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

Yue-Ting Deng; Jia You; Yu He; Yi Zhang; Hai-Yun Li; Xin-Rui Wu; Ji-Yun Cheng; Yu Guo; Zi-Wen Long; Yi-Lin Chen; Ze-Yu Li; Liu Yang; Ya-Ru Zhang; Shi-Dong Chen; Yi-Jun Ge; Yu-Yuan Huang; Le-Ming Shi; Qiang Dong; Ying Mao; Jian-Feng Feng; Wei Cheng; Jin-Tai Yu

doi:10.1016/j.cell.2024.10.045

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

Cell. 2024 Nov 15:S0092-8674(24)01268-6. doi: 10.1016/j.cell.2024.10.045. Online ahead of print.

Authors

Yue-Ting Deng¹, Jia You², Yu He¹, Yi Zhang¹, Hai-Yun Li¹, Xin-Rui Wu¹, Ji-Yun Cheng¹, Yu Guo¹, Zi-Wen Long³, Yi-Lin Chen¹, Ze-Yu Li², Liu Yang¹, Ya-Ru Zhang¹, Shi-Dong Chen¹, Yi-Jun Ge¹, Yu-Yuan Huang¹, Le-Ming Shi⁴, Qiang Dong¹, Ying Mao⁵, Jian-Feng Feng⁶, Wei Cheng⁷, Jin-Tai Yu⁸

Affiliations

¹ Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
² Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
³ Department of Gastric Cancer Surgery, Fudan University Shanghai Cancer Center, Shanghai, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
⁴ State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, China.
⁵ Department of Neurosurgery, Huashan Hospital Fudan University, Shanghai, China. Electronic address: maoying@fudan.edu.cn.
⁶ Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China; Department of Computer Science, University of Warwick, Coventry, UK. Electronic address: jianfeng64@gmail.com.
⁷ Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China. Electronic address: wcheng@fudan.edu.cn.
⁸ Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China. Electronic address: jintai_yu@fudan.edu.cn.

PMID: 39579765
DOI: 10.1016/j.cell.2024.10.045

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.

Keywords: atlas; diagnosis; disease; disease association; health; pQTL; prediction; protein; proteomics; therapeutic targets.