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

Quanli Wang,Alex Mackay,Michael Hühn,Keren Carss,Katherine R Smith,Sri V V Deevi ,Susan J Monkley ,Abhishek Nag,Dimitrios Vitsios,Adam Platt,Ryan S Dhindsa,Carolina Haefliger,Sebastian Wasilewski,Ruth March,Andrew Harper ,Henric Olsson,Ioanna Tachmazidou,Daniel Muthas,Slavé Petrovski

doi:10.1038/s41586-021-03855-y

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 traits1,2. 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/).

Highlights

The UK Biobank (UKB) offers an unprecedented opportunity to assess the contribution of both common and rare genetic variation to thousands of human traits and diseases[1,2,9,10,11,12,13]
We considered 17,361 binary traits and 1,419 quantitative traits, which we categorized into 22 ICD-10-based chapters (Extended Data Fig. 1a, b, Supplementary Table 1)
We performed a phenome-wide association study (PheWAS) using exome sequences of 269,171 UKB participants of European ancestry combined with records of 18,780 phenotypes, followed by a pan-ancestry analysis that incorporated an additional 11,933 UKB participants of African, East Asian and South Asian ancestries

Summary

Discussion

We performed a PheWAS using exome sequences of 269,171 UKB participants of European ancestry combined with records of 18,780 phenotypes, followed by a pan-ancestry analysis that incorporated an additional 11,933 UKB participants of African, East Asian and South Asian ancestries. Phenotypes may be refined through combining binary, phenotypic and temporal data The results of this PheWAS are publicly available (http://azphewas.com/), which we anticipate will help to elucidate disease mechanisms, identify phenotypic expansions and enable the development of human genetically validated drugs. D. et al Advancing human genetics research and drug discovery through exome sequencing of the UK Biobank. T. et al Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts. S. et al An exome sequencing study to assess the role of rare genetic variation in pulmonary fibrosis. Ultra-rare genetic variation in common epilepsies: a case–control sequencing study. J. et al Spontaneous coronary artery dissection: insights on rare genetic variation from genome sequencing. D. et al Phenome-wide association studies across large population cohorts support drug target validation.

Methods

Findings

Code availability