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

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

Nature, 2021, vol. 597, issue 7877, 527-532

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 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/ ).

Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (16)

Downloads: (external link)
https://www.nature.com/articles/s41586-021-03855-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:nature:v:597:y:2021:i:7877:d:10.1038_s41586-021-03855-y

Ordering information: This journal article can be ordered from
https://www.nature.com/

DOI: 10.1038/s41586-021-03855-y

Access Statistics for this article

Nature is currently edited by Magdalena Skipper

More articles in Nature from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().