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dc.contributor.authorWang, Quanli
dc.contributor.authorDhindsa, Ryan S
dc.contributor.authorCarss, Keren
dc.contributor.authorHarper, Andrew R
dc.contributor.authorNag, Abhishek
dc.contributor.authorTachmazidou, Ioanna
dc.contributor.authorVitsios, Dimitrios
dc.contributor.authorDeevi, Sri VV
dc.contributor.authorMackay, Alex
dc.contributor.authorMuthas, Daniel
dc.contributor.authorHühn, Michael
dc.contributor.authorMonkley, Susan
dc.contributor.authorOlsson, Henric
dc.contributor.authorAstraZeneca Genomics Initiative
dc.contributor.authorWasilewski, Sebastian
dc.contributor.authorSmith, Katherine R
dc.contributor.authorMarch, Ruth
dc.contributor.authorPlatt, Adam
dc.contributor.authorHaefliger, Carolina
dc.contributor.authorPetrovski, Slavé
dc.date.accessioned2021-10-26T23:30:31Z
dc.date.available2021-10-26T23:30:31Z
dc.date.issued2021-09
dc.identifier.issn0028-0836
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/329919
dc.description.abstractGenome-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/ ).
dc.format.mediumPrint-Electronic
dc.languageeng
dc.publisherSpringer Science and Business Media LLC
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectAstraZeneca Genomics Initiative
dc.titleRare variant contribution to human disease in 281,104 UK Biobank exomes.
dc.typeArticle
prism.endingPage532
prism.issueIdentifier7877
prism.publicationDate2021
prism.publicationNameNature
prism.startingPage527
prism.volume597
dc.identifier.doi10.17863/CAM.77362
dcterms.dateAccepted2021-07-28
rioxxterms.versionofrecord10.1038/s41586-021-03855-y
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2021-09
dc.contributor.orcidDhindsa, Ryan S [0000-0002-8965-0813]
dc.contributor.orcidHarper, Andrew R [0000-0001-5327-0328]
dc.contributor.orcidDeevi, Sri VV [0000-0002-0405-4335]
dc.contributor.orcidOlsson, Henric [0000-0002-5101-8871]
dc.contributor.orcidPlatt, Adam [0000-0002-3455-1789]
dc.contributor.orcidHaefliger, Carolina [0000-0002-5095-5716]
dc.contributor.orcidPetrovski, Slavé [0000-0002-1527-961X]
dc.identifier.eissn1476-4687
rioxxterms.typeJournal Article/Review
cam.issuedOnline2021-08-10


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International