This study aimed to investigate the potential mechanisms underlying the therapeutic effects of Fructus Ligustri Lucidi in the treatment of diabetic nephropathy (DN) through bioinformatics analysis. The research commenced with a comprehensive database search for DN-associated datasets and gene targets of Fructus Ligustri Lucidi. Subsequently, the ssGSEA method was employed to score the drug target gene sets, and based on these scores, subjects were categorized. Further analysis involved differential analysis and enrichment analysis techniques to elucidate differentially expressed genes (DEGs) and associated pathways between the two groups. Based on the ssGSEA scoring results, the data were stratified into two groups: the "High NZZ group" and the "Low NZZ group". Through differential analysis, a total of 18 DEGs were identified, comprising 14 upregulated genes (EGR1, CCL2, CDH6, VCAN-AS1, VCAN, C3, MMP7, RNASE6, C1QC, MOXD1, APOC1, SFRP2, CCL21, and LUM) and four downregulated genes (OTTHUMG00000152025, RERG, B3GALT2, and NELL1). Notably, several genes exhibited concurrent expression patterns in both the DN and High NZZ groups, including VCAN-AS1, CCL21, VCAN, MOXD1, CCL2, SFRP2, MMP7, C3, RNASE6, LUM, C1QC, APOC1, and CDH6. Enrichment analysis revealed significant enrichment in pathways related to "regulation of apoptotic cell clearance" and "granulocyte chemotaxis", among others. These findings highlighted the potential value of Fructus Ligustri Lucidi in the treatment of DN and unveiled novel potential targets for prognosis and therapy in DN patients. This study offered promising avenues for enhancing both the prognosis and treatment outcomes for individuals affected by this condition.
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