Metabolomics-Defined Subtypes of Prediabetes and Risk of Cardiovascular-Kidney-Metabolic Outcomes.

Abstract

ARTICLE HIGHLIGHTS Previous studies have identified heterogeneity among prediabetes subgroups using clinical characteristics; however, biological and metabolic heterogeneity remains insufficiently captured. This study examined whether data-driven clustering based on metabolomic biomarkers could define distinct prediabetes subtypes with differential type 2 diabetes, cardiovascular disease, and chronic kidney disease risk. Using 16 metabolomic biomarkers, we identify three metabolically distinct clusters showing progressively higher risks of incident type 2 diabetes, cardiovascular disease, and chronic kidney disease. Differential diet-cluster associations across clusters were obtained, and Mendelian randomization supported potential causal roles for several metabolomic biomarkers. Metabolomics-based stratification may improve risk prevention and enable cluster-specific dietary interventions in prediabetes.