The distribution of common-variant effect sizes.
Journal
Nature genetics
ISSN: 1546-1718
Titre abrégé: Nat Genet
Pays: United States
ID NLM: 9216904
Informations de publication
Date de publication:
08 2021
08 2021
Historique:
received:
16
09
2020
accepted:
23
06
2021
pubmed:
31
7
2021
medline:
11
9
2021
entrez:
30
7
2021
Statut:
ppublish
Résumé
The genetic effect-size distribution of a disease describes the number of risk variants, the range of their effect sizes and sample sizes that will be required to discover them. Accurate estimation has been a challenge. Here I propose Fourier Mixture Regression (FMR), validating that it accurately estimates real and simulated effect-size distributions. Applied to summary statistics for ten diseases (average [Formula: see text]), FMR estimates that 100,000-1,000,000 cases will be required for genome-wide significant SNPs to explain 50% of SNP heritability. In such large studies, genome-wide significance becomes increasingly conservative, and less stringent thresholds achieve high true positive rates if confounding is controlled. Across traits, polygenicity varies, but the range of their effect sizes is similar. Compared with effect sizes in the top 10% of heritability, including most discovered thus far, those in the bottom 10-50% are orders of magnitude smaller and more numerous, spanning a large fraction of the genome.
Identifiants
pubmed: 34326547
doi: 10.1038/s41588-021-00901-3
pii: 10.1038/s41588-021-00901-3
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1243-1249Informations de copyright
© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.
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