Heritability Estimates from Summary Statistics

Written by: Stephen Hsu

Primary Source:  Information Processing

This paper describes a method for estimating heritability of a complex trait due to a single locus (DNA region), which the authors refer to as local heritability. It does not make the GCTA assumption of random effects. Instead, it uses GWAS estimates of individual effect sizes and the population LD matrix (covariance matrix of loci). Common SNPs in aggregate are found to account for significant heritability for various complex traits, including height, edu years (proxy for cognitive ability), schizophrenia risk (SCZ), etc. (See table below.)

Note, I could not find a link to the Supplement, which apparently contains some interesting results.

See also GCTA missing heritability and all that.

Contrasting the genetic architecture of 30 complex traits from summary association data
http://dx.doi.org/10.1101/035907

Variance components methods that estimate the aggregate contribution of large sets of variants to the heritability of complex traits have yielded important insights into the disease architecture of common diseases. Here, we introduce new methods that estimate the total variance in trait explained by a single locus in the genome (local heritability) from summary GWAS data while accounting for linkage disequilibrium (LD) among variants. We apply our new estimator to ultra large-scale GWAS summary data of 30 common traits and diseases to gain insights into their local genetic architecture. First, we find that common SNPs have a high contribution to the heritability of all studied traits. Second, we identify traits for which the majority of the SNP heritability can be confined to a small percentage of the genome. Third, we identify GWAS risk loci where the entire locus explains significantly more variance in the trait than the GWAS reported variants. Finally, we identify 55 loci that explain a large proportion of heritability across multiple traits.

 

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Stephen Hsu
Stephen Hsu is vice president for Research and Graduate Studies at Michigan State University. He also serves as scientific adviser to BGI (formerly Beijing Genomics Institute) and as a member of its Cognitive Genomics Lab. Hsu’s primary work has been in applications of quantum field theory, particularly to problems in quantum chromodynamics, dark energy, black holes, entropy bounds, and particle physics beyond the standard model. He has also made contributions to genomics and bioinformatics, the theory of modern finance, and in encryption and information security. Founder of two Silicon Valley companies—SafeWeb, a pioneer in SSL VPN (Secure Sockets Layer Virtual Private Networks) appliances, which was acquired by Symantec in 2003, and Robot Genius Inc., which developed anti-malware technologies—Hsu has given invited research seminars and colloquia at leading research universities and laboratories around the world.