered at

the routine ultrasound examination at week 17-19

Population

Eligible women were identified by one of the three PhD candidates in the project Invitation to

participate was sent to eligible women as they were registered for obstetric care at the

beginning of pregnancy Those interested in participating confirmed by phone to a secretary

who enrolled them in the study The number of women invited to participate varied over time

due to capacity The capacity for the oral glucose tolerance test (OGTT) was the ldquorate-limiting

steprdquo The drop-out rate was very low 33 of those who were included Thirty-two women

were excluded because of twin pregnancies or malformations that were diagnosed at the

routine ultrasound scan

45

Figure 9 Flow chart showing inclusion of participants in the STORK study

Withdrawn before

inclusion

n=141

Excluded

n=32

Lost

n=37

Invited to participate

n=4122

Accepted invitation

n=1241

Included

n=1100

Followed up

n=1031

Study design

The STORK study has a longitudinal design Each pregnant woman had four antenatal visits

(visit 1-4) scheduled at weeks 14-16 22-24 30-32 and 36-38 of pregnancy The newborns

were examined shortly after birth

Data collection

Clinical data

Background data was collected at the first visit including past medical and obstetric history

Clinical examination was repeated at every visit Data on the delivery and postpartum period

were extracted from hospital records

Blood samples

Blood samples were drawn at each visit between 0730 and 0830 after an overnight fast

centrifuged and stored at -80ordm C immediately Plasma glucose was measured by Accucheck

(Roche Diagnostics Mannheim Germany)

46

Birthweight

Newborns were weighed on a calibrated scale and measured by the attending midwife or

childrenrsquos nurse within two hours after birth

Ultrasound

Ultrasound examinations were done at visit 2 - visit 4 using an Acuson Aspen machine

(Acuson Mountain View CA USA) Biometric measurements included head circumference

(HC) abdominal circumference (AC) and femur length (FL) Each measurement was made

three times and the mean value was calculated and used in the analyses Estimated fetal

weight (EFW) was calculated by Combs formula [106] Percentiles for estimated fetal weight

and the individual biometric measurements were calculated according to Norwegian charts

[107108] Fetal growth in the third trimester was calculated as the difference between

measurements made at visit 3 and visit 4 for EFW and HC AC or FL respectively

Table 1 Data collection in the STORK study

Statistical analysis

Descriptive statistics were used to characterize the study population Bivariate associations

were explored by scatter plots and correlation analyses Univariate linear regression was used

to study the associations between selected maternal characteristics and the dependent

variablesoutcome variables birthweight and several fetal growth parameters in Paper 1 and

placental weight in Paper 2 Variables with a p-value lt 01 were considered in the multiple

linear regression models Multiple linear regression models were used to study the

Visit 1

14-16 w

Visit 2

22-24 w

Visit 3

30-32 w

Visit 4

36-38 w

At birth

Clinical examination + + + + +

Anthropometric measures

(skin fold thickness)

+ + + + +

Fasting blood samples + + + +

Oral glucose tolerance test + +

Ultrasound

(evaluation of fetal growth)

+ + +

Diet questionnaire + +

Physical activity questionnaire + +

47

associations between selected maternal characteristics and the outcome variables birthweight

fetal growth and placental weight A p-value lt 05 was considered statistically significant

All analyses were done by SPSS 180

Ethical aspects

All participants signed a written consent The study was approved by The Regional

Committee for Ethics South Norway (S- 01191)

48

The STORK-Placenta study

Study design

The STORK-Placenta study was designed to serve several purposes One purpose was to

study placental aspects of fetal growth and this was done as a cross-sectional study among

healthy pregnant women Secondly the study served as a case-control study with two groups

one consisting of preeclamptic patients and one with healthy controls

Population

There are two subgroups of the STORK-Placenta study in Paper 3 and Paper 4 respectively

In Paper 3 we included 40 women Inclusion criteria were healthy non-smoking women with

uncomplicated singleton pregnancy who were scheduled for elective caesarean section

Exclusion criteria were pre-existing co-morbidity any medication and pregnancy

complications like preeclampsia or insulin-dependent gestational diabetes Women who

arrived at the delivery ward with contractions prior to scheduled caesarean section were

excluded The recruitment was done at the out-patient clinic either during the appointment

when caesarean section was decided or during scheduled preoperational information

In paper 4 we included 12 patients with preeclampsia and 7 healthy pregnant women

Inclusion criteria for the study group were the diagnosis of preeclampsia and indication for

caesarean section prior to labour The control group consisted of healthy pregnant women

scheduled for elective caesarean section

Data collection

Medical and obstetrical history was taken at inclusion Clinical data was collected at inclusion

and at the day of delivery

Blood sampling

Blood samples were drawn from both the maternal and the umbilical (fetal) circulation during

caesarean section in spinal anaesthesia Fasting maternal blood samples were obtained by the

obstetrician from the uterine vein preferable on the same side as placenta just before uterine

49

incision Simultaneously blood was drawn by the anaesthesiologist from an arterial line in the

radial artery We assumed similar blood composition in the radial and the uterine artery In

addition blood was drawn from a venous catheter in the cubital vein or dorsal vein network of

the hand Directly after delivery blood samples were obtained from the umbilical artery and

vein immediately after cord clamping Blood was drawn into SAFETY Blood Collection Set

with Luer Adapter (Vaccuette Geiner Bio-One GmbH Austria) Blood samples were

immediately transferred to ethylenediaminetetraacetic acid (EDTA) vacutainers and stored on

ice until all samples were obtained They were then centrifuged at 4-6ordmC 2500 G for 20

minutes before the supernatants were removed and aliquotted and stored at -80ordmC until

analyses were performed

Analyses of samples

Glucose and insulin

Analyses were performed according to standard laboratory methods (Department of Medical

Biochemistry Oslo University Hospital Rikshospitalet) during three consecutive days

Glucose was measured using the hexokinaseglucose-6-phosphate dehydrogenase method

(Roche) Insulin was analysed using the Elecsys insulin analysis which is an enzyme-linked

immunosorbant assay (ELISA) technique with two monoclonal antibodies (Roche)

sFlt-1 and sEng

The concentrations of sFlt-1 and sEng were measured by commercially available ELISA kits

(RampD Systems Minneapolis MN USA) Assays were conducted in duplicate and in one run

The coefficients of variance were lt 10

50

Statistical analyses

Descriptive data were reported as mean values with standard deviations (SD) or percentages

as appropriate The differences in maternal characteristics between groups were compared by

unpaired t-test (Paper 4)

Glucose values were reported as mean values (SD) Comparisons between concentrations of

glucose in maternal and fetal vessels respectively were performed by paired t-tests Due to

skewed distributions insulin concentrations were reported as median values with inter quartile

ranges (IQR) and comparisons of related samples were performed by Wilcoxon sign rank test

