| Title: | Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection |
| Journal: | Nature Communications |
| Published: | 15 Feb 2019 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/30770844/ |
| DOI: | https://doi.org/10.1038/s41467-019-08424-6 |
| URL: | https://www.nature.com/articles/s41467-019-08424-6.pdf |
| Citations: | 130 (40 in last 2 years) as of 8 Aug 2024 |
Publication 8692
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Abstract
Understanding the role of rare variants is important in elucidating the genetic basis of human disease. Negative selection can cause rare variants to have larger per-allele effect sizes than common variants. Here, we develop a method to estimate the minor allele frequency (MAF) dependence of SNP effect sizes. We use a model in which per-allele effect sizes have variance proportional to [p(1 − p)]α, where p is the MAF and negative values of α imply larger effect sizes for rare variants. We estimate α for 25 UK Biobank diseases and complex traits. All traits produce negative α estimates, with best-fit mean of -0.38 (s.e. 0.02) across traits. Despite larger rare variant effect sizes, rare variants (MAF < 1%) explain less than 10% of total SNP-heritability for most traits analyzed. Using evolutionary modeling and forward simulations, we validate the α model of MAF-dependent trait effects and assess plausible values of relevant evolutionary parameters.</p>
10 Authors
- Armin P. Schoech
- Daniel M. Jordan
- Po-Ru Loh
- Steven Gazal
- Luke J. O'Connor
- Daniel J. Balick
- Pier F. Palamara
- Hilary K. Finucane
- Shamil R. Sunyaev
- Alkes L. Price
1 Application
| Application ID | Title |
|---|---|
| 16549 | Components of heritability in a UK Biobank cohort |
Enabling scientific discoveries that improve human health