{"title":"53 026 名成年人健康和疾病时的血浆蛋白质组图谱","authors":"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, Jin-Tai Yu","doi":"10.1016/j.cell.2024.10.045","DOIUrl":null,"url":null,"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 (<span><span>https://proteome-phenome-atlas.com/</span><svg aria-label=\"Opens in new window\" focusable=\"false\" height=\"20\" viewbox=\"0 0 8 8\"><path d=\"M1.12949 2.1072V1H7V6.85795H5.89111V2.90281L0.784057 8L0 7.21635L5.11902 2.1072H1.12949Z\"></path></svg></span>) to help elucidate the biological mechanisms of diseases and accelerate the development of disease biomarkers, prediction models, and therapeutic targets.","PeriodicalId":9656,"journal":{"name":"Cell","volume":"188 1","pages":""},"PeriodicalIF":45.5000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Atlas of the plasma proteome in health and disease in 53,026 adults\",\"authors\":\"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, Jin-Tai Yu\",\"doi\":\"10.1016/j.cell.2024.10.045\",\"DOIUrl\":null,\"url\":null,\"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 (<span><span>https://proteome-phenome-atlas.com/</span><svg aria-label=\\\"Opens in new window\\\" focusable=\\\"false\\\" height=\\\"20\\\" viewbox=\\\"0 0 8 8\\\"><path d=\\\"M1.12949 2.1072V1H7V6.85795H5.89111V2.90281L0.784057 8L0 7.21635L5.11902 2.1072H1.12949Z\\\"></path></svg></span>) to help elucidate the biological mechanisms of diseases and accelerate the development of disease biomarkers, prediction models, and therapeutic targets.\",\"PeriodicalId\":9656,\"journal\":{\"name\":\"Cell\",\"volume\":\"188 1\",\"pages\":\"\"},\"PeriodicalIF\":45.5000,\"publicationDate\":\"2024-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cell\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1016/j.cell.2024.10.045\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.cell.2024.10.045","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Atlas of the plasma proteome in health and disease in 53,026 adults
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.
期刊介绍:
Cells is an international, peer-reviewed, open access journal that focuses on cell biology, molecular biology, and biophysics. It is affiliated with several societies, including the Spanish Society for Biochemistry and Molecular Biology (SEBBM), Nordic Autophagy Society (NAS), Spanish Society of Hematology and Hemotherapy (SEHH), and Society for Regenerative Medicine (Russian Federation) (RPO).
The journal publishes research findings of significant importance in various areas of experimental biology, such as cell biology, molecular biology, neuroscience, immunology, virology, microbiology, cancer, human genetics, systems biology, signaling, and disease mechanisms and therapeutics. The primary criterion for considering papers is whether the results contribute to significant conceptual advances or raise thought-provoking questions and hypotheses related to interesting and important biological inquiries.
In addition to primary research articles presented in four formats, Cells also features review and opinion articles in its "leading edge" section, discussing recent research advancements and topics of interest to its wide readership.