GeMes, clusters of DNA methylation under genetic control, can inform genetic and epigenetic analysis of disease

Yun Liu; Xin Li; Martin J Aryee; Tomas J Ekström; Leonid Padyukov; Lars Klareskog; Amy Vandiver; Ann Zenobia Moore; Toshiko Tanaka; Luigi Ferrucci; M Daniele Fallin; Andrew P Feinberg

doi:10.1016/j.ajhg.2014.02.011

GeMes, clusters of DNA methylation under genetic control, can inform genetic and epigenetic analysis of disease

Am J Hum Genet. 2014 Apr 3;94(4):485-95. doi: 10.1016/j.ajhg.2014.02.011. Epub 2014 Mar 20.

Authors

Affiliations

¹ Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
² Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02114, USA.
³ Center for Molecular Medicine, Karolinska Institutet and University Hospital, Stockholm 17176, Sweden; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm 17176, Sweden.
⁴ Center for Molecular Medicine, Karolinska Institutet and University Hospital, Stockholm 17176, Sweden; Rheumatology Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm 17176, Sweden.
⁵ Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
⁶ Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Deparment of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205, USA. Electronic address: dfallin@jhsph.edu.
⁷ Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA. Electronic address: afeinberg@jhu.edu.

Abstract

Epigenetic marks such as DNA methylation have generated great interest in the study of human disease. However, studies of DNA methylation have not established population-epigenetics principles to guide design, efficient statistics, or interpretation. Here, we show that the clustering of correlated DNA methylation at CpGs was similar to that of linkage-disequilibrium (LD) correlation in genetic SNP variation but for much shorter distances. Some clustering of methylated CpGs appeared to be genetically driven. Further, a set of correlated methylated CpGs related to a single SNP-based LD block was not always physically contiguous-segments of uncorrelated methylation as long as 300 kb could be interspersed in the cluster. Thus, we denoted these sets of correlated CpGs as GeMes, defined as potentially noncontiguous methylation clusters under the control of one or more methylation quantitative trait loci. This type of correlated methylation structure has implications for both biological functions of DNA methylation and for the design, analysis, and interpretation of epigenome-wide association studies.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

DNA Methylation*
Epigenesis, Genetic*
Genetic Predisposition to Disease*
Genome-Wide Association Study
Humans
Linkage Disequilibrium
Polymorphism, Single Nucleotide
Smoking / genetics

Abstract

Publication types

MeSH terms

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