Abstract
Diabetic nephropathy (DN), a common diabetes-related complication, is the leading cause of progressive chronic kidney disease (CKD) and end‑stage renal disease. Despite the rapid development in the treatment of DN, currently available therapies used in early DN cannot prevent progressive CKD. The exact pathogenic mechanisms and the molecular events underlying DN development remain unclear. Ginsenoside Rg3 is a herbal medicine with numerous pharmacological effects. To gain a greater understanding of the molecular mechanism and signaling pathway underlying the effect of ginsenoside Rg3 in DN therapy, an RNA sequencing approach was performed to screen differential gene expression in a rat model of DN treated with ginsenoside Rg3. A combined bioinformatics analysis was then conducted to obtain insights into the underlying molecular mechanisms of the disease development, in order to identify potential novel targets for the treatment of DN. Six Sprague‑Dawley male rats were randomly divided into 3 groups: Normal control group, DN group and ginsenoside‑Rg3 treatment group, with two rats in each group. RNA sequencing was adopted for transcriptome profiling of cells from the renal cortex of DN rat model. Differentially expressed genes were screened out. Cluster analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to analyze the differentially expressed genes. In total, 78 differentially expressed genes in the DN control group were identified when compared with the normal control group, of which 52 genes were upregulated and 26 genes were downregulated. Differential expression of 43 genes was observed in the ginsenoside‑Rg3 treatment group when compared with the DN control group, consisting of 10 upregulated genes and 33 downregulated genes. Notably, 21 that were downregulated in the DN control group compared with the control were then shown to be upregulated in the ginsenoside‑Rg3 treatment group compared with the DN control group. In addition, 7 upregulated genes in the DN control group compared with the control were then shown to be downregulated in the ginsenoside‑Rg3 treatment group compared with the DN control group. Cluster analysis based on differentially expressed genes indicated that the transcriptomes are quite different among the samples. Distinct GO terms associated with these groups of genes were shown to be enriched. KEGG pathway analysis demonstrated that differentially expressed genes were predominantly involved in the fatty acid metabolism pathway and peroxisome proliferator‑activated receptor (PPAR) signaling pathway. To the best of our knowledge, this study was the first to present whole genome expression profiling in DN with ginsenoside‑Rg3 treatment by RNA‑Seq. A set of differentially expressed genes and pathways were identified. These data provided an insight into understanding the molecular mechanisms underlying the effect of ginsenoside‑Rg3 treatment of DN.
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