Dataset Information

Improving Phenotypic Prediction by Combining Genetic and Epigenetic Associations.

ABSTRACT: 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.

SUBMITTER: Shah S

PROVIDER: S-EPMC4572498 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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Improving Phenotypic Prediction by Combining Genetic and Epigenetic Associations.

Shah Sonia S Bonder Marc J MJ Marioni Riccardo E RE Zhu Zhihong Z McRae Allan F AF Zhernakova Alexandra A Harris Sarah E SE Liewald Dave D Henders Anjali K AK Mendelson Michael M MM Liu Chunyu C Joehanes Roby R Liang Liming L Levy Daniel D Martin Nicholas G NG Starr John M JM Wijmenga Cisca C Wray Naomi R NR Yang Jian J Montgomery Grant W GW Franke Lude L Deary Ian J IJ Visscher Peter M PM

American journal of human genetics 20150625 1

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 pro ...[more]

PMID: 26119815

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Dataset Information

Improving Phenotypic Prediction by Combining Genetic and Epigenetic Associations.

Publications

Improving Phenotypic Prediction by Combining Genetic and Epigenetic Associations.

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