Data-driven phenotypic profiling of prediabetes reveals heterogeneous cardiometabolic risks in Chinese adults
Authors' conclusion
Prediabetes exhibits substantial phenotypic heterogeneity, and delineation of distinct metabolic profiles enables refined risk stratification and informs precision prevention strategies.
Study context
- Population
- Chinese adults with prediabetes from three large-scale prospective cohorts in China
- Participants
- 79,000 adults3 cohorts
- Exposure
- Phenotypic profiles of prediabetes
- Outcome
- Incidence of T2D, CVD and kidney events by phenotype probability
Methodological detailsthree large-scale prospective cohorts, soft-clustering (uniform manifold approximation and projection (UMAP) proximity network, graph-clustering, Gaussian mixture models)
- Three large-scale prospective cohorts
- Soft-clustering (UMAP proximity network, graph-clustering, Gaussian mixture models)
Main finding
As reported in the abstract
- Phenotypic profiles identified
- 6
- Profiles with distinct metabolic features (≈70% of population); one without significant features
- 5
- Hypertensive profile, per 20% higher probability: higher risk of T2D, cardiovascular disease (CVD) and CKD, respectively
- 9, 6, and 12%
- Profile with high lipids, creatinine and liver enzyme: increased risk of T2D and kidney events
- 10%
- Adding phenotypic probabilities to multivariable models improved risk prediction (likelihood ratio test)
- P < 0.05
Observational data: associations, not effects.
Original publication
Data-driven phenotypic profiling of prediabetes reveals heterogeneous cardiometabolic risks in Chinese adults. Cardiovasc Diabetol. Published 2 December 2025. doi:10.
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