Blood protein assessment of leading incident diseases and mortality in the UK Biobank

Danni A Gadd1,2, Robert F Hillary1,2, Zhana Kuncheva1,3

  • 1Optima Partners, Edinburgh, UK.

Nature Aging
|July 10, 2024
PubMed

Insights

This study analyzed 1,468 Olink proteins in UK Biobank participants to identify associations with age-related diseases and mortality. ProteinScores showed promise in predicting disease onset, outperforming existing risk predictors for type 2 diabetes.

Area of Science:

  • Biochemistry and Molecular Biology
  • Genomics and Proteomics
  • Epidemiology and Public Health

Background:

  • The circulating proteome provides valuable insights into disease mechanisms.
  • Understanding proteomic contributions to age-related diseases is crucial for early detection and prevention.

Purpose of the Study:

  • To investigate associations between plasma protein levels and the incidence of 23 age-related diseases and mortality.
  • To develop and validate protein-based risk scores (ProteinScores) for predicting disease onset.
  • To compare the predictive performance of ProteinScores against established risk assessment tools.

Main Methods:

  • Analysis of 1,468 Olink protein levels in 47,600 UK Biobank participants.
  • Statistical association testing between protein levels and 21 incident age-related outcomes.
  • Development of ProteinScores using penalized Cox regression models.
  • Validation of ProteinScores in independent test sets and comparison with polygenic risk scores and clinical markers.

Main Results:

  • Identified 3,209 significant associations between 963 protein levels and 21 incident outcomes.
  • Six ProteinScores demonstrated improved prediction of 10-year disease onset beyond traditional risk factors.
  • The ProteinScore for type 2 diabetes outperformed both polygenic risk scores and HbA1c levels.

Conclusions:

  • Plasma proteomic profiling reveals early contributions to major age-related diseases.
  • ProteinScores offer a novel and effective tool for enhancing disease risk stratification.
  • The findings underscore the potential of the proteome in personalized medicine and disease prevention strategies.

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