The Pennsylvania State University

The Graduate School

Intercollege Graduate Degree Program in Genetics

GENETIC CONTRIBUTIONS TO DISPARITIES IN PRETERM BIRTH AMONG

AFRICAN-AMERICAN WOMEN

A Dissertation in

Genetics

by

Laurel N. Pearson

2012 Laurel N. Pearson

Submitted in Partial Fulfillment of the Requirements

for the Degree of

Doctor of Philosophy

August 2012

ii

The dissertation of Laurel N. Pearson was reviewed and approved* by the following:

Mark D. Shriver Professor of Anthropology Thesis Advisor

David J. Vandenbergh Associate Professor of Biobehavioral Health Chair of Committee

Kenneth M. Weiss Evan Pugh Professor of Anthropology and Genetics and Science, Technology, and Society

Nina G. Jablonski Distinguished Professor of Anthropology

Jerome F. Strauss III Dean, School of Medicine Special Member Virginia Commonwealth University Robert F. Paulson Professor of Veterinary and Biomedical Sciences Chair, Intercollege Graduate Degree Program in Genetics

*Signatures are on file in the Graduate School

iii

ABSTRACT

In the United States African-American women experience the poorest pregnancy

outcomes of any ethnic group. Compared to women of European-American ancestry,

African-American women have a substantially greater risk of preterm birth, low birth

weight neonates, and infant mortality. A variety of factors have been hypothesized to

contribute to disparities in these complex pregnancy phenotypes including environment,

lifestyle, social factors, stress, and genetics. This dissertation investigates genetic

ancestry and the role of genes in contributing to risk of poor pregnancy outcomes among

African-American women.

In the first portion of this research the association between West African genomic

ancestry and birth weight and the association between genomic ancestry, skin

pigmentation, and serum vitamin D level were investigated. Increasing West African

ancestry among female neonates was found to be significantly associated with lower birth

weight. Additionally, serum vitamin D level was inversely correlated with increasing

West African genomic ancestry and increasing melanin content in the skin.

For the next phase of this project an admixture mapping approach was used to

help identify novel regions of the genome that are associated with the largest contributor

to preterm birth, preterm premature rupture of membranes (PPROM). In this case-control

analysis of African-American neonates, regions on five chromosomes were identified to

be associated with increased risk of PPROM. Five regions on four chromosomes (5, 8,

11, and 19) were associated with African ancestry and one large region on chromosome

21 was associated with European ancestry. Although these regions are relatively large,

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they provide areas for future research into the genetic contributions to risk of preterm

birth due to PPROM.

In the final portion of this research, tests for accelerated evolution were conducted

to help prioritize candidate genes to investigate the role of genetics in the increased risk

of preterm birth among African-American women. Using three test statistics: locus-

specific branch length (LSBL), log of the ratio of heterozygosities (lnRH) and normalized

Tajima’s D, 90 previously reported preterm birth candidate genes were screened for

evidence of accelerated evolution in the parental populations that contribute to African-

American admixture, European and West African. From these tests, forty-four of the

preterm birth candidate genes had evidence of non-neutral evolution. This analysis

helped to identify genes that are more likely to contribute to the increased risk of preterm

birth in African-American women compared to European-American women.

Future work will include a replication of the admixture mapping study to refine

the chromosomal regions found to be associated with risk of preterm birth due to

PPROM. Additionally, genotyping of the forty-four preterm birth candidate genes

nominated by the three tests for accelerated evolution is planned to look for risk alleles

that contribute to the disparity in preterm birth among African-American women.

v

TABLE OF CONTENTS

List of Figures .......................................................................................................................... viii

List of Tables ........................................................................................................................... ix

Acknowledgements .................................................................................................................. x

Chapter 1 Introduction ............................................................................................................. 1

Background ...................................................................................................................... 2

Preterm Delivery, PPROM, and Low Birth Weight ................................................. 4 Preterm Delivery and Low Birth Weight in Africa .................................................. 7 Risk Factors Associated with Preterm Birth ............................................................ 8 Genetic Contributions to Preterm Birth.................................................................... 11 Genomic Ancestry Estimation and Admixture Mapping ......................................... 13 Candidate Genes Previously Implicated in Preterm Birth ........................................ 16 Screens for Accelerated Evolution ........................................................................... 17

Conclusion ....................................................................................................................... 18 Literature Cited ................................................................................................................ 19

Chapter 2 Genomic Ancestry and Pregnancy-Related Phenotypes ......................................... 24

Abstract ............................................................................................................................ 24 Introduction ...................................................................................................................... 25

Background .............................................................................................................. 26 Genomic Ancestry .............................................................................................. 26 Birth Weight and Genomic Ancestry .................................................................. 28 Skin Pigmentation, Vitamin D, and Genomic Ancestry ...................................... 29 Materials and Methods ..................................................................................................... 32

Research Design ....................................................................................................... 32 Genomic Ancestry Estimates ................................................................................... 33 Statistical Analysis ................................................................................................... 35

Results .............................................................................................................................. 35 Genomic Ancestry .................................................................................................... 36 Birth Weight, Gestational Age, and Ancestry .......................................................... 40 Genomic Ancestry, Pigmentation, and Vitamin D ................................................... 43

Discussion ........................................................................................................................ 46 Future Directions ...................................................................................................... 48

Literature Cited ................................................................................................................ 50

Chapter 3 Admixture Mapping to Detect Novel Candidate Regions for Preterm Premature Rupture of Membranes (PPROM) in African-American Women ................................... 54

Abstract ............................................................................................................................ 54 Introduction ...................................................................................................................... 55

Background .............................................................................................................. 56 Previous Studies of the Genetics of PPROM ...................................................... 57

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Admixture Mapping for the Discovery of Novel Candidate Regions for PPROM .................................................................................................................... 58

Previous Admixture Mapping Studies in Preterm Birth ..................................... 63 Materials and Methods ..................................................................................................... 64

Study Sample ........................................................................................................... 64 Genotyping ............................................................................................................... 65 Data Cleaning ........................................................................................................... 67

Samples Removed from Analysis ........................................................................ 67 Markers Removed from Analysis ........................................................................ 67 Departures from Hardy-Weinberg Equilibrium ................................................. 68

Admixture Mapping ................................................................................................. 69 Estimating Genomic Ancestry ................................................................................. 70

Results .............................................................................................................................. 71 Genomic Ancestry Estimates ................................................................................... 72 Admixture Mapping ................................................................................................. 75

Discussion ........................................................................................................................ 80 Future Directions ...................................................................................................... 83

Literature Cited ................................................................................................................ 85

Chapter 4 Investigating Evidence for Accelerated Evolution at Preterm Birth Candidate Genes ................................................................................................................................ 89

Abstract ............................................................................................................................ 89 Introduction ...................................................................................................................... 90

Background .............................................................................................................. 91 Materials and Methods ..................................................................................................... 93

Admixture Mapping ................................................................................................. 93 Candidate Genes ....................................................................................................... 96 Tests of Accelerated Evolution ................................................................................ 97

Sample Populations and Genotyping Panel ....................................................... 97 Locus-Specific Branch Length (LSBL) ............................................................... 97 Log of the Ratio of Heterozygosities (lnRH) ...................................................... 101 Normalized Tajima’s D ...................................................................................... 102

Evaluating the Significance of the Tests of Accelerated Evolution ......................... 104 Results .............................................................................................................................. 106

Screens for Accelerated Evolution from Admixture Mapping Results for PPROM ............................................................................................................ 106

Tests of Accelerated Evolution in Preterm Birth Candidate Genes ......................... 116 Discussion ........................................................................................................................ 140

Future Directions ...................................................................................................... 145 Literature Cited ................................................................................................................ 146

Chapter 5 Concluding Remarks ............................................................................................... 149

Relationship between Genomic Ancestry and Pregnancy-related Phenotypes ................ 149 Admixture Mapping and Genomic Regions Associated with Risk of PPROM ............... 151 Prioritizing Replication and Genotyping of Candidate Genes for Future Studies ........... 154 Future Directions .............................................................................................................. 155

Genotyping of Additional Mothers and Newborns for Ancestry Association Studies .............................................................................................................. 155

Replication of Admixture Mapping and Investigation of Candidate Genes ............ 156

vii

Conclusion ...................................................................................................................... 157 Literature Cited ................................................................................................................ 158

Appendix A Details on the University of Minnesota 107 Ancestry Informative Marker (AIMs) Panel .................................................................................................................... 160

Appendix B Details on the Illumina African-American Admixture Panel 1,509 Ancestry Informative Marker (AIMs) ............................................................................................. 164

Appendix C Admixture Mapping Results from ADMIXMAP for PPROM .......................... 203

Case-Control Ancestry Association and Allelic Association Values at each AIM .......... 204 Case-Only Ancestry Association Score Maps ................................................................. 241 Case-Only Ancestry Association and Allelic Association Values at each AIM .............. 248

Appendix D Screens for Accelerated Evolution for PPROM Admixture Mapping Results .............................................................................................................................. 281

Full Chromosomal Ancestry Association Peak Screens – West African ......................... 282 Full Chromosomal Ancestry Association Peak Screens – European ............................... 283 Individual AIMs within Chromosomal Ancestry Association Peak Screens – West

African ..................................................................................................................... 284 Individual AIMs within Chromosomal Ancestry Association Peak Screens –

European ................................................................................................................. 285

Appendix E Screens for Accelerated Evolution in 90 Previously Reported Preterm Birth Candidate Genes .............................................................................................................. 286

West African .................................................................................................................... 287 European .......................................................................................................................... 290

viii

LIST OF FIGURES

Figure 1-1. Infant Mortality in the United States by Ethnicity. ............................................... ....3

Figure 1-2. Pregnancy Outcomes by Ethnicity ........................................................................ …4

Figure 2-1. Distribution of Genomic Ancestry in Research Subjects ...................................... ..38

Figure 2-2. Birth Weight Plotted Against Gestational Age ..................................................... ..41

Figure 2-3. Birth Weight Plotted Against West African Genomic Ancestry ........................... ..42

Figure 2-4. Proportion of West African Ancestry, Skin Pigmentation, and Vitamin D .......... ..45

Figure 3-1. Linkage Disequilibrium Created by Admixture .................................................... ..60

Figure 3-2. Illustration of Admixture Mapping Ancestry Association Peak ........................... ..62

Figure 3-3. Illumina African-American Admixture Panel Minor Allele Freqeuncy Differences ....................................................................................................................... ..66

Figure 3-4. Genomic Ancestry Distribution of Study Samples for Admixture Mapping Analysis ........................................................................................................................... ..74

Figure 3-5. Genome-wide Ancestry Association Z-scores Plotted for African Ancestry ....... ..77

Figure 3-6. Ancestry Association Score Maps for Chromosomes with Significant Peaks in PPROM Admixture Mapping .......................................................................................... ..78

Figure 4-1. Illustration of Locus-Specific Branch Length (LSBL) .......................................... 100

Figure 4-2. Results of the Tests for Accelerated Evolution in PPROM Admixture Mapping Ancestry-Association Regions .......................................................................... 109

Figure 4-3. Results of the Tests for Accelerated Evolution in Previously Published Preterm Birth Candidate Genes ........................................................................................ 118

ix

LIST OF TABLES

Table 2-1. Average Allele Frequency Difference Between Parental Populations for 107 Ancestry Informative Marker Panel ................................................................................. ..34

Table 2-2. Maternal Characteristics ......................................................................................... ..39

Table 3-1. Average Delta Calculated between Parental Populations for Illumina African-American Admixture Panel. ............................................................................................. ..72

Table 3-2. Average Genomic Ancestry for PPROM (cases) and Controls .............................. ..73

Table 3-3. Ancestry Association Peaks for Admixture Mapping of PPROM ......................... ..79

Table 4-1. Description of Chromosomal Ancestry Association Peaks Identified by Admixture Mapping in PPROM ..................................................................................... ..95

Table 4-2.Empirical Distribution Cut-offs for Tests of Accelerated Evolution in Ancestry Informative Marker Panel used in PPROM Admixture Mapping Study ......................... 105

Table 4-3.Summary of Tests of Accelerated Evolution for PPROM Admixture Mapping Peaks ................................................................................................................................ 114

Table 4-4.Summary of Tests of Accelerated Evolution for Ancestry Informative Markers within PPROM Admixture Mapping Peaks ..................................................................... 114

Table 4-5.Summary of Tests of Accelerated Evolution for Preterm Birth Candidate Genes .. 137

Table 4-6.Significant Results for Screens of Accelerted Evolution in Preterm Birth Candidate Genes Summarized ......................................................................................... 139

x

ACKNOWLEDGEMENTS

There are many people that I would like to thank for making this dissertation

possible. First and foremost, I am grateful for the mentorship of my advisor, Mark

Shriver. I would also like to thank the members of my dissertation committee – David

Vandenbergh, Ken Weiss, Nina Jablonski, and Jerome Strauss – who provided many

thoughtful suggestions on improving my research and dissertation.

My dissertation could not have been completed without the support of

collaborators including Drs. Jerome Strauss, Roberto Romero, and Juan Pedro Kusanovic

who generously provided the PPROM data, and Dr. Hyagriv Simhan, Dr. Lisa Bodner,

and David Crowe at Magee Womens Hospital.

No one at Penn State has been a bigger cheerleader for me than Dr. Rick Ordway,

the former chair of the genetics program. His faith in me and encouragement kept me

going even when times were tough.

The anthropology department at Penn State has been a wonderful home for an

interdisciplinary program graduate student. Thank you for treating me like one of your

own.

I am grateful to have been a member of the Shriver Lab family with Abby

Bigham, Ellen Quillen, Denise Liberton, Jen Wagner, Kerri Matthes Rosana, Xianyun

Mao, Marc Bauchet, Arslan Zaidi, and Wei Yao. Thank you for all of your advice,

support, and fun distractions over the years.

xi

The friends that I made at Penn State and in State College – Abby Bigham, Jason

De Leon, Ellen Quillen, Geoff Vasile, Holly Dunsworth, Kevin Stacey, Sam and Jen

Sholtis, Kirk Straight, Maria Inclan, Dawn Miller, Sharon DeWitte, Eric Jones, Logan

Kistler, Anna Sewell, Chris Percival, Carolyn Keagel, Erick and Sarah Rochette, Ryan

Peterson, and the ladies from book club and knitting group – helped me keep my sanity

and made graduate school much more fun.

I would like to thank my parents, Ken and Dinah Pearson, and my sister, Erin, for

their love and support.

Finally, none of this would have been possible without the love, encouragement,

and patience of my fiancé, Kirk French. Thank you for all of the great adventures. I look

forward to many more in the years to come.

1

Chapter 1

Introduction

African-American women experience the poorest pregnancy outcomes of any

U.S. ethnic group. Disparities in pregnancy outcomes for these women include much

higher rates of preterm birth, low birth weight neonates for gestational age, and increased

risk of infant mortality compared to women of self-described European-American

ancestry. Many possible explanations have been suggested for these apparent disparities

in pregnancy phenotypes among African-American women, including environment,

lifestyle, access to healthcare, stress, and genetics.

The current research will investigate the genetic and gene-environment factors

that may influence pregnancy outcomes from the perspective of genomic ancestry. It will

also exploit recent admixture in African Americans to help identify novel genomic

regions contributing to risk for preterm birth due to preterm premature rupture of

membranes (PPROM) by admixture mapping. Finally, tests for accelerated evolution in

West African and European parental populations will be used to prioritize previously

reported preterm birth candidate genes and ancestry-associated risk-regions for PPROM

for future studies of genetic contributions to disparity in preterm birth risk in African

Americans.

This research addresses four main questions: 1) Is West African genomic ancestry

associated with low birth weight for gestational age among African-American neonates

2) Is West African genomic ancestry associated with serum vitamin D level, a possible

2

contributor to preterm birth? 3) Can admixture mapping be used to identify novel

candidate regions of the genome for risk of premature birth due to PPROM in African-

American women? 4) Can screens for accelerated evolution help prioritize previously

reported candidate genes for preterm birth and genomic regions identified as risk regions

for PPROM by admixture mapping for future investigation of disparity in preterm birth

risk among African-American women?

Background

Preterm birth (PTB) is the leading cause of neonatal mortality and infant

morbidity in the United States [1]. The annual economic burden of preterm birth was

estimated at $26.2 billion in 2005 by the Institute of Medicine [2]. This figure does not

include the lifelong healthcare costs attributable to chronic illness associated with

preterm delivery [3]. The rate of PTB in the U.S. is higher than most other developed

nations and appears to be rising [4-6]. The rise in PTB is partially attributable to the

increased use of assisted reproductive technologies (ART) and the increased number of

multiple gestations [7]. However, after correcting for these factors, PTB rate is still

increasing. Causes of PTB are numerous with 80% considered spontaneous due to either

preterm labor (PTL) or preterm premature rupture of membranes (PPROM) [5]. The

remaining 20% of preterm births are medically induced due to factors such as fetal

malformation, multiple gestations, or maternal health factors, like pregnancy-induced

hypertension (preeclampsia).

3

Within the framework of PTB there is considerable disparity between African-

American and European-American women in terms of risk. African-American women

exhibit a significantly higher rate of PTB compared to European-American women, with

18.5% of neonates born to African-American women delivered preterm compared to

11.6% for European-American women [8, 9]. Additionally, African-American women

have the highest rate of low birth weight and very low birth weight infants of any

racial/ethnic group and the highest rate of infant mortality in the United States (Figures 1-

1 and 1-2) [10].

Many factors have been implicated to explain these differences, including

behavior, environment, social factors, risk of infection, and genetics. This research is

focused on investigating the contribution of genetic ancestry to disparity in pregnancy

outcomes and exploiting the relatively recent admixture in African-Americans to help

identify novel candidate genes for preterm delivery due to PPROM.

Figure 1-1. Infant mortality per 1,000 live births by ethnicity. Figure from the 2004 National Vital Statistics Reports.

4

Figure 1-2. Pregnancy outcomes by ethnicity: preterm birth and low birth weight. Adapted from Martin et al. (2009) [9].

Preterm Delivery, PPROM, and Low Birth Weight

In humans, normal term gestation for singleton pregnancies is 37 to 41 weeks

[10]. Changes in maternal and fetal physiology near the end of pregnancy are thought to

promote the normal progression of parturition at term, through both hormonal and

mechanical processes. These changes promote the formerly quiescent uterus to start

contracting and the breakdown of the fetal membranes that together facilitate

5

spontaneous birth. There are a variety of factors thought to contribute to early changes in

these pathways that can result in spontaneous preterm birth [11].

Preterm delivery (PTB) is defined as birth prior to 37 weeks gestation, with

gestational age determined from first day of the last menstrual period or early second

trimester ultrasound estimation, the “gold standard” for confirming gestational age [12].

Preterm delivery falls into two categories, spontaneous and medically induced.

Spontaneous PTB is caused by preterm labor or preterm premature rupture of membranes

(PPROM). In the United States, spontaneous preterm birth occurs in approximately

12.8% of all deliveries. Among African-American women, the frequency is 18.7%,

much greater than the 11.7% incidence of PTB among European-American women [9].

Additionally, African-American women are at disproportionately higher risk of very

preterm delivery (<32 weeks gestation) than any other U.S. ethnic group [10].

Preterm premature rupture of membranes (PPROM) is characterized by rupture of

the fetal membranes prior to 37 complete weeks of gestation without onset of labor.

PPROM occurs in approximately 1-2% of all pregnancies and accounts for 30-40% of all

preterm deliveries [13]. The recurrence rate of PPROM is approximately 21% [14].

