Plasma proteomic profiles predict individual future health risk

• Published in: Nature communications Vol. 14; no. 1; pp. 7817 - 13
• Main Authors: You, Jia, Guo, Yu, Zhang, Yi, Kang, Ju-Jiao, Wang, Lin-Bo, Feng, Jian-Feng, Cheng, Wei, Yu, Jin-Tai
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 28.11.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114/1305; 631/45/475; 692/308/575; 692/53/2423; 692/699; Biobanks; Cancer; Dementia disorders; Equivalence; Health risk assessment; Health risks; Humanities and Social Sciences; Humans; Indicators; Laboratory tests; Mortality; multidisciplinary; Neoplasms - diagnosis; Neural networks; Performance indices; Performance prediction; Plasma proteins; Proteins; Proteomics; Risk Assessment; Risk Factors; Science; Science (multidisciplinary); United Kingdom > UK

Developing a single-domain assay to identify individuals at high risk of future events is a priority for multi-disease and mortality prevention. By training a neural network, we developed a disease/mortality-specific proteomic risk score (ProRS) based on 1461 Olink plasma proteins measured in 52,006...