Phenome-wide analysis of copy number variants in 470,727 UK Biobank genomes

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Authors: Xueqing Zoe Zou, Fengyuan Hu, Haiyi Lou, Oliver S. Burren, Xiaoyin Li, Karyn Mégy, Eleanor Wheeler, Qiang Wu, Santosh S. Atanur, Marcin Karpiński, Douglas Loesch, Zammy Fairhurst-Hunter
+82 more Sri V. V. Deevi, Erin Oerton, Sean Wen, Xiao Jiang, Cecilia Salvoro, Jonathan Mitchell, Abhishek Nag, Ben Hollis, Amanda O’Neill, AstraZeneca Genomics Initiative, Lauren Anderson-Dring, Mohammad Bohlooly-Y, Lisa Buvall, Sophia Cameron-Christie, Bram Prins, Suzanne Cohen, Regina F. Danielson, Andrew M Davis, Wei Jun Ding, Brian Andrew Dougherty, Manik Garg, Benjamin Georgi, Andrew S. Harper, C. Haefliger, Mårten Hammar, Richard N. Hanna, Ian Henry, Kousik Kundu, Zhongwu Lai, Mark Lal, Glenda Lassi, Yupu Liang, Margarida Lopes, Kieren T. Lythgow, Meeta Maisuria-Armer, Ruth Karen March, Dorota Matelska, Rob Menzies, Erik Michaëlsson, Bill Mowrey, Daniel Muthas, Yoichiro Ohne, Benjamin S Pullman, Sonja Hess, Arwa Bin Raies, Anna Reznichenko, Xavier Romero Ros, Helen Stevens, Ioanna Tachmazidou, Coralie Viollet, Dimitrios Vitsios, Anna Walentinsson, Lily Wang, Qing-Dong Wang, Anna Cuomo, Daniel Elias Martin Herranz, Jared O’Connell, Jorge L. Del-Aguila, Anish Konkar, Benjamin Challis, Adam Platt, Tatiana Ort, James Garnett, Xiao-Rong Peng, Gabrielle Baumberg, Natalia Frydrych, Luca Stefanucci, Anna Szymaniak, Anna Maria Tsakiroglou, Rahul Sharma, Jennifer Harrow, Stewart MacArthur, Sebastian Wasilewski, Sean O’Dell, Lifeng Tian, Katherine R. Smith, Guillermo del Angel, Margarete A. Fabre, Ryan S. Dhindsa, Quanli Wang, Slavé Petrovski, Keren Carss
Cited by: 1
References: 59

Abstract

. Here we evaluate the role of CNVs across a broad range of human phenotypes and diseases by analysing CNVs from 470,727 UK Biobank whole-genome sequences and conducting a variant- and gene-level phenome-wide association study (PheWAS) with 2,941 plasma protein abundance measurements, 13,336 binary clinical phenotypes and 1,911 quantitative traits. Proteomic analyses validated functional associations of CNVs with nearby genes (cis-protein quantitative trait loci; cis-pQTLs)-with deletions and duplications typically associated with reduced and increased protein levels, respectively-and uncovered previously unknown protein-protein interactions (trans-pQTLs). Our PheWAS recapitulated known associations and uncovered associations in both coding and non-coding regions. Notably, we identified a rare deletion in ZNF451 associated with increased leukocyte telomere length and a non-coding deletion of a SLC2A9 enhancer associated with reduced gout risk. In addition, by combining CNVs with protein-coding single nucleotide variants and indels, we enhanced the power of our study to detect gene-disease associations. Finally, we leveraged this multiomics dataset to identify several pQTLs that constitute candidate biomarkers, including TMPRSS5 for Charcot-Marie-Tooth disease type 1A. This multiancestry whole-genome-sequence CNV PheWAS offers insights into the roles of CNVs in human health outcomes and could serve as a valuable resource for therapeutic development.

Fields of Study & Subjects

Genomic variations and chromosomal abnormalities Genomics and Rare Diseases Genetic Associations and Epidemiology

Publication details

Journal / source
Nature
Publisher
Springer Science and Business Media LLC
Volume
652
Issue
8110
Pages
675–685
Publication date
4 February 2026
Language
EN