Within spontaneous PTB, PPROM accounts for the majority of preterm births. Shen et

al. (2008) found that African-American women had a 2-fold greater risk of PPROM

compared to European-American women [15]. In addition to social, demographic, and

behavioral contributors to PPROM, various biological mechanisms have been postulated

for pathological rupture of the fetal membranes, among them are early degradation of the

membranes and inflammation [16].

6

Low birth weight (LBW) is the largest contributor to neonatal mortality. Infants

are considered low birth weight if they are smaller than 2,500 grams (5 pounds 8 ounces)

at birth. Preterm neonates are at increased risk of LBW due to shorter gestation. When

considering prematurity of infants it is important to consider birth weight in relation to

gestational age. More African-American neonates are considered small for gestational

age (SGA) (<10th percentile) than European-American neonates [17].

Whether small for gestational age represents a pathological condition in African-

American neonates, such as intrauterine growth restriction, or a normal “tailing-off” of

growth near the end of pregnancy has been debated [18, 19]. Kramer et al. (2006) state

that ethnic-specific fetal growth charts should not be created because low birth weight,

small for gestational age African-American neonates represent a pathological condition

and are not within the range of normal human variation. This is evidenced in the

increased neonatal mortality of premature African-American babies [19]. Conversely,

Steer (1998) suggested that African-American neonates are healthier at a smaller size for

gestational age than European neonates at the same gestational age [18]. As evidence he

cites a shorter average gestational length among African women [20] and increased lung

maturity in preterm African-American babies. Other researchers have suggested that

African-American neonates are more mature for gestational age despite being somewhat

smaller than European-American neonates [21, 22]. These conflicting studies suggest

that a better understanding of the contribution of genetic ancestry, in this case West

African ancestry, to birth weight is important in understanding the implications of LBW

in African-American neonates. This relationship is investigated in Chapter 2.

7

Preterm Birth and Low Birth Weight in Africa

Research on the prevalence of preterm birth and low birth weight in Africa is

limited. This is primarily due to the large proportion of women that deliver outside of a

hospital setting and a lack of vital records reported at the national level in developing

countries. In a review of the world incidence of preterm birth conducted by the World

Health Organization (WHO), it was estimated that Africa has a preterm birth rate of

approximately 11.9% [23]. In West Africa, the source of a majority of the African

ancestry found in the U.S. African-American population, the rate is approximately

10.1%. These African levels are similar to the average reported in the in the U.S.

(12.8%), but less than those reported for African-American women (18.5%) [9]. The

authors of the WHO review concede that estimates from developing countries are likely

low since the data is incomplete and primarily from facilities instead of from nationally

collected sources. Additionally, neonates born prematurely are more likely to die in

developing countries where there are limited resources to improve the chances of survival

of a preterm neonate. It is possible that premature births that result in the death of the

neonate are not consistently recorded. It is clear that the rate of preterm birth in Africa is

high, but the contribution of genetic influences to preterm birth in Africa is unknown.

Beck et al. (2010) suggest that the largest contribution to preterm birth in Africa is likely

infection, only one of the many factors considered to contribute to the complexity of

increased risk of preterm birth among African-American women in the United States

[23].

8

Low birth weight is also a major concern in Africa, as it is among African-

American neonates in the United States. A publication by A.K.I. Airede (1996) in the

East African Medical Journal summarizes the trends in birth weight for African

newborns [24]. The author reports a low birth weight prevalence of 17% in West Africa,

the highest of any region in Africa. This is similar to the reported 18.5% low birth

weight figure for newborns delivered to African-American women in the United States

[9]. Numerous factors were evaluated in this review that are thought to contribute to low

birth weight in Africa including malaria, socio-economic conditions, and poor maternal

nutrition. While some of the non-genetic factors are similar between the African

environment and the United States, the role that genes may play in smaller birth weight

neonates in women of African ancestry both in Africa and the United States is largely

unexplored. The association of West African genetic ancestry and birth weight will be

investigated further in Chapter 2.

Risk Factors Associated Preterm Birth

Many different factors have been proposed to contribute to the elevated incidence

of PTB in African-American women as compared to European-American women. These

include socioeconomic factors (access to healthcare, education, and neighborhood

poverty), behaviors (smoking, drinking, and drug use), infection, pre-pregnancy body

mass, parity, previous preterm delivery, interval between pregnancies, stress, and vitamin

D deficiency.

9

Social factors that have been investigated include access to prenatal care and

socioeconomic factors like years of education, household income, neighborhood

employment rate, and insurance coverage. While some studies have found an effect of

social factors, the results of these studies are not consistent. When there is equal access

to prenatal care, such as in a military setting, PTB is still more prevalent among African-

American women [25, 26]. Additionally, risk of preterm birth among higher SES

African-American women is still much higher than that seen in European women with

the same level of education [27].

Behavioral traits such as smoking, illicit drug use, and alcohol use are associated

with an increased risk of preterm birth. Smoking is a known risk factor for PTB and low

birth weight neonates, and cocaine use during pregnancy has also been associated with

PTB. However, some studies have shown that European-American women are more

likely to smoke cigarettes and use drugs during pregnancy [28, 29]. Therefore, it is

unlikely that behavioral traits can fully explain the significant increase in PTB among

African-American women.

Infection has been correlated with risk of PTB [30, 31]. Although many varieties

of infection have been investigated, bacterial vaginosis appears to be the most common

contributor to PTD from infection [32, 33]. BV is more common in African-American

women although the reason is not completely understood. Treatment with antibiotics has

been shown to reduce the risk of PTD due to infection.

One of the most significant factors contributing to preterm birth is a previous

preterm delivery. Carr-Hill and Hall (1989) reported that in women who have

10

experienced one previous PTB, the risk of subsequent PTB is 15.4%. The risk is 3-fold

higher for women who have had two prior preterm deliveries [34]. This trend lends

support to the hypothesis that genetic factors contribute to risk of PTB.

Stress is a known risk factor for preterm delivery. Numerous studies have

investigated how differential levels of stress contribute to the disparity in risk of PTD

between African-American and European-American women. Psychological stress has

been shown to alter physiology by increasing levels of stress related hormones circulating

in the body; these chemicals include cortisol and corticotrophin-releasing hormone

(CRH) [35]. In both term and preterm deliveries, a rapid increase in CRH levels is

observed just prior to the initiation of labor [36]. In addition to preterm birth, stress

response has been implicated in hypertension, cardiovascular disease, diabetes, and

obesity. It has been proposed that in addition to stress caused by socioeconomic factors

and interpersonal relationships, perceived racial discrimination can contribute to stress

related disparities in health outcomes among African Americans. Chronic stress

experienced as the result of discrimination is thought to cause a cascading suite of

physiological responses that can result in disease and early death [37].

Recently, vitamin D deficiency has been suggested as a risk factor for poor

pregnancy outcomes like preeclampsia, increased risk of bacterial vaginosis infection (a

known contributor to preterm birth), and preterm birth [38-40]. The potential role for

vitamin D in birth timing is of particular interest for the study of preterm birth disparity

among African-American women because a large proportion of pregnant women and

women of childbearing age have been found to be vitamin D deficient [41-43]. Vitamin

D deficiency in African-Americans is not surprising since the majority of serum vitamin

11

D is synthesized by the body from exposure to ultraviolet radiation (UVB) from the sun

and melanin in darkly pigmented skin substantially reduces the UVB absorbed by the

skin especially in northern latitudes where there is lower UVB radiation.

The reduced vitamin D level in African Americans was recently investigated by

Signorello et al. (2011) who found a negative association between West African ancestry

and serum vitamin D (25(OH)D) levels [44]. Additionally, increasing West African

ancestry proportions among African-Americans is known to be associated with greater

melanin index (M), a measure of skin pigmentation [45, 46]. To better evaluate the

potential role of vitamin D to pregnancy-related phenotypes, the relationship of serum

vitamin D level to constitutive skin pigmentation and genomic ancestry will be explored

in Chapter 2.

Genetic Contributions to Preterm Birth

Genetic contribution to variation in risk of preterm birth has been widely debated.

Several researchers have suggested that the disparity in risk of PTB between African-

American women and European-American women is primarily due to socioeconomic,

behavioral (smoking alcohol use, and illicit drug use) and environmental stress, ruling-

out genetic influences as contributors to risk. However, in many other studies when these

factors are controlled for and familial risk is investigated, it is apparent that genetic

factors are likely responsible for a portion of the risk of preterm delivery and low birth

weight [47-50].

12

Evidence for a genetic contribution to preterm birth has been suggested by studies

of families with histories of prematurity. Research that has focused on birth timing in

families across multiple generations, as well as twin studies and studies of sisters indicate

that familial prematurity contributes to risk [51-53]. Within individuals, the risk of

prematurity is elevated after a previous preterm delivery [34, 54]. Additionally,

numerous studies have demonstrated that after controlling for the confounding effects of

environment, behavior, and social factors, risk of preterm birth and prematurity of

newborns is significantly greater among African-American women [15, 47]. These

studies implicate a role for genetics in the risk of preterm delivery.

Recently, York et al. (2010) investigated the contribution of unique and shared

environments within and between the African-American and European-American women

in Virginia [55]. The authors found that unique environment, that is differences in

environmental circumstances between pregnancies, is the largest contributor to the

variance in birth timing among African-American women compared to European-

American women, accounting for 65.4%. However, among African-American mothers

there is still a significant contribution of maternal genetic factors to variation in

gestational age at delivery, 13.8%. This research supports the idea that preterm birth is a

complex disease with both environmental and genetic causes. The authors suggest that a

better understanding of the environmental contributions to preterm birth as well as the

interaction between genes and environment will be key to better understanding the

disparity in preterm birth risk seen between African-American women and European

women in the United States.

13

Chapters 3 and 4 will address genetic contributions to preterm birth through an

admixture mapping analysis of preterm premature rupture of membranes among African-

American women and tests to identify candidate genes that show evidence of accelerated

evolution in the West African and European parental populations known to contribute to

admixture in high risk African Americans.

Genomic Ancestry Estimation and Admixture Mapping

Although the use of “race” as a variable in epidemiological and pharmacological

research is arguably useful, caution should be taken not to confuse “race” with individual

genomic ancestry. While genomic ancestry describes biogeographical or genetic

affiliations, “race” is a more complex concept that includes social and cultural factors

[56]. Although self-reported “race” may provide insights into disease risk attributable to

biological ancestry, it can be confounded by culturally defined variables, such as

socioeconomic status, smoking habits, stress from discrimination, patterns of health care,

and environmental risk factors [57]. This is especially important in studies of preterm

delivery and birth weight where myriad factors have been suggested to contribute to the

increased risk seen among African-American women.

African-American populations have experienced substantial admixture over the

500 years (~25 generations) since enslaved West Africans first arrived in the New World.

Modern U.S. African-American populations have an average European contribution to

admixture of approximately 20% [58, 59]. To obtain a more accurate understanding of

14

the risk associated with genetic ancestry, individual genomic ancestry can be estimated

using panels of Ancestry Informative Markers (AIMs) [60, 61]. AIMs are Single

Nucleotide Polymorphisms (SNPs) that show large allele frequency differentials between

parental populations and are identified using large-scale whole genome studies of

modern, unadmixed parental groups and published HapMap frequency data [62]. SNPs

are generally considered ancestry-informative if they have an absolute value difference in

allele frequencies between parental populations, δ, greater than 0.5 [63]. To assess

individual genomic ancestry in African-Americans, a three-way model of admixture

between West African, European, and Native American parental is most commonly

employed. Using the Maximum Likelihood method described by Chakraborty and Weiss

(1986) and Hanis et al. (1986), individual continental ancestry proportions can be

estimated from multilocus genotype data obtained on assaying a number of AIMs [64,

65].

Genomic ancestry estimates are valuable for understanding differences in

phenotypes in several ways. First, genomic ancestry estimates can be used to control for

admixture stratification, when substantial variation in genomic ancestry exists. Several

studies on PTB have used small panels of AIMs to control for admixture stratification in

their candidate gene studies [66-68]. Additionally, genomic ancestry can be used to

evaluate variation of phenotypes with proportional admixture. Recently Tsai et al. (2009,

2011) reported on an association of genetic ancestry and risk of preterm delivery [69, 70].

They found that risk of PTB increased with proportion of West African ancestry. A

similar analysis is performed in Chapter 2 to investigate the association between genomic

ancestry and birth weight for gestational age, as well as the relationship of West African

15

genomic ancestry and serum vitamin D level. Finally, large panels of AIMs can be used

for admixture mapping (AM) studies to identify regions of the genome associated with

increased prevalence of a phenotype or disease risk with population attributable

differences in frequency, like the AM study for PPROM risk reported in Chapter 3 [46,

71, 72].

Given the limited success of candidate gene studies to understanding genetic

contributions to increased risk of preterm birth in African-American women, Anum et al.

(2009) suggested that admixture mapping could be a promising approach for identifying

genes contributing to disparity in preterm birth [47]. In phenotypes that show large

differences between populations, admixture mapping is an approach that can lead to the

identification of novel chromosomal risk regions and candidate genes.

Admixture between previously isolated populations, like Europeans and West

Africans, creates very large regions of chromosomal linkage disequilibrium that decay as

a function of recombination and demographic factors over the generations since

admixture began [72-75]. AM can exploit this linkage to identify risk alleles associated

with a disease or trait that varies in parental populations [58, 76, 77]. Large panels of

ancestry informative markers (AIMs) spanning the entire genome, like the 1,509 marker

Illumina (San Diego, California) African-American Admixture array, are used for

genotyping studies for admixture mapping [61]. The design of these panels assumes that

AIMs that are found to be associated with the phenotype of interest, PPROM in the

current study (Chapter 3), will be in linkage disequilibrium with potentially causative

alleles. Fine-scale mapping can then be used in replication studies to locate genes and

alleles that contribute to risk [59]. AM studies have been used to identify risk regions

16

and genes associated with increased risk of asthma and prostate cancer [78-82].

Recently, Manuck et al. (2011) reported the first admixture mapping study of preterm

birth among African Americans (citation)[82]. Admixture mapping for preterm

premature rupture (PPROM) of membranes, a more specific phenotype of preterm birth,

is reported in Chapter 3.

Candidate Genes Previously Implicated in Preterm Delivery

Previous research into the genetics of prematurity has focused on candidate gene

approaches. Numerous genes have been reported to contribute to risk of preterm birth.

They fall into a variety of pathways associated with birth timing and labor, including

inflammatory response, matrix metabolism, uterine contraction, coagulation, and

endocrine [47]. A list of previously reported preterm birth candidate genes can be found

(http://bioinformatics.aecom.yu.edu/ptbgene/index.html) in the online Preterm Birth

Database [83].

It is important to consider that candidate gene association studies have, for the

most part, used self-reported “race” to assess instead of considering the contribution and

potential confounding of genomic ancestry. With the exception of the research of Wang

et al. (2006) on PPROM and SERPINH1, candidate gene approaches have not looked at

the contribution of genetic ancestry to risk of prematurity, and few have controlled for

potential stratification caused by unmatched levels of genetic ancestry between case and

control subjects [68]. Wang et al. (2006) is also the only candidate gene study to report a

17

polymorphism that confers an increased risk of preterm birth (PPROM) to African-

Americans. This allele was found to have a different frequency between African and

European parental populations (12.4% vs. 4.1%).

In Chapter 4, previously reported preterm birth candidate genes are screened for

evidence of accelerated evolution in West African and European parental populations

know to contribute to African-American admixture. The goal of this methodology is to

prioritize a list of genes for future studies that may contribute to the disparity in risk of

preterm birth in African-American women.

Screens for Accelerated Evolution

Over approximately the last 200,000 years as humans evolved in Africa and

began to migrate out the rest of the world, random changes (mutations and genetic drift),

demographic factors (gene flow and fluctuations in population size), and adaptation to

new environments (natural and sexual selection) have shaped the genome and contributed

to normal phenotypic and disease variation seen in modern human populations today.

The actions of these forces of evolution leave their signature on the genome in the form

of population-specific changes in allele frequency and regions of reduced heterozygosity.

Tests for accelerated evolution such as Tajima’s D, log of the ratio of heterozygosities

(lnRH), and locus specific branch length (LSBL) have been developed to identify these

signatures [84-86].

18

Tests for accelerated evolution have revealed genes that contribute to population-

specific adaptations to climate (skin pigmentation change, altitude adaptation), pathogens

(malaria), and diet (dietary lactose) (citations). This type of approach may help elucidate

regions of the genome or candidate genes that have been affected by recent evolutionary

processes that contribute to differences in population-specific risk of complex diseases.

In Chapter 4, previously reported candidate genes for preterm birth as well as genomic

regions associated with preterm premature rupture of membranes (PPROM) identified by

admixture mapping (Chapter 3) are investigated for evidence of accelerated evolution in

West African and European parental populations. Genes nominated by accelerated

evolution may be more likely to contribute to differences in genetic components of risk to

preterm birth between African-American and European-American women.

Conclusion

Great disparity exists in pregnancy outcomes for African-American women

compared to all other ethnic groups in the U.S. The purpose of this research is to

investigate the difference in pregnancy outcome by assessing the contribution of genetic

ancestry to pregnancy related phenotypes, risk of low birth weight neonates, and vitamin

D deficiency (a possible contributor to prematurity). Additionally, recent linkage

disequilibrium created by recent admixture between West African and European parental

populations will be used to help identify novel candidate genes for preterm premature

rupture of membranes (PPROM) in African-American women using an admixture

mapping approach. Finally, screens for accelerated evolution will help prioritize

19

previously reported candidate genes and genomic regions associated with preterm birth

for future research to elucidate genetic contributors to increased risk of preterm birth

among African-American women.

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24

Chapter 2

Genomic Ancestry and Pregnancy-Related Phenotypes

Abstract

In the United States, substantial disparity exists in pregnancy outcomes between

African-American and European-American women. African-American women are at

increased risk of premature delivery, and their newborns are at increased risk of low birth

weight and infant mortality. Although a great number of studies have evaluated

pregnancy-related disparities among African-American women, few have considered

genomic ancestry as a risk factor in pregnancy-related phenotypes and outcomes.

In this study, the relationships between genomic ancestry and neonatal birth

weight, and between genomic ancestry and serum vitamin D level were tested. The

research participants included in the current analysis are women of self-reported African-

American (n=187) and European-American (n=151) ancestry who were recruited during

the first trimester of their pregnancies to participate in a prospective study of

environmental and genetic contributions to preterm birth. Maternal DNA was genotyped

for a panel of 107 ancestry informative markers and genomic ancestry proportions for

each study subject was estimated for three-way admixture between West African,

European, and Native American parental populations. Associations between genomic

ancestry and birth weight adjusted for gestational age, as well as between genomic

ancestry, serum vitamin D level, and constitutive skin pigmentation were assessed.

25

The average contribution of European ancestry to African-American women in

the study cohort is 20%, with a range from 0-85%. On average, European-American

women are found to have very low levels of admixture, with an average contribution of

3% West African ancestry. West African genomic ancestry is correlated with birth

weight adjusted for gestational age in female neonates, although not in males.

Additionally, skin pigmentation is found to be positively associated with increasing West

African ancestry, and serum vitamin D level is negatively associated with both increased

melanin index (skin pigmentation) and increased West African genomic ancestry.

Substantial heterogeneity exists in genomic admixture among African-Americans.

Evaluating genomic ancestry may contribute to a better understanding of the increased

risk of adverse pregnancy outcomes among African-American women.

Introduction

African-American women have the poorest pregnancy outcomes of any “racial”

group in the United States. This includes a significantly increased risk of preterm birth, a

greater proportion of neonatal deaths, and a higher rate of low birth weight newborns.

