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Plasma proteomic profiles predict individual future health risk

Medicine and Health

Plasma proteomic profiles predict individual future health risk

J. You, Y. Guo, et al.

A revolutionary proteomic risk score (ProRS) was developed by Jia You, Yu Guo, Yi Zhang, Ju-Jiao Kang, Lin-Bo Wang, Jian-Feng Feng, Wei Cheng, and Jin-Tai Yu, leveraging a vast dataset of 52,006 UK Biobank participants. This cutting-edge method not only stratifies the risk for a multitude of diseases, including cancer and dementia, but also surpasses conventional clinical indicators. Independent validation may soon pave the way for its real-world application.

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Playback language: English
Abstract
Developing a single-domain assay to identify individuals at high risk of future events is a priority for multi-disease and mortality prevention. This study developed a disease/mortality-specific proteomic risk score (ProRS) based on 1461 Olink plasma proteins measured in 52,006 UK Biobank participants using a neural network. ProRS effectively stratified risk for 45 common conditions and achieved high accuracy in predicting 10 endpoints (e.g., cancer, dementia, death). ProRS often outperformed established clinical indicators. While incorporating clinical predictors enhanced predictive power, the improvement over ProRS alone was limited. Proteins like GDF15 showed strong discriminative value across various diseases. The study demonstrated potential clinical utility, though independent external validation is needed before clinical application.
Publisher
Nature Communications
Published On
Nov 28, 2023
Authors
Jia You, Yu Guo, Yi Zhang, Ju-Jiao Kang, Lin-Bo Wang, Jian-Feng Feng, Wei Cheng, Jin-Tai Yu
Tags
proteomic risk score
disease prevention
clinical indicators
biobank
neural network
GDF15
mortality
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