Correlations were reported as Pearsonrsquos correlation coefficient if one variable was normally

distributed whereas Spearmanrsquos rank correlation coefficient was used in the case of

correlation between two skewed variables

The distribution of the concentrations for sFlt-1 and sEng were not normally distributed

hence they were log transformed to obtain normal distribution in order to use parametric

methods for statistical analyses Arithmetic median levels are reported in the text and figures

The differences in concentrations between groups were compared by unpaired t-test and the

concentrations in the radial artery and uterine vein from the same individual were compared

by paired t-test However non-parametric tests on the original data gave the same results

Ethical aspects

All participants signed a written consent The study was approved by The Regional

Committee for Medical Research Ethics South Norway (S-071742011-2419)

51

4 Summary of results

Paper 1

In Paper 1 we analyzed the associations between selected maternal characteristics and

birthweight measured as z-scores adjusted for gestational age and fetal sex We found that the

following maternal characteristics were independent determinants of birthweight and

statistically significant in the multiple regression model

Parity (B 046 95 CI 033-059 plt0001)

BMI (B 0048 95 CI 003-006 plt0001)

Gestational weight gain (B 006 95 CI 004-008 plt0001)

Fasting glucose (B 033 95 CI 018-048 plt0001)

In addition placental weight was a determinant for birthweight

Placental weight (B 041 95 CI 038-044 plt0001)

Adjusting for placental weight in the multiple model left the following maternal determinants

statistically significant

Parity (B 036 95 CI 025-047 plt0001)

BMI (B 0018 95 CI 0004-003 p= 0012)

Gestational weight gain (B 0036 95 CI 002-005 plt0001)

Fasting plasma glucose (B 022 95 CI 0009-034 plt0001)

Introducing placental weight as a covariate reduced the effect estimate of the other variables

in the model by 62 for BMI 40 for weight gain 33 for glucose and 22 for parity

The magnitude of reduction was estimated by change in the regression coefficient B of the

linear regression

Fetal growth in third trimester was estimated as the difference in EFW percentiles between

visit 3 and visit 4

In the multiple model the following maternal determinants remained statistically significant

Parity (B 473 95 CI 016-807 p=0006)

BMI (B 064 95 CI 023-106 p=0002)

Gestational weight gain (B 070 95 CI 024-116 p=0003)

52

In addition placental weight was a determinant for intrauterine growth

Placental weight (B 260 95 CI 16-36 plt0001)

Adjusting for placental weight in the multiple model left the following determinants

significant

Parity (B 39 95 CI 075-70 p=0015)

BMI (B 049 95 CI 008-089 p=002)

Gestational weight gain (B 060 95 CI 015-106 p=001)

Introducing placental weight reduced the effect of BMI on intrauterine fetal growth by 23

weight gain by 17 and parity by 14

We also analyzed the associations between maternal factors and the individual biometric

measurements Results from the multiple analyses for the increase in abdominal

circumference showed statistically significant associations for

Parity (B 018 95 CI 007-029 p=0001)

BMI (B 0022 95 CI 0005-003 p=0002)

Gestational weight gain (B 0026 95 CI 0008-004 p=0001)

Fasting glucose (B 044 95 CI -008-017 p=048)

In addition placental weight was a determinant for increase in abdominal circumference

Placental weight (B 011 95 CI 008-014 plt0001)

In the multiple model adjusting for all listed variables and placental weight fasting plasma

glucose was not significant (B 0016 95 CI -011-014 p=08) BMI reached borderline

significance (B 0014 95 CI 000-0028 p=0048) as an independent determinant when

adjusted for parity weight gain and placental weight For growth of the fetal abdominal

circumference BMI showed the largest reduction in B (36 ) when placental weight was

included

53

Paper 2

Given the importance of placental weight for birthweight and fetal growth we studied the

associations between maternal factors and placental weight in Paper 2 Mean placental weight

was 711 g (SD 156)

In the multiple regression model the following maternal factors were independent

determinants of placental weight

Parity (B 292 95 CI 101-484 p=0003)

BMI (B 67 95 CI 41-93 plt0001)

Gestational weight gain (B 56 95 CI 28-84 plt0001)

Fasting glucose (B 329 95 CI 100-557 p=0005)

Boys were heavier (3667 g vs 3494 plt0001) and longer (513 cm vs 503 cm plt0001)

than girls Boys also had a higher fetal placental ratio than girls (526 g vs 508 plt0001)

When stratified by fetal sex fasting glucose was significantly associated with placental

weight in females but not in males

Paper 3

We measured glucose and insulin concentrations in the uteroplacental and umbilical

circulations and calculated arterio-venous gradients The subjects were 40 healthy women

with a mean age of 36 years (SD 32) Mean birthweight was 3571 (SD 527) g range 2680-

4955g

The highest concentration of glucose was found in the maternal arterial circulation with a

mean concentration of 471 mmoll (SD 048) The uterine vein had a lower concentration

giving an arterio-venous difference of 029 mmoll on the maternal side The maternal

concentration of glucose was higher than the fetal concentration The maternal-fetal gradient

was 122 mmoll (SD 042) The concentration in the umbilical vein was 384 mmoll (SD

041) In the umbilical artery the concentration was lower 348 mmoll (SD 045) giving a

fetal venous-arterial difference of 038 (SD 031)

54

Maternal arterial and fetal venous concentrations of glucose were highly correlated (r=086

plt0001) Maternal arterial glucose concentration was not significantly correlated to the fetal

glucose v-a difference (r=03 p=007) The maternal a-v glucose difference was neither

correlated to the level of glucose in the umbilical vein nor the fetal glucose difference The

maternal-fetal gradient was highly correlated to the fetal glucose difference (r=08 plt0001)

The maternal-fetal glucose gradient was also correlated to the glucose concentration in the

umbilical artery (r=-038 p=0017) whereas it was not correlated to the glucose concentration

in the umbilical vein Similarly the fetal glucose v-a difference was only correlated with the

glucose concentration in the umbilical artery (r=-045 p=0004) but not with the glucose

concentration in the umbilical vein

The glucose concentration in the umbilical vein was not correlated to birthweight or placental

weight whereas correlation between the fetal glucose v-a difference and birthweight just

reached borderline significance (r=032 p=0049)

We found no relation between maternal and fetal insulin values (rho=-01 p=057) Maternal

and fetal concentrations of insulin were not statistically different On the maternal side

glucose and insulin concentrations were correlated (r=052 p=0001) On the fetal side

however no such correlation was found (r=012 p=048) Fetal insulin was correlated to both

placental weight (r=046 p=0003) and birthweight (r=058 plt0001)

