A method to estimate the contribution of rare coding variants to complex trait heritability
Nazia Pathan, Wei Q. Deng, Matteo Di Scipio, Mohammad Daud Khan, Shihong Mao, Robert W. Morton, Ricky Lali, Marie Pigeyre, Michael Chong, Guillaume Paré
Abstract
Abstract It has been postulated that rare coding variants (RVs; MAF < 0.01) contribute to the “missing” heritability of complex traits. We developed a framework, the Rare variant heritability (RARity) estimator, to assess RV heritability ( h 2 RV ) without assuming a particular genetic architecture. We applied RARity to 31 complex traits in the UK Biobank ( n = 167,348) and showed that gene-level RV aggregation suffers from 79% (95% CI: 68-93%) loss of h 2 RV . Using unaggregated variants, 27 traits had h 2 RV > 5%, with height having the highest h 2 RV at 21.9% (95% CI: 19.0-24.8%). The total heritability, including common and rare variants, recovered pedigree-based estimates for 11 traits. RARity can estimate gene-level h 2 RV , enabling the assessment of gene-level characteristics and revealing 11, previously unreported, gene-phenotype relationships. Finally, we demonstrated that in silico pathogenicity prediction (variant-level) and gene-level annotations do not generally enrich for RVs that over-contribute to complex trait variance, and thus, innovative methods are needed to predict RV functionality.