Abstract

Individuals with prediabetes and type 2 diabetes mellitus (T2DM) have poor ability to adapt to diet-triggered perturbations. We investigated global metabolic responses to a mixed meal test (MMT) in morbidly obese individuals with different diabetic status by performing plasma metabolomic profiling. Abnormal metabolism of carbohydrates, (branched-chain) amino acids, fatty acids and acylcholines in individuals with (pre)diabetes was observed. Moreover, differences in metabolic responses were associated with altered fecal metagenomics and transcriptomes of liver, jejunum and adipose tissues, which revealed a modified gut microbiome and multi-tissue metabolism in individuals having insulin resistance. Finally, using integrative machine learning models, we built a predictive model based on metabolomics data after 2h MMT, and identified possible new biomarkers for glycemic control including N-acetylaspartate and phenylalanine-derived metabolites that may be useful for diagnosis, intervention and prevention of T2DM.