Improved sex-specific cardiovascular risk prediction with multi-omics data in people with type 2 diabetes
Authors' conclusion
Sex-specific proteomic signatures markedly improved 10-year MACE risk prediction in individuals with T2D. In men but not in women, further integration of metabolomics may enhance model performance whereas adding the CVD-PRS is not needed. External validation is warranted.
Study context
- Population
- UK Biobank participants with T2D, age 40–69 years, no prior major adverse cardiovascular events (MACE), complete multi-omics datacomplete multi-omics data
- Participants
- 990 participants
- Comparison
- SCORE2-Diabetes model with added proteomics, metabolomics and CVD-PRS vs SCORE2-Diabetes alone
- Outcome
- Model discrimination (Harrell's C-index) for 10-year MACE prediction
- Follow-up
- 10-year
Methodological detailsUK Biobank, bootstrap-LASSO regression, sex-specific
- UK Biobank
- bootstrap-LASSO regression
- Sex-specific
Performance
As reported in the abstract
Harrell's C-index for 10-year MACE prediction (total population)
SCORE2-Diabetes
0.766
SCORE2-Diabetes + proteomics
0.835
P < 0.001
- Further adding metabolites significantly improved model performance (C-index)
- 0.846, P = 0.035
Further findings
Adding metabolites, by sex
- Males: ∆C-index
- 0.012, P = 0.078
- Females: ∆C-index
- 0.004, P = 0.723
Original publication
Improved sex-specific cardiovascular risk prediction with multi-omics data in people with type 2 diabetes. Cardiovasc Diabetol. Published 24 December 2025. doi:10.
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