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Physicist, Startup Founder, Blogger, Dad

Monday, August 14, 2017

Estimation of genetic architecture for complex traits using GWAS data

These authors extrapolate from existing data to predict sample sizes needed to identify SNPs which explain a large portion of heritability in a variety of traits. For cognitive ability (see red curves in figure below), they predict sample sizes of ~million individuals will suffice.

See also More Shock and Awe: James Lee and SSGAC in Oslo, 600 SNP hits.
Estimation of complex effect-size distributions using summary-level statistics from genome-wide association studies across 32 complex traits and implications for the future

Yan Zhang, Guanghao Qi, Ju-Hyun Park, Nilanjan Chatterjee (Johns Hopkins University)

Summary-level statistics from genome-wide association studies are now widely used to estimate heritability and co-heritability of traits using the popular linkage-disequilibrium-score (LD-score) regression method. We develop a likelihood-based approach for analyzing summary-level statistics and external LD information to estimate common variants effect-size distributions, characterized by proportion of underlying susceptibility SNPs and a flexible normal-mixture model for their effects. Analysis of summary-level results across 32 GWAS reveals that while all traits are highly polygenic, there is wide diversity in the degrees of polygenicity. The effect-size distributions for susceptibility SNPs could be adequately modeled by a single normal distribution for traits related to mental health and ability and by a mixture of two normal distributions for all other traits. Among quantitative traits, we predict the sample sizes needed to identify SNPs which explain 80% of GWAS heritability to be between 300K-500K for some of the early growth traits, between 1-2 million for some anthropometric and cholesterol traits and multiple millions for body mass index and some others. The corresponding predictions for disease traits are between 200K-400K for inflammatory bowel diseases, close to one million for a variety of adult onset chronic diseases and between 1-2 million for psychiatric diseases.


This figure shows predicted effect size distributions for a number of quantitative traits. You can see that height and intelligence are somewhat different, but dramatically so.

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