Paper 4

We measured the anti-angiogenic factors sFlt-1 and sEng in a group of preeclamptic patients

and in healthy controls Both factors have been suggested to be released by the placenta and

involved in the pathogenesis of preeclampsia

Preeclamptic women had

Higher concentration of sFlt-1 than healthy controls (median of 17450 pgml of sFlt-1

compared to 5055 pgml in the control group p= 0003)

Higher concentration of sEng than healthy controls (median of 687 ngml in the

preeclampsia group versus a median of 287 ngml in the control group p= 0003)

55

We compared the concentration in the blood entering the uteroplacental unit (radial artery as a

proxy for uterine artery) and the blood leaving the uteroplacental unit (uterine vein)

Preeclamptic women had

Higher concentration of sFlt-1 in the uterine vein than in the radial artery (22450 vs

17450 pgml p=0005) whereas the concentration of sEng was not statistically different

(757 vs 687 ngml p=012)

Among healthy controls

No significant differences in the concentration between the uterine vein and the radial

artery for sFlt-1 (6193 vs 5055 pgml p=039)

No significant differences in the concentration between the uterine vein and the radial

artery for sEng (307 vs 287 ngml p=059)

56

5 Discussion

51 Methodological issues STORK

511 Design

The STORK study has a longitudinal design with four antenatal visits and observations at

birth for the 1031 women and children included Longitudinal studies are well suited to study

associations between explanatory variables and outcomes but not suitable to assess causality

The associations found in our study would need to be tested in a RCT or experimental model

to assess causality

512 Validity

The word valid is derived from the Latin validus meaning strong Validity in terms of

research refers to whether the results obtained answer the questions asked in the study

Validity can further be divided into internal and external validity [109]

Internal validity

Internal validity refers to whether the conclusions reached are likely to be correct for the

circumstances of that particular study Bias undermines the internal validity and includes

selection bias information bias and confounding bias [110]

Selection bias

Selection bias can result when the selection of subjects into a study (subject selection bias) or

their likelihood of being retained in the study (loss to follow up bias) leads to a result that is

different from what you would have obtained if you had enrolled the entire target population

[110]

57

Subject selection bias

In the current study invitation to participate was sent to 4122 and 1241 accepted the invitation

The number of invitations sent per week varied according to the capacity to enroll in the study

and the limiting factor was four Oral Glucose Tolerance Tests per day There were periods of

reduced capacity like holidays when fewer invitations were sent but it is not likely that the

women invited would be any different to the ones not invited due to varying capacity

The self-selection procedure (the women themselves phoned to be enrolled) might have

resulted in selection of women that were particularly motivated to participate The opportunity

to get closer follow-up than standard antenatal care may have caused selection bias Three

evaluations of fetal well-being and fetal growth by ultrasound could theoretically have

attracted women with a previous history of fetal growth abnormalities Data on birthweight of

previous children revealed that for those who had one previous child average birthweight was

3655 g (SD599) whereas the second child on average weighed 3808 g (SD 706) The data was

normally distributed with no overrepresentation of SGA or LGA (data not shown) Thus there

was no obvious selection of women with a history of fetal growth abnormalities in our study

population

Loss to follow up bias

The number of patients lost was 37 giving a drop-out rate of only 33 The number of

patients excluded was 32 The numbers lost are small and not likely to have influenced the

results substantially All participants had birthweight and placental weight recorded

However the outcome intrauterine fetal growth could only be estimated for those who

attended both third and fourth visit 918 in total Those who gave birth prematurely (54)

were not included in this outcome Maternal characteristics were not different in this group

compared to the total group (data not shown)

The selection bias only influences the results if the women selected or lost differ in either their

characteristics or in the outcomes which does not seem to be the case in our study

Information Bias

Information bias arises if the information has not been gathered in the same way for all

participants It includes observational bias misclassification and measurement errors and can

58

occur during collection of data as well as coding and processing of the data Misclassification

includes classifying binary or discrete variables incorrectly We minimized misclassification

by using mostly continuous variables rather than categorical variables Bias might be

introduced by the observer (interviewer bias biased follow-up) by the study participants

(recall bias) or by measurement tools such as questionnaires or instruments

We might have introduced biased follow-up for at least one group of women The women

diagnosed with gestational diabetes mellitus at visit 3 were taught and encouraged to make

changes in diet and physical activity to prevent further deterioration in their glucose

metabolism This might have had an influence by reducing the outcomes birthweight and

intrauterine fetal growth in third trimester

Recall bias occurs when there are systematic differences in the way subjects remember or

report exposures or outcomes We tried to avoid recall bias by eg using measured weight and

height to calculate BMI instead of self-reported prepregnancy BMI Reviewing available data

on the relationship between self-reported and directly measured height and weight has shown

trends of under-reporting for weight and BMI and over-reporting for height [111]

Measurement errors will be discussed under data collection below

Confounding bias

A confounder is defined in epidemiological terms as a covariate that influence both the

independent and the dependent variable and can be controlled for by adding it to a multiple

regression model Confounders must be identified and then appropriately adjusted for in the

analyses [112] The statistical considerations around confounding will be discussed under

statistical issues in the discussion below

In Randomized Controlled Trials (RCT) confounding is avoided by randomly assigned groups

that differ only in the factor being studied and thereby removes the need to statistically control

for confounders In an observational study like STORK we tried to reduce the need for

adjusting for confounding factors related to comorbidities by selecting healthy women and to

avoid ethnic factors by selecting women of Scandinavian heritage

59

External validityRepresentativity

External validity or representativity refers to whether the results obtained in one study can be

generalized to other situations and to other populations [110]

To assess representativity we did two comparisons Our cohort was compared to a group of

women who delivered at Ullevaringl the largest obstetric unit in Oslo The comparison was

restricted to women of Scandinavian heritage and our cohort only differed in having fewer

smokers and single mothers (data not published)

We also compared our cohort to data from the Birth Registry of Norway Our study

population was comparable to women who gave birth in Oslo in 2009 on parameters like

maternal age parity gestational age (GA) at birth and birthweight (BW)

Figure 10 Comparison between STORK cohort and Oslo

0

10

20

30

40

50

60

Age P0 GA BW

STORK

OSLO 2009

Retrieved electronically from the Birth Registry of Norway [1]

60

513 Statistical issues

Longitudinal data

Analyzing longitudinal data with variables that are correlated over time is a statistical

challenge which can be solved by the use of mixed models However these methods are

complicated and require statistical knowledge that was not readily available to our group We

therefore chose our variables to be able to use conventional linear regression models Fetal

growth was defined as growth between visit 3 and visit 4 thereby confining fetal growth to

the third trimester The whole trajectory of fetal growth was thereby not fully explored

