Diabetic foot (DF) is one of the serious chronic complications of diabetes. Accurate prediction of the risk of DF may take timely intervention measures to prevent its occurrence. The understanding of metabolomic changes in the progression of diabetes to DF may reveal new targets for interventions. We hypothesized that changes in metabolic pathways during DF would lead to changes in the metabolic profile, which could be predictive signature specific to it. In the present study, 43 participants with type 2 diabetes mellitus (T2DM), 32 T2DM participants with DF (T2DM-F), and 36 healthy subjects were enrolled and their serum samples were used for targeted and nonpolar metabolic analysis with liquid chromatography-tandem mass spectrometry. Differential metabolites related to T2DM-F were discovered in metabolomic analysis. Lasso machine learning regression model, random forest algorithm, causal mediation analysis, disease risk assessment, and clinical decision model were carried out. T2DM and T2DM-F groups could be distinguished with the healthy control group. The differential metabolites were all enriched in alpha-linolenic acid and linoleic acid metabolic pathways including arachidonic acid, docosapentaenoic-acid 22N-6, and docosahexaenoic-acid, which were significantly lower in the T2DM and T2DM-F groups compared with the healthy control group. The differential metabolites in T2DM-F vs T2DM groups were enriched to branched-chain amino acid (BCAA) catabolic pathways involving in methylmalonic acid, succinic acid, 3-methyl-2-oxovaleric acid, and ketoleucine, which were the BCAA catabolic intermediates and significantly lower in the T2DM-F compared with the T2DM group except for succinic acid. We reveal a new set of predictive signatures and associate the lower BCAA catabolic intermediates with the progression from T2DM to T2DM-F.
Keywords: Branched chain amino acid catabolic pathways; Diabetic foot; Metabolic markers.
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