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

Author

Listed:
  • Fengzhe Xu

    (Fudan University
    Westlake University)

  • Evan Yi-Wen Yu

    (Southeast University)

  • Xue Cai

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine)

  • Liang Yue

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine)

  • Li-peng Jing

    (Sun Yat-sen University
    Lanzhou University)

  • Xinxiu Liang

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine)

  • Yuanqing Fu

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine)

  • Zelei Miao

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine)

  • Min Yang

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine)

  • Menglei Shuai

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine)

  • Wanglong Gou

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine)

  • Congmei Xiao

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine)

  • Zhangzhi Xue

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine)

  • Yuting Xie

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine)

  • Sainan Li

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine)

  • 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
    Berlin Institute of Health at Charité–Universitätsmedizin Berlin)

  • Jian Yang

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake Institute for Advanced Study)

  • Yu-ming Chen

    (Sun Yat-sen University)

  • Tiannan Guo

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake Institute for Advanced Study)

  • Ju-Sheng Zheng

    (Westlake University
    Westlake Laboratory of Life Sciences and Biomedicine
    Westlake Institute for Advanced Study
    Westlake University)

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.

Suggested Citation

  • 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, 2023. "Genome-wide genotype-serum proteome mapping provides insights into the cross-ancestry differences in cardiometabolic disease susceptibility," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-36491-3
    DOI: 10.1038/s41467-023-36491-3
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