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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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2017-04-01
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| Series: | PLoS Genetics |
| Online Access: | https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1006711&type=printable |
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| author | Tian Ge Chia-Yen Chen Benjamin M Neale Mert R Sabuncu Jordan W Smoller |
| author_facet | Tian Ge Chia-Yen Chen Benjamin M Neale Mert R Sabuncu Jordan W Smoller |
| author_sort | Tian Ge |
| collection | DOAJ |
| 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. |
| format | Article |
| id | doaj-art-ae10b0ead08a41cf904780facae7a05e |
| institution | OA Journals |
| issn | 1553-7390 1553-7404 |
| language | English |
| publishDate | 2017-04-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Genetics |
| spelling | doaj-art-ae10b0ead08a41cf904780facae7a05e2025-08-20T02:31:58ZengPublic Library of Science (PLoS)PLoS Genetics1553-73901553-74042017-04-01134e100671110.1371/journal.pgen.1006711Phenome-wide heritability analysis of the UK Biobank.Tian GeChia-Yen ChenBenjamin M NealeMert R SabuncuJordan W SmollerHeritability 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.https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1006711&type=printable |
| spellingShingle | Tian Ge Chia-Yen Chen Benjamin M Neale Mert R Sabuncu Jordan W Smoller Phenome-wide heritability analysis of the UK Biobank. PLoS Genetics |
| 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 |
| url | https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1006711&type=printable |
| work_keys_str_mv | AT tiange phenomewideheritabilityanalysisoftheukbiobank AT chiayenchen phenomewideheritabilityanalysisoftheukbiobank AT benjaminmneale phenomewideheritabilityanalysisoftheukbiobank AT mertrsabuncu phenomewideheritabilityanalysisoftheukbiobank AT jordanwsmoller phenomewideheritabilityanalysisoftheukbiobank |