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Epigenetics, Diet and Disease Giles Elliott

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Page 1: Unit Presentation Dec 08 Short

Epigenetics, Diet and Disease

Giles Elliott

Page 2: Unit Presentation Dec 08 Short

Epigenetics

Disease

Diet

DNA Methylation

Colon Cancer

Overview

Page 3: Unit Presentation Dec 08 Short

What is DNA Methylation?

CC C C C CAA A A AAA AGGGG G G G GT T T T TT

CC C C CC C CAA A A AA G G G G GGT T T T T TT T

Dnmt3

CC C C CC C CAA A A AA G G G G GGT T T T T TT T

Dnmt1

Covalent DNA modificationRetained through mitosis

CC C C C CAA A A AAA AGGGG G G G GT T T T TT

Page 4: Unit Presentation Dec 08 Short

What does DNA methylation do?

Global Methylation

Regional Methylation

Low denisityGenomic stabilityRepression of transposable elements

High Density – CpG Islands (CGIs)Located in promoters and intronsGene Silencing

Promoter Gene

Page 5: Unit Presentation Dec 08 Short

DNA methylation in relation to disease - cancer

Tumour samples exhibited reduced methylation compared to corresponding normal tissue- Feinberg and Vogelstein, 1983

Due to reduction in global methylation - hypomethylation

Increased genomic instability – increased mutation rate

Reactivation of transposable elements – chromosomal rearrangements

Loss of imprinting

Page 6: Unit Presentation Dec 08 Short

DNA methylation in relation to disease - cancer

Hypermethylation of CpG IslandsSilencing of tumour suppressor

genesAffects genes involved in: cell cycle, DNA repair, cell-cell interactions, angiogenisis, proliferation, apoptosis...

Present in both hereditary and sporadic types of cancer

Occurs at all stages of cancer development

Interacts with genetic lesions – 2 hit

Underlying causes inducing hypermethylation unknown

Page 7: Unit Presentation Dec 08 Short

Age related hypermethylation

Page 8: Unit Presentation Dec 08 Short

DNA methylation in relation to disease – Colorectal cancer

Healthy Mucosa AdenomaLifetime risk 50%

CarcinomaLifetime risk 5%

APC K-ras p53Somatic mutation…..

MLH1 p16

Epigenetic deregulation…ESR-1

Tumour Biology

Diet-Related “Field Effects” ?

Dietary and microbiological factorsact on the mucosa fordecades before theemergence of tumours.

Page 9: Unit Presentation Dec 08 Short

Evidence for the Field Effect

Page 10: Unit Presentation Dec 08 Short

Evidence for the Field Effect

canceradenomaNo-neoplasia

3.0

2.5

2.0

1.5

1.0

0.5

0.0

Perc

ent M

eth

yla

tion

APC tissue mean methylation

Healthy Mucosa Adenoma Carcinoma

Diet-Related “Field Effects” ?

Page 11: Unit Presentation Dec 08 Short

Evidence for the Field Effect

CancerAdenomaNo-neoplasia

25

20

15

10

5

Perc

ent M

eth

yla

tion

ESR1 tissue mean methylation

Healthy Mucosa Adenoma Carcinoma

Diet-Related “Field Effects” ?

Page 12: Unit Presentation Dec 08 Short

Evidence for the Field Effect

Multinomial models, based on CGI methylation profiles from normal mucosa correctly identified:

78.9% of cancer patients 87.9% of non- cancer patients informative variables: APC, HPP1, p16, SFRP4, WIF1

and ESR1

CGI methylation of SFRP4, SFRP5 and WIF1 was used to correctly identify:

61.5% of adanoma patients 78.9% of neoplasia-free subjects

This indicates that apparently normal mucosa of patients with neoplasia has undergone significant epigenetic modification associated with the onset of carcinogenesis. Methylation of the genes selected by the models may play a role in the earliest stages of the development of colorectal neoplasia.

What influences the field effect?

Diet?

Page 13: Unit Presentation Dec 08 Short

Age related hypermethylation

Inter-individual variation possibly

due to diet?

