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Phenome-wide heritability analysis of the UK Biobank

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 estimatio...

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Autores principales: Ge, Tian, Chen, Chia-Yen, Neale, Benjamin M., Sabuncu, Mert R., Smoller, Jordan W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5400281/
https://www.ncbi.nlm.nih.gov/pubmed/28388634
http://dx.doi.org/10.1371/journal.pgen.1006711
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author Ge, Tian
Chen, Chia-Yen
Neale, Benjamin M.
Sabuncu, Mert R.
Smoller, Jordan W.
author_facet Ge, Tian
Chen, Chia-Yen
Neale, Benjamin M.
Sabuncu, Mert R.
Smoller, Jordan W.
author_sort Ge, Tian
collection PubMed
description 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.
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spelling pubmed-54002812017-05-15 Phenome-wide heritability analysis of the UK Biobank Ge, Tian Chen, Chia-Yen Neale, Benjamin M. Sabuncu, Mert R. Smoller, Jordan W. PLoS Genet Research Article 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. Public Library of Science 2017-04-07 /pmc/articles/PMC5400281/ /pubmed/28388634 http://dx.doi.org/10.1371/journal.pgen.1006711 Text en © 2017 Ge et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ge, Tian
Chen, Chia-Yen
Neale, Benjamin M.
Sabuncu, Mert R.
Smoller, Jordan W.
Phenome-wide heritability analysis of the UK Biobank
title Phenome-wide heritability analysis of the UK Biobank
title_full Phenome-wide heritability analysis of the UK Biobank
title_fullStr Phenome-wide heritability analysis of the UK Biobank
title_full_unstemmed Phenome-wide heritability analysis of the UK Biobank
title_short Phenome-wide heritability analysis of the UK Biobank
title_sort phenome-wide heritability analysis of the uk biobank
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5400281/
https://www.ncbi.nlm.nih.gov/pubmed/28388634
http://dx.doi.org/10.1371/journal.pgen.1006711
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