Epigenetic Prediction of Complex Traits and Death

Overview

Journal Genome Biol

Specialties Biology
Genetics

Date 2018 Sep 28

PMID 30257690

Citations 97

Authors

Daniel L McCartney

Robert F Hillary

Anna J Stevenson

Stuart J Ritchie

Rosie M Walker

Qian Zhang

Stewart W Morris

Mairead L Bermingham

Archie Campbell

Alison D Murray

Heather C Whalley

Catharine R Gale

David J Porteous

Chris S Haley

Allan F McRae

Naomi R Wray

Peter M Visscher

Andrew M McIntosh

Kathryn L Evans

Ian J Deary

Riccardo E Marioni

Affiliations

Soon will be listed here.

Abstract

Background: Genome-wide DNA methylation (DNAm) profiling has allowed for the development of molecular predictors for a multitude of traits and diseases. Such predictors may be more accurate than the self-reported phenotypes and could have clinical applications.

Results: Here, penalized regression models are used to develop DNAm predictors for ten modifiable health and lifestyle factors in a cohort of 5087 individuals. Using an independent test cohort comprising 895 individuals, the proportion of phenotypic variance explained in each trait is examined for DNAm-based and genetic predictors. Receiver operator characteristic curves are generated to investigate the predictive performance of DNAm-based predictors, using dichotomized phenotypes. The relationship between DNAm scores and all-cause mortality (n = 212 events) is assessed via Cox proportional hazards models. DNAm predictors for smoking, alcohol, education, and waist-to-hip ratio are shown to predict mortality in multivariate models. The predictors show moderate discrimination of obesity, alcohol consumption, and HDL cholesterol. There is excellent discrimination of current smoking status, poorer discrimination of college-educated individuals and those with high total cholesterol, LDL with remnant cholesterol, and total:HDL cholesterol ratios.

Conclusions: DNAm predictors correlate with lifestyle factors that are associated with health and mortality. They may supplement DNAm-based predictors of age to identify the lifestyle profiles of individuals and predict disease risk.

Citing Articles

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Epigenome-Wide and Methylation Risk Score Analysis of Body Mass Index Among People with HIV.

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