Identifying Mitochondria-Related Candidate Biomarkers of Ligustri Lucidi Fructus in Diabetic Nephropathy

Mitochondrial dysfunction and excessive oxidative stress within mitochondria are key pathological factors driving renal tubular injury in diabetic nephropathy (DN). Although Ligustri Lucidi Fructus (LLF) is traditionally used to treat DN, the mechanisms involved, particularly those relating to mitochondria-associated genes and pathways, remain poorly understood. This study used differential expression analysis of the GSE142025 dataset to identify differentially expressed genes (DEGs) related to DN. Feature genes were selected by cross-referencing the outputs of four machine learning models. Genes that showed significant differential expression and consistent expression patterns in both datasets were further evaluated by receiver operating characteristic (ROC) curve analysis. Those with an area under the curve (AUC) > 0.7 in both datasets were defined as candidate biomarkers. Functional enrichment, immune infiltration, network construction, and molecular docking analyses were performed. A DN mouse model was used to assess blood glucose, urinary microalbumin, histopathology, and RT-qPCR expression of the candidate biomarkers. CAT and MAOA were significantly upregulated in vivo. Candidate biomarkers were enriched in pathways related to ribosome function, valine, leucine, and isoleucine degradation, cytokine-cytokine receptor interactions, and peroxisomes. They were negatively correlated with CD8+ T cells and activated mast cells and positively correlated with activated NK cells and naïve B cells. Taxifolin, beta-sitosterol, and eriodictyol showed binding energies below -5 kcal/mol with the candidate biomarkers. CAT and MAOA are promising candidates that warrant further mechanistic investigation.