To date, few studies have evaluated the contribution of genomic ancestry to

disparities in pregnancy related phenotypes [1, 2]. Most have used self-reported “race”

when conducting analyses to investigate the potential genetic contributions to differences

among populations in pregnancy outcomes. While self-reported “race” may capture some

components of social and environmental similarity among individuals, there is

26

tremendous heterogeneity in genetic composition among highly admixed populations,

like African Americans, that may not be completely accounted for by defining study

populations by racial categories [3, 4].

In the current study, genomic ancestry was estimated from a panel of 107 ancestry

informative markers (AIMs) genotyped in women of self-reported African-American and

European-American ancestry who enrolled in a prospective study of genetic and

environmental factors contributing to preterm birth at Magee-Womens Hospital in

Pittsburgh, Pennsylvania. The goals of this research were to 1) evaluate genomic

admixture in the study sample, 2) test for association between West African genomic

ancestry and newborn birth weight for women of European-American and African-

American ancestries, and 3) test for association between West African genomic ancestry

and skin pigmentation and serum vitamin D level in the study population.

Background

Genomic Ancestry

Admixture in modern African-American populations is composed primarily of genomic

contributions from West African and European parental populations. The degree of

admixture varies substantially between individuals and among African-American

communities across the country [5]. This stratification can confound studies of health

disparities when self-identified “race” is used as a proxy for biological similarity. By

27

estimating genomic ancestry proportions, it is possible to evaluate the contribution of

ancestry to differences in disease prevalence among populations, to investigate potential

stratification in study samples, and to help identify potentially causative genetic variants

contributing to disease disparity through admixture mapping.

Modest panels of single nucleotide polymorphisms with large allele frequency

differences between parental populations (delta, δ) known to contribute to admixture can

be used to generate usefully accurate estimates of genomic admixture proportions [6].

These markers are often referred to as ancestry informative markers (AIMs). For

estimating African-American admixture, panels of approximately 100 AIMs have been

used to reliably estimate genomic contributions from West African, European, and Native

American parental populations [7]. Previous studies indicate that the European genomic

contribution to African-American admixture is approximately 20% and with a range from

6.8-22.5% across the country [5, 8].

Genomic ancestry has been used to evaluate health disparities among African-

Americans in risk of prostate cancer, cardiovascular disease, and asthma [9-13].

However, the use of genomic ancestry to evaluate pregnancy related disparities is still in

its infancy. To date there has been one study that used genomic ancestry to control for

population stratification in a candidate gene (SERPINH1) study of preterm birth resulting

from preterm premature rupture of membranes [14]. Additionally, an admixture mapping

analysis conducted by Manuck and colleagues (2011) exploited genomic ancestry to help

identify chromosomal regions contributing to spontaneous preterm birth among African-

Americans [15]. Finally, two recent reports by Tsai et al. (2009, 2011) have investigated

the contribution of West African ancestry to risk of preterm birth [1, 2].

28

Birth Weight and Genomic Ancestry

In the United States African-American women have smaller neonates on average

than European-American women. They also have an increased risk of neonates that are

small for gestational age or low birth weight, <2,500 grams at term delivery. Low birth

weight (LBW) has been associated with long-term risk of chronic diseases, like

hypertension, type 2 diabetes and coronary artery disease, referred to as the Barker

Hypothesis [16]. Smoking, drug use, and low pre-pregnancy maternal BMI have all been

suggested to contribute to risk of low birth weight [17]. However, these factors do not

explain all of the increased risk of LBW neonates among African-American women.

Additional environmental, social (stress), and potentially genetic influences may account

for the increased risk of LBW among African-Americans.

It is well established that female neonates are smaller for gestational age than

males, and fetal growth curves have been established accordingly [18, 19]. Tailored birth

weight curves by ethnicity do exist; however, their applicability to the smaller size of

African-American neonates has been debated [20-24]. Kramer et al. (2006) suggest that

the increased risk of small for gestational age (SGA) neonates born to women of African-

American ancestry compared to European-American women and foreign-born Africans,

as well as the poorer outcome for African-American neonates born at all gestational ages,

indicates a likely pathological condition and not a physiologically normal difference in

birth size [23]. However, Thomas et al. (2000) argue that, like differences in male and

female growth during gestation, there are biological and/or physiological contributors to

29

ethnic differences in birth weight for gestational age. They suggest that growth curves

should be modified to reflect differences in growth for neonatal sex and ethnicity [21].

Interestingly, although African-American women have a substantially increased

risk of preterm and low birth weight neonates, these newborns have a lower mortality rate

than European-Americans and Hispanics [25, 26]. Additionally, risk of low birth weight

increases with the number of African-American parents. That is, there is a higher risk of

low birth weight for neonates with one African-American parent compared to two

European-American parents, and an even greater risk for newborns with an African-

American mother and father [27, 28].

To date, genomic ancestry has not been used to evaluate the contribution of West

African ancestry to birth weight for gestational age. Assessing genomic ancestry could

help inform the discussion on the differences in birth weight for gestational age observed

between newborns of European-American and African-American women. Evaluating

women, or fetuses, during pregnancy for genomic ancestry might provide a predictive

value of appropriate birth weight for gestational age for the individual newborn.

Skin Pigmentation, Vitamin D, and Genomic Ancestry

Skin pigmentation is known to vary in human populations as a result of adaptation

to varying levels of ultraviolet radiation from sun exposure at different latitudes. The

most darkly pigmented human populations are found near the equator and the populations

with the lightest skin pigmentation are found in northern latitudes where extremely low

30

levels of UV radiation are experienced during the winter months [29, 30]. The ability to

synthesize vitamin D in the skin may have been one of the strongest selection pressures

for skin lightening as darkly pigmented hominids began to move from equatorial Africa

to areas of the globe with low UV radiation [29, 31].

Vitamin D is important for proper bone development, and vitamin D deficiency

has been long understood to contribute to the bone deforming condition called rickets.

The majority of vitamin D is synthesized by sun exposure; however, supplementation

through the diet in the form of naturally occurring rich sources of Vitamin D, like oily

fish, and fortified foods, such as cereals and milk, can increase serum levels of 25(OH)D

[32]. In modern populations, supplementation of vitamin D is important for people

living in northern latitudes where natural vitamin D synthesis cannot occur during the

winter months. Supplementation is especially important for individuals with darkly

pigmented skin who have higher epidermal melanin content. Darker skin pigmentation

acted as a natural defense to intense UV exposure in tropical latitudes; however, in the

northern U.S. dark skin prevents these individuals from synthesizing sufficient vitamin D

[31].

Recently, considerable research has suggested a role for vitamin D deficiency in

increasing risk of infection, cancer and autoimmune disorders, like multiple sclerosis and

lupus [33-36]. Risk of these conditions has been shown to be correlated with higher

latitudes, and consequently lower levels of naturally synthesized vitamin D [37]. Vitamin

D deficiency has also been suggested to contribute to adverse pregnancy outcomes such

as preterm birth, preeclampsia, and increased risk of infection with bacterial vaginosis (a

risk factor for preterm birth) [36, 38, 39]. In a study of pregnancies in the northern

31

United States, Bodnar and Simhan (2008) found that season of conception was

significantly correlated to preterm birth risk, with fewer preterm births associated with

summer and fall conceptions [40]. Although not directly measured, they suggest that

vitamin D deficiency associated with low UVB exposure during winter months

contributes to the seasonal variation in preterm risk. Additionally, Jabolonski and

Chaplin (2000) observed that universally women have lighter skin pigmentation than

men. They suggest that lighter skin permitted increased synthesis of vitamin D needed

for absorption of additional calcium required during pregnancy [29].

Several studies have shown that the vast majority of African-American women

and their neonates are vitamin D deficient [41-43]. Vitamin D deficiency in infants has

been associated with poor health outcomes and increased risk of rickets [43]. To date,

only one published study, Signorello et al. (2010), has investigated the association

between West African genomic ancestry and serum vitamin D [44]. They found serum

vitamin D levels to be negatively associated with increasing West African ancestry. The

current research hopes to build on this study by evaluating the correlation between

genomic ancestry, constitutive skin pigmentation (melanin index), and serum vitamin D

in pregnant women of self-reported African-American and European-American ancestry.

32

Materials and Methods

Research Design

Women with singleton pregnancies were recruited prior to 13 weeks gestation at

Magee-Womens Hospital of the University of Pittsburgh Medical Center to participate in

a prospective study of genetic and environmental factors contributing to risk of preterm

birth. Exclusion criteria for participation in the study included vaginal bleeding, known

fetal abnormalities, diabetes prior to pregnancy, comprised immune system (including

HIV), chronic hypertension treated with medication, and autoimmune disorders.

Self-identified race was recorded during a face-to-face interview. Racial

categories were determined by those used by the U.S. census (White, Black, American

Indian, and Asian/Pacific Islander). In this chapter women of self-reported “Black” race

will be referred to as African American and “White” women will be referred to as

European American. Additional demographic and medical information was obtained

through questionnaires administered at the time of enrollment.

Gestational age of the pregnancy at the time of enrollment was measured from the

last menstrual period confirmed by first or second trimester ultrasound. Only women

who enrolled in the study prior to the thirteenth week of gestation, participated in the

study for the duration of their pregnancies, complied with the study protocols, delivered

after 18 weeks gestation, and on whom there is complete demographic and medical

information are included in the research reported in this chapter.

33

Skin pigmentation was measured by reflectance spectrophotometer

(DermaSpectrometer, Cortex, Denmark). Three measures of constitutive skin

pigmentation (M index) were collected from the upper inner left arm during the first

study visit. The melanin values were averaged to obtain an M value for use in the

analyses presented in this study. Women who reported using self-tanning cream within

the last month or who visited a tanning salon in the past three months were excluded from

the analyses of skin pigmentation.

Whole blood from each participant was collected during the first study visit.

DNA was extracted for genotyping of ancestry informative markers to assess genomic

ancestry. Additionally, serum vitamin D level was assayed at Magee Womens Hospital

and reported in nanograms per milliliter (ng/mL).

Genomic Ancestry Estimates

Maternal DNA was genotyped on a panel of 107 single nucleotide polymorphisms

(SNPs) by the BioMedical Genomics Core Facility at the University of Minnesota. This

panel was designed by Dr. Esteban Burchard of the University of California, San

Francisco and Dr. Kenneth Beckman of the University of Minnesota to assess admixture,

and includes SNPs with large allele frequency differences between three parental

populations known to contribute to admixture in the United States - West African,

European, and Native American [7]. These SNPs are referred to as ancestry informative

markers (AIMs). The average allele frequency difference, calculated as delta (δ),

between each of the parental populations is shown in Table 2-1. The full panel of AIMs

34

with parental allele frequencies derived from the International HapMap Project is

provided in Appendix A.

Table 2-1. Average allele frequency difference, delta (δ), between parental populations for the 107 SNPs included in the University of Minnesota Ancestry Informative Marker Panel.

West African -

European West African -

Native American European -

Native American

Avg. Delta (δ) 0.43 0.64 0.42

Sum Delta 46.48 68.45 44.52

Individual genomic ancestry proportions for a three-way model of admixture

between West Africans, Europeans, and Native Americans were estimated using the

maximum likelihood estimation (MLE) method described by Hanis et al. (1986) and

Chakraborty and Weiss (1986) [45, 46]. Proportions of genomic contribution from each

parental population are generated in a range from 0 to 1, with the sum of ancestry for

each research subject equal to 1. Individuals with ancestry estimates generated from

fewer than 70% of the genotyped AIMs were excluded from further analysis, as these

estimates are not as reliable.

35

Statistical Analysis

Comparisons between groups were assessed using Student’s t-test or Mann-

Whitney U test for continuous variables (for normally and non-parametrically distributed

variables, respectively) and χ2-test for categorical variables. Linear regression or

multiple linear regression was used to assess associations of genetic ancestry with

gestational age, birth weight, pigmentation, and vitamin D level. All statistical analyses

were performed in R (version 2.13.2) (http://www.r-project.org). Covariates considered

for regression analyses included marital status; education (less than high school); alcohol

use, drug use, or cigarette smoking during pregnancy; number of previous live births;

history of previous spontaneous preterm birth; genomic ancestry; and body mass index

(BMI).

Results

Research participants with complete demographic surveys who self-reported

European-American (White) or African-American (Black) ancestry and with births that

occurred between 18 and 42 weeks gestation are included in the analyses for this study.

This included 187 self-identified African-American women and 151 self-identified

European-American women.

Maternal characteristics by self-reported ancestry are available in Table 2-2. In

addition to significant differences in genomic ancestry proportions between African-

36

American and European-American research participants discussed in the next section,

only infant birth weight, previous preterm births, and marital status differs significantly

between the two study groups. African-American women have significantly smaller

neonates, are more likely to have had a previous spontaneous preterm birth, and are less

likely to be married than the European-American women included in this cohort study.

Genomic Ancestry

Three-way genomic ancestry estimates for each study participant were generated

from 104 of the 107 genotyped ancestry informative markers (AIMs) using the maximum

likelihood estimation method [45]. Distributions of West African ancestry are displayed

as histograms in Figure 2-1 for African-American and European-American research

participants. Additionally, a triangle plot depicts point estimates of three-way admixture

between West African, European, and Native American parental groups for each study

participant.

The distribution of West African ancestry for African-American women ranges

from 15 to 100%, with a median value of 78%. Average European contribution to

African-American admixture in the study subjects is 20%. Self-reported European-

American women show a broad distribution of West African ancestry (0-93%); however,

the majority of West African values fall below 15%. The median West African genomic

contribution for European-American research participants is 3%. Native American

genomic contribution to admixture in both the African-American and European-

37

American study groups is low, on average 1% and 4%, respectively. However, among

European-American research subjects there are several individuals with greater than 25%

Native American ancestry. The distributions of genomic ancestry and median values are

shown in Table 2-2.

38

Figure 2-1. The distribution of genomic ancestry for African-American and European-American research subjects. Histograms show West African ancestry by self-reported ancestry. The triangle plot at the bottom of the figure shows three-way admixture for all research subjects (West African, European, and Native American). Self-identified African-American and European-American subjects are represented in orange and blue, respectively.

39

Table 2-2. Maternal characteristics compared by participant population.

*Continuous variables compared with Mann-Whitney U test, categorical variables with χ2 test.

40

Birth Weight, Gestational Age, and Ancestry

Birth weight was evaluated only for term pregnancies (<37 weeks gestation) due

to a limited number of preterm pregnancies and the possibility of introducing

pathological factors related to prematurity that could affect fetal growth to the analysis.

Excluding preterm births reduced the total number of research participants to 300

women, 175 African-American and 125 European-American. For assessment of birth

weight and gestational age, the sample was further divided by neonatal sex. There were a

total of 159 males (90 born to African-American mothers and 69 to European-American

mothers) and 141 females (from 75 African-American women and 66 European-

American women).

Analyses of the correlation of birth weight and gestational age are highly

significant. Using all male neonates the adjusted R2 value is 0.299 (p<0.0001) and for all

females the adjusted R2 value is 0.146 (p<0.0001). Scatter plots for the regression of

birth weight on gestational age for both males and females are shown in Figure 2-2.

41

Figure 2-2. Birth weight plotted against gestational age for males (top) and females (bottom). In each plot, self-identified African-American individuals are shown as orange circles and European-Americans as blue circles. The trend lines represent the regression for African-American study subjects (orange) and European-Americans study subjects (blue). ****=p<0.001, ***=p<0.01, **=p<0.01, and *=p<0.05

42

West African ancestry shows a small but significant correlation with birth

weight in the combined sample of female neonates (R2 = 0.0216, p<0.05), but not in male

neonates or when the samples are separated by self-reported maternal ancestry. Figure 2-

3 shows the correlation between birth weight and West African genomic ancestry for

female neonates. Including West African ancestry in the model improves the R2 and p

values for association of neonatal birth weight and gestational age for female neonates,

adjusted R2=0.1657 (p<0.0001). By including smoking, BMI and West African ancestry

as covariates, the R2 value is increased to 0.2278 (p<0.0001) for the correlation between

birth weight and gestational age in female neonates. The addition of covariates,

including West African genomic ancestry proportion, does not improve the model for the

association between birth weight and gestational age in male neonates.

Figure 2-3. Birth weight in grams plotted against maternal West African genomic ancestry proportion for all female infants born at term (>37 weeks gestation). Self-identified African-American individuals are shown as orange circles and European-Americans as blue circles. The trend line represents the regression for all female newborns. *p=<0.05

43

Genomic Ancestry, Pigmentation, and Vitamin D

Pigmentation and vitamin D levels were not available for all of the women

who participated in this research who were evaluated for genomic ancestry. For the

comparison genomic ancestry and vitamin D, 306 women (169 African-American and

137 European-American) were included in the analysis. Seventy-three self-identified

African-American and 50 European-American women (total of 123) were included in

analyses of pigmentation and genomic ancestry. Finally, data for the analysis of vitamin

D and pigmentation (and ancestry) included 107 women (62 African-American and 45

European-American).

When skin pigmentation, measured as a melanin index (M) value, is compared

to West African genomic ancestry proportion in the combined sample of European-

American and African-American women, a strong correlation is observed. A plot of

pigmentation values compared to West African ancestry is shown in Figure 2-4(a). There

is not a significant association between genomic West African ancestry and skin

pigmentation for European-American women evaluated separately (R2=-0.0062);

however, analysis of African-American women shows a significant correlation between

West African ancestry and skin pigmentation (R2=0.231, p<0.0001).

Vitamin D is associated with West African ancestry (R2=0.225, p<0.0001) and

skin pigmentation (R2=0.242, p<0.0001) in the full sample of women. The R2 value is

increased (R2=0.371, p<0.001) when West African ancestry and skin pigmentation are

combined in the test for association with vitamin D. However, there is a not significant

44

association between vitamin D and West African ancestry and skin pigmentation when

(European-American and African-American) are tested independently.

45

Figure 2-4. Proportion of West African genomic ancestry, skin pigmentation (M), and vitamin D (ng/mL). Self-identified African-American women are shown as orange circles and European-Americans as blue circles. ****=p<0.001, ***=p<0.01, **=p<0.01, and *p=<0.05

46

Discussion

Genomic ancestry estimates for the African-American and European-American

research participants are within previously reported ranges [5, 47]. Parra et al. (1998)

noted varying genomic contributions of European ancestry to African-American

admixture across the United States that ranged from 6.8% to 22.5%, with an average

European contribution of approximately 20% [5]. Interestingly, the European admixture

proportion value reported by Parra et al. (1998) for individuals sampled from Pittsburgh,

Pennsylvania, the study site for the current analysis, was 20.1%. This is quite similar to

the 22% average found in the African-American women included in this study. The

distribution of European ancestry in the African-American study subjects is broad and

overlaps slightly with the distribution of European ancestry in the self-reported

European-American women.

Interestingly several of the European-American women appear to have substantial

genomic admixture from the Native American parental population (>25%). High levels

of Native American ancestry are unlikely to reflect genotyping error and can more likely

be attributed to Hispanic or Native American ancestry that was not reported on the

demographic questionnaire.

Not surprisingly, there is a strong correlation between gestational age for term

deliveries (>37 weeks gestation) and neonatal birth weight. West African ancestry is

significantly associated with birth weight for female neonates, although not for males.

Female neonates appear to be smaller with increasing West African admixture in the

study sample. It is still unclear whether smaller neonatal weight for gestational age in

47

African-American neonates compared to European-American neonates represents a

pathological condition or normal physiological variation. With a much larger sample of

admixed research subjects, mothers and/or neonates, growth curves based upon genomic

ancestry might be able to better predict “normal” birth weight for gestational age in

neonates of admixed ancestry.

