英国剑桥阿斯利康生物制药研发中心Keren Carss团队取得一项新突破。他们的研究提出了470727个UK Biobank基因组拷贝数变异的表型分析。相关论文于2026年2月4日发表在《自然》杂志上。

在这里，课题组通过分析来自470727个UK Biobank全基因组序列的CNVs，并通过2941个血浆蛋白丰度测量、13336个二元临床表型和1911个数量性状进行变异和基因水平的全表型关联研究（PheWAS），评估了CNVs在广泛的人类表型和疾病中的作用。蛋白质组学分析证实了CNVs与附近基因（顺式-蛋白质数量性状位点；顺式- pQTLs）的功能关联，缺失和重复通常分别与蛋白质水平的降低和增加相关，并揭示了以前未知的蛋白质-蛋白质相互作用（反式-pQTLs）。他们的PheWAS概括了编码区和非编码区已知的关联和未发现的关联。

值得注意的是，课题组在ZNF451中发现了与白细胞端粒长度增加相关的罕见缺失，以及与降低痛风风险相关的SLC2A9增强子的非编码缺失。此外，通过将CNVs与蛋白质编码单核苷酸变异和索引结合，该研究组增强了它们检测基因-疾病关联的研究能力。最后，该团队利用这个多组学数据集确定了几个构成候选生物标志物的pQTLs，例如与1A型腓骨肌萎缩症相关的TMPRSS5。这种多祖先全基因组序列CNV PheWAS提供了CNV在人类健康结果中的作用的见解，并可作为治疗开发的有价值的抵抗。

据了解，拷贝数变异（CNVs）是人类多样性和疾病风险的关键驱动因素。

附：英文原文

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

Author: Zou, Xueqing Zoe, Hu, Fengyuan, Lou, Haiyi, Burren, Oliver S., Li, Xiaoyin, Megy, Karyn, Wheeler, Eleanor, Wu, Qiang, Atanur, Santosh S., Karpinski, Marcin, Loesch, Douglas, Fairhurst-Hunter, Zammy, Deevi, Sri V. V., Oerton, Erin, Wen, Sean, Jiang, Xiao, Salvoro, Cecilia, Mitchell, Jonathan, Nag, Abhishek, Hollis, Ben, ONeill, Amanda, Harrow, Jen, MacArthur, Stewart, Wasilewski, Sebastian, ODell, Sean, Tian, Lifeng, Smith, Katherine R., del Angel, Guillermo, Fabre, Margarete, Dhindsa, Ryan S., Wang, Quanli, Petrovski, Slav, Carss, Keren

Issue&Volume: 2026-02-04

Abstract: Copy number variants (CNVs) are key drivers of human diversity and disease risk1. 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.

DOI: 10.1038/s41586-025-10087-x

Source: https://www.nature.com/articles/s41586-025-10087-x