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From promises to practical strategies in epigenetic epidemiology

Abstract

The epigenome has been heralded as a key 'missing piece' of the aetiological puzzle for complex phenotypes across the biomedical sciences. The standard research approaches developed for genetic epidemiology, however, are not necessarily appropriate for epigenetic studies of common disease. Here, we discuss the optimal execution of population-based studies of epigenetic variation, which will contribute to the emerging field of 'epigenetic epidemiology' and emphasize the importance of establishing a causal role in pathology for disease-associated epigenetic changes. We propose that improved understanding of the molecular mechanisms underlying human health and disease are best achieved through carrying out studies of epigenetics in populations as a part of an integrated functional genomics strategy.

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Figure 1: Examples of study designs for analysing epigenetic variation in populations.
Figure 2: Longitudinal analysis of epigenetic changes in a population cohort of monozygotic twins.

References

  1. Visscher, P. M., Brown, M. A., McCarthy, M. I. & Yang, J. Five years of GWAS discovery. Am. J. Hum. Genet. 90, 7–24 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Bernstein, B. E. et al. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

    Google Scholar 

  3. Relton, C. L. & Davey Smith, G. Is epidemiology ready for epigenetics? Int. J. Epidemiol. 41, 5–9 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Rakyan, V. K., Down, T. A., Balding, D. J. & Beck, S. Epigenome-wide association studies for common human diseases. Nature Rev. Genet. 12, 529–541 (2011).

    Article  CAS  PubMed  Google Scholar 

  5. Heyn, H. & Esteller, M. DNA methylation profiling in the clinic: applications and challenges. Nature Rev. Genet. 13, 679–692 (2012).

    Article  CAS  PubMed  Google Scholar 

  6. Tomizawa, S. & Sasaki, H. Genomic imprinting and its relevance to congenital disease, infertility, molar pregnancy and induced pluripotent stem cell. J. Hum. Genet. 57, 84–91 (2012).

    Article  CAS  PubMed  Google Scholar 

  7. Baylin, S. B. & Jones, P. A. A decade of exploring the cancer epigenome — biological and translational implications. Nature Rev. Cancer 11, 726–734 (2011).

    Article  CAS  Google Scholar 

  8. Feil, R. & Fraga, M. F. Epigenetics and the environment: emerging patterns and implications. Nature Rev. Genet. 12, 97–109 (2011).

    Google Scholar 

  9. Joubert, B. R. et al. 450K epigenome-wide scan identifies differential DNA methylation in newborns related to maternal smoking during pregnancy. Environ. Health Perspect. 120, 1425–1431 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Breitling, L. P., Yang, R., Korn, B., Burwinkel, B. & Brenner, H. Tobacco-smoking-related differential DNA methylation: 27K discovery and replication. Am. J. Hum. Genet. 88, 450–457 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Monick, M. M. et al. Coordinated changes in AHRR methylation in lymphoblasts and pulmonary macrophages from smokers. Am. J. Med. Genet. B 159, 141–151 (2012).

    Article  CAS  Google Scholar 

  12. Landan, G. et al. Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues. Nature Genet. 44, 1207–1214 (2012).

    Article  CAS  PubMed  Google Scholar 

  13. Feinberg, A. P. & Irizarry, R. A. Evolution in health and medicine Sackler colloquium: stochastic epigenetic variation as a driving force of development, evolutionary adaptation, and disease. Proc. Natl Acad. Sci. USA 107 (Suppl. 1), 1757–1764 (2010).

    Article  PubMed  Google Scholar 

  14. Jeffries, A. R. et al. Stochastic choice of allelic expression in human neural stem cells. Stem Cells 30, 1938–1947 (2012).

    Article  PubMed  Google Scholar 

  15. Smith, G. D. Epidemiology, epigenetics and the 'gloomy prospect': embracing randomness in population health research and practice. Int. J. Epidemiol. 40, 537–562 (2011).

    Article  PubMed  Google Scholar 

  16. Godfrey, K. M., Gluckman, P. D. & Hanson, M. A. Developmental origins of metabolic disease: life course and intergenerational perspectives. Trends Endocrinol. Metab. 21, 199–205 (2010).

    Article  CAS  PubMed  Google Scholar 

  17. Bateson, P. et al. Developmental plasticity and human health. Nature 430, 419–421 (2004).

    Article  CAS  PubMed  Google Scholar 

  18. Tobi, E. W. et al. DNA methylation differences after exposure to prenatal famine are common and timing- and sex-specific. Hum. Mol. Genet. 18, 4046–4053 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Kuehnen, P. et al. An Alu element-associated hypermethylation variant of the POMC gene is associated with childhood obesity. PLoS Genet. 8, e1002543 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. van Dongen, J., Slagboom, P. E., Draisma, H. H., Martin, N. G. & Boomsma, D. I. The continuing value of twin studies in the omics era. Nature Rev. Genet. 13, 640–653 (2012).

    Article  CAS  PubMed  Google Scholar 

  21. Kaminsky, Z., Wang, S. C. & Petronis, A. Complex disease, gender and epigenetics. Ann. Med. 38, 530–544 (2006).

    Article  CAS  PubMed  Google Scholar 

  22. Kong, A. et al. Parental origin of sequence variants associated with complex diseases. Nature 462, 868–874 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Heijmans, B. T. & Mill, J. Commentary: the seven plagues of epigenetic epidemiology. Int. J. Epidemiol. 41, 74–78 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  24. The Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661–678 (2007).

  25. Bell, J. T. et al. Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population. PLoS Genet. 8, e1002629 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Houseman, E. A. et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics 13, 86 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Leek, J. T. et al. Tackling the widespread and critical impact of batch effects in high-throughput data. Nature Rev. Genet. 11, 733–739 (2010).

    Article  CAS  PubMed  Google Scholar 

  28. Relton, C. L. & Davey Smith, G. Two-step epigenetic Mendelian randomization: a strategy for establishing the causal role of epigenetic processes in pathways to disease. Int. J. Epidemiol. 41, 161–176 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Boks, M. P. et al. Current status and future prospects for epigenetic psychopharmacology. Epigenetics 7, 20–28 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Laird, P. W. Principles and challenges of genomewide DNA methylation analysis. Nature Rev. Genet. 11, 191–203 (2010).

    Article  CAS  PubMed  Google Scholar 

  31. Sandoval, J. et al. Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome. Epigenetics 6, 692–702 (2011).

    Article  CAS  PubMed  Google Scholar 

  32. Ng, J. W. et al. The role of longitudinal cohort studies in epigenetic epidemiology: challenges and opportunities. Genome Biol. 13, 246 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Barres, R. et al. Acute exercise remodels promoter methylation in human skeletal muscle. Cell. Metab. 15, 405–411 (2012).

    Article  CAS  PubMed  Google Scholar 

  34. Gordon, L. et al. Neonatal DNA methylation profile in human twins is specified by a complex interplay between intrauterine environmental and genetic factors, subject to tissue-specific influence. Genome Res. 22, 1395–1406 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Khulan, B. et al. Periconceptional maternal micronutrient supplementation is associated with widespread gender related changes in the epigenome: a study of a unique resource in the Gambia. Hum. Mol. Genet. 21, 2086–2101 (2012).

    Article  CAS  PubMed  Google Scholar 

  36. Bock, C. Analysing and interpreting DNA methylation data. Nature Rev. Genet. 13, 705–719 (2012).

    Article  CAS  PubMed  Google Scholar 

  37. Riggs, A. D., Xiong, Z., Wang, L. & LeBon, J. M. in Novartis Foundation Symposium 214 — Epigenetics (eds Chadwick, D. K. & Cardew, G.) 214–232 (1998).

    Google Scholar 

  38. Davies, M. N. et al. Functional annotation of the human brain methylome identifies tissue-specific epigenetic variation across brain and blood. Genome Biol. 13, R43 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Vanhees, K. et al. Epigenetics: prenatal exposure to genistein leaves a permanent signature on the hematopoietic lineage. FASEB J. 25, 797–807 (2011).

    Article  CAS  PubMed  Google Scholar 

  40. Talens, R. P. et al. Epigenetic variation during the adult lifespan: cross-sectional and longitudinal data on monozygotic twin pairs. Aging Cell 11, 694–703 (2012).

    Article  CAS  PubMed  Google Scholar 

  41. Jaffe, A. E. et al. Bump hunting to identify differentially methylated regions in epigenetic epidemiology studies. Int. J. Epidemiol. 41, 200–209 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Lee, H. et al. DNA methylation shows genome-wide association of NFIX, RAPGEF2 and MSRB3 with gestational age at birth. Int. J. Epidemiol. 41, 188–199 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Wang, H. et al. Widespread plasticity in CTCF occupancy linked to DNA methylation. Genome Res. 22, 1680–1688 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Stoger, R. The thrifty epigenotype: an acquired and heritable predisposition for obesity and diabetes? Bioessays 30, 156–166 (2008).

