Characterisation of Ethnic Differences in DNA Methylation Between UK-resident South Asians and Europeans

Overview

Journal Clin Epigenetics

Publisher Biomed Central

Specialty Genetics

Date 2022 Oct 15

PMID 36243740

Authors

Hannah R Elliott

Kimberley Burrows

Josine L Min

Therese Tillin

Dan Mason

John Wright

Gillian Santorelli

George Davey Smith

Deborah A Lawlor

Alun D Hughes

Nishi Chaturvedi

Caroline L Relton

Affiliations

Soon will be listed here.

Abstract

Ethnic differences in non-communicable disease risk have been described between individuals of South Asian and European ethnicity that are only partially explained by genetics and other known risk factors. DNA methylation is one underexplored mechanism that may explain differences in disease risk. Currently, there is little knowledge of how DNA methylation varies between South Asian and European ethnicities. This study characterised differences in blood DNA methylation between individuals of self-reported European and South Asian ethnicity from two UK-based cohorts: Southall and Brent Revisited and Born in Bradford. DNA methylation differences between ethnicities were widespread throughout the genome (n = 16,433 CpG sites, 3.4% sites tested). Specifically, 76% of associations were attributable to ethnic differences in cell composition with fewer effects attributable to smoking and genetic variation. Ethnicity-associated CpG sites were enriched for EWAS Catalog phenotypes including metabolites. This work highlights the need to consider ethnic diversity in epigenetic research.

Citing Articles

Insights from a methylome-wide association study of antidepressant exposure.

Davyson E, Shen X, Huider F, Adams M, Borges K, McCartney D Nat Commun. 2025; 16(1):1908.

PMID: 39994233 PMC: 11850842. DOI: 10.1038/s41467-024-55356-x.

Characterizing biomarkers of ageing in Singaporeans: the ABIOS observational study protocol.

Lu J, Wang W, Soh J, Sandalova E, Lim Z, Seetharaman S Geroscience. 2025; .

PMID: 39825169 DOI: 10.1007/s11357-025-01511-1.

Ethnicity-specific patterns of epigenetic age acceleration in rheumatoid arthritis.

Sharma-Oates A, Dunne N, Raza K, Padyukov L, Rivera N, van der Helm-van Mil A Geroscience. 2025; .

PMID: 39797936 DOI: 10.1007/s11357-025-01508-w.

Genome-wide methylation profiling of maternal cell-free DNA using methylated DNA sequencing (MeD-seq) indicates a placental and immune-cell signature.

van Vliet M, Boers R, Boers J, Schaffers O, van der Meeren L, Steegers-Theunissen R Eur J Clin Invest. 2024; 55(3):e14363.

PMID: 39589853 PMC: 11810559. DOI: 10.1111/eci.14363.

MIR124-3 and NKX6-1 hypermethylation profiles accurately predict metachronous gastric lesions in a Caucasian population.

Lopes C, Almeida T, Macedo-Silva C, Costa J, Paulino S, Jeronimo C Clin Epigenetics. 2024; 16(1):113.

PMID: 39169394 PMC: 11340155. DOI: 10.1186/s13148-024-01712-z.

References

Demerath E, Guan W, Grove M, Aslibekyan S, Mendelson M, Zhou Y . Epigenome-wide association study (EWAS) of BMI, BMI change and waist circumference in African American adults identifies multiple replicated loci. Hum Mol Genet. 2015; 24(15):4464-79. PMC: 4492394. DOI: 10.1093/hmg/ddv161. View

Sun Y, Richmond R, Suderman M, Min J, Battram T, Flatberg A . Assessing the role of genome-wide DNA methylation between smoking and risk of lung cancer using repeated measurements: the HUNT study. Int J Epidemiol. 2021; 50(5):1482-1497. PMC: 8580278. DOI: 10.1093/ije/dyab044. View

Aslibekyan S, Demerath E, Mendelson M, Zhi D, Guan W, Liang L . Epigenome-wide study identifies novel methylation loci associated with body mass index and waist circumference. Obesity (Silver Spring). 2015; 23(7):1493-501. PMC: 4482015. DOI: 10.1002/oby.21111. View

Tillin T, Hughes A, Godsland I, Whincup P, Forouhi N, Welsh P . Insulin resistance and truncal obesity as important determinants of the greater incidence of diabetes in Indian Asians and African Caribbeans compared with Europeans: the Southall And Brent REvisited (SABRE) cohort. Diabetes Care. 2012; 36(2):383-93. PMC: 3554271. DOI: 10.2337/dc12-0544. View

Geurts Y, Dugue P, Joo J, Makalic E, Jung C, Guan W . Novel associations between blood DNA methylation and body mass index in middle-aged and older adults. Int J Obes (Lond). 2017; 42(4):887-896. DOI: 10.1038/ijo.2017.269. View