Page 14: Unit Presentation Dec 08 Short

Evidence for the involvement of diet

Older twins exhibited more differences in epigenetic status than young twins

Due to environmental not genetic factors

Page 15: Unit Presentation Dec 08 Short

Effect of individual dietary components

Deficiency in methyl donors (folate, choline, vit B12) can induce global

hypomethylation

Treatment of cells with polyphenols can reduce hypermethylatiion by

inhibition of dnmt1

Majority of studies performed in cancer cell lines or animal models

What is going on in humans?

Page 16: Unit Presentation Dec 08 Short

Diet and colon cancer in man

CRC predominantly a western diseaseImpact of western diet highlighted by increased CRC incidence in JapanRisk of CRC increased by obesityInflammatory bowel disease increases risk of CRC

Page 17: Unit Presentation Dec 08 Short

Increased age related hypermethylation in UC

Hypothesis:Inflammatory signals due to dietary (or microbial) factors lead to aberrant DNA methylation resulting in a predisposition to CRC

Page 18: Unit Presentation Dec 08 Short

Aim: To use faecal DNA methylation as a surrogate marker of colonic methylation

Quantify faecal methylation levels

Determine if faecal and tissue methylation correlate?

Are there significant differences in faecal methylation between patient groups?Predicting disease status

Could surrogate markers be used in dietary intervention studies?

Page 19: Unit Presentation Dec 08 Short

Previous work

Page 20: Unit Presentation Dec 08 Short

Summary of early studiesHypermethylated CGIs detected more frequently in cancer than non cancer patients faecal sample

Indicated that a panel of genes may be necessary

Majority of studies performed using non- or semi-quantitative assays

little attempt to correlate to tissue

Page 21: Unit Presentation Dec 08 Short

Study design

Matching tissue and faecal samples from:19 Cancer patients18 Adenoma patients20 Patients with no-neoplasia

Faecal samples from 169 health individuals~10 males and 10 females/decade until 80 years old

Measured methylation of 8 CGIs

Page 22: Unit Presentation Dec 08 Short

Analysis of faecal methylation levels in patients

0

10

20

30

40

50

60

70

80

90

APC Ecad HPP1 ESR1 MLH1 p14 SFRP2 Vim MSP Vim QMSP

% M

e

Normal

Adenoma

cancer

**

***

**

* *

*

CancerAdenomaNo-neoplasia

25

20

15

10

5

Perc

ent M

eth

yla

tion

ESR1 tissue mean methylation

* p ≤ 0.05, ** p ≤ 0.01, ***p ≤ 0.001

Page 23: Unit Presentation Dec 08 Short

Predicting disease status

Multinomial modelling

Age + ESR1Overall = 77%Sensitivity = 63% , Specificity =

84% ESR1 and p14

Overall = 71% Sensitivity = 42%, Specificity =

86%

Page 24: Unit Presentation Dec 08 Short

Correlation between tissue and faecal samples

252015105

25

20

15

10

5

Tissue methylation

Sto

ol m

eth

yla

tion

ESR1 methylation stool vs tissue

ESR1 was the only CGI to correlate

Page 25: Unit Presentation Dec 08 Short

Summary

Some differences in faecal methylation seen between patient groups

Unable to significantly predict disease status from faecal methylation profiles

Faecal methylation profiles do not correlate with corresponding tissue samples

Page 26: Unit Presentation Dec 08 Short

Study limitations

Number of patientsAge difference between patient groupsUse of patients with no-neoplasia as controlsComparison to age and sex matched

volunteers to patient groups

Page 27: Unit Presentation Dec 08 Short

Age and Sex matched Patients vs. Volunteers

No-Neoplasia Adenoma cancer0

5

10

15

20

25

30

35Patient group

Volunteers

Per

cen

t M

eth

ylat

ion

Page 28: Unit Presentation Dec 08 Short

Quantify faecal methylation levels

Determine if faecal and tissue methylation correlate?

Are there significant differences in faecal methylation between patient groups?

Predicting disease statusCould surrogate markers be used in dietary intervention studies?

?

Page 29: Unit Presentation Dec 08 Short

Acknowledgments

IFRNigel BelshawIan JohnsonLiz LundKasia PrzybylskaJack Dainty

Newcastle university

John MathersAmanda CoupeWendy Bal

Wansbeck

Hospital D M Bradburn

TNO NetherlandsRobert Kleeman

FundingFSABBSRC CSGNuGO