Similarly we only used fasting glucose concentrations at one time point as a covariate in the

multiple models instead of the change in glucose levels over time

Continuous versus categorical variables

We have chosen to use mostly continuous variables both as outcome and explanatory

variables instead of dichotomizing or creating groups This is based on both methodological

theory and published data on physiology in pregnancy Dichotomizing leads to several

problems [113] According to Altman much information is lost the statistical power is

reduced one may underestimate variation and non-linearity in the relation between variable

and outcome may be concealed [114] A large study of hyperglycemia in pregnancy (HAPO)

has shown that there is a linear relationship and no threshold value between fasting glucose

and adverse pregnancy outcomes [115] A similar relationship was seen between BMI and

adverse pregnancy outcomes [116]

Confounders mediators and colliders

A number of potential factors can influence the associations of interest These must be

identified and possibly corrected for in the regression models Whether to adjust for these

factors depend on classification of the factors into true confounders mediators and colliders

[112] Confounders should be included while colliders should no be included in regression

models to avoid introducing bias

A confounder (defined above) can be controlled for by adding it to a multiple regression

model The choice of which confounders to include in the model requires physiological

61

Independent variable Outcome

Confounder

Independent variable Outcome

Mediator

Independent variable Outcome

Collider

knowledge and requires statistical considerations when it comes to the number of observations

required [117] A mediator is considered a covariate that is on the causal pathway between the

independent and the dependent variable A collider is considered a covariate that is related to

both the independent and dependent variable in a common consequence [117] In our material

no included variables were considered to be colliders

Figure 11 Confounders mediators and colliders

62

Mediation

A mediator variable can either account for all or some of the observed relation between two

variables The effect of mediation can be assessed by judging what happens to the relation

between the independent and dependent variable when the mediator is included into the

regression model or not Full mediation would occur if inclusion of the mediation variable

removed the relation between the independent variable and dependent variable This rarely

occurs The most likely event is that the association becomes weaker yet still a significant

path with the inclusion of the mediator Partial mediation occurs when the mediating variable

accounts for some but not all of the relationship between the independent variable and

dependent variable Partial mediation implies that there is not only a significant relation

between the mediator and the dependent variable but also some direct relation between the

independent and dependent variable

One method to assess mediation was proposed by Baron and Kenny in 1986 [118] They laid

out several requirements that must be met to form true mediation relationships which are

summarized below

Step 1 Confirm that the independent variable is a significant predictor of the dependent

variable Independent Variable Dependent Variable

Y = β10 + β11 X + 1

β11 is significant

Step2 Confirm that the independent variable is a significant predictor of the mediator If the

mediator is not associated with the independent variable then it couldnrsquot possibly mediate

anything Independent Variable Mediator

Me = β20 + β21 X + 2

β21 is significant

Step 3 Confirm that the mediator is a significant predictor of the dependent variable while

controlling for the independent variable This step involves demonstrating that when the

mediator and the independent variable are used simultaneously to predict the dependent

63

variable the previously significant path between the independent and dependent variable is

now greatly reduced if not nonsignificant

Y = β30 + β31 X + β32 Me + 3

β32 is significant

β31 should be smaller in absolute value than the original mediation effect (β11 above)

Placental weight can be considered a mediator in this study Regression models are therefore

done with and without placental weight as a covariate in the model to show its role as a

possible mediator We applied the model by Baron and Kenny described above to show a

possible role of the placenta as a mediator Our results point at possible mediating pathways

involving the placenta on the causal pathway to fetal growth In order to quantify how much

of the effect that goes through the placenta we could have applied path analyses However

this method required more advanced statistical methods which were not available

64

52 Data collection STORK

521 Dependent variablesoutcomes

Birthweight

We chose to use birthweight as a summary measure of overall fetal growth It is widely used

and therefore suitable to compare our data to other publications We chose to use birthweight

as a continuous variable We wanted to report associations between maternal factors and

birthweight in the total STORK cohort as previous publications from the same cohort only

reported birthweight in sub cohorts andor using birthweight as a categorical value with a cut-

off of gt4200 g Birthweight was expressed as Z-scores adjusted for gestational age and fetal

sex

The standard score (Z-score) represents the distance between the raw score and the population

mean in units of the standard deviation Z is negative when the raw score is below the mean

positive when above The z-score is calculated as

where

x is the observed value

μ is the mean of the population

σ is the standard deviation of the population

Mean and standard deviation of the population were taken from a Norwegian reference

material [119]

Intrauterine fetal growth

There are no internationally accepted consensus on how to define and assess intrauterine fetal

growth [11] The longitudinal design of the STORK study enabled us to assess intrauterine

fetal growth We chose third trimester visit 3 to visit 4 which is the period of maximum

Z =

x - μ

σ

65

growth and a period in which maternal metabolic factors are important in terms of fetal

growth [120]

Fetal size and fetal growth were estimated by ultrasound Fetal size was expressed as both

estimated fetal weight (EFW) in grams and as EFW percentile according to Norwegian

growth charts [107] Intrauterine fetal growth was defined as the change in estimated fetal size

parameters from visit 3 to visit 4 expressed as either change in EFW (g) or change in

percentiles Combs formula was chosen as the equation to estimate fetal weight as it is the

formula in use in clinical practice at our department and the basis for the growth charts we

used as reference [106]

Errors in ultrasonographic assessment of fetal weight can be attributed to at least two factors

errors due to the equation and errors due to observer error Observer error can further be

divided into intra-observer and inter-observer error [121] Intra-observer error refers to the

variance in measurements performed by the same observer All measurements were

performed three times and we used the mean of the three values to minimize intra-observer

error Inter-observer error refers to the variance in measurements that occur because different

observers measure differently To minimize inter-observer error all measurements were done

by only three investigators and each participant was measured by the same investigator at all

visits Among errors in ultrasonographic assessment of fetal weight observer error has been

shown to be a relatively minor component compared to the larger error due to the equation

[18] To be able to assess fetal growth we compared our data to reference curves based on

data from University of Bergen Norway as that population was considered the most

comparable to our population [107] We also evaluated fetal growth as changes in each of the

three components that make up EFW according to Combs equation namely HC AC and

femur length Once again we compared our data with Norwegian reference data [108]

There are other types of fetal growth charts available Customized curves have been

developed to adjust for factors like race fetal sex parity and maternal size which are factors

known to influence birthweight and factors that differ in different populations [13] We chose

not to use customized growth charts since the aim of our study was to study the effect of

maternal factors on fetal growth In customized charts maternal factors are controlled for and

therefore unsuited to study the effect of maternal factors

Conditional growth curves take into account the estimated size measured at one point and

gives an estimation of the expected growth for a fetus of that particular size for a specified

period of time As an example a larger fetus at the 75 percentile at week 30 will be expected

to grow more during the next weeks than a smaller fetus at the 10 percentile at week 30 during