    Article  PubMed  Google Scholar 

  45. Horvath, S. et al. Aging effects on DNA methylation modules in human brain and blood tissue. Genome Biol. 13, R97 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Hellman, A. & Chess, A. Gene body-specific methylation on the active X chromosome. Science 315, 1141–1143 (2007).

    Article  CAS  PubMed  Google Scholar 

  47. Maunakea, A. K. et al. Conserved role of intragenic DNA methylation in regulating alternative promoters. Nature 466, 253–257 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Gelfman, S., Cohen, N., Yearim, A. & Ast, G. DNA-methylation effect on cotranscriptional splicing is dependent on GC architecture of the exon-intron structure. Genome Res. 23, 789–799 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Aran, D., Sabato, S. & Hellman, A. DNA methylation of distal regulatory sites characterizes dysregulation of cancer genes. Genome Biol. 14, R21 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Klug, M. & Rehli, M. Functional analysis of promoter CpG methylation using a CpG-free luciferase reporter vector. Epigenetics 1, 127–130 (2006).

    Article  PubMed  Google Scholar 

  51. Bocker, M. T. et al. Genome-wide promoter DNA methylation dynamics of human hematopoietic progenitor cells during differentiation and aging. Blood 117, e182–189 (2011).

    Article  CAS  PubMed  Google Scholar 

  52. Gong, L., Pan, Y. X. & Chen, H. Gestational low protein diet in the rat mediates Igf2 gene expression in male offspring via altered hepatic DNA methylation. Epigenetics 5, 619–626 (2010).

    Article  CAS  PubMed  Google Scholar 

  53. Bernstein, B. E. et al. The NIH Roadmap Epigenomics Mapping Consortium. Nature Biotech. 28, 1045–1048 (2010).

    Article  CAS  Google Scholar 

  54. [No authors listed.] Time for the epigenome. Nature 463, 587 (2010).

  55. Dempster, E. L. et al. Disease-associated epigenetic changes in monozygotic twins discordant for schizophrenia and bipolar disorder. Hum. Mol. Genet. 20, 4786–4796 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Guintivano, J., Aryee, M. J. & Kaminsky, Z. A. A cell epigenotype specific model for the correction of brain cellular heterogeneity bias and its application to age, brain region and major depression. Epigenetics 8, 290–302 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Liu, Y. et al. Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nature Biotech. 31, 142–147 (2013).

    Article  CAS  Google Scholar 

  58. Grossniklaus, U., Kelly, B., Ferguson-Smith, A. C., Pembrey, M. & Lindquist, S. Transgenerational epigenetic inheritance: how important is it? Nature Rev. Genet. 14, 228–235 (2013).

    Article  CAS  PubMed  Google Scholar 

  59. Daxinger, L. & Whitelaw, E. Transgenerational epigenetic inheritance: more questions than answers. Genome Res. 20, 1623–1628 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Daxinger, L. & Whitelaw, E. Understanding transgenerational epigenetic inheritance via the gametes in mammals. Nature Rev. Genet. 13, 153–162 (2012).

    Article  CAS  PubMed  Google Scholar 

  61. Pembrey, M. E. Male-line transgenerational responses in humans. Hum. Fertil. 13, 268–271 (2010).

    Article  Google Scholar 

  62. Kaati, G., Bygren, L. O., Pembrey, M. & Sjostrom, M. Transgenerational response to nutrition, early life circumstances and longevity. Eur. J. Hum. Genet. 15, 784–790 (2007).

    Article  CAS  PubMed  Google Scholar 

  63. Sasaki, H. & Matsui, Y. Epigenetic events in mammalian germ-cell development: reprogramming and beyond. Nature Rev. Genet. 9, 129–140 (2008).

    Article  CAS  PubMed  Google Scholar 

  64. Weaver, I. C. et al. Epigenetic programming by maternal behavior. Nature Neurosci. 7, 847–854 (2004).

    Article  CAS  PubMed  Google Scholar 

  65. Crews, D. et al. Epigenetic transgenerational inheritance of altered stress responses. Proc. Natl Acad. Sci. USA 109, 9143–9148 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  66. Seisenberger, S. et al. The dynamics of genome-wide DNA methylation reprogramming in mouse primordial germ cells. Mol. Cell 48, 849–862 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Borgel, J. et al. Targets and dynamics of promoter DNA methylation during early mouse development. Nature Genet. 42, 1093–1100 (2010).

