Data-driven phenotypic profiling of prediabetes reveals heterogeneous cardiometabolic risks in Chinese adults.

ABSTRACT:

Background

The heterogeneous and complex nature of prediabetes presents a major challenge in identifying individuals predisposed to developing incident diabetes and related complications. We aimed to identify phenotypic subgroups of prediabetes at risk and to explore their distinct associations with cardiometabolic outcomes.

Methods

This study included 79,000 individuals with prediabetes from the three large-scale prospective cohorts in China. Phenotypic heterogeneity was identified using a soft-clustering algorithm based on the proximity network derived from uniform manifold approximation and projection (UMAP), combined with graph-clustering and Gaussian mixture models. Associations between phenotype probabilities and the incidence of type 2 diabetes (T2D), cardiovascular d

SUBMITTER: Jia X 

PROVIDER: S-EPMC12777505 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature