Identification of markers that distinguish adipose tissue and glucose and insulin metabolism using a multi-modal machine learning approach.

ABSTRACT: The study of metabolomics has improved our knowledge of the biology behind type 2 diabetes and its related metabolic physiology. We aimed to investigate markers of adipose tissue morphology, as well as insulin and glucose metabolism in 53 non-obese male individuals. The participants underwent extensive clinical, biochemical and magnetic resonance imaging phenotyping, and we also investigated non-targeted serum metabolites. We used a multi-modal machine learning approach to evaluate which serum metabolomic compounds predicted markers of glucose and insulin metabolism, adipose tissue morphology and distribution. Fasting glucose was associated with metabolites of intracellular insulin action and beta-cell dysfunction, namely cysteine-s-sulphate and n-acetylgarginine, whereas fasting insulin w

SUBMITTER: Henninger J 

PROVIDER: S-EPMC8382765 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature