Metabotype identification via fasting and postprandial metabolomics and its association with type 2 diabetes incidence
Authors' conclusion
We provided a comprehensive overview of associations between metabolomics-based metabotypes and T2DM risk across different prandial states.
Study context
- Population
- Participants of the Netherlands Epidemiology of Obesity (NEO) study with fasting and postprandial (150 min after meal) metabolomic data
- Participants
- 5,320 participants
- Exposure
- Metabotype 4 vs metabotype 1, by prandial state
- Outcome
- Incident T2D
- Follow-up
- Median 6.7 years
Methodological detailsk-means clustering, Cox proportional hazard models, random forest models, external validation in UK Biobank
- K-means clustering
- Cox proportional hazard models
- Random forest models
- External validation in UK Biobank
Main finding
As reported in the abstract
Metabotype 4 vs Metabotype 1Adjusted hazard ratio (95% CI)
Fasting state
3.4(2.2–5.3)
Postprandial state
2.4(1.6–3.8)
Observational data: associations, not effects.
Further findings
Core metabolites and diet of metabotype 4 (fasting, postprandial)
- Core metabolites were lipoproteins (e.g., MVLDLTG, SHDLC); higher-risk metabotypes had an unhealthier habitual diet
External validation
- Association between fasting metabotypes and incident T2D validated in the UK Biobank
Original publication
Metabotype identification via fasting and postprandial metabolomics and its association with type 2 diabetes incidence. Cardiovasc Diabetol. Published 8 July 2025. doi:10.
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