Atlas of the plasma proteome in health and disease in 53,026 adults

Yue‐Ting Deng(Fudan University), Jia You(Shanghai Center for Brain Science and Brain-Inspired Technology), Yu He(Fudan University), Yi Zhang(Fudan University), Haiyun Li(Fudan University), Xinrui Wu(Fudan University), Ji-Yun Cheng(Fudan University), Yu Amanda Guo(Fudan University), Zi-Wen Long(Fudan University Shanghai Cancer Center), Yi-Lin Chen(Fudan University), Zeyu Li(Shanghai Center for Brain Science and Brain-Inspired Technology), Yang Liu(Fudan University), Ya-Ru Zhang(Fudan University), Shi-Dong Chen(Fudan University), Yi‐Jun Ge(Fudan University), Yuyuan Huang(Fudan University), Leming Shi(Fudan University), Qiang Dong(Fudan University), Ying Mao(Huashan Hospital), Jianfeng Feng(Shanghai Center for Brain Science and Brain-Inspired Technology), Wei Cheng(Fudan University), Jin‐Tai Yu(Huashan Hospital)
Cell
November 22, 2024
Cited by 223Open Access
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Abstract

Large-scale proteomics studies can refine our understanding of health and disease and enable precision medicine. Here, we provide a detailed atlas of 2,920 plasma proteins linking to diseases (406 prevalent and 660 incident) and 986 health-related traits in 53,026 individuals (median follow-up: 14.8 years) from the UK Biobank, representing the most comprehensive proteome profiles to date. This atlas revealed 168,100 protein-disease associations and 554,488 protein-trait associations. Over 650 proteins were shared among at least 50 diseases, and over 1,000 showed sex and age heterogeneity. Furthermore, proteins demonstrated promising potential in disease discrimination (area under the curve [AUC] > 0.80 in 183 diseases). Finally, integrating protein quantitative trait locus data determined 474 causal proteins, providing 37 drug-repurposing opportunities and 26 promising targets with favorable safety profiles. These results provide an open-access comprehensive proteome-phenome resource (https://proteome-phenome-atlas.com/) to help elucidate the biological mechanisms of diseases and accelerate the development of disease biomarkers, prediction models, and therapeutic targets.


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