West African genomic ancestry is associated with both skin pigmentation and

serum vitamin D level. Associations between skin pigmentation and genomic ancestry

for both African-Americans and Hispanics have been previously reported [48-50]. Large

degree of stratification within these populations due to relatively recent admixture

contributes to this association. When the relationship of West African ancestry and

pigmentation is assessed in the European-American study subjects, there is no evidence

for association. This is likely because there is very little admixture in non-Hispanic,

European-American populations.

One previous publication, Signorello et al. (2010), reported an association with

decreased vitamin D level and increased West African ancestry [44]. This study did not

incorporate measures of pigmentation; however, studies consistently show strong

correlations between West African genomic ancestry and constitutive pigmentation in

African-American populations [5].

Recent research suggests that vitamin D (25(OH)D) deficiency may be related to

adverse pregnancy outcomes such as preterm birth, risk of bacterial vaginosis (a known

risk factor for preterm delivery), and preeclampsia [36, 38, 39]. The current cutoff for

vitamin D insufficiency in adults is 30ng/mL (75nmol/L); however, there is no clear

48

threshold for sufficiency during pregnancy and lactation [41, 51]. Using the established

cutoff of 30ng/mL, 97.6% of the African-American women and 82.4% of the European-

American women in this study are insufficient or deficient for vitamin D. These values

are substantially higher than those reported by Nesby-O’Dell et al. (2002) for women of

childbearing age, 42.5% and 4.2% for African-American and European-American

women, respectively [42]. More similar vitamin D insufficiency and deficiency was

reported by Bodnar et al. (2007) for pregnant African-American (95.9%) and European-

American (62.3%) women sampled at the same study site used in the current research,

Magee-Womens Hospital in Pittsburgh, Pennsylvania [41].

Season of blood collection for vitamin D assay as well as information on dietary

supplementation of vitamin D through diet and prenatal vitamins was not available at the

time of the current analysis. While it has been suggested that 25(OH)D levels are less

affected by season and dietary supplementation, this information could be valuable to

incorporate into future analyses [41, 42]. Additionally, a paucity of spontaneous preterm

deliveries due to small sample sizes available for this study prevented assessment of

association of pigmentation and vitamin D level with risk of preterm birth.

Future Directions

In the time since the genotyping of the ancestry informative marker panel for this

research, the number of women that have been recruited to participate in the study has

nearly doubled. Genotyping of these women for ancestry informative markers will

49

increase the power of the analyses presented in this research. Additionally, the number of

spontaneous preterm births in the dataset has increased with the increased number of

women who have enrolled in the study. To date, two publications by Tsai et al. (2009,

2011) have investigated the association between genomic ancestry and risk of preterm

birth. In both reports, they found increased West African ancestry to be associated with

increased risk of preterm birth among African-American mothers [1, 2]. The larger

sample size available for future research may permit analyses on the contribution of

genetic ancestry to risk of preterm birth and the role of vitamin D in risk of prematurity.

Additionally, cord blood samples are available for the neonates of the women

who participated in this research. DNA samples from each newborn will be genotyped

and genomic ancestry will be estimated for each of the neonates. With information on

genomic ancestry for both mothers and their newborns, a better understanding of the

contribution of ancestry to pregnancy-related phenotypes can be explored. Two possible

research areas for future study with the addition of fetal ancestry are, 1) how fetal and

maternal West African ancestry contributes to birth weight and 2) how differences in

maternal and fetal ancestry affect risk of preterm birth. The second research focus is of

interest because, studies by Palomar et al. (2007) and Simhan and Krohn (2008) suggest

that paternal West African ancestry is associated with increased risk of preterm birth [52,

53]. In both studies only self-reported paternal race was used to investigate risk of

prematurity. Although paternal DNA has not been collected as part of the current

research design, average contribution of paternal ancestry to the fetus can be estimated

from neonate and maternal ancestry estimates. The ability to use genomic ancestry

50

estimates to investigate the role of ancestry in birth timing will improve upon these

previously reported findings.

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41. Bodnar, L.M., et al., High prevalence of vitamin D insufficiency in black and white pregnant women residing in the northern United States and their neonates. J Nutr, 2007. 137(2): p. 447-52.

42. Nesby-O'Dell, S., et al., Hypovitaminosis D prevalence and determinants among African American and white women of reproductive age: third National Health and Nutrition Examination Survey, 1988-1994. Am J Clin Nutr, 2002. 76(1): p. 187-92.

43. Lee, J.M., et al., Vitamin D deficiency in a healthy group of mothers and newborn infants. Clin Pediatr (Phila), 2007. 46(1): p. 42-4.

44. Signorello, L.B., et al., Blood vitamin d levels in relation to genetic estimation of African ancestry. Cancer Epidemiol Biomarkers Prev, 2010. 19(9): p. 2325-31.

45. Hanis, C.L., et al., Individual admixture estimates: disease associations and individual risk of diabetes and gallbladder disease among Mexican-Americans in Starr County, Texas. Am J Phys Anthropol, 1986. 70(4): p. 433-41.

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49. Klimentidis, Y.C., G.F. Miller, and M.D. Shriver, Genetic admixture, self-reported ethnicity, self-estimated admixture, and skin pigmentation among Hispanics and Native Americans. Am J Phys Anthropol, 2009. 138(4): p. 375-83.

50. Shriver, M.D., et al., Skin pigmentation, biogeographical ancestry and admixture mapping. Hum Genet, 2003. 112(4): p. 387-99.

51. Wimalawansa, S.J., Vitamin D in the new millennium. Curr Osteoporos Rep, 2012. 10(1): p. 4-15.

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52. Palomar, L., et al., Paternal race is a risk factor for preterm birth. Am J Obstet Gynecol, 2007. 197(2): p. 152 e1-7.

53. Simhan, H.N. and M.A. Krohn, Paternal race and preterm birth. Am J Obstet Gynecol, 2008. 198(6): p. 644 e1-6.

54

Chapter Three

Admixture Mapping to Detect Novel Candidate Regions for Preterm Premature

Rupture of Membranes (PPROM) in African-American Women

Abstract

Preterm birth is a complex disorder that is a leading contributor to infant mortality

in the United States, particularly among African-American women, who are at increased

risk. It is evident that risk of preterm delivery is not limited to social and environmental

factors, suggesting a role for genetic influences. In this study genome-wide admixture

mapping was used to identify gene regions that affect the risk of preterm delivery,

specifically preterm premature rupture of membranes (PPROM), in African-American

women. PPROM is characterized by spontaneous rupture of fetal membranes prior to 37

weeks gestation and accounts for 30-40% of preterm deliveries. This methodology has

revealed novel candidate regions for future studies of PPROM.

African-American women were recruited at the time of delivery to participate in

this study. Cord blood or umbilical cords were collected for DNA extraction from

neonates born to women with PPROM to serve as cases (n = 352) and from women with

uncomplicated, term deliveries to serve as controls (n = 264). DNA samples from the

research subjects were genotyped on a genome-wide panel of 1,509 ancestry informative

markers (AIMs) specifically designed for admixture mapping in African-American

populations. ADMIXMAP, an admixture mapping statistical package, was used to

control for admixture stratification and to test for associations between PPROM and

55

ancestry across the genome. Ancestry estimates and phenotype-ancestry associations

were generated using prior allele frequencies from three parental populations, West

African, European, and East Asian. The average West African contribution to genetic

ancestry in the combined sample is 80%. Regions on five chromosomes were identified

as contributing to risk of PPROM in the African-American sample, four associated with

West African ancestry (chromosomes 5, 8 11, and 19) and one associated with European

ancestry (chromosome 21).

Introduction

Preterm premature rupture of membranes (PPROM) is the largest contributor to

preterm birth, accounting for 30-40% of all preterm deliveries [1]. PPROM is

characterized by the rupture of the fetal membranes prior to the onset of labor at less than

37 weeks gestation. PPROM occurs at a substantially greater frequency among African-

American women than any other “racial” group in the United States [2, 3]. To date, very

few studies have focused on understanding the genetics of this sub-phenotype of preterm

birth. These studies have used candidate gene approaches that have focused on suspected

pathways involved in PPROM, primarily inflammation and matrix metabolism. And only

one, Wang et al. (2006), has identified an association that explains the increased

prevalence of this disorder among African-American women [4]. The current research

uses a genome-wide admixture mapping approach with the goal of identifying regions of

the genome that contain novel candidate genes contributing to risk of PPROM and a

better understanding of the disparity in risk of this preterm birth phenotype.

56

Background

The difference in incidence of preterm birth seen in African-American women

compared to other U.S. populations has been the subject of much research. It is clear

from epidemiological studies that the difference in risk of preterm birth cannot be

completely explained by lifestyle and environment factors, suggesting a likely genetic

component to the increased risk of preterm delivery seen in these women [5]. Most

studies that have investigated the role for genetics in risk of prematurity have not

distinguished between the causes that result in preterm delivery, including preterm labor

and preterm premature rupture of membranes (PPROM). There is some debate as to

whether these sub-phenotypes should be considered separately. However, it is important

to recognize that the different sub-phenotypes of preterm birth may result from different

pathways, and even from the contributions of different genomes (mother v. fetus). While

combining all causes of prematurity in genetic studies has the potential to increase

sample sizes, it may also reduce the effectiveness of identifying associations due to the

heterogeneity of the broader phenotype. Additionally, differing composition of sub-

phenotypes in sample populations across studies may make replication of genetic

findings across studies difficult. Difficulty in defining phenotypes has been suggested as

an impediment to replications of genome-wide association study (GWAS) findings [6, 7].

It is for this reason, in spite of the challenge of acquiring adequate sample sizes, that this

research focuses only on the preterm birth sub-phenotype PPROM.

57

Previous Studies of the Genetics of PPROM

There are several reasons to hypothesize that there is a genetic component to

preterm premature rupture of membranes (PPROM) risk. Like preterm birth, PPROM

clusters in families and women with a previous history of preterm rupture are more likely

to experience PPROM in future pregnancies [1, 8-10]. It has also been shown that

women carrying a fetus with a Mendelian connective tissue disorder, like Ehler-Danlos

Syndrome, are at increased risk of PPROM [11-13]. Although the mechanisms involved

in PPROM are not fully understood, candidate genes studies have focused primarily on

matrix metabolism and inflammation.

Variation in several matrix metalloproteinase (MMP) genes (MMP1, MMP2,

MMP 8, and MMP9) has been shown to contribute to risk of PPROM. These genes

encode for enzymes that break down collagen and increased expression is associated with

risk of PPROM [2, 14-16]. Additionally, a recent study of 190 candidate genes in

Hispanic women by Romero et al. (2010) identified associations between PPROM and

three matrix related genes outside of the MMP family, TIMP2, COL4A3, and COL1A.

This study also implicated two genes related to inflammation and infection, EDN1 and

DEFA5[16]. Other infection and inflammation related candidate genes that have been

associated with PPROM include CARD15, TLR4, and TNFA [17, 18].

It is important to note, that none of the polymorphisms identified as contributing

to risk of PPROM in these previously described candidate genes has been shown to have

an increased frequency in African-Americans. As such, they are unlikely to explain the

disparity in preterm birth seen among African-American women. One candidate gene

58

study, Wang et al., 2006, identified a polymorphism that was a greater frequency among

African populations compared to European populations (12.4% vs. 4.1%) and is

associated with risk of PPROM among African-American women. This SNP is in the

promoter of SERPINH1 and is related to the structure of the amnion [4]. This was the

first ancestry informative marker identified to be associated with risk of preterm birth.

While candidate gene studies in PPROM have been important in identifying some

variants associated with risk, for the most part they have failed to explain the disparity in

preterm birth among African-American women compared to European-American

women. For disorders, like PPROM, where there is a significantly greater prevalence in

one population compared to another, an admixture mapping approach can help to identify

regions of the genome that contain variants that contribute to increased risk associated

with ancestry. This approach was implemented for the research described in this chapter.

Admixture Mapping for the Discovery of Novel Candidate Regions for PPROM

In 2009, Anum et al. suggested that admixture mapping could be the most

promising approach for identifying novel candidate genes that contribute to risk of

preterm birth [19]. In phenotypes that show large differences between populations, like

PPROM, admixture mapping is an approach that can lead to the identification of novel

candidate genes.

The admixture mapping method works by exploiting linkage disequilibrium

created by the admixture process. Linkage disequilibrium (LD) is created between loci,

59

both linked and unlinked, when admixture occurs between parental populations that differ

in allele frequencies, as in the case of African Americans [20-22]. The large

chromosomal regions of LD created by admixture gradually decay over generations after

initial admixture as a function of recombination, mutation rate, and demographic factors

(like continuous gene flow and assortative mating) [23]. These large regions of LD in

admixed populations make them well suited for association studies. Figure 3-1 depicts

the decay of LD over generations as well as the potential utility of ancestry associated LD

blocks in identifying chromosomal regions associated with the phenotype of interest [24].

60

Figure 3-1. In the top portion of this figure the admixture process is modeled in terms of the inheritance of chromosomes contributed by different populations (1 and 2) to each generation. Recombination creates large blocks of linkage disequilibrium that decrease in size as a factor of the number of generations since admixture. The concept of admixture mapping suggests that if population 1 and population 2 carry different alleles at a disease locus, represented in the lower portion of the drawing by a dashed line, then using whole-genome panels of ancestry informative markers can identify regions of the genome where there is a difference in the ancestry between the cases and controls (red v. blue above). These regions can then be targeted for evidence of loci associated with the disease phenotype. Figure from Darvasi and Shifman (2005) [24].

The goal of admixture mapping is to identify regions of the genome where

ancestry is associated with the disease or trait of interest [25-27]. This is accomplished

by genotyping genome-spanning panels of single nucleotide polymorphisms (SNPs) that

have large allele frequency differences (measured as δ) between parental populations,

called ancestry informative markers (AIMs). For admixture mapping in African-

American populations, Hoggart et al. (2004) suggest a panel of more than 1,200 AIMs

61

with δ > 0.5 and an average distance between markers less than 3 centimorgans (cM)

[28]. Genotyping arrays like the Illumina (San Diego, California) African-American

Admixture Panel have been specifically designed to meet these standards.

With AIMs spaced evenly across the genome it is assumed that genes functionally

affecting disease with risk will be in linkage disequilibrium with some of the ancestry

markers that are typed. In the case of a dichotomous disease phenotype, like PPROM, it

is expected that those affected by the disease will show a different pattern of ancestry in

the area surrounding risk regions of the genome compared to controls. Figure 3-2

illustrates the expected association of ancestry with a risk region in cases compared to

controls [29]. In a phenotype like PPROM where there is increased risk in African-

Americans compared to European-Americans, this peak representing an increased risk of

disease in cases might be expected to be associated with increased West African ancestry.

62

Figure 3-2. This drawing illustrates the potential usefulness of admixture mapping with a large panel of ancestry informative markers (AIMs) to identify chromosomal regions that are associated with a disease phenotype of interest. Surrounding a disease-associated locus there will be an excess of ancestry from one of the parental populations included in the model. Figure from Patterson et al. (2004) [29].

The potential success of admixture mapping is dependent upon the time since

admixture. If the population has only been admixed for a few generations, LD blocks are

expected to be large, resulting in large regions of association between ancestry and the

phenotype of interest. In this situation, isolating a potentially causative gene will be

much more difficult to achieve due to the large size of the region that would require fine-

scale mapping. In the inverse scenario, if many generations have passed since admixture

began, linkage disequilibrium blocks will be small and many more markers will be

required. African-American and Hispanic populations are well suited to admixture

mapping studies because they have undergone a modest number of generations of

admixture. For example, estimates from large genotyping arrays suggest an average

63

number of six generations, approximately 150 years, of admixture among African-

Americans [29, 30]. Bonilla et al. (2004) report slightly greater number estimate of seven

generations (~ 175 years) for Hispanics in the San Luis Valley of Colorado [31].

Using a genome-wide panel of AIMs has similar power as much larger panels of

tag SNPs used in genome-wide association studies (GWAS), but at a substantially

reduced cost [32]. The Illumina African-American Admixture panel that was genotyped

in this study has been used by other researchers to help identify novel candidate genes

associated with asthma [29, 33], cardiovascular disease [34-36], multiple sclerosis [37],

prostate cancer [38-40], obesity [41, 42], and recently premature birth [43].

Previous Admixture Mapping Studies in Preterm Birth

To date, only one research report has been published using an admixture mapping

approach to investigate preterm birth. Last year, Manuck et al. (2011) reported a case-

only study of 177 African-American women with one or more spontaneous preterm

births. Using the same genotyping platform as the present research, the Illumina African-

American Admixture Panel, and the ANCESTRYMAP analysis package, the authors

identified a region on chromosome 7 (7q21-7q22) associated with risk of preterm birth.

This peak is associated with a chromosomal region of increased West African ancestry.

The number of significant SNPs in this chromosomal region found to be associated with

the phenotype increased when the severity of prematurity was considered. Compared to

the three SNPs identified with suggestive Logarithm of Odds (LOD) scores using the full

64

sample of 177 women with gestation < 37 weeks, using only the 106 women with

previous very premature births (< 32 weeks gestation), fifteen significant SNPs were

reported that reached a suggestive LOD score of 1.50 or greater. The number of

significant polymorphisms is reduced to six for gestation < 32 weeks when only those

that reach a significance threshold greater than a LOD score of three are considered [43].

The current research looks to improve upon the Manuck et al. study by including a larger

sample and a more specific preterm birth phenotype, preterm premature rupture of

membranes (PPROM).

Materials and Methods

Study Sample

Study subjects included in this research are fetuses/neonates born from singleton

pregnancies to women of self-reported African-American ancestry. Pregnant women

were recruited to participate in the study at the time of admission to the hospital for

delivery from three study sites: Virginia Commonwealth University Health System

(Richmond, Virginia), Hutzel Hospital (Detroit, Michigan), and the University of

Pennsylvania Health System (Philadelphia, Pennsylvania) by Dr. Jerome Strauss, Dr.

Roberto Romero or Dr. Juan Pedro Kusanovic. Case subjects are those deliveries

complicated by preterm premature rupture of membranes (PPROM) prior to 37 complete

weeks of gestation without evidence of major fetal malformation, genetic diseases known

65

to contribute to prematurity, trauma, maternal drug use during pregnancy, or

preeclampsia. Criteria used to confirm the case state (PPROM) included pooling of

amniotic fluid in the vagina, a characteristic ferning pattern of the amniotic fluid, and a

positive nitrazine test [4]. The control subjects in this analysis consist of neonates from

singleton pregnancies born at term, after 37 weeks of gestation, without known

complications. Gestational age was determined by the last menstrual period (LMP)

method and confirmed by ultrasound. DNA was extracted from cord blood collected at

the time of delivery and whole genome amplified to accommodate genetic analyses.

Genotyping

All samples were genotyped on the Illumina (San Diego, California) African-

American Admixture Panel at the Hershey Genome Sciences Core Facility at the

Pennsylvania State University Medical Center. This panel uses GoldenGate® Assay

technology to genotype 1,509 single nucleotide polymorphisms (SNPs) that show large

allele frequency differences between West African and European populations, the two

parental groups with the largest genetic contribution to the modern African-American

population [44]. These SNPs are referred to as ancestry informative markers (AIMs).

