Identification of mitochondria-related key genes in type 2 diabetes mellitus and elucidation of the Zhimu-Huangbai herb Pair's mechanism: an integrated approach of bioinformatics, machine learning, and experimental validation
Abstract
BACKGROUND: Mitochondrial injury plays a critical role in type 2 diabetes mellitus (T2DM) pathogenesis by impairing cellular energy metabolism and insulin sensitivity. The Zhimu-Huangbai herb pair (ZB), a classic Traditional Chinese Medicine formulation composed of Anemarrhena asphodeloides and Phellodendron chinense, has shown efficacy in T2DM, but its molecular mechanisms remain unclear. In this study, we aimed to identify crucial mitochondrial related genes of type 2 diabetes and the potential mechanism of ZB.
METHODS: Gene expression datasets for T2DM (GSE76894, GSE25724, and GSE38642) were retrieved from the GEO database. Intersection targets of ZB herb pair and T2DM were identified by screening multiple databases, including the TCMSP and HERB. Mitochondrial function-related genes were obtained from human mitochondria-associated databases. WGCNA was employed to identify differentially expressed genes, which were then intersected with bioactive compound-target genes and mitochondrial-related genes to construct a PPI network. GO and KEGG enrichment analyses were subsequently performed. Four machine learning algorithms-SVM-RFE, RF, GLM, and XGB-were applied to screen feature genes and establish diagnostic models. Furthermore, the correlations between feature targets and immune cell infiltration were analyzed, single-gene GSEA was conducted, and molecular docking was performed to investigate the interactions between feature targets and bioactive constituents of ZB. For…
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