Untargeted metabolomics and mendelian randomization analysis identify adrenic acid as a novel biomarker of Type 2 diabetes mellitus.

PURPOSE: Given the differences between Chinese T2DM patients and those of other ethnicities, understanding the metabolic contributions in this population is essential. This study aimed to identify T2DM-associated metabolic biomarkers through clinical untargeted metabolomics and mendelian randomization (MR).

METHODS

This study included 120 Chinese participants, including 60 patients with T2DM and 60 control subjects. We employed ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) for non-targeted metabolomics analysis of plasma metabolites. Orthogonal partial least squares discriminant analysis (OPLS-DA) was used to identify T2DM-related metabolites. Integration of metabolomics and MR data identified novel key biomarkers for T2DM.

RESULTS

LC-MS/MS-based untargeted metabolomics identified 71 up-regulated and 37 down-regulated metabolites in the Chinese T2DM patients. In MR analysis, 52 metabolites exhibited causal associations with the risk of T2DM. Integrating metabolomic analysis with genetic evidence-based causal inference collectively confirmed that higher adrenic acid (AdA) was associated with an increased risk of T2DM and positively correlated with fasting blood glucose (FBG). The main impacted metabolic pathways were unsaturated fatty acids biosynthesis and linoleic acid metabolism.

CONCLUSIONS

Increased plasma AdA level was associated with higher FBG and an elevated risk of T2DM, suggesting that AdA represents a probable biomarker for T2DM.