This platform is a valuable tool for admixture mapping because it covers the entire

genome in just over 1,500 markers, unlike GWAS panels that require hundreds of

thousands of markers. It is estimated that this targeted panel contains 75-80% of the

power to detect associations as found with in much larger, and substantially more

expensive, genome-wide panels of polymorphic markers that contain 300,000 to one

66

million markers [28, 44]. Details on the AIMs included in the Illumina African-

American Admixture Panel are in Appendix B.

Figure 3-3. Illumina African-American Admixture Panel. Minor allele frequency (MAF) differences between West African v. European (orange) and West African v. Asian (blue). Modified from Illumina SNP genotyping datasheet for the African-American Admixture Panel [44].

67

Data Cleaning

Samples Removed from Analysis

Prior to analysis, the genotype data was cleaned to remove subjects that did not fit

the criteria for either case or control. Subjects who were excluded as cases included

those that were classified as preterm but not PPROM, medically induced preterm births,

and pregnancies with multiple gestations. Additionally, duplicate subjects were removed

from the analysis, and those with less than a 70% genotyping call rate were also excluded

due to presumed poor DNA quality. Finally, neonates from women who did not self-

report African-American ancestry or with very low West African genomic ancestry (<

20%) were removed prior to admixture mapping analysis. Of the 642 research subjects

that were genotyped, 616 met the criteria for inclusion in the study.

Markers Removed from Analysis

The data were also cleaned to remove genotyping markers that did not meet a

minimum threshold of 70% of genotypes called. Additionally, all genotyping markers on

the X chromosome (n=54) were excluded from these analyses due to lack of complete

data on the sex of the neonates to include in the model and the known deficiency of

ADMIXMAP to accommodate analysis of associations on the X chromosome [40].

Finally, some SNPs were excluded due to their departure from Hardy-Weinberg

68

equilibrium, as described in the next section. In total, 1,398 SNP genotyping markers

were included in the analysis.

Departures from Hardy-Weinberg Equilibrium

An initial analysis of the data included screening for departures from Hardy-

Weinberg equilibrium (HWE). Preliminarily, both case and control samples were

evaluated using both ADMIXMAP and PLINK [45, 46]. ADMIXMAP utilizes the entire

sample without regard to case or control status to test HWE. It is important to consider

the cases and controls separately because alleles with significant risk effects may exhibit

departures from HWE in a combined sample of cases and controls. Removing SNPs

from further analysis due to a departure from HWE seen in the sample as a whole might

risk the loss of a highly significant disease-associated marker prior to testing for

association. Unlike ADMIXMAP, PLINK tests for deviations from Hardy-Weinberg

equilibrium in cases-only, controls-only and for the entire sample. A departure from

HWE in cases only was not considered sufficient for exclusion of a genotyping marker

from inclusion in the admixture mapping analysis, as explained above. All markers

identified as departing significantly from HWE (p < 0.01) in the control-only PLINK

output were removed prior to admixture mapping analysis. The tests for departure from

Hardy-Weinberg equilibrium resulted in the exclusion of 93 SNPs from the admixture

mapping study.

69

Admixture Mapping

Admixture mapping analysis was performed with the Bayesian statistical program

ADMIXMAP v.3.8 for Windows (available for download at

http://www.homepages.ed.ac.uk/pmckeigu/admixmap/index.html) [28, 47]. This program

tests the association between a phenotype (continuous or dichotomous) and locus

ancestry by conditioning on parental admixture.

A three-way model of ancestry was specified with prior allele frequencies

included in the analysis from three parental populations, West African, European, and

East Asian. The phenotype was specified as a dichotomous variable where a PPROM

case subject was given a value of 1 and a control subject a value of 0. The program also

permits the inclusion of covariates; however, none were included in this analysis due to

lack of information for all of the subjects included in the study.

The program was run with 500 burn-in and 10,000 iterations, with samples

thinned to record to the output files every 5 iterations. The adequacy of the burn-in and

number of iterations was established by investigating the diagnostic plots generated by

the ADMIXMAP program. A smoothing of the line over the course of the run indicates

that sufficient iterations have been used in the analysis. Both a case-control model and an

affected-only model were run. Although the affected-only model is considered more

powerful for rare diseases, the frequency of preterm birth is substantial (12.5% of births

in the United States) and therefore output from only the case-control analysis is included

in the results section of this chapter. The output of both affected-only and the case-

control analysis are included in the appendix (Appendix C).

70

Ancestry associations are reported as z-scores with their associated p-values for

each locus included in the model. The z-score is a test statistic for association of the

phenotype (PPROM in this case) with ancestry at each locus. In viewing the overall plot

of ancestry association presented in the results, a positive z-score represents an

association with West African ancestry, while a negative score is an association with non-

West African ancestry, either European or East Asian. Individual plots of the ancestry

associations by parental population are available in the appendix (Appendix C).

Estimating Genomic Ancestry

Genomic ancestry for all research subjects was estimated using a three-way model

of admixture. Prior allele frequencies derived from three parental populations (West

African, European, and East Asian) were included in the ADMIXMAP analysis to

improve the model as well as to estimate individual genetic ancestry. The Hershey

Genome Sciences Core Facility at Penn State Medical Center provided the population-

specific prior allele frequencies that are included for analysis by Illumina [44]. However,

the allele frequencies for the West African and European parental populations were

originally described in Smith et al. (2004) [30]. East Asian parental frequencies are

derived from the International HapMap Project [48]. The method employed in the

ADMIXMAP software package has been validated as achieving equivalent ancestry

estimates to those calculated using the maximum likelihood estimation (MLE) method

and with the software program Structure, especially when a large panel of ancestry

informative markers and a large sample size are included in the model [28, 47, 49-52].

71

Results

From the initial 642 DNA samples that were genotyped, a total of 616 samples

with 1,398 genotypes met all of the inclusion criteria for analysis in this study. This

included 352 case samples with preterm premature rupture of membranes (PPROM) and

264 control samples. Additionally, 111 of the 1,509 ancestry informative markers

(AIMs) that were genotyped on the African-American Admixture panel were excluded

from the study for reasons detailed in the methods. The average difference in parental

allele frequency for each pairwise comparison (West African to European, West African

to East Asian, and European to East Asian), delta (δ), was not affected by the removal of

these markers as seen in Table 3-1. However, the average distance between genotyping

markers, measured in centimorgans (cM), increased from an average of 1.95 ∆cM for the

full panel of 1,509 AIMs to 2.75 ∆cM for the reduced panel of 1,398 markers. Figure 3-5

contains information on the average distance between genotyping markers calculated for

each chromosome.

72

Table 3-1. Average delta (δ) calculated between each parental population included in the full Illumina African-American Admixture Panel compared to the reduced panel used in the admixture mapping analysis for this study.

Delta (δ)

Number of SNPs

West African - European

West African - East Asian

European - East Asian

Full Ancestry Panel 1,509 0.738 0.568 0.193

Analysis Panel 1,398 0.736 0.565 0.194

Genomic Ancestry Estimates

Genomic ancestry was calculated as a parameter of the ADMIXMAP analysis

from user specified prior allele frequencies. The estimates are more robust with larger

sample sizes and increased numbers of ancestry informative markers (AIMs). On

average, cases and controls have similar levels of European admixture, 17.3% and 17.0%

respectively, as represented in Table 3-2. The distribution of West African ancestry

ranges are 42%-97% in cases and 48%-98% in controls (Figure 3-4). The mean genomic

ancestry estimate for the study sample is 80.8% West African, 17.2% European and 2.1%

East Asian. As expected, the East Asian average was very low for the sample as a whole.

The small East Asian component may more likely reflect a low level of Native American

admixture that was not assessed due to lack of available prior allele frequencies for all of

the loci included in the analyses. Additionally, the sum of intensities parameter gives an

73

estimated average time since admixture (τ) of 6.7 (with a 2.5% bound of 6.59 and 97.5%

bound of 6.83) generations. At a generation time of 25 years, this is approximately 168

years.

Table 3-2. Average genetic ancestry calculated for cases (PPROM) and controls in a 3-way admixture model (West African, European, and East Asian) using ADMIXMAP. Standard deviations included in parentheses.

Average Ancestry

Sample West African European East Asian

PPROM 352 80.4 (±8.0) 17.3 (±7.2) 2.3 (±3.1)

Control 264 81.3 (±7.8) 17.0 (±6.7) 1.7 (±3.0)

Total 616 80.8 (±7.9) 17.2 (±7.0) 2.1 (±3.1)

74

Figure 3-4. Genomic ancestry of the study sample. Triangle plots of three-way admixture for cases, controls and the full sample are shown in the top of the figure. Each circle represents the admixture proportions of a single subject. The histogram compares the distribution of West African genomic ancestry between case and control subjects. In both portions of the figure, controls are labeled in orange and cases in blue.

75

Admixture Mapping

Genome-wide ancestry association z-scores for the case-control analysis in

ADMIXMAP are plotted by chromosome and shown in Figure 3-5. Chromosomes with

ancestry association peaks above |z| = 2.5 (p < 0.01) are shown in Figure 3-6. These

peaks occur on chromosomes 5, 8, 11, 19, and 21. Each of these chromosomes has one

ancestry association peak, with the exception of chromosome 11 with a peak on either

end of the chromosome. The genetic ancestry association peaks on chromosomes 5, 8,

11, and 19 are in the West African direction; however the peak on chromosome 21 is

associated with European ancestry. Ancestry association z-scores and their associated p-

values are shown in Table 3-3. The SNP with the largest ancestry association is

rs2833775, located on chromosome 21. This SNP shows an increased European ancestry

with a z-score of -3.636 (p= 0.00028). It is located among a cluster of eight other SNPs

(rs9977512, rs380417, rs2070398, rs2832643, rs2284473, rs2834670, and rs718387) that

fall within a large peak on chromosome 21. The strongest West African ancestry

association is found on chromosome 19, rs10405317 (z = 3.263, p = 0.0011). This SNP

along with one other (rs2285972, z = 2.767, p = 0.0057) form a small peak near the

telomeric end of the short (p) arm of chromosome 19. In total, there are twenty-nine

SNPs with ancestry association z-scores greater than 2.5 (|z| > 2.5, p-value < 0.01) under

six peak on five chromosomes.

In addition to the plots shown in this chapter, ancestry association score maps

displaying the ancestry association z-scores plotted by location along each chromosome

for West African and European ancestry are shown in Appendix C for both the case-

76

control and affected-only admixture mapping analyses. Tables containing complete lists

of the ancestry association and allelic association values (z-score and p-value) by

genotyping marker for the case-control and affected-only analyses are also included in

the appendix (Appendix C).

77

Distance (cM)

(a)

(b)

Figure 3-5. a) Genome-wide ancestry associations from case-control admixture mapping analysis. Z-scores show associations with West African ancestry. b) Number of SNPs per chromosome and the average physical distance in centimorgans (cM) between SNPs for each chromosome included in the admixture mapping analysis.

78

Figure 3-6. Ancestry association score maps for chromosomes with significant peaks (Chromosomes 5, 8, 11, 19, and 21). Ancestry association z-scores for each locus are plotted along the chromosome in centimorgans (cM). a) Ancestry association maps for West African ancestry. b) Ancestry association map for European ancestry.

79

Table 3-3. Ancestry association peaks for case-control admixture mapping. The z-scores and p-values for each SNP within the ancestry association peaks are shown. Changes in the shading are used to distinguish the SNPs within each chromosomal peak of ancestry association.

Locus Physical AncestralName Chromosome Position z -score p -value Population

rs40030 5 36212631 2.635 0.0084077 Africanrs930072 5 36701828 2.793 0.00522288 Africanrs4869577 5 38254937 2.738 0.00618999 Africanrs12657366 5 39207788 2.909 0.00363159 Africanrs6883840 5 40322167 2.881 0.00396513 Africanrs16932440 8 67113059 2.941 0.00327326 Africanrs7933164 11 4050526 2.591 0.00957268 African

rs10768634 11 5149986 2.639 0.00831996 Africanrs10765838 11 11326144 2.751 0.00594973 Africanrs2403595 11 12341885 2.708 0.00677201 Africanrs6486270 11 15927515 2.994 0.00275669 Africanrs4148636 11 17383939 2.956 0.00311595 Africanrs11024739 11 18602419 2.857 0.00427769 African

rs647756 11 107040968 2.471 0.0134832 Africanrs566552 11 108726089 2.808 0.00498026 African

rs4622301 11 110301295 2.864 0.00417852 Africanrs6589360 11 112555502 2.933 0.00335893 Africanrs7934726 11 113415486 2.996 0.00273367 Africanrs2507874 11 114433145 2.488 0.0128593 Africanrs2285972 19 1309726 2.767 0.00565273 Africanrs10405317 19 1642725 3.263 0.00110079 Africanrs9977512 21 24556659 -2.737 0.00619357 Europeanrs380417 21 26194030 -2.8 0.00511056 Europeanrs2070398 21 29800235 -3.603 0.00031422 Europeanrs2832643 21 30450088 -3.602 0.00031533 Europeanrs2284473 21 31450991 -3.542 0.00039638 Europeanrs2833775 21 32634146 -3.636 0.00027695 Europeanrs2834670 21 35202246 -2.938 0.00330705 Europeanrs718387 21 36049947 -2.581 0.00984816 European

Ancestry Association

80

Discussion

Average genomic ancestry of the study subjects is similar to the average reported

by Parra et al. (1998) and Smith et al. (2004) for U.S. African-Americans, approximately

80% West African and 20% European. Additionally, the time since admixture reported

from the sum of intensities for this study was τ = 6.7, approximately 168 years. While

this value may seem low given the known historical introduction of enslaved West

Africans to the United State over 400 years ago (< 20 generations), it is within the ranges

previously reported, and similar to those found by Patterson et al. (2004) and Smith et al.

(2004) using similar high density SNP panels, τ = 6.0 and τ = 6.3, respectively.

Power calculations reported by Hoggart et al. (2004) suggest that the cutoff for

statistical significance for ADMIXMAP results is a z-score of 4.27 with a corresponding

p-value of 10-5. They determined that for an African-American population with average

admixture proportions approximating those found in this study (80% West African and

20% European) a sample of 800 subjects would be needed [28]. Not surprisingly, given

the much smaller sample available for this analysis, none of the ancestry associations

reported in this study reach this level of significance. The most significant result is the

large peak on chromosome 21 that is associated with excess European ancestry. This

peak is composed of eight SNPs that span a nearly 11.5 Mb region on chromosome

21q21-21q22. The center of the peak is composed of four SNPs (rs2070398, rs2832643,

rs2284473, and rs2833775) with z-scores near 3.6 (p-values < 0.003). This large peak of

European ancestry suggests a region where European ancestry is contributing to risk of

PPROM in the African-American research subjects.

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There are a number of genes within the large ancestry association peak on

chromosome 21. While none of these genes had been identified as a candidate gene for

preterm birth or PPROM, two related genes in the ADAMTS (ADAM metallopeptidase

with thrombospondin) family, ADAMTS1 (21q21.2) and ADAMTS5 (21q21.3), were

notable. This family of genes has been previously reported to be associated with

parturition and inflammation. Specifically, increased expression of ADAMTS1 has been

shown in mice to be involved in cervical ripening around the time of birth [53]. Given

their known involvement in inflammation and parturition, these genes may warrant

further investigation for their potential role in preterm birth.

Another potentially interesting result comes from the small ancestry association

peak on chromosome 8. This peak shows an increase in West African ancestry and

includes only one SNP, rs16932440. While the z-score associated with this SNP (z =

2.941, p = 0.0033) does not meet the significance cutoff of z > 4.27, it is located near the

corticotropin releasing hormone gene (CRH) at 8q13. With the expected long stretches of

linkage disequilibrium found in admixed populations, the proximity of rs16932440 to

CRH is worth investigating.

Corticotropin (CRH) is produced by the placenta and fetal membranes during

pregnancy [54, 55]. The level of CRH increases over the course of pregnancy, with high

levels detected in the maternal blood and amniotic fluid near the time of birth [56, 57].

CRH is thought to be important in the onset of uterine contractions and has also been

implicated in the rupture of fetal membranes through the activation of the matrix

metalloproteinase MMP-9 [57, 58]. Additionally, women who experience preterm birth

have higher levels of CRH than those that deliver at or after term [59].

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Although CRH is not listed as a preterm birth candidate gene, corticotropin

releasing hormone binding protein (CRHBP) was found to be strongly associated with

preterm birth risk by Velez et al. (2008) [60]. With the known role of corticotropin in

birth timing, the ancestry association near the CRH gene is intriguing and will be

investigated further in the planned replication of this study.

In addition to investigating the results of the admixture mapping ancestry

associations with known candidate genes, the results of the current study were compared

to the findings from Manuck et al. (2011) for evidence of overlap in significant ancestry

associations [43]. While Manuck et al. found an ancestry association peak on

chromosome 7, this was not replicated in the current admixture mapping analysis.

Additionally, none of the fifteen SNPs identified by Manuck et al. showed evidence of

significantly increased West African ancestry in the current study.

There may be several reasons that the current analysis failed to replicate the

results found by Manuck et al. First, the phenotype used in this study is a sub-phenotype

of preterm birth. Manuck et al. used only African-American ancestry and previous

preterm delivery as criteria for inclusion of samples in their study. There was no

discussion of analyzing samples by cause of preterm delivery. It is possible that different

genes may contribute to PPROM than to other mechanisms related to preterm birth, like

preterm labor or preeclampsia. Additionally, the Manuck et al. study used maternal DNA

and this study uses neonate DNA. The varying contributions of the maternal and fetal

genomes to parturition are not fully understood. It is likely that different genes in

mothers and fetuses play a role in both normal birth timing and preterm birth.

83

The use of admixture mapping to understand the genetics of preterm birth is still

in its infancy. With the availability of inexpensive methods for genotyping large panels

of polymorphisms, the ability to use admixture mapping to locate novel candidate regions

and to help identify genes contributing to the increased risk of preterm birth seen among

African-American women is promising.

Future Directions

Covariates were not included in the current analysis. This was due to a lack of

information for all genotyped individuals at the time of analysis. When these data are

available, the results presented in this chapter will be repeated to include the investigation

of covariates such as number of weeks gestation at the time of delivery (particularly to

consider early v. late preterm delivery), age of the mother, smoking status of the mother,

pre-pregnancy BMI, infection status, and parity, all known to potentially influence risk of

preterm delivery.

To improve the power to detect novel candidate regions for PPROM, a

continuation of this study is planned to increase the sample size. Presently, additional

PPROM cases are being collected to facilitate a replication of this work. In addition to

implementing an admixture mapping approach with the replication sample, tag SNPs

(polymorphisms used to infer variation across a region of the genome due to strong

linkage disequilibrium) will be included in future genotyping efforts to evaluate

84

previously implicated candidate genes for PPROM as well as putative candidate genes

that show evidence for accelerated evolution as described in Chapter 4.

Given that the Illumina (San Diego, California) African-American Admixture

Panel is no longer available, the use of a similarly powerful platform for admixture

mapping will be needed [44]. At present, Affymetrix (Santa Clara, California) is

marketing a whole genome (Axiom) exom genotyping array that contains over 318,000

markers [61]. In addition to its applications to genome-wide association studies, this

array has been validated for use on admixed populations with the inclusion of a large

panel of ancestry informative markers (AIMs). Another appealing aspect to this platform

is the ability to add a panel of up to 100,000 customer-selected markers to the off-the-

shelf exom array. This will facilitate the addition of SNPs identified as significant in the

current admixture mapping study that might not be represented on the basic exom array,

or the inclusion of SNPs within candidate genes previously implicated in PPROM.