    Article  CAS  PubMed  Google Scholar 

  68. Slatkin, M. Epigenetic inheritance and the missing heritability problem. Genetics 182, 845–850 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Schalkwyk, L. C. et al. Allelic skewing of DNA methylation is widespread across the genome. Am. J. Hum. Genet. 86, 196–212 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Gamazon, E. R. et al. Enrichment of cis-regulatory gene expression SNPs and methylation quantitative trait loci among bipolar disorder susceptibility variants. Mol Psych. 18, 340–346 (2012).

    Article  CAS  Google Scholar 

  71. Meaburn, E. L., Schalkwyk, L. C. & Mill, J. Allele-specific methylation in the human genome: implications for genetic studies of complex disease. Epigenetics 5, 578–582 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Jablonka, E. Epigenetic epidemiology. Int. J. Epidemiol. 33, 929–935 (2004).

    Article  PubMed  Google Scholar 

  73. Waterland, R. A. & Michels, K. B. Epigenetic epidemiology of the developmental origins hypothesis. Annu. Rev. Nutr. 27, 363–388 (2007).

    Article  CAS  PubMed  Google Scholar 

  74. Zhou, V. W., Goren, A. & Bernstein, B. E. Charting histone modifications and the functional organization of mammalian genomes. Nature Rev. Genet. 12, 7–18 (2011).

    Article  CAS  PubMed  Google Scholar 

  75. Raiber, E. A. et al. Genome-wide distribution of 5-formylcytosine in embryonic stem cells is associated with transcription and depends on thymine DNA glycosylase. Genome Biol. 13, R69 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  76. Yu, M. et al. Base-resolution analysis of 5-hydroxymethylcytosine in the mammalian genome. Cell 149, 1368–1380 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Nestor, C., Ruzov, A., Meehan, R. & Dunican, D. Enzymatic approaches and bisulfite sequencing cannot distinguish between 5-methylcytosine and 5-hydroxymethylcytosine in DNA. Biotechniques 48, 317–319 (2010).

    Article  CAS  PubMed  Google Scholar 

  78. Waterland, R. A. & Jirtle, R. L. Transposable elements: targets for early nutritional effects on epigenetic gene regulation. Mol. Cell. Biol. 23, 5293–5300 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Thompson, R. F. et al. Tissue-specific dysregulation of DNA methylation in aging. Aging Cell 9, 506–518 (2010).

    Article  CAS  PubMed  Google Scholar 

  80. Lumey, L. H. et al. Cohort profile: the Dutch Hunger Winter Families Study. Int. J. Epidemiol. 36, 1196–1204 (2007).

    Article  CAS  PubMed  Google Scholar 

  81. Heijmans, B. T. et al. Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proc. Natl Acad. Sci. USA 105, 17046–17049 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  82. Tobi, E. W. et al. Prenatal famine and genetic variation are independently and additively associated with DNA methylation at regulatory loci within IGF2/H19. PLoS ONE 7, e37933 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Fraser, A. et al. Cohort profile: the Avon Longitudinal Study of Parents and Children: ALSPAC mothers cohort. Int. J. Epidemiol. 42, 97–110 (2013).

    Article  PubMed  Google Scholar 

  84. Groom, A. et al. Postnatal growth and DNA methylation are associated with differential gene expression of the TACSTD2 gene and childhood fat mass. Diabetes 61, 391–400 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Relton, C. L. et al. DNA methylation patterns in cord blood DNA and body size in childhood. PLoS ONE 7, e31821 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Wong, C. C. et al. A longitudinal study of epigenetic variation in twins. Epigenetics 5, 516–526 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Wong, C. C. et al. Methylomic analysis of monozygotic twins discordant for autism spectrum disorder and related behavioural traits. Mol. Psych. http://dx.doi.org/10.1038/mp.2013.41 (2013).

  88. Heyn, H. et al. DNA methylation profiling in breast cancer discordant identical twins identifies DOK7 as novel epigenetic biomarker. Carcinogenesis http://dx.doi.org/10.1093/carcin/bgs321 (2012).

  89. Javierre, B. M. et al. Changes in the pattern of DNA methylation associate with twin discordance in systemic lupus erythematosus. Genome Res. 20, 170–179 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Mastroeni, D., McKee, A., Grover, A., Rogers, J. & Coleman, P. D. Epigenetic differences in cortical neurons from a pair of monozygotic twins discordant for Alzheimer's disease. PLoS ONE 4, e6617 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Rakyan, V. K. et al. Identification of type 1 diabetes-associated DNA methylation variable positions that precede disease diagnosis. PLoS Genet. 7, e1002300 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Loke, Y. J. et al. The Peri/Postnatal Epigenetic Twins Study (PETS). Twin Res. Hum. Genet. 16, 13–20 (2013).

    Article  PubMed  Google Scholar 

  93. Inskip, H. M. et al. Cohort profile: the Southampton women's survey. Int. J. Epidemiol. 35, 42–48 (2006).

    Article  PubMed  Google Scholar 

  94. Godfrey, K. M. et al. Epigenetic gene promoter methylation at birth is associated with child's later adiposity. Diabetes 60, 1528–1534 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Andersen, A. N., Westergaard, H. B. & Olsen, J. The Danish in vitro fertilisation (IVF) register. Dan. Med. Bull. 46, 357–360 (1999).

    CAS  PubMed  Google Scholar 

  96. Lidegaard, O., Pinborg, A. & Andersen, A. N. Imprinting diseases and IVF: Danish National IVF cohort study. Hum. Reprod. 20, 950–954 (2005).

    Article  PubMed  Google Scholar 

  97. Carone, B. R. et al. Paternally induced transgenerational environmental reprogramming of metabolic gene expression in mammals. Cell 143, 1084–1096 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Beyan, H. et al. Guthrie card methylomics identifies temporally stable epialleles that are present at birth in humans. Genome Res. 22, 2138–2145 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

J.M. is supported by grants from the US National Institutes of Health (grants AG036039 and HD068437), the Brain and Behavior Research Foundation (formerly NARSAD), the UK Medical Research Council (MRC) and a Senior Award from the American Asthma Foundation (AAF). B.T.H. is supported by grants from BBMRI‑NL, a Research Infrastructure financed by the Dutch government (NWO 184.021.007), the US National Institutes of Health (grant AG042190-01), the European Union’s Seventh Framework Program IDEAL (FP7/2007‑2011) under grant agreement number 259679, The Netherlands CardioVascular Research Initiative from the Dutch Heart Foundation, Dutch Federation of University Medical Centers, the Netherlands Organization for Health Research and Development and the Royal Netherlands Academy of Sciences, and the Netherlands Consortium for Healthy Ageing (grant 05060810) in the framework of the Netherlands Genomics Initiative and the Netherlands Organization for Scientific Research.

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Glossary

Chromatin

The combination of DNA, RNA and protein that constitute the chromosomes in eukaryotic cells. Broadly, heterochromatin is associated with transcriptional repression and euchromatin is associated with transcriptional activity.

DNA methylation

The covalent binding of a methyl group at position 5 of the cytosine pyrimidine ring in CG dinucleotides often associated with the repression of transcription when present at promoters and enhancers.

Epigenetic

Describes mitotically heritable, but reversible, changes in gene expression mediated primarily by modifications to DNA and chromatin structure.

Epigenome

The entirety of epigenetic information in a cell, including DNA methylation, histone modifications, histone variants and non-coding RNAs.

Epigenome-wide association studies

(EWASs). Systematic assessments of a specific epigenetic mark, usually DNA methylation, across the genome in groups of individuals that are different for a given environmental exposure, trait or disease with the goal of identifying differences associated with that exposure or phenotype.

Histone

Histone proteins package DNA into structural units called nucleosomes. Covalent post-translational histone modifications include acetylation, methylation, phosphorylation, sumoylation and ubiquitylation; these can influence gene expression through changes in chromatin structure.

Mendelian randomization

An approach that uses a genetic proxy for DNA methylation (that is, methylation quantitative trait loci (meQTLs)) to identify a causal relationship between exposure and epigenetic variation, assuming that genetic associations are largely immune to residual confounding and reverse causation. Although such an approach requires that DNA methylation at relevant loci is influenced by both the environment and genetic variation, some examples of such a scenario have been reported.

Methylation quantitative trait loci

(meQTLs). Genetic variants that influence DNA methylation in cis via allele-specific DNA methylation or in trans:for example, by affecting the gene function of a DNA methylation modifier.

Methylome

The entirety of DNA methylation marks across the genome.

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Mill, J., Heijmans, B. From promises to practical strategies in epigenetic epidemiology. Nat Rev Genet 14, 585–594 (2013). https://doi.org/10.1038/nrg3405

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