Rare variant contribution to human disease in 281,104 UK Biobank exomes
Author:
Wang Quanli, Dhindsa Ryan S.ORCID, Carss Keren, Harper Andrew R.ORCID, Nag Abhishek, Tachmazidou Ioanna, Vitsios Dimitrios, Deevi Sri V. V.ORCID, Mackay Alex, Muthas Daniel, Hühn Michael, Monkley Susan, Olsson HenricORCID, Angermann Bastian R., Artzi Ronen, Barrett Carl, Belvisi Maria, Bohlooly-Y Mohammad, Burren Oliver, Buvall Lisa, Challis Benjamin, Cameron-Christie Sophia, Cohen Suzanne, Davis Andrew, Danielson Regina F., Dougherty Brian, Georgi Benjamin, Ghazoui Zara, Hansen Pernille B. L., Hu Fengyuan, Jeznach Magda, Jiang Xiao, Kumar Chanchal, Lai Zhongwu, Lassi Glenda, Lewis Samuel H., Linghu Bolan, Lythgow Kieren, Maccallum Peter, Martins Carla, Matakidou Athena, Michaëlsson Erik, Moosmang Sven, O’Dell Sean, Ohne Yoichiro, Okae Joel, O’Neill Amanda, Paul Dirk S., Reznichenko Anna, Snowden Michael A, Walentinsson Anna, Zeron Jorge, Pangalos Menelas N., Wasilewski Sebastian, Smith Katherine R., March Ruth, Platt AdamORCID, Haefliger CarolinaORCID, Petrovski SlavéORCID,
Abstract
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/).
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Reference59 articles.
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