Rare variant contribution to human disease in 281,104 UK Biobank exomes

TLDR

Genome‑wide association studies have uncovered many common variants, yet the contribution of rare variants to common disease remains largely unexplored; the UK Biobank’s extensive phenotypic and medical record linkage offers an unprecedented opportunity to investigate rare variant effects across thousands of traits. The authors sought to determine how rare protein‑coding variants associate with 17,361 binary and 1,419 quantitative phenotypes in 269,171 European‑ancestry UK Biobank participants. They applied gene‑based collapsing analyses to exome sequencing data, performed ancestry‑specific and pan‑ancestry tests, and released the resulting summary statistics through an interactive portal. The analyses identified 1,703 significant gene‑phenotype associations (median OR 12.4), most of which were missed by single‑variant tests, and were enriched for loss‑of‑function mechanisms and approved drug targets, underscoring the substantial role of rare variants in common disease.

Abstract

Abstract Genome-wide association studies have uncovered thousands of common variants associated with human disease, but the contribution of rare variants to common disease remains relatively unexplored. The UK Biobank contains detailed phenotypic data linked to medical records for approximately 500,000 participants, offering an unprecedented opportunity to evaluate the effect of rare variation on a broad collection of traits 1,2 . Here we study the relationships between rare protein-coding variants and 17,361 binary and 1,419 quantitative phenotypes using exome sequencing data from 269,171 UK Biobank participants of European ancestry. Gene-based collapsing analyses revealed 1,703 statistically significant gene–phenotype associations for binary traits, with a median odds ratio of 12.4. Furthermore, 83% of these associations were undetectable via single-variant association tests, emphasizing the power of gene-based collapsing analysis in the setting of high allelic heterogeneity. Gene–phenotype associations were also significantly enriched for loss-of-function-mediated traits and approved drug targets. Finally, we performed ancestry-specific and pan-ancestry collapsing analyses using exome sequencing data from 11,933 UK Biobank participants of African, East Asian or South Asian ancestry. Our results highlight a significant contribution of rare variants to common disease. Summary statistics are publicly available through an interactive portal ( http://azphewas.com/ ).