Sikdar S, Joehanes R, Joubert B, Xu C, Vives-Usano M, Rezwan F . Comparison of smoking-related DNA methylation between newborns from prenatal exposure and adults from personal smoking. Epigenomics. 2019; 11(13):1487-1500. PMC: 6836223. DOI: 10.2217/epi-2019-0066. View

Maas S, Vidaki A, Wilson R, Teumer A, Liu F, van Meurs J . Validated inference of smoking habits from blood with a finite DNA methylation marker set. Eur J Epidemiol. 2019; 34(11):1055-1074. PMC: 6861351. DOI: 10.1007/s10654-019-00555-w. View

Agha G, Mendelson M, Ward-Caviness C, Joehanes R, Huan T, Gondalia R . Blood Leukocyte DNA Methylation Predicts Risk of Future Myocardial Infarction and Coronary Heart Disease. Circulation. 2019; 140(8):645-657. PMC: 6812683. DOI: 10.1161/CIRCULATIONAHA.118.039357. View

Houseman E, Accomando W, Koestler D, Christensen B, Marsit C, Nelson H . DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics. 2012; 13:86. PMC: 3532182. DOI: 10.1186/1471-2105-13-86. View

10.

Davegardh C, Garcia-Calzon S, Bacos K, Ling C . DNA methylation in the pathogenesis of type 2 diabetes in humans. Mol Metab. 2018; 14:12-25. PMC: 6034041. DOI: 10.1016/j.molmet.2018.01.022. View

11.

Florath I, Butterbach K, Heiss J, Bewerunge-Hudler M, Zhang Y, Schottker B . Type 2 diabetes and leucocyte DNA methylation: an epigenome-wide association study in over 1,500 older adults. Diabetologia. 2015; 59(1):130-138. DOI: 10.1007/s00125-015-3773-7. View

12.

Richard M, Huan T, Ligthart S, Gondalia R, Jhun M, Brody J . DNA Methylation Analysis Identifies Loci for Blood Pressure Regulation. Am J Hum Genet. 2017; 101(6):888-902. PMC: 5812919. DOI: 10.1016/j.ajhg.2017.09.028. View

13.

Battram T, Yousefi P, Crawford G, Prince C, Sheikhali Babaei M, Sharp G . The EWAS Catalog: a database of epigenome-wide association studies. Wellcome Open Res. 2022; 7:41. PMC: 9096146. DOI: 10.12688/wellcomeopenres.17598.2. View

14.

Creyghton M, Cheng A, Welstead G, Kooistra T, Carey B, Steine E . Histone H3K27ac separates active from poised enhancers and predicts developmental state. Proc Natl Acad Sci U S A. 2010; 107(50):21931-6. PMC: 3003124. DOI: 10.1073/pnas.1016071107. View

15.

Levine M, Lu A, Quach A, Chen B, Assimes T, Bandinelli S . An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY). 2018; 10(4):573-591. PMC: 5940111. DOI: 10.18632/aging.101414. View

16.

Bird P, McEachan R, Mon-Williams M, Small N, West J, Whincup P . Growing up in Bradford: protocol for the age 7-11 follow up of the Born in Bradford birth cohort. BMC Public Health. 2019; 19(1):939. PMC: 6626420. DOI: 10.1186/s12889-019-7222-2. View

17.

Das S, Forer L, Schonherr S, Sidore C, Locke A, Kwong A . Next-generation genotype imputation service and methods. Nat Genet. 2016; 48(10):1284-1287. PMC: 5157836. DOI: 10.1038/ng.3656. View

18.

Tillin T, Hughes A, Mayet J, Whincup P, Sattar N, Forouhi N . The relationship between metabolic risk factors and incident cardiovascular disease in Europeans, South Asians, and African Caribbeans: SABRE (Southall and Brent Revisited) -- a prospective population-based study. J Am Coll Cardiol. 2013; 61(17):1777-86. PMC: 3677086. DOI: 10.1016/j.jacc.2012.12.046. View

19.

Williams E, Nazroo J, Kooner J, Steptoe A . Subgroup differences in psychosocial factors relating to coronary heart disease in the UK South Asian population. J Psychosom Res. 2010; 69(4):379-87. PMC: 2946562. DOI: 10.1016/j.jpsychores.2010.03.015. View

20.

Florath I, Butterbach K, Muller H, Bewerunge-Hudler M, Brenner H . Cross-sectional and longitudinal changes in DNA methylation with age: an epigenome-wide analysis revealing over 60 novel age-associated CpG sites. Hum Mol Genet. 2013; 23(5):1186-201. PMC: 3919014. DOI: 10.1093/hmg/ddt531. View