We tested whether DNA-methylation profiles account for inter-individual variation in body mass index (BMI) and height and whether they predict these phenotypes over and above genetic factors. Genetic predictors were derived from published summary results from the largest genome-wide association studies on BMI (n ∼ 350,000) and height (n ∼ 250,000) to date. We derived methylation predictors by estimating probe-trait effects in discovery samples and tested them in external samples. Methylation profiles associated with BMI in older individuals from the Lothian Birth Cohorts (LBCs, n = 1,366) explained 4.9% of the variation in BMI in Dutch adults from the LifeLines DEEP study (n = 750) but did not account for any BMI variation in adolescents from the Brisbane Systems Genetic Study (BSGS, n = 403). Methylation profiles based on the Dutch sample explained 4.9% and 3.6% of the variation in BMI in the LBCs and BSGS, respectively. Methylation profiles predicted BMI independently of genetic profiles in an additive manner: 7%, 8%, and 14% of variance of BMI in the LBCs were explained by the methylation predictor, the genetic predictor, and a model containing both, respectively. The corresponding percentages for LifeLines DEEP were 5%, 9%, and 13%, respectively, suggesting that the methylation profiles represent environmental effects. The differential effects of the BMI methylation profiles by age support previous observations of age modulation of genetic contributions. In contrast, methylation profiles accounted for almost no variation in height, consistent with a mainly genetic contribution to inter-individual variation. The BMI results suggest that combining genetic and epigenetic information might have greater utility for complex-trait prediction.

Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Overview publication

TitleImproving Phenotypic Prediction by Combining Genetic and Epigenetic Associations.
DateJuly 2nd, 2015
Issue nameAmerican journal of human genetics
Issue numberv97.1:75-85
DOI10.1016/j.ajhg.2015.05.014
PubMed26119815
AuthorsShah S, Bonder MJ, Marioni RE, Zhu Z, McRae AF, Zhernakova A, Harris SE, Liewald D, Henders AK, Mendelson MM, Liu C, Joehanes R, Liang L, Levy D, Martin NG, Starr JM, Wijmenga C, Wray NR, Yang J, Montgomery GW, Franke L, Deary IJ & Visscher PM
InfoBIOS Consortium, Heijmans BT, 't Hoen PA, van Meurs J, Isaacs A, Jansen R, Franke L, Boomsma DI, Pool R, van Dongen J, Hottenga JJ, van Greevenbroek MM, Stehouwer CD, van der Kallen CJ, Schalkwijk CG, Wijmenga C, Zhernakova S, Tigchelaar EF, Slagboom PE, Beekman M, Deelen J, van Heemst D, Veldink JH, van den Berg LH, van Duijn CM, Hofman BA, Uitterlinden AG, Jhamai PM, Verbiest M, Suchiman HE, Verkerk M, van der Breggen R, van Rooij J, Lakenberg N, Mei H, van Iterson M, van Galen M, Bot J, van 't Hof P, Deelen P, Nooren I, Moed M, Vermaat M, Zhernakova DV, Luijk R, Bonder MJ, van Dijk F, Arindrarto W, Kielbasa SM, Swertz MA, van Zwet EW
Read Read publication