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Review
. 2011 Jul 12;12(8):529-41.
doi: 10.1038/nrg3000.

Epigenome-wide association studies for common human diseases

Vardhman K Rakyan  1 , Thomas A Down, David J Balding, Stephan Beck
Affiliations
Review

Epigenome-wide association studies for common human diseases

Vardhman K Rakyan et al. Nat Rev Genet. .

Abstract

Despite the success of genome-wide association studies (GWASs) in identifying loci associated with common diseases, a substantial proportion of the causality remains unexplained. Recent advances in genomic technologies have placed us in a position to initiate large-scale studies of human disease-associated epigenetic variation, specifically variation in DNA methylation. Such epigenome-wide association studies (EWASs) present novel opportunities but also create new challenges that are not encountered in GWASs. We discuss EWAS design, cohort and sample selections, statistical significance and power, confounding factors and follow-up studies. We also discuss how integration of EWASs with GWASs can help to dissect complex GWAS haplotypes for functional analysis.

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Figures

Figure 1
Figure 1. The different types of sample cohorts that could be used in an EWAS
Refer to text for a full discussion.
Figure 2
Figure 2. Hypothetical DNA methylation frequency spectra in cases and controls
Methylation states in controls (solid curve) and cases for four effect sizes (other curves) are shown under three scenarios. For (a) and (b), the proportions of individuals who are, respectively, unmethylated, intermediate, or methylated in controls and the four sets of cases are shown in the keys. The distributions of measured methylation states are assumed to follow the following beta distributions (i) unmethylated individuals: beta(1.5,6) distribution, which has mean = 0.2, SD = 0.14; (ii) intermediate individuals: beta(2,2), mean = 0.50, SD = 0.22; (iii) methylated individuals: beta(6,1.5), mean = 0.80, SD = 0.14. For (c), the methylation spectrum is assumed to follow a single beta distribution for controls and each set of cases, and its parameters are shown in the key
See this image and copyright information in PMC

References

    1. Hindorff LA, et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci U S A. 2009;106:9362–7. - PMC - PubMed
    1. Feinberg AP, Irizarry RA. Evolution in health and medicine Sackler colloquium: Stochastic epigenetic variation as a driving force of development, evolutionary adaptation, and disease. Proc Natl Acad Sci U S A. 2010;107(Suppl 1):1757–64. - PMC - PubMed
    1. Petronis A. Epigenetics as a unifying principle in the aetiology of complex traits and diseases. Nature. 2010;465:721–7. - PubMed
    1. Kulis M, Esteller M. DNA methylation and cancer. Advances in genetics. 2010;70:27–56. - PubMed
    1. Bernstein BE, Meissner A, Lander ES. The mammalian epigenome. Cell. 2007;128:66981. - PubMed

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