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Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection

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 eff...

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Detalles Bibliográficos
Autores principales: Schoech, Armin P., Jordan, Daniel M., Loh, Po-Ru, Gazal, Steven, O’Connor, Luke J., Balick, Daniel J., Palamara, Pier F., Finucane, Hilary K., Sunyaev, Shamil R., Price, Alkes L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377669/
https://www.ncbi.nlm.nih.gov/pubmed/30770844
http://dx.doi.org/10.1038/s41467-019-08424-6
Descripción
Sumario: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.