Phenome-wide heritability analysis of the UK Biobank
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Author(s) • • • •
Ge, Tian
Chen, Chia-Yen
Sabuncu, Mert R.
Neale, Benjamin
Smoller, Jordan
Date Issued
April 2017
Journal
PLoS Genetics
Publisher
Public Library of Science
Citation
Ge, Tian; Chen, Chia-Yen; Neale, Benjamin M.; Sabuncu, Mert R. and Smoller, Jordan W. “Phenome-Wide Heritability Analysis of the UK Biobank.” Edited by Benjamin W. Domingue. PLOS Genetics 13, no. 4 (April 2017): e1006711 © 2017 Ge et al
Version
Final published version
Abstract
Heritability estimation provides important information about the relative contribution of genetic and environmental factors to phenotypic variation, and provides an upper bound for the utility of genetic risk prediction models. Recent technological and statistical advances have enabled the estimation of additive heritability attributable to common genetic variants (SNP heritability) across a broad phenotypic spectrum. Here, we present a computationally and memory efficient heritability estimation method that can handle large sample sizes, and report the SNP heritability for 551 complex traits derived from the interim data release (152,736 subjects) of the large-scale, population-based UK Biobank, comprising both quantitative phenotypes and disease codes. We demonstrate that common genetic variation contributes to a broad array of quantitative traits and human diseases in the UK population, and identify phenotypes whose heritability is moderated by age (e.g., a majority of physical measures including height and body mass index), sex (e.g., blood pressure related traits) and socioeconomic status (education). Our study represents the first comprehensive phenome-wide heritability analysis in the UK Biobank, and underscores the importance of considering population characteristics in interpreting heritability.
MIT Department
Broad Institute of MIT and Harvard
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Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.1371/journal.pgen.1006711