Data-driven subgroups of prediabetes and the associations with outcomes in Chinese adults

Prediabetes and its pathophysiology remain important issues. We aimed to examine the cluster characteris-tics of prediabetes and explore their associations with developing diabetes and its complications based on 12 variables representing body fat, glycemic measures, pancreatic b cell function, insulin resistance, blood lipids, and liver enzymes. A total of 55,777 individuals with prediabetes from the China Cardiometabolic Disease and Cancer Cohort (4C) were classified at baseline into six clusters. During a median of 3.1 years of follow-up, sig-nificant differences in the risks of diabetes and its complications between clusters were observed. The odds ratios of diabetes stepwisely increase from cluster 1 to cluster 6. Clusters 1, 4, and 6 have increased chronic kidney diseases risks, while the prediabetes in cluster 4, characterized by obesity and insulin resistance, con-fers higher risks of cardiovascular diseases compared with others. This subcategorization has potential value in developing more precise strategies for targeted prediabetes prevention and treatment.