The American Journal of Human GeneticsGeneticsPeer-reviewed journal article
Partitioning gene-level contributions to complex-trait heritability by allele frequency identifies disease-relevant genes
Kathryn S. BurchiD, Kangcheng HouiD, Yi DingiD, Yifei WangiD, Steven GazaliD, Huwenbo ShiiD, Bogdan PaşaniuciD
Abstract
Recent works have shown that SNP-heritability--which is dominated by low-effect common variants--may not be the most relevant quantity for localizing high-effect/critical disease genes. Here, we introduce methods to estimate the proportion of phenotypic variance explained by a given assignment of SNPs to a single gene (genelevel heritability). We partition gene-level heritability across minor allele frequency (MAF) classes to find genes whose gene-level heritability is explained exclusively by "low-frequency/rare" variants (0.5% [≤] MAF < 1%). Applying our method to ~17K protein-coding genes and 25 quantitative traits in the UK Biobank (N=290K), we find that, on average across traits, ~2.5% of nonzero-heritability genes have a rare-variant component, and only ~0.8% (370 gene-trait pairs) have heritability exclusively from rare variants. Of these 370 gene-trait pairs, 37% were not detected by existing gene-level association testing methods, likely because existing methods combine signal from all variants in a region irrespective of MAF class. Many of the additional genes we identify are implicated in phenotypically related Mendelian disorders or congenital developmental disorders, providing further evidence of their trait-relevance. Notably, the rare-variant component of gene-level heritability exhibits trends different from those of common-variant gene-level heritability. For example, while total gene-level heritability increases with gene length, the rare-variant component is significantly larger among shorter genes; the cumulative distributions of gene-level heritability also vary across traits and reveal differences in the relative contributions of rare/common variants to overall gene-level polygenicity. We conclude that the proportion of gene-level heritability attributable to low-frequency/rare variation can yield novel insights into complex-trait genetic architecture.
- organism: human
- assay: GWAS summary statistics
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 14
- FWCI
- 1.51
- Field percentile
- top 19%
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