66

the same period of time Conditioning on a previous measurement gives information on

whether a particular fetus grows fast or slowly relative to other fetuses of the same size We

chose not to use conditional growth curves in the current study as preliminary analyses did not

indicate major changes in the results making use of the conceptionally more difficult variable

less justified

Placental weight

Placenta was weighed including umbilical cord and membranes by the midwife or childrenrsquos

nurse within one hour after birth The placental weight was expressed in grams The placentas

were not trimmed but there is a close correlation between trimmed and non-trimmed

placentas (r= 098) [122]

Rationale for using placental weight as a proxy for placental function

There is no single parameter that measures placental function as placenta has a range of

functions Placental weight was chosen as outcome as a surrogate for placental function

Placental weight is a measure commonly used to summarize placental growth and aspects of

placental function In normal pregnancy it is reasonable to assume that placental weight is

related to aspects of functional capacity of the placenta [123] We had no estimations of

placental weight or mass during pregnancy Placenta exhibits linear growth throughout

pregnancy [5556] making it reasonable to use placental weight after birth instead of

estimations of placental mass during pregnancy

We wanted to use a variable that reflects those aspects of placental function which are

relevant to fetal growth of which nutrient transport is an obvious factor Density or activity of

nutrient transport proteins in the placenta could have been used as an alternative measurement

of placental function but these data are not yet available in our cohort An underlying

assumption for nutrients to be transported across placenta is that the maternal or umbilical

blood flow is not impaired We performed Doppler measurements in the uterine artery and

umbilical artery In our cohort of healthy women only 35 had notching in the uterine artery

at visit 2 and 32 had a pulsatile index above 2 SD for gestational age at visit 4

(unpublished data)

67

Placental weight correlates well with surface area which is a major determinant for nutrient

transport [124] The maternal plasma level of hormones produced in the placenta are directly

related to placental weight [125]

522 Explanatory independent variables

The explanatory variables were chosen based on publications from our study [126ndash129] and

literature on fetal growth in general We selected some maternal characteristics that were

known to influence birthweight in order to study their relation to intrauterine fetal growth

Maternal factors

Maternal age was noted at the first visit in whole years Age was normally distributed

Parity was categorized into P0 and P1+ as the largest difference in birthweight is

known to be between the first child and second child and less between consecutive

children [43]

BMI was calculated based on height and weight measured at the first visit We did not

use pregestational BMI to avoid recall bias and false self-reporting

GWG was calculated as the difference in weight between visit 4 and visit 1 We did

not use weight measured at admission for delivery as there were many missing values

Fasting glucose was measured by the use of Accucheck (Roche Diagnostics

Mannheim Germany) in order to obtain the measured values immediately This

enabled us to inform the women of the result the same morning and in cases of

impaired glucose metabolism to give advice on diet and physical activity during the

consultation Analyses of glucose over the seven years of inclusion revealed that there

was an unexpected increase in fasting glucose of 06 mmolL over time We found no

accompanying increase in maternal age BMI or in insulin that could give a biological

plausible explanation for this increasing trend Thus the time trend in fasting glucose

most likely had an analytical cause The glucose values were de-trended according to

the coefficients from linear regression under the assumption of a linear increase

during the entire period and de-trending of the data removed the increasing trend

[130]

68

Placental weight

The rationale for using placental weight to reflect aspects of placental function has been

discussed above When placental weight was used as an explanatory variable in the regression

models placental weight was entered in 100 grams instead of 1 gram to avoid getting effect

estimates with too many decimals

Placental pathology

There were 55 placentas not characterized as normal which makes up 53 of the samples

Theoretically it is possible that the placental weight in these cases does not reflect function in

the same way as placentas characterized as normal Eg a placenta with infarctions has areas

of tissue that do not take part in nutrient transport Such a small percentage of pathological

placentas are not likely to have influenced the results to a significant extent

69

53 Methodological issues STORK-Placenta

Design

The STORK-Placenta study had a cross-sectional design which means the women were only

examined once which in our study was at delivery This design gives no opportunity to assess

earlier gestational ages or longitudinal changes throughout the pregnancy In Paper 3 all the

study subjects were healthy women and there was no need for a control group In paper 4 we

applied a case-control design in which the preeclampsia group was compared to a control

group of healthy pregnant women

Validity

Internal validity

Selection bias

Only women delivered by cesarean section were recruited to this study This lead to selection

bias for both the healthy women and the preeclamptic patients For the healthy women the

most common indications for cesarean section were prior cesarean section or patient request

due to traumatic previous delivery Few healthy primiparas are delivered by elective cesarean

the exception being breech presentation In Paper 3 the selection therefore resulted in age and

parity that were relatively higher than average Avoiding selection bias in a study like this was

not possible given the population eligible for participation

For the preeclamptic women the selection lead to overrepresentation of early onset

preeclampsia and cases of serious preeclampsia as late onset or less serious cases in many

cases can deliver vaginally In Paper 4 this was reflected in lower gestational age in the

preeclampsia group than the controls

Information bias

We assumed similar blood composition in the radial and the uterine artery This was done to

avoid puncturing the uterine artery as bleeding would be easier to control in the radial artery

As the blood is pumped out of the aorta it is reasonable to assume that the composition does

70

not change substantially between the blood reaching the radial artery compared to the blood

that reaches the uterine artery

External validityrepresentativity

The representativity of the results from the STORK-Placenta study is discussed in light of the

selection of the participants

Parity was higher in Paper 3 than average From our results in Paper 1 and Paper 2 we have

seen that parity was an independent variable with effect on fetal growth In Paper 3 the added

effect of parity on fetal growth could give a bias if the effect of parity also affects the glucose

transport across the placenta Hitherto the question can not be answered So far our results are

only valid for the glucose metabolism among healthy women with relatively normal BMI

Which changes that occur in the glucose metabolism in women with chronic diseases will

probably vary according to the disease Higher BMI would probably influence the glucose

metabolism both directly as higher BMI might lead to higher glucose levels in many cases

but possibly also indirectly by changes in inflammatory factors and by changes in the

transport of other nutrients as amino-acids and lipids

In Paper 4 gestational age was lower in the preeclampsia group than in controls Early-onset

and late-onset preeclampsia are by many considered two different subgroups of preeclampsia

due to the differences in risk factors pathogenesis and clinical presentation [90] Our findings

may not be valid for late-onset preeclampsia where maternal risk factors play a larger role in

the patophysiology and the endothelial dysfunction might be more prominent Therefore it is

possible that the results are valid only when the placental dysfunction is the major feature in

the pathophysiology like in early-onset preeclampsia

Statistical issues

In both papers from the STORK-Placenta study the numbers of participants were relatively

small due to the demanding logistics of the project Small numbers lead to some statistical

challenges that need to be discussed

In Paper 3 we included 40 patients which were sufficient to show significant glucose gradients

on both maternal and fetal side as well as a gradient across the placenta However the small

number restricted the possibilities to study interesting associations between maternal factors

and glucose transport or glucose transport in relation to fetal growth by the use of regression

