Personalized Epigenomic Signatures That Are Stable Over Time and Covary with Body Mass Index
Science Translational Medicine • 15 Sep 2010 • Vol 2, Issue 49 • p. 49ra67 • DOI: 10.1126/scitranslmed.3001262
The Writing is on the Genes: Can Epigenomics Predict Disease Risk?
In the nature versus nurture debate about human traits, epigenomics holds a special place. Epigenetic changes are physical changes that happen to genes but do not change the gene (DNA) sequence itself—such as DNA methylation. The regulation of these changes is not yet well-understood, providing new ammunition to the age-old argument. It is possible that the methylation pattern is all “nature”, predetermined by a person’s genetic makeup, or alternatively methylation could be a result of “nurture”, reflecting the influence of regulatory signals outside the cell, that is, the environment. Having analyzed the detailed methylation patterns in several dozen individuals at two different time points, over a decade apart, Feinberg et al. present evidence that the answer may actually be both—a combination of genetic determinants and environmental regulation.
In this study, the authors analyzed the full methylation pattern at 4.5 million sites genome-wide in 74 volunteers. The participants, who were on average 74 years old at the time of the first visit, provided blood samples again 11 to 14 years later, allowing for comparison of methylation patterns both between individuals, and in the same individuals across time. In doing this, the authors found 227 variably methylated regions (VMRs), which varied widely between the study participants. Of these, 119 VMRs remained stable within each individual over time, constituting an epigenetic fingerprint that may be genetically predetermined and differed between pairs of individual participants. The remaining VMRs were highly variable over time, suggesting that their pattern is affected by environmental influences. Four of the stable VMRs consistently correlated with study subjects’ body mass index in both visits. All four of these sites were located at or near genes that are known to be involved in the pathogenesis of diabetes or obesity, lending biological plausibility to the correlation between the methylation pattern and obesity risk.
Through their analysis of the epigenome in a large pool of volunteer subjects, Feinberg et al. have demonstrated a unique signature of stable epigenetic changes within each individual. Several of these stable methylation sites were correlated with the patients’ body mass index. If these results are confirmed in younger individuals and consistent throughout the life span, tests for methylation might be used to screen patients in childhood and identify those at risk for obesity, allowing preventative treatment. In theory, similar testing for other common diseases that may have a stable epigenetic component, such as diabetes or asthma, could allow early intervention and prevention.
Abstract
The epigenome consists of non–sequence-based modifications, such as DNA methylation, that are heritable during cell division and that may affect normal phenotypes and predisposition to disease. Here, we have performed an unbiased genome-scale analysis of ~4 million CpG sites in 74 individuals with comprehensive array-based relative methylation (CHARM) analysis. We found 227 regions that showed extreme interindividual variability [variably methylated regions (VMRs)] across the genome, which are enriched for developmental genes based on Gene Ontology analysis. Furthermore, half of these VMRs were stable within individuals over an average of 11 years, and these VMRs defined a personalized epigenomic signature. Four of these VMRs showed covariation with body mass index consistently at two study visits and were located in or near genes previously implicated in regulating body weight or diabetes. This work suggests an epigenetic strategy for identifying patients at risk of common disease.
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Supplementary Material
Summary
Table S1. Variably methylated regions across individuals.
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Note
Citation: A. P. Feinberg, R. A. Irizarry, D. Fradin, M. J. Aryee, P.Murakami, T. Aspelund, G. Eiriksdottir,T. B. Harris, L. Launer, V. Gudnason, M. D. Fallin, Personalized epigenomic signatures that are stableover time and covary with body mass index. Sci. Transl. Med. 2, 49ra67 (2010).
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Published In
Science Translational Medicine
Volume 2 • Issue 49 • 15 September 2010
Pages: 49ra67
History
Received: 5 May 2010
Accepted: 26 August 2010
Copyright
Copyright © 2010, American Association for the Advancement of Science.
