Integrated Genomic-Metabolomic Analysis for Tri-Categorical Classification of Type 2 Diabetes Status in the Korean Ansan-Ansung Cohort.

ABSTRACT: Identifying high-risk individuals for type 2 diabetes (T2D), particularly during prediabetes (PD), remains challenging owing to its complex metabolic etiology. In this study, we aimed to develop and validate an integrative multi-omics model for the tri-categorical classification of T2D status (Normal Glucose Tolerance, PD, and T2D) by combining genomic and metabolomic data from a Korean cohort. Based on cross-sectional data from 1819 participants in the Ansan-Ansung cohort, significant metabolites associated with glycemic traits and T2D status were identified using regression analysis. A metabolite-adjusted genome-wide association study (GWAS) was conducted to identify T2D-associated genetic variants. Finally, three nested prediction models (Clinical, Metabolite-Enriched, and integrated Mu

SUBMITTER: Cha J 

PROVIDER: S-EPMC12691764 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature