Genome-wide genotype-serum proteome mapping provides insights into the cross-ancestry differences in cardiometabolic disease susceptibility

Fengzhe Xu, Evan Yi-Wen Yu, Xue Cai, Liang Yue, Li-peng Jing, Xinxiu Liang, Yuanqing Fu, Zelei Miao, Min Yang, Menglei Shuai, Wanglong Gou, Congmei Xiao, Zhangzhi Xue, Yuting Xie, Sainan Li, Sha Lu, Meiqi Shi, Xuhong Wang, Wensheng Hu, Claudia Langenberg, Jian Yang, Yu-ming Chen (), Tiannan Guo () and Ju-Sheng Zheng ()
Additional contact information
Fengzhe Xu: Fudan University
Evan Yi-Wen Yu: Southeast University
Xue Cai: Westlake University
Liang Yue: Westlake University
Li-peng Jing: Sun Yat-sen University
Xinxiu Liang: Westlake University
Yuanqing Fu: Westlake University
Zelei Miao: Westlake University
Min Yang: Westlake University
Menglei Shuai: Westlake University
Wanglong Gou: Westlake University
Congmei Xiao: Westlake University
Zhangzhi Xue: Westlake University
Yuting Xie: Westlake University
Sainan Li: Westlake University
Sha Lu: Hangzhou Women’s Hospital (Hangzhou Maternity and Child Health Care Hospital)
Meiqi Shi: Hangzhou Women’s Hospital (Hangzhou Maternity and Child Health Care Hospital)
Xuhong Wang: Hangzhou Women’s Hospital (Hangzhou Maternity and Child Health Care Hospital)
Wensheng Hu: Hangzhou Women’s Hospital (Hangzhou Maternity and Child Health Care Hospital)
Claudia Langenberg: University of Cambridge School of Clinical Medicine
Jian Yang: Westlake University
Yu-ming Chen: Sun Yat-sen University
Tiannan Guo: Westlake University
Ju-Sheng Zheng: Westlake University

Nature Communications, 2023, vol. 14, issue 1, 1-12

Abstract: Abstract Identification of protein quantitative trait loci (pQTL) helps understand the underlying mechanisms of diseases and discover promising targets for pharmacological intervention. For most important class of drug targets, genetic evidence needs to be generalizable to diverse populations. Given that the majority of the previous studies were conducted in European ancestry populations, little is known about the protein-associated genetic variants in East Asians. Based on data-independent acquisition mass spectrometry technique, we conduct genome-wide association analyses for 304 unique proteins in 2,958 Han Chinese participants. We identify 195 genetic variant-protein associations. Colocalization and Mendelian randomization analyses highlight 60 gene-protein-phenotype associations, 45 of which (75%) have not been prioritized in Europeans previously. Further cross-ancestry analyses uncover key proteins that contributed to the differences in the obesity-induced diabetes and coronary artery disease susceptibility. These findings provide novel druggable proteins as well as a unique resource for the trans-ancestry evaluation of protein-targeted drug discovery.

Date: 2023
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DOI: 10.1038/s41467-023-36491-3

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