71

models As an example we found an interesting association between maternal BMI and fetal

glucose v-a difference but the scatter plott revealed one woman with BMI 39 and analyses

showed that without that observation the association was no longer significant

In Paper 4 we found a significant difference in sFlt-1 but not in sEng across the uteroplacental

circulation among preeclamptic patients There is a possibility that lack of power influenced

this finding Possibly a larger sample could have given a significant difference for sEng in

which case our finding could represent a type 1 error (reject the hypothesis that there was a

difference even if it is true)

Both non-parametric tests on original data and parametric tests on log transformed data were

done giving the same results in terms of statistically significant differences We chose to use

the log transformed data for statistical analyses (as that seemed to be the most conventional

method used in relevant references) but presented arithmetic data in figures and tables to

make it easier for the reader

54 Data collection STORK-Placenta

Blood sampling

All procedures were standardized to minimize systematic errors Sampling was therefore done

by a small group of four trained obstetricians and handling the samples in the laboratory was

restricted to only three investigators In the few cases where sampling was inadequate it was

mostly due to failure in inserting the arterial line or in a few cases inadequate amount of blood

obtained from the umbilical artery Blood samples were kept on ice until centrifugation

Blood samples were taken in fasting condition to obtain a steady state situation This is

particularly relevant for glucose and insulin which show large post-prandial variation

Cesarean section was done under spinal anesthesia no participants received oxygen or

intravenous glucose infusion

Analyses

Glucose and insulin were analyzed at the laboratory at Oslo University Hospital The samples

were analyzed during three consecutive days

72

sFlt-1 and sEng were analyzed by commercially available ELISA kits (RampD systems) We

chose to use ELISA kits from RampD for comparison reasons as they were commonly used in

papers on preeclampsia published at the time

73

55 Interpretation of results

Paper 1 and 2

In Paper 1 and Paper 2 we have studied the associations between maternal characteristics

placental weight and fetal growth in healthy pregnant women ie these are studies of normal

physiological relations Together the results from these papers illustrate some of the interplay

between the mother the placenta and the fetus

Paper 1

Paper 1Paper 2

-parity

-BMI

-GWG

-glucose

We found largely the same determinants for both birthweight and intrauterine fetal growth in

third trimester with the exception of fasting glucose (see below) The weight of the placenta

was influenced by similar maternal metabolic and nutritional factors In summary our results

are compatible with the concept that maternal factors can influence fetal growth directly and

indirectly by promoting placental growth

We found a direct effect of maternal factors both on birthweight and intrauterine growth in the

third trimester For both birthweight and intrauterine fetal growth placental weight was an

independent determinant Hence as the placenta grows and becomes larger some of the effect

of maternal factors on fetal growth is likely to be mediated by growth of the placenta

We found independent effects of several maternal factors (parity BMI and GWG) on

intrauterine fetal growth in third trimester We did not find independent effect of age The

small variation in age (SD) might partly explain why we did not find any effect of age

74

Furthermore age has been shown to exhibit an inverse u-shaped relation to birthweight and we

only tested for linear relationships Somewhat surprisingly we did not find an independent

effect of fasting glucose on intrauterine fetal growth in third trimester The discrepancy

between the effect of glucose on birthweight and on intrauterine growth may have several

explanations One possible explanation lies in how fetal growth is assessed Fat accumulation

resulting from increased maternal glucose and subsequent increased insulin secretion in the

fetus is likely to be accumulated on extremities and truncus of the fetus as well as the

abdomen The estimation of fetal size and fetal growth used in our study included assessment

of head circumference abdominal circumference and femur length Of these only abdominal

circumference would be likely to reflect fat deposition We did not however find an

independent association between fasting glucose and change in abdominal circumference

There is no consensus on whether the diagnosis of abnormal growth should be based on EFW

or AC or both [11] Another possible explanation for the described discrepancy could be

found in the concept of conditional growth Conditional fetal growth refers to differences in

expected fetal growth depending on the size estimated at the last measurement As an

example a fetus that is large at week 30 will be expected to grow more in the remaining

weeks of the pregnancy than a fetus that is relatively smaller at week 30 Factors like impaired

glucose metabolism in early pregnancy leading to higher fasting glucose values might have

resulted in a large fetus already at week 30

Placental weight was used as a measure of placental function Introducing placental weight in

the multiple regression models gave two interesting results

First placental weight was an independent determinant of birthweight and fetal growth and

showed a positive effect on fetal growth A small placenta is commonly associated with a

growth restricted fetus hence a reduced placental function Fetalplacental ratio can be used

as an indicator of placental efficiency and includes both fetal weight and placental weight

Preliminary analyses in our material showed that the maternal factors associated with

fetalplacental ratio in the multiple model were maternal age parity and BMI Maternal

gestational weight gain was not significantly associated in the univariate model and hence not

included in the multiple model Fasting glucose was not significant in the multiple model

using fetalplacental ratio as outcome

Secondly placental weight can be viewed as a mediator in the associations between maternal

factors and fetal growth This implies that some of the effect of the maternal factors might

work through growth of the placenta There are several possible biological reasons for the

75

reduced effects of the maternal characteristics on birthweight or intrauterine fetal growth

when placental weight was included in the models The selected maternal characteristics may

exert their effects on fetal growth by affecting transplacental transport Transplacental

transport is affected by blood flow both on maternal and fetal side Furthermore the number

and efficiency of placental transport proteins may also be influenced by maternal factors The

total number of transport proteins is dependent on both the area of the syncytio-endothelial

membrane and the density of the transporting proteins In addition it can not be excluded that

placental production of growth factors may be affected

We have studied both modifiable and non-modifiable maternal factors Parity is a non-

modifiable factor present before pregnancy There is a well-known effect of parity on

birthweight We showed that this effect is evident also for intrauterine growth and placental

weight The effect of parity is relatively larger than many other maternal factors eg larger

than fasting glucose BMI and GWG Modifiable factors include BMI GWG and fasting

glucose BMI and fasting glucose may be modified before pregnancy and GWG and glucose

during pregnancy

The present study did not include data on neither fetal factors that stimulate or inhibit

placental growth function or maternal factors nor placental factors that influence maternal

metabolism Theoretically however there are possible pathways including signals from the

fetus that can stimulate placental growth and possibly placental factors that can influence

maternal metabolism

Taken together the results from Paper 1 and Paper 2 show that maternal factors influence

both placental weight and fetal growth and it is likely that some of the effect on fetal growth is

mediated through placental growth This does not exclude the possibility that an increased

fetal growth following increased maternal energy supply may lead to release of fetal growth

factors that feed back on placental growth

Clinical implications

We have only studied birthweight and intrauterine growth in third trimester which might be

too late to intervene in cases of abnormal fetal growth In order to intervene it is necessary to

know which factors influence intrauterine growth at different gestational ages As both low

