Improving 10-year cardiovascular risk prediction in patients with type 2 diabetes with metabolomics
Authors' conclusion
Incorporating seven metabolomic biomarkers in the SCORE2-Diabetes model enhanced its ability to predict MACE in patients with type 2 diabetes. Given the latest cost reduction and standardization efforts, NMR metabolomics has the potential for translation into the clinical routine.
Study context
- Population
- Patients with T2D from the UK Biobank (UKB) and the German ESTHER cohortUKB 10,257
- Comparison
- SCORE2-Diabetes plus seven metabolomic biomarkers vs SCORE2-Diabetes alone
- Outcome
- 10-year major adverse cardiovascular events (MACE) prediction (Harrell's C-index)
- Follow-up
- 10-year
Methodological detailssex-specific LASSO regression with bootstrapping, internal and external validation, 249 metabolites measured by nuclear magnetic resonance (NMR) spectroscopy
- Sex-specific LASSO regression with bootstrapping
- Internal and external validation
- 249 metabolites measured by NMR spectroscopy
Performance
As reported in the abstract
Harrell's C-index, internal validation (30% of UKB), total sample
SCORE2-Diabetes + metabolites
0.678
SCORE2-Diabetes
0.660
P = 0.037
- Seven metabolomic biomarkers selected by LASSO (3 for both sexes, 3 male- and 1 female-specific)
- 7
Further findings
| Outcome | C-index increase | P value |
|---|---|---|
| Harrell's C-index, external validation (ESTHER)Higher with SCORE2-Diabetes + metabolites | + 0.043 | P = 0.011 |
Metabolites improving C-index
- Especially albumin and omega-3-fatty-acids-to-total-fatty-acids-percentage in males and lactate in females improved the C-index
Original publication
Improving 10-year cardiovascular risk prediction in patients with type 2 diabetes with metabolomics. Cardiovasc Diabetol. Published 13 January 2025. doi:10.
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