Diabetic nephropathy (DN) has been pathophysiologically associated with macrophage activity; however, the molecular mechanisms underlying this relationship remain unclear. This study aimed to explore the regulatory mechanisms linking DN and macrophages using integrated bioinformatics and experimental validation. The DN datasets were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified by comparing DN samples with controls. Weighted gene co-expression network analysis (WGCNA) was performed to identify macrophage-related modular genes, which were intersected with DEGs to obtain differentially expressed macrophage-related genes (DE-MRGs). Key genes were screened using protein–protein interaction (PPI) analysis, least absolute shrinkage and selection operator (LASSO) regression, and support vector machine–recursive feature elimination (SVM-RFE). Single-cell RNA sequencing was applied to evaluate the expression of key genes at the single-cell level. Functional enrichment, immune infiltration, and drug correlation analyses were subsequently conducted. Finally, animal models were constructed to validate gene expression using RT-qPCR. Four pivotal genes—LUM, FBN1, COL15A1, and LOX—were identified as significantly associated with immune cell infiltration, particularly macrophages and myeloid dendritic cells. The transcription factor FOXC1 was predicted to regulate all four key genes simultaneously. RT-qPCR confirmed that LUM, FBN1, and COL15A1 expression levels were markedly elevated in DN rat models compared with controls, consistent with bioinformatics findings. This study identified four macrophage-related key genes (LUM, FBN1, COL15A1, and LOX) closely associated with the pathogenesis of diabetic nephropathy. These findings provide novel insights into the immunoregulatory mechanisms of DN and potential therapeutic targets for future research.
Wang et al. (Thu,) studied this question.