85

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Chapter 4

Investigating Evidence for Accelerated Evolution at Preterm Birth Candidate Genes

Abstract

Preterm birth is a complex phenotype that is a leading cause of infant mortality in

the United States. Although social and environmental factors play a role in risk of

prematurity, it is increasingly understood that genes likely contribute to risk. African-

American women experience the greatest risk of preterm birth among U.S. populations,

nearly twice that of European-American women. In this study, tests to screen for

accelerated evolution of both the regions identified by admixture mapping and or

previously reported preterm birth candidate genes were used to prioritize a panel of

genomic regions and candidate genes to better understand the role of genetics in the

increased risk of preterm birth among African-American women.

In Chapter 3, admixture mapping analysis was conducted using a sample of 616

neonates born to women of self-reported African-American ancestry. Genotyping of

DNA from the newborns of 352 women with confirmed preterm premature rupture of

membranes (PPROM) and neonates from 264 women with normal term pregnancy

outcomes was completed using a genome-wide panel of ancestry informative markers

(AIMs) designed for admixture mapping analysis in African-American populations.

Bayesian admixture mapping identified six regions on five chromosomes (5, 8, 11, 19

and 21) that contribute to risk of PPROM. These ancestry association peaks as well as

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90 previously reported candidate genes for preterm birth were tested for signatures of

accelerated evolution using locus specific branch length (LSBL), log of the ratio of

heterozygosities (lnRH), and normalized Tajima’s D. All of the genomic regions found

by admixture mapping to be associated with risk of PPROM among African-American

women had significant evidence of accelerated evolution. Additionally, 31 of the 90

candidate genes screened were found to show signatures of accelerated evolution in West

Africans and 24 in Europeans. For phenotypes that vary among populations, like preterm

birth, tests for accelerated evolution may be a useful method for nominating candidate

regions and candidate genes for further study.

Introduction

In the United States incidence of preterm birth is substantially greater among

African-American women compared to women of any other ancestry. It has been

suggested that while social and environmental factors may account for a portion of the

increased incidence of preterm birth seen in African-American women, there is likely a

genetic component to risk. To date, numerous studies have been undertaken to identify

genes that contribute to risk of preterm delivery with limited success in identifying

genetic variants that explain the disparity in risk experienced by African-American

women [1]. In an attempt to prioritize candidate genes that influence risk of preterm

birth in the admixed African-American population, previously identified regions of the

genome found to be associated with preterm premature rupture of membranes (PPROM)

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(Chapter 3) and previously published preterm birth candidate genes were screened for

evidence of accelerated evolution in West African and European parental populations.

Background

Modern human populations exhibit a large amount of phenotypic variation both in

many normal traits and in susceptibility to various diseases. Evolutionary forces have

shaped the genes contributing to this variation over the past 100-200 thousand years as

anatomically modern humans evolved in Africa and small populations began migrating to

inhabit a variety of environments outside of Africa [2, 3].

As large genotyping and sequencing platforms have become available, testing the

genome for signatures of departures from neutrality, or accelerated evolution, has become

possible. A variety of statistical methods have been created to localize genes shaped by

evolution due to random change such as genetic drift, demographic effects such as

population bottlenecks or expansions, and directional selection (purifying or positive)

resulting from adaptation to varying environments and pathogens. These tests exploit

predictable patterns in the genome that are likely to occur when evolution is acting. As

selection acts to increase the frequency of the advantageous allele a reduction in

heterozygosity at the gene under selection and at linked loci in the area surrounding the

gene will occur. This phenomenon is referred to as a “selective sweep”. Additionally,

large differences in allele frequency between populations are an indication that evolution

has been acting differentially among populations.

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Some of the strongest signals of evolution in the genome appear to be in genes

that confer a fitness advantage to the population under study. Evidence for strong

selection has been reported for variation in normal human phenotypes like skin

pigmentation, genes that confer resistance to pathogens such as malaria, and even among

genes associated with diet like the convergent evolution of lactase persistence at the LCT

gene among Northern Europeans and some African populations [4-6].

Complex disease phenotypes that show differential risk among human

populations are likely the result of the interplay between environment, lifestyle, and

genetic factors, as is likely the case with preterm birth. Although natural selection is

unlikely to contribute directly to disparity in preterm birth, the pathways that have been

implicated in birth timing, like inflammation and endocrine, affect many tissues and

systems of the body. Due to the pleiotropic effects of these genes, if selection has acted

for a different phenotype, it is possible that changes in these genes have affected preterm

birth risk. Identifying genomic regions and candidate genes that have signatures of

evolution may provide insight into the genetic contributions to disparity in disease risk.

For this study three tests for accelerated evolution, locus specific branch length

(LSBL), log of the ratio of heterozygosities (lnRH), and normalized Tajima’s D, were

conducted on the six chromosomal regions previously reported to contribute to risk of

preterm premature rupture of membranes (PPROM) among Africa-American women (see

Chapter 3) and ninety previously reported candidate genes for preterm birth [7-9]. The

goal of this research is to prioritize genomic regions and candidate genes for future

genotyping efforts that are more likely to explain the difference in risk of preterm birth

experienced by African-American women.

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Materials and Methods

Admixture Mapping

As described in Chapter 3, DNA samples from 616 newborns of self-identified

African-American women 352 with preterm premature rupture of membranes (PPROM),

the largest contributor to preterm birth, and 264 with normal pregnancy outcomes were

analyzed on the Illumina (San Diego, California) African-American Admixture Panel

[10, 11]. The panel is comprised of 1,509 single nucleotide polymorphisms (SNPs)

spanning the human genome. These markers were specifically selected for admixture

mapping because they are ancestry informative, that is, they have large allele frequency

differences between the West African and European parental populations known to

contribute to African-American admixture [12-14]. These SNPs are called ancestry

informative markers and are referred to as AIMs in this chapter.

Admixture mapping analysis was conducted in ADMIXMAP using the 1,398

AIMs that passed quality controls and met the other inclusion criteria previously

described in Chapter 3 [15-17]. The analysis resulted in the identification of five

chromosomes with peaks of significant ancestry association with PPROM (|z| > 2.5, p-

value < 0.01). Chromosomes 5, 8, 11 (two peaks), and 19 had evidence of association

with West African ancestry while a large peak on chromosome 21 was associated with

European ancestry. In total six chromosomal regions on five chromosomes were found

to have ancestry association with the phenotype of interest, PPROM. These peaks and

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the AIMs that were within the peaks were analyzed for evidence of accelerated evolution

using three tests, locus-specific branch length (LSBL), log of the ratio of heterozygosities

(lnRH) and normalized Tajima’s D. For the analysis of the ancestry associated peaks a

window beginning 200 kilobases (kb) before the first AIM in the ancestry peak and

ending 200 kb beyond the last AIM in the peak were analyzed. The start and end

positions of the first and last AIM within each ancestry associated peak are shown in

Table 4-1 along with the AIMs that are found within the ancestry peak and the ancestral

population of ancestry association. It is important to note that the first ancestry

association peak on chromosome 11 described in Chapter 3 has been divided into two

different peaks for the analyses included in this study because not all of the SNPs within

the peak had significant ancestry association values (p < 0.01). The two test regions

created from this one ancestry association peak have continuous significant SNPs from

the African-American Admixture panel; they are labeled 11 Peak 1 and 11 Peak 2. The

third peak analyzed in this study, 11 Peak 3, is the second peak on chromosome 11

described in Chapter 3.

In addition to the analysis of each chromosomal region found to be associated

with PPROM by admixture mapping, each AIM within the peaks was investigated for

evidence of accelerated evolution. As with the peak analysis, a 200 kb window upstream

and downstream of the AIM position was used for the screens. There is no overlap

between test windows for AIMs from the same ancestry association peak. The

chromosomal position and test window location for each of the AIMs is shown in Table

4-3 of the results.

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Table 4-1. Description of chromosomal peaks identified by admixture mapping as associated with PPROM. The peak “start” and “end” positions are determined by the subtracting 200kb from the first SNP found within the peak and adding 200kb to the last ancestry-associated SNP within the peak. The ancestry association of each peak is listed in the “Assoc. Pop.” column of this table.

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Candidate Genes

Genes that have been previously described in candidate gene studies of preterm

birth were chosen for investigation in this study. This included 84 genes listed in the

Preterm Birth Gene database (PTBGene database)

(http://bioinformatics.aecom.yu.edu/ptbgene/index.html) and in Preterm Birth: Causes,

Consequences and Prevention (Behrman and Butler 2007) [18, 19]. Dr. Jerome Strauss

of Virginia Commonwealth University suggested an additional six genes from more

recent publications (ENPP1, SERPINH1, FSHR, TIMP2, IGF2, and COL4A3) for

inclusion in this analysis (personal communication with Dr. Strauss). The candidate

genes listed in the PTBGene database and Behrman and Butler (2007) are not limited to

any specific phenotype associated with preterm birth, such as preterm premature rupture

of membranes or preterm labor. These genes are found in a variety of pathways thought

to be associated with birth timing and possibly preterm birth, including inflammatory,

uteroplacental, endocrine, uterine contraction, coagulation, metabolic, and matrix

metabolism pathways. In total ninety genes were tested for accelerated evolution.

For each gene analyzed the transcription start and end positions were determined

using the UCSC Genome Browser (http://genome.ucsc.edu/cgi-bin/hgGateway) [20]. For

the tests of accelerated evolution a window was created to include the gene plus 200

kilobases (kb) upstream and downstream of the gene. A full list of the candidate genes

included in this analysis and their chromosomal positions are shown in Appendix E.

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Tests for Accelerated Evolution

Sample Populations and Genotyping Panel

The data set used for this study consists of genome-wide genotype data from four

parental populations known to contribute to admixture in the United States, European,

West African, East Asian, and Native American. Three of the populations included are

from the International HapMap Consortium [21]. These include CEPH European

individuals from Utah (n = 60), Yoruba individuals from Ibidan, Nigeria (n = 60), and

East Asians from Beijing, China (Han Chinese) and Tokoyo, Japan (n = 90).

Additionally, Indigeous American (n = 88) individuals from four Central and South

American locations were also analyzed but not used in the current study. Genotyping of

DNA from these individuals was performed on the Affymetrix (Santa Clara, California)

Genome-wide Human SNP Array 6.0 [22]. This genotyping panel included 906,600

single nucleotide polymorphism distributed across the nuclear and mitochondrial

genomes at an average marker spacing of ~1.7 kilobases (kb). Genotyping markers and

individuals with low call rates (< 95%) were excluded from the analysis.

Locus Specific Branch Length (LSBL)

The first test for accelerated evolution assessed in this research is locus-specific

branch length (LSBL). This test uses pairwise measurements of FST in three populations

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to identify directional change in frequency of an allele of interest. F-statistics were first

described by Sewall Wright as a way to measure inbreeding by looking at reductions in

heterozygosity [23]. The FST statistic determines how much of the variation exists

within subpopulations (S) compared to the total population (T). Pairwise FST is

calculated using the following equation:

where, σ is the variance in allele frequencies in a single population and p and q (q = 1 - p)

are the mean allele frequencies in the whole population.

Values of FST range from 0 to 1. A value of 0 indicates there is no difference

between populations whereas FST equal to 1 indicates that the variation all of the variation

is between populations and that an allele is fixed in one population and lost in the other.

Large values of FST can occur due to natural selection, however they can also indicate

demographic factors like population bottlenecks or genetic drift.

Weir and Cockerham (1984) developed an unbiased FST estimator that is used in

this analysis [24]. The unbiased FST (θ) is a more appropriate test than Wright’s FST for

human data because it accounts for variation in sample size between populations and the

inability in natural populations to sample all of the genetic variation. Weir and

Cockerham’s unbiased FST equation is:

Fst =σp

2

pq

99

where, a is the variance between populations, b is the variance between individuals

within a population, and c is the variance between gametes within individuals.

To calculate locus specific branch length (LSBL) first pairwise FST was calculated

between each parental population, West Africans and Europeans (dWE), West Africans

and East Asians (dWA), and Europeans and East Asians (dEA) [7] (see Figure 4-1). Then

each branch length was calculated using the following formulas:

West African LSBLW = (dWE + dWA – dEA)/2

European LSBLE = (dWE + dEA – dWA)/2

East Asian LSBLA = (dWA + dEA – dWE)/2

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Figure 4-1. Diagram of Locus Specific Branch Length (LSBL) using the three populations modeled in this study: West African (W), European (E), and East Asian (A). LSBL is calculated from the genetic distances (D) between the population of interest and two other populations. For this study, LSBLW was calculated as (dWE + dWA – dEA) / 2 and LSBLE was calculated as (dWE + dEA – dWA)/2. Adapted from Shriver et al. (2004) [7].

A long branch length in a particular population can be interepreted in two ways, either

that the change occurred specifically in that population or that the change occurred in the

other two populations after their divergence from the common ancestor of the population

of interest. For example, a large branch length in West Africans could indicate evolution

in Africa after Europeans and East Asians migrated out of Africa or evolution occurring

in European and East Asian populations, or the common ancestor of these populations,

since their split with Africa. Large positive values of LSBL at a locus reflects dramatic

101

change in allele frequency either due to the action of natural selection or random genetic

drift.

Empirical distributions of LSBL values were generated for West Africans and

Europeans and SNPs that fell within the top 5% of the distribution were considered

significant. The cut-off for the West African sample was 0.3664 and the value for

Europeans was 0.2232.

Log of the Ratio of Heterozygosity (lnRH)

Under the neutral expectation, two populations should maintain the same level of

genetic diversity that existed prior to their divergence. In this case, the level of

heterozygosity in both populations should be the same. If, however, genetic drift or

natural selection has acted at a locus, a reduction in heterozygosity is expected. The

lnRH statistic was developed by Schlotterer and Dieringer (2005) to measure this

difference in genetic variation between two populations [8, 25]. Using this statistic, a

reduction in heterozygosity in population 1 compared to population 2 will result in a

negative lnRH value and indicate that an evolutionary force, like natural selection or

genetic drift, has acted on the tested locus in the first population and not in the second.

The equation for lnRH is shown below. In this equation H is the expected

heterozygosity determined for each of the two populations from the known allele

frequencies in the populations.

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In this study the lnRH values were calculated for the ratio of West

African/European (for West Africans) and also European/West African (for Europeans)

for each SNP in the specified gene window. As described previously, negative values

indicate accelerated evolution in the population of interest (population 1) compared to a

reference population (population 2). Significance cut-off values for lnRH determined

established from the bottom 5% of the empirical distribution for West Africans is -3.5837

and -6.9975 for Europeans.

Normalized Tajima’s D

The Tajima’s D statistic was developed to detect regions of the genome that

depart from the neutral expectation. Using sequence data two different measure of gene

diversity (θ) are compared, the number of segregating sites (S) and the average number of

pairwise differences (π) [9]. In the absence of evolution or changes in population size, the

values of S and π will be equal. However, if differences in these values exist D will

become either positive or negative. Positive values of D occur when π is greater than S

and indicate either balancing selection or a reduction in population size. A large S value

lnRH = ln

E 11− HPop1

2

−1

E1

1− HPop2

2

−1

= lnGene Diversity Population 1Gene Diversity Population 2

103

will result in a negative Tajima’s D. Negative values of D can indicate either positive or

purifying selection or a population expansion. Tajima’s D is calculated using the

equation below. The values of the variables a1, e1 and e2 are related to the number of

sequences included in the calculation.

For this study, Tajima’s D was calculated using overlapping sliding windows of

100 kb in 25 kb increments to accommodate the use of SNPs instead of sequence data

[26]. The number of SNPs in each window varies as a result of the genotyping platform

used for this analysis. Windows containing fewer than five successfully genotyped SNPs

were not considered. Tajima’s D is sensitive to demographic factors, especially to

population expansion after a bottleneck which leads to an excess of rare variants. To

account for the varying effects of demographic factors across populations, the Tajima’s D

values used in this analysis were normalized by dividing the D value calculated in each

window by the average genome-wide D value for the population of interest, West African

and European in this analysis.

For the purposes of this study, only negative D values, evidence of directional

selection, were considered. The 5% cutoffs established by the empirical distributions for

normalized Tajima’s D were -1.7708 and -1.9209 for the West African and European

populations, respectively.

D =π − S

a1

e1S + e2S(S −1)

104

Evaluating the Significance of the Tests of Accelerated Evolution

For each PPROM ancestry association peak or preterm birth candidate gene a 200

kilobase (kb) window surrounding the SNP or gene was tested for evidence of

accelerated evolution using three tests, locus specific branch length (LSBL), log of the

ratio of heterozygosities (lnRH) and normalized Tajima’s D in this analysis. Tests of

accelerated evolution were conducted for both West African and European parental

populations. Figures were generated for each test of evolution for each chromosomal

region or candidate gene that was tested for both West Africans and Europeans. Each

blue or orange vertical line represents an individual SNP (LSBL and lnRH) or sliding

window (Tajima’s D) tested within the peak of interest. SNPs or windows that fall in the

appropriate 5% tail of the distribution are considered significant for the test, as described

in the methods, and are displayed in orange.

A consideration when conducting the screens of accelerated evolution on the

regions and SNPs identified by admixture mapping is that all of the markers used on the

Illumina African-American Admixture Panel are ancestry informative and may be

enriched for areas of the genome that are not neutral. To verify that there was not

increased evidence for accelerated evolution at the panel AIMs, a 200kb region

surrounding each marker in the admixture mapping panel was tested in West Africans for

each of the screens of accelerated evolution. The empirical distribution of the SNPs

(LSBL and lnRH) or windows (normalized Tajima’s D) was generated and the 5% cut-

off was established for each test. In all of the tests, the 5% cut-off for the AIMs panel is

less stringent than for the panel of SNPs used to evaluate accelerated evolution. That is

105

to say, the cut-off for lnRH and normalized Tajima’s D are less negative for the AIMs

panel than for the SNP panel and more positive for LSBL. Table 4-2 displays the 5%

empirical cut-off values for the full SNP panel and the admixture mapping AIMs panel.

Table 4-2. The 5% empirical distribution cut-off values for each test of accelerated evolution in the regions surrounding the Ancestry Informative Markers in the array used for admixture mapping compared to the 5% cut-off for the SNP panel used for the tests of accelerated evolution.

West African

#SNPs/Windows 5% AIMs Distribution 5% SNPs Cutoff

LSBL 174526 0.4516 0.3664

lnRH 206989 -6.2630 -6.8090

Tajima's D 22455 -1.4690 -1.7708

To summarize the tests of accelerated evolution a Perl script was used to calculate

the proportion of significant SNPs/windows for each test in each chromosomal region or

candidate gene tested. Nearly every chromosomal region or candidate gene analyzed had

significant values for at least one of the tests of evolution. To avoid reporting spurious

results and to help prioritize a manageable number of candidate regions and genes for

future analysis a significance threshold was established. Preterm birth candidate genes

and PPROM ancestry association regions were considered significant if there was

evidence of departure from the neutral expectation, no evolution, in all three of the tests

106

performed (LSBL, lnRH, and normalized Tajima’s D) or if more than 5% of the SNPs or

windows in the candidate gene were significant in two of the tests. Setting a threshold of

significance may remove candidate regions and genes that have experienced accelerated

evolution, however it reduces the probability of prioritizing false-positive results

negatively impacting future genotyping efforts.

Results

Screens for Accelerated Evolution from Admixture Mapping Results for PPROM

In the current study, the chromosomal regions found to have ancestry association

in the admixture mapping analysis were tested for evidence of accelerated evolution in

both West Africans and Europeans. This included one region on each of chromosomes 5,

8, 19 and 21, and three peaks on chromosome 11. Plots of the screens for accelerated

evolution are shown in Figure 4-2.

In the West African tests for accelerated evolution, each of the seven PPROM

ancestry association peaks, except for the small region on chromosome 8, showed

evidence for accelerated evolution in West African populations for all three tests (LSBL,

lnRH and normalized Tajima’s D). The strongest evidence of accelerated evolution

among the West African tests was in chromosome 11 peak 1 (11 Peak 1). This peak has

significance values at greater than 5% of the SNPs or windows for each of the three tests

(LSBL 5.9%, lnRH 6.13%, and normalized Tajima’s D 8.33%).

107

For the European screens, all of the ancestry association peaks evaluated were

significant for at least two of the tests of accelerated evolution. Of note is the small peak

on chromosome 8 (8 Peak) that is the only chromosomal segment tested that has greater

than 5% significant SNPs or windows for each of the three tests of accelerated evolution

(LSBL 6.82%, lnRH 7.84%, and normalized Tajima’s D 25.0%). This peak is the

smallest chromosomal region identified by admixture mapping with ancestry association

with PPROM and contains only one AIM (rs16932440).

A summary of the significant tests of accelerated evolution by ancestry

association peak and population is displayed in Table 4-3. A table with the percentage of

significant SNPs or windows for each test for each ancestry association peak tested is

shown in Appendix D.

The chromosomal regions identified by admixture mapping to have significant

ancestry association with PPROM are not uniform in size and therefore will not contain

the same number of SNPs or windows for the tests of evolution. For example, the largest

ancestry association peak is on Chromosome 21 and contains eight ancestry associated

AIMs over 11.5 megabases (Mb). By contrast, the smallest peak is on chromosome 8

which contains just one ancestry associated AIM. To evaluate the composition of these

peaks more consistently, each AIM within the ancestry association peaks was also tested

for evidence of accelerated evolution. Table 4-4 contains a summary of the significant

tests for each AIM within the PPROM ancestry association peaks. The individual AIM

values for each test and the plots of the accelerated evolution screens can be found in

Appendix D.

108

Analysis of the individual AIMs within the PPROM ancestry association peaks

revealed that while the entire peak may show evidence for accelerated evolution, when

evaluated separately, not all of the AIMs within the peak are significant. Additionally, in

some cases, when an ancestry association peak appears to be positive for accelerated

evolution in both West Africans and Europeans, the individual AIM analysis suggests

population-specific patterns of evolution within the peak. One example of this is peak 2

on chromosome 11 (11 Peak 2). When the full peak is tested for evidence of accelerated

evolution, both populations (West African and European) appear to have significant

values for the three tests evaluated. However, screening of the individual AIMs within

this peak shows a shifting pattern, with significant evolution in Europeans at the first

three AIMs (rs10765838, rs2403595, and rs6486270) in the peak followed by two AIMs

(rs4148636 and rs11024739) that are significant in West Africans. A similar shifting

trend of accelerated evolution between West Africans and Europeans is seen in the

ancestry association peak on chromosome 5 and the second peak on chromosome 11.

109

(a) West African Admixture Mapping Peaks

Chromosome 5

110

Chromosome 11 – Peak 2

Chromosome 11 – Peak 3

111

(b) European Admixture Mapping Peaks

Chromosome 5

Chromosome 8

Chromosome 21

112

Chromosome 11 – Peak 2

Chromosome 11 – Peak 3

Chromosome 11 – Peak 1

113

Figure 4-2. Results of the tests for accelerated evolution in all of the chromosomal regions found to be associated with preterm premature rupture of membranes (PPROM) by admixture mapping. Each bar represents a SNP (LSBL and lnRH) or window (Tajima’s D) plotted along the chromosome. Blue bars are not significant and orange bars fall in the 5% tail of the empirical distribution for the given test in the population under study. The populations presented in this figure are (a) West African (b) European.

Chromosome 21

Chromosome 19

114

Table 4-3. Summary of the tests for accelerated evolution in the PPROM ancestry association peaks identified by admixture mapping. The position of the test window was determined by subtracting 200kb from the first AIM in the ancestry association peak and adding 200kb to the last AIM in the peak. An ‘X’ represents a positive test either because greater than 5% of the SNPs or windows within the region are significant (bold “X”) or because all three tests have evidence for accelerated evolution. Gray regions of the plot represent ancestry association peaks that are not significant for the population listed.

Table 4-4. Summary of the tests for accelerated evolution in the AIMs that make-up the PPROM ancestry association peaks identified by admixture mapping. The start position of the test window was determined by subtracting 200kb from the AIM position and the end of the window was likewise by adding 200kb to physical position of the AIM. An ‘X’ represents a positive test either because greater than 5% of the SNPs or windows within the region are significant (bold “X”) or because all three tests have evidence for accelerated evolution. Gray regions of the plot represent AIMs that are not significant for the population listed.

115

116

Tests of Accelerated Evolution in Preterm Birth Candidate Genes

In addition to investigating accelerated evolution in the chromosomal regions

identified as significantly associated with preterm premature rupture of membranes by

admixture mapping, previously published candidate genes for preterm birth were also

evaluated. Figure 4-3 displays plots of each test for the candidate genes that were found

to be significant in each population, and a summary of the significant results is shown in

Table 4-5.

In total 90 genes were screened in both West African and European parental

populations for evidence of accelerated evolution. Forty-four of the candidate genes

tested were found to be significant in at least one of the populations studied. Of these, 31

were significant in West Africans and 24 in Europeans. Twelve genes showed evidence

of evolution in both populations. Forty-six of the candidate genes included in the

analysis were not found to be significant for either West Africans or Europeans. Table

4-6 summarizes the genes that were found to be significant for each population.

Among the 44 preterm birth candidate genes identified in West Africans, six have

greater than 5% significant SNPs/windows for all three of the tests. These genes are

PTGER3, AGTR1, FGB, VEGF, FL, and CBS. In Europeans only two of the 24

significant candidate genes have greater than 5% significance for each of the three tests

of accelerated evolution, CYP2E1 and CYP1A1. Of the twelve candidate genes that

overlap between the tests in West Africans and Europeans, only three genes have

evidence for accelerated evolution in the three screens performed in this analysis, VEGF,

117

F2 and CBS. However, none of these candidate genes has values for all three tests in

both populations with greater than 5% significant SNPs/windows.

Plots for the genes with non-significant tests for accelerated evolution are shown

in Appendix E, as is a table with the detailed information of each test for all of the

candidate genes included in this study.

118

(a) West African Candidate Gene Screens

TNFRSF1B – 1p36.22

PTGER3 – 1p31.2

SELE – 1q22-q25

119

PPARG – 3p25

AGTR1 – 3q24

ADD1 4q16.3

120

TLR2 – 4q32

FGB – 4q28

ITGA2 – 5q11.2

121

PART1 – 5q12.1

CRHBP – 5q11.2-q13.3

ADRB2 – 5q31-q32

122

LTA – 6q21.3

ENPP1 – 6q22-q23

VEGF – 6p12

123

SERPINE1 – 7q21.3-q22

PLAT – 8q12

CYP2C19 – 10q24

124

F2 – 11p11

PGR – 11q22-q23

GNB3 – 12q3

125

ALOX5AP – 13q12

F7 – 13q34

NQO1 – 16q22.1

126

NOS2A – 17q11.2-q12

ITGB3 – 17q21.32

ACE – 17q23.3

127

TIMP2 – 17q25

ICAM1 – 19p13.3-p13.2

CBS – 21q22.3

128

(b) European Candidate Gene Screens

TNFRSF1B – 1p36.22

MTHFR – 1p36.3

GSTT1 – 22q11.23

129

IL1RN – 2q14.2

IL1B – 2q14

FASLG– 1q23

130

FGB – 4q28

TLR2 – 4q32

PPARG – 3p25

131

IL4 – 5q31.1

IL5 – 5q31.1

ENPP1 – 6p22-q23

132

PLAT – 8q12

VEGF – 6p12

TREM1 – 6q21.1

133

F2 – 11p11

IGF2 – 11p15.5

CYP2E1 – 10q2.3-qter

134

GNB3 – 12q13

TNFRSF1A – 12p13.2

SERPINH1 – 11q13.5

135

CYP1A1 – 15q24.1

F7 – 13q34

KL – 13q12

136

Figure 4-3. Results of the significant tests for accelerated evolution in previously published candidate genes for preterm birth. Each bar represents a SNP (LSBL and lnRH) or window (Tajima’s D) plotted along the chromosome. Blue bars are not significant and orange bars fall in the 5% tail of the empirical distribution for the given test in the population under study. The populations shown in this figure are (a) West African (b) European.

NQO1 – 16q22.1

137

Table 4-5. Summary of the genes that are significant for tests of accelerated evolution. An “X” signifies at least 5% of the SNPs or windows tested are significant (bold “X”), or in the case that all three tests have significant values, there may be an “X” listed even if the test does not contain at least 5% significant SNPs or windows. Gray bars denote that the tests were not found to be significant in the population shown.

138

139

Table 4-6. Significant results of screens for accelerated evolution surrounding previously reported candidate genes for preterm birth. Both West African (a) and European (b) analyses are displayed in this figure.

Population # Significant Genes Genes

West African 31

TNFRSF1B, PTGER3, SELE, PPARG, AGTR1, ADD1, TLR2, FGB, ITGA2, PART1, CRHBP, ADRB2, VEGF, LTA, ENPP1, SERPINE1, PLAT, CYP2C19, F2, PGR, GNB3, ALOX5AP, F7, NQO1, NOS2A, ITGB3, ACE, TIMP2, ICAM1, CBS, GSTT1

European 24

MTHFR, TNFRSF1B, FASLG, IL1B, IL1RN, PPARG, TLR2, FGB, IL5, IL4, ENPP1, VEGF, TREM1, PLAT, CYP2E1, IGF2, F2, SERPINH1, TNFRSF1A, GNB3, KL, F7, CYP1A1, NQO1

Both Populations 12 TNFRSF1B, PPARG, TLR2, FGB, ENPP1, VEGF, PLAT, F2, GNB3, F7, NQO1, CBS

A summarized list of the forty-four candidate genes with significant evidence for

accelerated evolution in at least one of the parental populations investigated in this

analysis includes: MTHFR, TNFRSF1B, PTGER3, SELE, FASLG, IL1B, IL1RN,

PPARG, AGTR1, ADD1, TLR2, FGB, ITGA2, PART1, CRHBP, IL5, IL4, ADRB2, LTA,

TREM1, ENPP1, VEGF, SERPINE1, PLAT, CYP2C19, CYP2E1, IGF2, F2, SERPINH1,

PGR, TNFRSF1A, GNB3, ALOX5AP, KL, F7, CYP1A1, NQO1, NOS2A, ITGB3, ACE,

TIMP2, ICAM1, CBS, and GSTT1.

140

Discussion

This research uses tests of accelerated evolution to investigate regions of the

genome identified by admixture mapping (see Chapter 3) that contribute to risk of

preterm premature rupture of membranes (PPROM) among African-American women.

Additionally, ninety previously reported preterm birth candidate genes were screened for

evidence of evolution in the parental populations that contribute to African-American

admixture, West African and European. The goal of this study is to inform the planned

replication of the PPROM study reported in Chapter 3 and to create a list of prioritized

candidate genes for future investigations of disparity in preterm birth risk found among

U.S. African-American women.

Analysis of chromosomal regions found in the previously described admixture

mapping study revealed that all of the ancestry-associated peaks had evidence of

evolution in at least one of the populations considered. These ancestry-associated

chromosomal regions vary in size with different numbers of AIMs within each peak. The

windows generated to test the ancestry association peaks range in size from 400 kilobases

(kb), with only one AIM in the peak plus 200kb on either side, to nearly 12 megabases

(Mb) on chromosome 21. Within these peaks there may be evidence for varying effects

of accelerated evolution across the chromosomal region. By evaluating the individual

AIMs within the ancestry association peaks, variation in the patterns of evolution became

apparent and that different regions had evidence in Europeans compared to West

Africans. That is to say, AIMs in one region of a peak may have evidence of accelerated

141

evolution in Europeans while other AIMs in the same peak are significant in West

Africans.

One of the most dramatic ancestry associations with preterm birth due to preterm

premature rupture of membranes (PPROM) found in the admixture mapping results

(reported in Chapter 3) was the very large peak on chromosome 21 spanning 11.5

megabases (Mb) that was associated with European ancestry. In the screens for

accelerated evolution presented here, both West African and European parental

populations were significant with a slightly different pattern of SNPs within the peak for

each population. Interestingly, only one of the previously reported candidate genes for

preterm birth falls on chromosome 21, CBS. This gene showed evidence for accelerated

evolution in both West Africans and Europeans in the current analysis. CBS has been

reported in two previous studies of preterm birth; however, both studies were conducted

in populations of European ancestry, one in the United States and the other in Australia

[27, 28]. Of the two, only Velez et al. (2008) found an association between a

polymorphism in CBS among European-American neonates and risk of preterm birth.

With the large ancestry association peak found on this chromosome by admixture

mapping and evidence of accelerated evolution in both the ancestry association peak and

the preterm birth candidate gene CBS, chromosome 21 warrants further study for its

potential role in preterm birth risk.

Of the forty-four preterm birth candidate genes with positive screens for

signatures of accelerated evolution in this study, only five are previously reported

candidates for preterm premature rupture of membranes (PPROM). These genes include

SERPINH1, IL1B, TIMP2, PLAT, and LTA [1, 29-31]. Of these genes, only SERPINH1

142

has been previously demonstrated to contribute to the disparity in preterm birth risk

among African-American women. These five genes are of particular interest for the

planned replication of the PPROM study reported in Chapter 3.

Interestingly, the proportion of candidate genes that were identified using the

screens for signatures of accelerated evolution was higher than expected: 44 of 90

candidate genes in either the West African or European parental population. This large

number is likely due to the liberal cutoffs chosen for evidence of accelerated evolution.

By definition, alleles that contribute to difference in genetic risk of preterm birth between

African-American and European-American women will show a substantial frequency

difference between the parental populations that contribute to these groups. The tests

performed in this analysis help identify candidate genes and genomic regions with

evidence of ancestry-informative differences, those that are more likely to contribute to

differences in risk of preterm birth. For this analysis the primary goal was to prioritize

candidate genes and genomic regions for future evaluation of contribution to disparity in

preterm birth among African-American women. To that end, it was important to use a

liberal cutoff to reduce the number of genes for genotyping and to maximize statistical

power by excluding candidate genes that are unlikely to contribute to the disparity in risk

by virtue of having insufficient evolution since the divergence of the parental populations

in question.

Signatures of accelerated evolution detected in preterm birth candidate genes and

genomic regions identified by admixture mapping may indicate natural selection (either

ecological selection or sexual selection), genetic drift, or the effects of demographic

factors such as population expansion. While it is unlikely that natural selection has acted

143

to increase disease phenotypes like preterm birth, it is possible that the role of these

candidate genes in other important biological functions has been the target of natural

selection. It could also be postulated that natural selection has acted to favor preterm

birth in the African environment where there is limited medical intervention to deliver

neonates that are too large to pass through the pelvis, a situation that could reduce the

fitness of the mother by interfering with future fertility or by causing death.

Additionally, selection on a complex phenotype that was advantageous in the past

African environment may be maladaptive in an industrialized environment like the U.S.

with different environmental pressures. This idea has been proposed to explain the

increased risk of metabolic disorders like diabetes and obesity among individuals of

Native American ancestry living in the U.S. today. Adaptive strategies that helped

prevent starvation in the past are detrimental to populations who have continual access to

high calorie foods.

To further evaluate the large proportion of candidate genes found to have

signatures of accelerated evolution, future work is planned to test similar size sets of

randomly chosen genes. It is possible that similar proportions of genes in the randomly

selected sets will be found to contain signatures of accelerated evolution. This outcome

might be expected given the relaxed thresholds used to define significant signatures of

accelerated evolution used in this analysis. Even if preterm birth genes have a similar

patterns of significance to randomly chosen genes, the analysis has still accomplished the

goal of drawing attention to the genes that are more likely to contribute to difference in

risk and removing from consideration those that could not be responsible for the variation

in preterm birth observed between populations. However, if randomly selected sets of

144

genes reveal smaller proportions of significant tests, it could be argued that preterm birth

candidate genes have experienced greater average levels of accelerated evolution. In

humans, primates, and most other organisms, research to identify signatures of natural

selection routinely point to genes involved in reproduction as producing among the

strongest signals. Therefore, it may not be a surprise to find enrichment for signatures of

accelerated evolution in preterm birth candidate genes given their role in the biology of

reproduction. In this case, a more stringent cut-off might be warranted to identify the

most important and probable candidate genes contributing to increased risk of preterm

birth among African-American women.

Although not considered in the current study, recent evolution among African-

Americans could be a source of variation seen in disease risk in the United States. An

attempt to identify evidence of natural selection in African-Americans was recently

reported by Jin et al. (2012) [32]. They postulated that the extreme change in

environment and exposure to new pathogens faced by West Africans who arrived in the

Americas as slaves would result in selection that could be detected in modern African-

American individuals. Their study revealed six regions of the genome that have excess

of either West African or European ancestry and fourteen regions that are highly

differentiated between African-Americans and the Yoruba West African parental

population. These regions of natural selection may reveal interesting candidate genes for

a variety of diseases where there is increased risk among African-Americans. However,

in the current study, none of the admixture mapping peaks or the preterm birth candidate

genes with evidence of accelerated evolution overlap with the genomic regions of natural

selection among African-Americans reported by Jin et al (2012).

145

Tests of accelerated evolution have identified genes that are known to contribute

to variation in phenotypes across human populations, especially those that are related to

adaptation to varying environments and pathogens, like skin pigmentation change or

resistance to malaria. It is unlikely that positive selection is acting directly on preterm

birth to generate the demonstrated population differences in susceptibility. However,

genes contributing to preterm birth may have experienced accelerated evolution due to

their role in other phenotypes (pleiotropy). Genes that contribute to differences in disease

risk may have evidence of a population-specific evolutionary history that can be

exploited to prioritize genotyping efforts. Using the results of the current study will

complement planned genotyping strategies for identifying genes that contribute to

disparities in risk of preterm birth and preterm premature rupture of membranes.

Future Directions

As described in Chapter 3, a replication of the admixture mapping results is

planned with the possible use of the newly available Affymetrix (Santa Clara, California)

Axiom exom array [33]. In addition to the 318,000 markers included on the array,

there is the option to include up to 100,000 additional customer-specified markers to the

genotyping platform. With the information provided by the screens of accelerated

evolution conducted in this study, SNPs in five previously reported candidate genes for

PPROM were found to have significant evidence of evolution in West Africans or

146

Europeans. These genes, SERPINH1, IL1B, TIMP2, PLAT, and LTA, will also be

prioritized in the replication effort and included on the custom portion of the exom array.

Using the results of the current study, another area of future research could

include the development of an accelerated evolution nominated panel of candidate genes

to facilitate the investigation of the genetic contributions to the disparity of preterm birth

risk among African-American women.

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and inflammation pathway gene variants. PLoS One, 2008. 3(9): p. e3283. 28. Gibson, C.S., et al., Genetic polymorphisms and spontaneous preterm birth.

Obstet Gynecol, 2007. 109(2 Pt 1): p. 384-91. 29. Wang, H., et al., Genetic and epigenetic mechanisms combine to control MMP1

expression and its association with preterm premature rupture of membranes. Hum Mol Genet, 2008. 17(8): p. 1087-96.

30. Bitner, A. and J. Kalinka, IL-1beta, IL-6 promoter, TNF-alpha promoter and IL-1RA gene polymorphisms and the risk of preterm delivery due to preterm premature rupture of membranes in a population of Polish women. Arch Med Sci, 2010. 6(4): p. 552-7.

31. Romero, R., et al., A genetic association study of maternal and fetal candidate genes that predispose to preterm prelabor rupture of membranes (PROM). Am J Obstet Gynecol, 2010. 203(4): p. 361 e1-361 e30.

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32. Jin, W., et al., Genome-wide detection of natural selection in African Americans pre- and post-admixture. Genome Res, 2012. 22(3): p. 519-27.

33. Affymetrix. Axiom Exome Genotyping Array Data Sheet. http://www.affymetrix.com/support/technical/datasheets/axiom_exome_array_datasheet.pdf. March 12, 2012.

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Chapter 5

Concluding Remarks

The purpose of this research was to investigate the disparity that exists in

pregnancy outcomes in African-American women compared to other U.S. populations.

African-American women have a significantly increased risk of experiencing preterm

birth and their neonates are more likely to be low birth weight for gestational age and

have higher mortality. The results of a considerable amount of research focused on

identifying the causes of disparity in pregnancy outcomes for African-American women

suggest that there are likely environmental, social, and genetic factors that contribute.

The goal of the research presented in the previous three chapters was to gain better

understanding of genetic and gene-environment interactions that contribute to disparity

among African-Americans. The results of this research are reviewed below and future

directions are discussed.

Relationship between Genomic Ancestry and Pregnancy-related Phenotypes

To date, very few studies of disparities in pregnancy related phenotypes have

addressed genomic ancestry contributions to admixture in African-Americans as potential

risk factors. Unlike most European-American populations, a significant degree of

variation exists in European genomic contribution to admixture within and among

African-American populations and across the United States [1]. Classification of

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individuals in studies of health disparities by “race” without accounting for variation in

genomic West African admixture assumes a degree of biological homogeneity within the

African-American community that is inaccurate. To better understand how genomic

ancestry contributes to phenotypic variation genomic ancestry can be estimated using

genotype data from modest panels of ancestry informative markers and tested for

association with variation in the phenotype of interest. For example, greater West

African ancestry is associated with increased skin pigmentation, lower vitamin D level,

and recently has been reported to be associated with increased risk of preterm birth [2-5].

The research presented in Chapter 2 evaluates the relationship between genomic

ancestry and two pregnancy related phenotypes, low birth weight and serum vitamin D

level (a suspected contributor to preterm birth risk). Using pregnant women of self-

reported European-American and African-American ancestry living in Western

Pennsylvania a considerable degree of variation in West African genomic ancestry was

seen among African-American women (range 15%-100%, mean = 20%) that was not

observed in the European-American women. West African genomic ancestry was

correlated with birth weight adjusted for gestational age for female neonates (p<0.0001)

in the combined sample of European-American (n=151) and African-American (n=187)

women; however this association was not significant for male newborns. This result

suggests that West African ancestry may contribute to the smaller neonatal size observed

among African-American women. A larger sample of admixed individuals would

improve this analysis and clarify the potential contribution of genomic ancestry to birth

weight.

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As reported in previous studies, West African genomic ancestry was highly

correlated with skin pigmentation in this research [1, 6]. Increasing West African

ancestry is associated with an increase in melanin index (M) as measured by reflectance

spectrophotometer (DermaSpectrometer, Cortex, Denmark) in both the African-American

and combined sample of research participants. Additionally, vitamin D level was

inversely correlated with both West African genomic ancestry (p<0.0001), as similarly

reported by Signorello et al. (2011) and with skin pigmentation. This is the first study to

report an association between serum vitamin D and quantifiably measured skin

pigmentation.

Considerable recent research suggests a role for vitamin D deficiency in chronic

health disorders, including preterm birth [7]. The contribution of vitamin D level to

preterm birth was not investigated in this analysis due to a limited sample size. A larger

sample has been collected by our collaborators and future analyses are planned to

investigate the potential role of vitamin D to disparity in pregnancy outcomes among

African-American women.

Admixture Mapping and Genomic Regions Associated with Risk of PPROM

Research to identify genetic contributions to increased risk of preterm birth in

African-American women compared to other U.S. populations has had limited success.

A majority of reported studies have investigated candidate genes and only one genetic

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polymorphism has been identified that contributes to preterm birth specifically among

African-American women, SERPINH1 [8].

In Chapter 3, an admixture mapping approach was used to identify regions of the

genome that are associated with genomic ancestry that contribute to risk of preterm birth

due to preterm premature rupture of membranes (PPROM), a major contributor to

spontaneous preterm births. This approach is valuable for investigating disease

phenotypes showing substantial prevalence difference between parental populations and

has been successful in identifying novel risk regions in other diseases where African-

Americans are at greater risk, like prostate cancer [9, 10]. The case-control admixture

mapping study presented in Chapter 3 identified six genomic regions on five

chromosomes associated with increased risk of PPROM. Five regions were associated

with West African ancestry (on chromosomes 5, 8, 11, and 19) and one large ancestry

peak on chromosome 21 was associated with European ancestry. The large region of

European association may seem unexpected since African-American women are at

significantly increased risk of preterm birth and PPROM compared to European-

American women; however, risk in admixed groups can come from either parental

population contributing to admixture, West African or European in the case of African-

Americans. Freedman et al. (2006), and later Bock et al. (2009), reported a similar

European ancestry-associated risk region on chromosome 8q24 in a study of prostate

cancer in high-risk African-American men [9, 10].

The ancestry-associated regions identified in this analysis are not found near

previously reported preterm birth candidate genes and do not overlap with the previously

published admixture mapping study in preterm birth, Manuck et al. (2011) [11].

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However, given the limited success of previous candidate gene studies in identifying

genetic contributors to disparity in preterm birth, identifying novel candidate regions that

were in the AM analysis was not unexpected. Additionally, this is the first admixture

mapping study to investigate this specific subphenotype of preterm birth, preterm

premature rupture of membranes. It is unlikely that the results presented here would

replicate the findings of the Manuck et al. study (2011) since they did not distinguish

between the cause of spontaneous preterm birth in recruiting participants to include in

their admixture mapping analysis. An advantage to focusing on a defined subphenotype

of preterm birth is that there is an increased likelihood of replicating the results of this

analysis in a second PPROM sample due to reduced disease heterogeneity. However,

since PPROM accounts for only 30-40% of spontaneous preterm births, it is challenging

to collect the large sample sizes needed to have adequate power to detect significant

associations in an admixture mapping study.

A shortcoming of this study is that the results of the admixture mapping analysis

meet a suggestive significance value of |z|>2.5 (p<0.01), but they do not meet the

genome-wide criteria for significance (|z|>4.27) recommended by Hoggart et al. (2004)

[12]. The inability to detect statistically significant associations in this admixture

mapping study was likely the result of a lack of power due to a limited sample size, 352

cases and 264 controls. However, sample collection is currently underway to increase the

sample size for a replication of this study. Admixture mapping has the potential to

contribute greatly to the understanding of genetic influences on increased risk of preterm

birth in African-American women.

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Prioritizing Replication and Genotyping of Candidate Genes for Future Studies

Preterm birth risk is much greater in African-American women than other U.S.

ethnic groups, and very few studies have identified genes that are likely to explain this

difference in risk. With the expectation that genes contributing to differential risk in

preterm birth between populations may show evidence of population-specific

evolutionary histories, tests for accelerated evolution can be used to help prioritize these

genes as candidates for investigations of genes contributing to disparity.

In the research presented in Chapter 4, three tests for accelerated evolution,

LSBL, lnRH, and normalized Tajima’s D, were used to screen 90 previously reported

preterm birth candidate genes in both European and West African populations. Thirty-

one candidate genes in West Africans and 24 in Europeans had evidence of accelerated

evolution. Only 12 of these showed significant signatures in both parental populations.

Additionally, five candidate genes previously associated with preterm premature rupture

of membranes (PPROM), the subphenotype of preterm birth investigated in Chapter 3,

had evidence of accelerated evolution (SERPINH1, IL1B, TIMP2, PLAT, and LTA).

In addition to testing preterm birth candidate genes, screens for accelerated

evolution were performed on the regions found to be associated with PPROM reported in

Chapter 3. These tests revealed that all of the ancestry-associated risk regions from the

admixture mapping analysis had evidence for accelerated evolution. In all but the small

chromosomal region on chromosome 8, there was evidence of accelerated evolution in

both West African and European parental populations. Further investigation within the

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ancestry-associated risk regions for PPROM revealed differing patterns of European and

West African evolution.

Although screens for accelerated evolution have not been previously reported in

investigations of complex diseases, this approach may help identify candidate genes or

genomic regions that have greater probability of contributing to disparity in disease

phenotypes with known population differences in risk. By eliminating candidate genes

that do not show evidence of population differences, a more targeted genotyping strategy

can be employed.

This study has identified a prioritized list of candidate genes that can be used for

future investigations into the genetic contributions to differences in preterm birth risk.

Additionally, the results of screens for accelerated evolution in the genomic regions

reported in the admixture mapping analysis for PPROM suggest that all of these regions

are good candidates for future replication studies.

Future Directions

Genotyping of Additional Mothers and Newborns for Ancestry Association Studies

Since the initial genotyping of ancestry informative markers in the mothers

recruited to participate in the prospective study of genetic and environmental factors

contributing to preterm birth at Magee-Womens Hospital of the University of Pittsburgh

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Medical Center, over 100 additional women with complete phenotype and demographic

data have been enrolled. In addition DNA samples from each of the neonates collected

from cord blood at the time of delivery is available for analysis. Genotyping of the same

panel of AIMs reported in Chapter 2 is planned for these additional maternal and fetal

samples. The analyses performed in Chapter 2 will be replicated with the new maternal

data, and the association of fetal genomic ancestry to birth weight for gestational age will

be investigated. Additionally, if a sufficient number of the new maternal samples are

from pregnancies that resulted in preterm birth, the association between genomic ancestry

and preterm birth will be investigated.

Replication of Admixture Mapping and Investigation of Candidate Genes

A replication of the PPROM analysis presented in Chapter 3 is planned. In the

replication study DNA will be genotyped from a new sample of neonates born to African-

American women who had preterm deliveries due to preterm premature rupture of

membranes (PPROM). Since the Illumina (San Diego, California) African-American

Admixture Mapping Panel is no longer available, and the cost of genotyping has

decreased substantially in the past few years, a full exom array created by Affymetrix

(Santa Clara, California) will likely be used as the genotyping platform for the replication

study [13]. The Axiom array contains over 300,000 SNPs spread across the genome

that include a large number of ancestry informative markers [14]. This array can also be

customized to include up to 100,000 customer-selected markers. This feature is

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appealing for the replication study because additional SNPs in the regions identified in

the current admixture mapping analysis can be included for a more fine-scale mapping

approach to locate potentially causative alleles associated with PPROM risk. Also, SNPs

in the five PPROM candidate genes (SERPINH1, IL1B, TIMP2, PLAT, and LTA) that

were found to have evidence of accelerated evolution, in Chapter 4, can be included in

the replication on this array [8, 15-17]. Combining a replication of the admixture

mapping analysis with fine-scale mapping of previously identified chromosomal regions

associated with PPROM and candidate genes nominated using screens for accelerated

evolution may increase the likelihood of identifying genes that contribute to the increased

risk of preterm birth due to PPROM seen in African-American women.

Additionally, the screens for accelerated evolution presented in Chapter 4 helped

prioritize a list of candidate genes that may contribute to disparity in preterm birth among

African-American women. Using a custom designed genotyping array, tag SNPs within

these genes could be investigated in a case-control sample of African-American mothers

and neonates to investigate the role of these accelerated evolution nominated genes on

risk of preterm birth.

Conclusion

The research presented in this dissertation is an effort to investigate the genetic

contributions to disparity in pregnancy outcomes for African-American women.

Although poor pregnancy outcomes can affect women of all ancestral backgrounds,

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prioritizing studies in high-risk African-American women is a strategy that may reveal

new insights into role of gene and gene-environment interactions in pregnancy

phenotypes.

Literature Cited

1. Parra, E.J., et al., Estimating African American admixture proportions by use of population-specific alleles. Am J Hum Genet, 1998. 63(6): p. 1839-51.

2. Shriver, M.D., et al., Skin pigmentation, biogeographical ancestry and admixture mapping. Hum Genet, 2003. 112(4): p. 387-99.

3. Signorello, L.B., et al., Blood vitamin d levels in relation to genetic estimation of African ancestry. Cancer Epidemiol Biomarkers Prev, 2010. 19(9): p. 2325-31.

4. Tsai, H.J., et al., Role of African ancestry and gene-environment interactions in predicting preterm birth. Obstet Gynecol, 2011. 118(5): p. 1081-9.

5. Tsai, H.J., et al., Association of genetic ancestry with preterm delivery and related traits among African American mothers. Am J Obstet Gynecol, 2009. 201(1): p. 94 e1-10.

6. Parra, E.J., R.A. Kittles, and M.D. Shriver, Implications of correlations between skin color and genetic ancestry for biomedical research. Nat Genet, 2004. 36(11 Suppl): p. S54-60.

7. Bodnar, L.M. and H.N. Simhan, Vitamin D may be a link to black-white disparities in adverse birth outcomes. Obstet Gynecol Surv, 2010. 65(4): p. 273-84.

8. Wang, H., et al., A functional SNP in the promoter of the SERPINH1 gene increases risk of preterm premature rupture of membranes in African Americans. Proc Natl Acad Sci U S A, 2006. 103(36): p. 13463-7.

9. Bock, C.H., et al., Results from a prostate cancer admixture mapping study in African-American men. Hum Genet, 2009. 126(5): p. 637-42.

10. Freedman, M.L., et al., Admixture mapping identifies 8q24 as a prostate cancer risk locus in African-American men. Proc Natl Acad Sci U S A, 2006. 103(38): p. 14068-73.

11. Manuck, T.A., et al., Admixture mapping to identify spontaneous preterm birth susceptibility loci in African Americans. Obstet Gynecol, 2011. 117(5): p. 1078-84.

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12. Hoggart, C.J., et al., Design and analysis of admixture mapping studies. Am J Hum Genet, 2004. 74(5): p. 965-78.

13. Illumina, Illumina African American Admixture Panel, 2010. p. 1-3. 14. Affymetrix, Axiom Exome Genotyping Array Data Sheet. 15. Wang, H., et al., Genetic and epigenetic mechanisms combine to control MMP1

expression and its association with preterm premature rupture of membranes. Hum Mol Genet, 2008. 17(8): p. 1087-96.

16. Bitner, A. and J. Kalinka, IL-1beta, IL-6 promoter, TNF-alpha promoter and IL-1RA gene polymorphisms and the risk of preterm delivery due to preterm premature rupture of membranes in a population of Polish women. Arch Med Sci, 2010. 6(4): p. 552-7.

17. Romero, R., et al., A genetic association study of maternal and fetal candidate genes that predispose to preterm prelabor rupture of membranes (PROM). Am J Obstet Gynecol, 2010. 203(4): p. 361 e1-361 e30.

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Appendix A

Parental Allele Frequencies and Delta Calculations for the 107 Ancestry Informative Marker Panel from the University of Minnesota Genomics Core Facility

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Appendix B

Parental Allele Frequencies and Delta Calculations for the 1,509 Illumina African-American Admixture Panel

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Appendix C

Admixture Mapping Ancestry and Allelic Associations for Case-Control and Case-only Analysis.

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Case-Control: Ancestry and Allelic Association Values for each AIM in the PPROM Admixture Mapping analysis. Values that are bold have a significant z-score (|z|>2.5, p<0.01)

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Case-Only Ancestry Association Score Maps

Ancestry score maps generated by ADMIXMAP for European and West African ancestry association with PPROM. Z-scores shown plotted along each chromosome in centimorgans (cM).

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Case-Only: Ancestry and Allelic Association Values for each AIM in the Admixture Mapping analysis. Values that are bold have a significant z-score (|z|>2.5, p<0.01)

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Appendix D

Screens for Accelerated Evolution in the PPROM Admixture Mapping Ancestry-Association Peaks

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Screens for accelerated evolution in the full PPROM ancestry-association peaks from ADMIXMAP in the West African parental population

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Screens for accelerated evolution in the full PPROM ancestry-association peaks from ADMIXMAP in the European parental population

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Screens for accelerated evolution for each ancestry informative marker in the PPROM ancestry-association peaks identified using admixture mapping for the West African parental population

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Screens for accelerated evolution for each ancestry informative marker in the PPROM ancestry-association peaks identified using admixture mapping for the West African parental population

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Appendix E

Screens for Accelerated Evolution in 90 Previously Reported Preterm Birth Candidate Gene

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Screens for accelerated evolution in each of 90 previously reported preterm birth candidate genes for the West African parental population

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Screens for accelerated evolution in each of 90 previously reported preterm birth candidate genes for the West African parental population

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Vita

Laurel N. Pearson Education 2012 Ph.D., Pennsylvania State University, Intercollege Graduate Degree Program in Genetics,

Department of Anthropology, Dissertation Advisor: Mark D. Shriver, Ph.D. 2001 B.A., summa cum laude, Louisiana State University, Anthropology Awards 2012 Matson-Benson Award for Service, Anthropology Museum, Department of

Anthropology, Pennsylvania State University. 2011 American Association of Anthropological Genetics Outstanding Student Presentation

Prize 2010 Omid Harandi Award for Exceptional Contributions to The Pennsylvania State

University Intercollege Graduate Degree Program in Genetics. 2005 University Research Fellowship, Pennsylvania State University. Selected Publications and Presentations 2007 Bauchet M, McEvoy B, Pearson LN, Quillen EE, Sarkisian T, Hovhannesyan K, Deka

R, Bradley DG, Shriver MD. Measuring European population stratification with microarray genotype data. American Journal of Human Genetics. 80(5): 948-56.

2005 Nerurkar PV, Pearson L, Efird JT, Adeli K, Theriault AG, Nerurkar VR. Microsomal triglyceride transfer protein gene expression and ApoB secretion are inhibited by bitter melon in HepG2 cells. Journal of Nutrition. 135(4): 702-706.

2003 Nerurkar PV, Pearson L, Frank J, Yanagihara R, Nerurkar VR. Highly active antiretroviral therapy (HAART)-associated lactic acidosis: in vitro effects of combination of nucleoside analogues and protease inhibitors on mitochondrial function and lactic acid production. Cellular and Molecular Biology (Noisy-le-Grand). 49(8): 1205-11.

Selected Presentations 2011 Pearson LN, Bigham AW, Mao X, Kusanovic JP, Romero R, Strauss JF 3rd, Shriver

MD. A combined approach to identifying preterm risk genes: admixture mapping and signatures of selection. Poster Presentation, American Society of Human Genetics/International Congress of Human Genetics Meeting. Montreal, Canada.

2011 Pearson LN. Genetic and environmental contributions to disparities in preterm birth. Invited Podium Presentation, Genetics Symposium. Pennsylvania State University, University Park, PA.

2011 Pearson LN, Kusanovic JP, Romero R, Strauss JF 3rd, Shriver MD. Using tests for signatures of selection to validate and prioritize admixture mapping results. Poster Presentation, American Association of Physical Anthropology Annual Meeting. Minneapolis, MN.

2009 Pearson LN, Weddle AL, Shriver MD. Evaluating genes related to non-metric dental variation in European Americans. Podium Presentation, American Association of Physical Anthropology Annual Meeting. Chicago, IL.

Professional Memberships American Society of Human Genetics, American Association of Physical Anthropologists, American Association of Anthropological Genetics