Genomic atlas of 7,000 plasma proteins and their associations with diseases and traits in East Asian populations

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Authors: Alfred Pozarickij, Baihan Wang, Ahmed Mohamed, Kuang Lin, Sam Morris, Christiana Kartsonaki, Neil Wright, Hannah Fry, Yiping Chen, Huaidong Du, Derrick Bennett, Ling Yang
+15 more Daniel Avery, Dan Schmidt, Liming Lin, Jun Lv, Canqing Yu, Dianjianyi Sun, Pei Pei, Junshi Chen, Michael Hill, R. Peto, Rory Collins, Robert Clarke, Iona Y. Millwood, Zhengming Chen, Robin G Walters
Cited by: 3
References: 52

Abstract

Abstract Proteogenomic studies integrating genetic, molecular, and phenotypic data have transformed target discovery, yet remain heavily biased toward European populations. Here, we present a large-scale proteogenomic atlas in a non-European population, analysing 7,289 plasma proteins profiled by SomaScan v4.1 in 3,965 Chinese adults. Genome-wide association analyses identified 3,212 protein quantitative trait loci (pQTLs), including 1,092 proteins with a cis -pQTL. Integrating these data with East Asian phenotypes and disease outcomes, we performed proteome-wide phenome scans and identified 7,936 protein-phenotype associations with strong colocalization support (PP.H4 > 0.8). Mendelian randomisation analyses using cis -pQTL instruments further prioritised 1,975 protein-phenotype associations, with 645 high-confidence pairs supported by both colocalisation and causal inference. Notably, we identified ancestry-specific pQTLs that contributed to associations undetectable in European studies alone. These associations organised into coherent biological networks, most prominently involving lipid metabolism and cardiovascular disease. Together, this study expands the global proteogenomic landscape and establishes a publicly valuable atlas of genetically anchored protein-phenotype relationships, providing a foundational resource for future genetic, functional, and translational studies, including drug-target prioritisation and risk-benefit assessment.

Fields of Study & Subjects

Genetic Associations and Epidemiology Bioinformatics and Genomic Networks Genetics and Physical Performance

Publication details

Journal / source
medRxiv
Publisher
openRxiv
Publication date
6 February 2026
Document type
Preprint