76

BMI and low GWG is related to increased risk of IUGR patients with high risk of IUGR

could be advised to increase their BMI or make sure they gain sufficient weight according to

recommendations Similarly as high BMI and high GWG increase fetal growth women could

be advised to obtain a normal BMI prior to getting pregnant and not gain unnecessary weight

during pregnancy As there is a linear and continuous relation between fasting glucose and

adverse fetal outcomes including fetal growth pregnant women with fasting glucose values

just below the GDM criteria can benefit from the same advice concerning diet and physical

activity as GDM-patients receive In particular women with multiple risk factors of impaired

fetal growth should be given advice even if she does not meet the criteria of GDM or obesity

Paper 3

Glucose is the major source of energy for the fetus and the placenta and therefore has an

obvious importance in fetal nutrition Glucose transport across the placenta in humans is

interesting to study for several reasons There is a lack of human in vivo studies in contrast to

the body of evidence on mechanisms and transporter proteins etc from in vitro studies It is of

major importance to acknowledge the distinction between maternal nutrition and fetal

nutrition [2] The placenta is not just a simple conduit for gases nutrients and waste products

but has its own complex metabolism with corresponding requirements for oxygen and

nutrients

In this paper we found a close correlation between maternal and fetal glucose concentrations

which is in line with the concept that the maternal-fetal gradient is the driving force in the

transplacental transport of glucose across the placenta However the fetal v-a glucose

difference was not merely a reflection of the maternal glucose concentration or the

uteroplacental uptake of glucose but rather related to the maternal-fetal gradient and the

concentration in the umbilical artery The relation between maternal and fetal glucose

concentration has been shown in several papers Although the umbilical venous concentration

is closely related to the maternal concentration the fetal v-a difference seemed to be less

related to maternal concentrations but more to the concentration in the umbilical artery fetal

insulin placental weight and birthweight We therefore speculate that the fetus has a saying in

determining the fetal glucose consumption This might at first seem to be in conflict with the

Pedersen hypothesis which was first presented in 1952 [131] His theory was that high

maternal glucose was transferred to the fetus which responds by secreting more insulin

77

which in turn lowers the blood glucose of the newborn Compared to the 1950s pregnant

women of today are older when they get pregnant have higher prepregnancy BMI and gain

more weight in pregnancy The metabolic environment a fetus experiences today is likely to

differ from the environment some decades ago in several aspects more energy-rich altered

balance between glucose and lipids and more inflammation [132] The non-glucose factors

like lipids may have augmented their role as several factors have changed in the population

since the proposal was made by Pedersen We can only speculate as to how the relative

importance of these factors might influence the regulation of transport of nutrients to the

fetus

Our results can not explain or show the complex regulation of glucose transport and

metabolism and leaves us with some unanswered questions We only presented correlation

analyses as we did not yet have enough samples to do multivariate analyses to evaluate the

relative importance of the factors involved We were not able to do path analyses to quantify

the influence of each of these factors Do the relationships we have described work differently

in pathological pregnancies in which there is either abnormal placental function or the mother

exhibits abnormalities in her metabolism or the fetus experiences abnormal growth These

questions can hopefully be answered by future research

The amount of glucose consumed by the placenta can be changed under hypoxic conditions

[63] It is not likely that our participants were hypoxic to a large degree We only measured

oxygen in a few cases which were all normal

Clinical implications

In obstetric practice there are numerous examples of cases of abnormal fetal growth occurring

in pregnancies of healthy mothers with normal metabolism and apparently normal placental

function Placental function might still be compromised resulting in reduced fetal nutrition

Fetal under nutrition may result from compromised transplacental transfer of nutrients In the

other end of the spectrum are the fetuses that experience overgrowth despite strict glycemic

control of their diabetic mothers Some authors argue that this might be due to intermittent

hyperglycemia rather than constant hyperglycemia but another option is that hyperglycemia

is accompanied by other nutrients or other factors that increases the total energy supply to the

fetus

78

Human in vivo studies are rare and therefore valuable in terms of extrapolation to relevant

settings in clinical practice However in vivo settings include multiple factors working

together making it difficult to assess individual effects In vitro settings however can control

for one factor at a time to gain mechanistic knowledge which can hardly be drawn from in

vivo settings The clinical significance of factors operating in vitro is often difficult to assess

Paper 4

The multifactorial etiology and heterogeneous clinical presentations seen in preeclampsia

makes it an intriguing and challenging condition to study Since preeclampsia is a pregnancy

complication in which the placenta is believed to play a crucial role in the pathophysiology it

was both interesting and relevant to choose preeclampsia in order to study aspects of placental

function in pathological pregnancies Furthermore preeclampsia is still a leading cause of

mortality and morbidity worldwide Despite decades of research there is still no causal

treatment leaving timing of delivery the only intervention to balance the needs of the mother

and the fetus

In our study we found as expected that preeclamptic women had higher concentrations of sFlt-

1 and sEng than healthy controls as has been shown in numerous previous publications

Preeclamptic women further had higher concentrations of sFlt-1 in the uterine vein than the

radial artery giving a gradient across the uterus There was no gradient for sEng among

preeclamptic women and no gradients were found in the healthy controls for either of the two

factors tested The gradient across placenta is consistent with the concept that the placenta

secretes sFlt-1 into the maternal circulation The source of excess sFlt-1 and sEng in

preeclamptic patients is assumed to be the placenta based on enhanced expression of both

factors in trophoblastic tissue [133134] Enhanced expression of sFlt-1 and sEng in

trophoblastic tissue does not necessarily prove that the circulating sFlt-1 and sEng found in

preeclamptic patients originate from the placenta or that the placenta is the only source There

is a possibility that sFlt and sEng originate from circulating cells in the maternal circulation or

endothelial cells Peripheral blood mononuclear cells have been suggested to be an additional

extra-placental source of sFlt-1 [134]

Our results support the hypothesis that at least a part of the circulating sFlt-1 originates in the

placenta and is transported into the maternal circulation whereas we did not find evidence to

support that this holds for sEng The discrepancy between our results for sFlt-1 and sEng

could have several explanations

79

There might be a biological difference such that sFlt-1 only or to a larger extent than sEng is

released from the syncytiotrophoblasts in the placenta whereas sEng to a larger extent is

produced elsewhere [135] There might also be a statistical explanation suggesting that we had

inadequate power to show a statistically significant difference in sEng which would represent

a type 1 error (rejecting the hypothesis that there was a difference even if it is true)

