| Title: | Phenome-wide heritability analysis of the UK Biobank |
| Journal: | PLOS Genetics |
| Published: | 7 Apr 2017 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/28388634/ |
| DOI: | https://doi.org/10.1371/journal.pgen.1006711 |
| URL: | https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1006711&type=printable |
| Citations: | 199 (38 in last 2 years) as of 8 Aug 2024 |
Publication 2066
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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.5 Authors
- Tian Ge
- Chia-Yen Chen
- Benjamin M. Neale
- Mert R. Sabuncu
- Jordan W. Smoller
1 Application
| Application ID | Title |
|---|---|
| 32568 | Phenomewide Heritability Analysis |
Enabling scientific discoveries that improve human health