Serum Metabolic Differences Across Glucose Metabolic States Using Untargeted UPLC-HRMS Metabolomics

Abstract Insulin resistance (IR) and impaired glucose regulation (IGR) involve metabolic disturbances beyond changes in blood glucose. This cross-sectional study applied untargeted UPLC-HRMS metabolomics to serum from 109 participants across normal glucose tolerance (NGT), IR, IGR, and type 2 diabetes mellitus (T2DM). An integrated analysis of 457 putatively annotated metabolites combined multivariate statistics, clustering, and machine learning to characterize differences among glycometabolic groups and assess the discriminatory information. Pairwise comparisons respectively identified 60, 42, and 59 differential metabolites for NGT vs IR, IR vs IGR, and IGR vs T2DM, including five shared across all comparisons. LASSO and random forest evaluated fixed differential-metabolite panels through stratified 5-fold cross-validation repeated ten times and 1,000 label permutations. The corresponding pooled AUC ranges were 0.918–0.923, 0.995–0.996, and 0.828–0.950. Because panel selection preceded cross-validation, these estimates describe within-cohort discrimination rather than generalizable predictive performance. Pathway analysis of the union of differential metabolites indicated nominal enrichment of lysine degradation and nicotinate and nicotinamide metabolism. Shared metabolites also showed associations with clinical measures of glucose homeostasis and insulin response. These findings characterize distinct yet partly shared metabolic features across glycometabolic states and provide candidates for targeted confirmation and independent longitudinal validation.