Epigenomics in Translational Research

Published:October 04, 2014DOI:
      This issue of Translational Research features articles reviewing the progress and promise of epigenomics in the context of human health and disease. These articles provide examples of epigenomics, the study of genomic modifications causing and maintaining heritable changes in gene expression that cannot be attributed to changes in the primary DNA sequence, in a wide range of disorders from cancer (Nickel et al, Figueroa et al, Costa et al Stadler et al, Langevin et al, Kishi et al) to neurodegenerative (Bennett et al) and metabolic (Evans-Molina et al) diseases. This diversity in diseases highlights the breadth of the potential for clinical applications of epigenomics. At their most basic level, epigenomic studies help to elucidate disease etiology and pathogenesis. Building on this foundation, epigenomic insights can guide the development of diagnostic and prognostic tools. As epigenomic marks can be responsive to the environment, there is a lot of interest in their potential role as mediators of the effect of nongenetic risk factors for disease; these mechanistic insights into the consequences of environmental and other risk factors may provide targets for drug development. Further the cell-type specificity of epigenomic marks (Arnett et al) suggests that drugs that specifically target diseased epigenomic states, such as histone deacetylase and DNA methyltransferase inhibitors, may be useful in the context of cancers and inflammatory diseases (Lopez et al). Finally, tools arising from engineered epigenomic states, such as induced pluripotent stem cells, hold potential to fundamentally alter drug testing, disease modeling, tissue repair, and transplantation (Kobayashi et al).
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        • Hindorff L.A.
        • Sethupathy P.
        • Junkins H.A.
        • 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: 9362-9367
        • De Jager P.L.
        • Srivastava G.
        • Lunnon K.
        • et al.
        Alzheimer's disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci.
        Nat Neurosci. 2014; 17: 1156-1163
        • Rakyan V.K.
        • Beyan H.
        • Down T.A.
        • et al.
        Identification of type 1 diabetes-associated DNA methylation variable positions that precede disease diagnosis.
        PLoS Genet. 2011; 7: e1002300
        • Bock C.
        Analysing and interpreting DNA methylation data.
        Nat Rev Genet. 2012; 13: 705-719
        • Michels K.B.
        • Binder A.M.
        • Dedeurwaerder S.
        • et al.
        Recommendations for the design and analysis of epigenome-wide association studies.
        Nat Methods. 2013; 10: 949-955
        • Feinberg A.P.
        • Irizarry R.A.
        • Fradin D.
        • et al.
        Personalized epigenomic signatures that are stable over time and covary with body mass index.
        Sci Transl Med. 2010; 2: 49ra67
        • Liu Y.
        • Li X.
        • Aryee M.J.
        • et al.
        GeMes, clusters of DNA methylation under genetic control, can inform genetic and epigenetic analysis of disease.
        Am J Hum Genet. 2014; 94: 485-495
        • Frazer K.A.
        • Ballinger D.G.
        • Cox D.R.
        • et al.
        • International HapMap Consortium
        A second generation human haplotype map of over 3.1 million SNPs.
        Nature. 2007; 449: 851-861
        • Barfield R.T.
        • Almli L.M.
        • Kilaru V.
        • et al.
        Accounting for population stratification in DNA methylation studies.
        Genet Epidemiol. 2014; 38: 231-241
        • Nicolae D.L.
        • Gamazon E.
        • Zhang W.
        • et al.
        Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS.
        PLoS Genet. 2010; 6: e1000888
        • Nica A.C.
        • Montgomery S.B.
        • Dimas A.S.
        • et al.
        Candidate causal regulatory effects by integration of expression QTLs with complex trait genetic associations.
        PLoS Genet. 2010; 6: e1000895
        • Raj T.
        • Rothamel K.
        • Mostafavi S.
        • et al.
        Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes.
        Science. 2014; 344: 519-523
        • Fairfax B.P.
        • Humburg P.
        • Makino S.
        • et al.
        Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression.
        Science. 2014; 343: 1246949
        • Lee M.N.
        • Ye C.
        • Villani A.C.
        • et al.
        Common genetic variants modulate pathogen-sensing responses in human dendritic cells.
        Science. 2014; 343: 1246980
        • Trynka G.
        • Sandor C.
        • Han B.
        • et al.
        Chromatin marks identify critical cell types for fine mapping complex trait variants.
        Nat Genet. 2013; 45: 124-130
        • Maurano M.T.
        • Humbert R.
        • Rynes E.
        • et al.
        Systematic localization of common disease-associated variation in regulatory DNA.
        Science. 2012; 337: 1190-1195
        • Lunnon K.
        • Smith R.
        • Hannon E.
        • et al.
        Methylomic profiling implicates cortical deregulation of ANK1 in Alzheimer's disease.
        Nat Neurosci. 2014; 17: 1164-1170