Proteomic risk scores for predicting common diseases using linear and neural network models in the UK biobank

Abstract Plasma proteomics provides a unique opportunity to enhance disease prediction by capturing protein expression patterns linked to diverse pathological processes. Leveraging data from 2,923 proteins measured in 53,030 UK Biobank participants, we developed proteomic risk scores for 27 common o...

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Bibliographic Details
Main Authors: Alexander Smith, Paul Elliott, Manuel Mayr, Abbas Dehghan, Ioanna Tzoulaki
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-025-06232-1
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