In this paper as most studies involving preeclamptic patients and healthy controls there was a

difference in gestational age among cases and controls The difference in gestational age

raises some questions to be discussed There are publications reporting an increase in sFlt-1

and sEng with increasing gestational age both for controls and preeclamptic patients but more

so in preeclampsia [136137] Assuming this relationship for our controls we would expect to

find a lower concentration at week 30 among healthy controls than what we found near term

giving an even greater difference than we observed Thus we do not think that the difference

in gestational age can explain the observed difference in sFlt-1 and sEng between preclamptic

patients and healthy controls We did not include samples from preeclamptic patients at term

as they mostly deliver vaginally Our group of preeclamptic patients thus represents early-

onset preeclampsia In most cases preeclampsia was accompanied by a degree of intrauterine

growth restriction Whether our findings are representative for late onset preeclampsia in

which the placental dysfunction is perhaps less prominent and the endothelial dysfunction

more prominent is not clear from our study

Anti-angiogenic factors in a clinical setting

Anti-angiogenetic factors have been proposed used as diagnostic tools for preeclampsia

There is hope for a therapeutic option in treating preeclampsia in the future but whether

angiogenetic agents can be used to improve the angiogenic imbalance seen in preeclampsia is

not known At the moment the most useful implications of these types of studies is increased

knowledge on the pathogenesis including the possibility to differentiate between early- and

late-onset preeclampsia

80

6 Conclusions

In conclusion results from the first part of this thesis (Paper 1 and 2) underline the importance

of the placenta and placental functions in normal pregnancies Placenta is an important factor

to consider when studying associations between maternal factors and measures of fetal

growth birthweight intrauterine growth or body composition The effect of maternal

metabolic and nutritional factors on fetal growth is likely to go partly through growth of the

placenta There is an important distinction between maternal and fetal nutrition as one has to

consider the placenta as an active organ and not a passive conduit of nutrients and gases

In the second part of this thesis a method has been established that makes it possible to study

placental function in the human in both normal and pathological pregnancies like

preeclampsia

7 Further research

I believe the greatest challenges in the two studies that make up my thesis also reflect the

potentials for further research

In the STORK study we collected large amounts of data on a large group of women

Therefore selecting and analyzing the relevant outcomes and appropriate explanatory

variables was the greatest challenge There are large amounts of data still to be analyzed For

the STORK data my plans for a postdoc is to study in more detail the relations between

maternal metabolism and pregnancy outcomes More specifically to differentiate between

healthy and unhealthy obese pregnant women in metabolic terms and relate this to pregnancy

outcomes including fetal growth

In the STORK-Placenta study establishing the method and achieving the data collection were

the greatest challenges with demanding logistics at any time of the day There are few larger

human in vivo studies of placental nutrient transfer In particular studies of arterio-venous

differences on maternal side of placenta are scarce The main reason this kind of studies are so

limited is that such studies are logistically very requiring To our knowledge we are the only

group employing this procedure The samples obtained by this method give unique

opportunities to study concentration gradients and transplacental transfer of any nutrient

81

across placenta and how endocrine and inflammatory factors may interact with nutrient

transfer The study also includes measurements of maternal and fetal blood flow enabling us

to quantify the amounts of nutrients being transported The study has currently been

expanded to around 100 pregnancies Data collection still goes on aiming to get enough

samples to continue analyzing interesting associations linking maternal metabolism placental

functions and the fetus and extending the data to include cases of pathological pregnancies

like preeclampsia diabetes mellitus and abnormal fetal growth Samples from preeclamptic

women are currently being analyzed for Placental growth factor

The potential for further research lies in combining the data retrieved from the two studies

Ultimately I would like to be able to link preeclampsia and fetal growth in the two studies

82

8 References

Reference List

1 2009) wwwmfr-nesstaruibno Medical birth Registry Norway Available

2 Harding JE (2001) The nutritional basis of the fetal origins of adult disease Int J

Epidemiol 30 15-23

3 Barker DJ Thornburg KL (2013) The obstetric origins of health for a lifetime Clinical

Obstetrics and Gynecology 56 511-519

4 Forsdahl A (1978) Living conditions in childhood and subsequent development of risk

factors for arteriosclerotic heart disease The cardiovascular survey in Finnmark 1974-

75 J Epidemiol Community Health 32 34-37

5 Forsdahl A (1979) Are poor living conditions in childhood and adolescence and

important risk factor for arteriosclerotic heart disease Int J Rehabil Res 2 238-239

6 Barker DJ (2005) The developmental origins of insulin resistance Horm Res 64 Suppl

3 2-7

7 Barker DJ Shiell AW Barker ME Law CM (2000) Growth in utero and blood

pressure levels in the next generation J Hypertens 18 843-846

8 Barker DJ (1997) The long-term outcome of retarded fetal growth Clinical Obstetrics

and Gynecology 40 853-863

9 Gude NM Roberts CT Kalionis B King RG (2004) Growth and function of the

normal human placenta Thromb Res 114 397-407

10 Voldner N (2010) Modifiable determinants of newborn macrosomia and birth

complications [dissertation]

11 Mayer C Joseph KS (2013) Fetal growth a review of terms concepts and issues

relevant to obstetrics Ultrasound Obstet Gynecol 41 136-145

12 Zhang J Merialdi M Platt LD Kramer MS (2010) Defining normal and abnormal

fetal growth promises and challenges Am J Obstet Gynecol 202 522-528

13 Gardosi J Figueras F Clausson B Francis A (2011) The customised growth potential

an international research tool to study the epidemiology of fetal growth Paediatr

Perinat Epidemiol 25 2-10

14 Rohrer F (1921) The index of corpulence as measure of nutritional state Munchener

medizinische Wochenschrift 580-582

15 Catalano PM Thomas AJ Avallone DA Amini SB (1995) Anthropometric estimation

of neonatal body composition Am J Obstet Gynecol 173 1176-1181

16 Godang K Qvigstad E Voldner N Isaksen GA Froslie KF et al (2010) Assessing

body composition in healthy newborn infants reliability of dual-energy x-ray

absorptiometry J Clin Densitom 13 151-160

17 Pay AS Froen JF Staff AC Jacobsson B Gjessing HK (2013) A new population-

based reference curve for symphysis-fundus height Acta Obstet Gynecol Scand 92

925-933

18 Anderson NG Jolley IJ Wells JE (2007) Sonographic estimation of fetal weight

comparison of bias precision and consistency using 12 different formulae Ultrasound

Obstet Gynecol 30 173-179

19 Cetin I Alvino G (2009) Intrauterine growth restriction implications for placental

metabolism and transport A review Placenta 30 Suppl A S77-S82

20 Mei Z Grummer-Strawn LM Pietrobelli A Goulding A Goran MI et al (2002)

Validity of body mass index compared with other body-composition screening indexes

for the assessment of body fatness in children and adolescents Am J Clin Nutr 75

978-985