Amelioration of STZ-induced nephropathy in diabetic rats by saffron hydro alcoholic extract

Demethylzeylasteral reduces the level of proteinuria in diabetic nephropathy: Screening of network pharmacology and verification by animal experiment

This study aimed to use network pharmacology to detail the natural components isolated from Triptergium wilfordii Hook F (TwHF) and examine the effect of the main component (demethylzeylasteral, DEM) on rat models of diabetic nephropathy (DN). In this study, we used network pharmacology to detail the natural components isolated from TwHF, referenced a gene library when screening for components effective in the management of DN, and DEM was confirmed in DN rats. All data were analyzed using the Discovery Studio 4.5 System and the systems Dock online docking method platform. All 24 rats were divided into 4 groups: control, DN, TwHF, and DEM. Blood and urine samples were tested at 0, 8, and 12 weeks. Renal histopathological changes were scored. Network pharmacology indicated that 370 compounds and 46 small molecules (including DEM) were biologically active constituents of TwHF, mainly affecting the inflammatory response through PI3K-Akt and Jak-STAT pathways. Proteinuria in the TwHF and DEM groups was significantly lower than in the DN group (p ≤ .001), and the decrease in proteinuria in the DEM group was more obvious than in the TwHF group (p = .004). The tubular interstitial scores were better in the DEM group than in the TwHF and DN groups. These results indicate that DEM effectively reduced proteinuria and alleviated the tubular interstitial changes in rat models of DN, which may be provide a scientific foundation for the development of novel drugs for treatment of DN.

Integrated Bioinformatics and Clinical Correlation Analysis of Key Genes, Pathways, and Potential Therapeutic Agents Related to Diabetic Nephropathy

Background

Diabetic nephropathy (DN) is a common microvascular complication of diabetes and a major cause of end-stage renal disease, resulting in a substantial socioeconomic burden around the world. Some unknown biomarkers, mechanisms, and potential novel agents regarding DN are yet to be identified.

Methods

GSE30528 and GSE1009 were downloaded as training datasets to identify differentially expressed genes (DEGs) of DN. Common DEGs were selected for further analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of DEGs were performed to explore molecular mechanisms and pathways. Protein-protein interaction (PPI) network of DEGs was used to identify the top 10 hub genes of DN. Expression profiles of the hub genes were validated in GSE96804 and GSE47183 datasets. The clinical correlation analyses were conducted to confirm the association between key genes and clinical characteristics in the Nephroseq v5 database. The Drug Gene Interaction Database was used to predict potential targeted drugs.

Results

345 and 1228 DEGs were identified in GSE30528 and GSE1009, respectively; and 120 common DEGs were found. The biological process of DEGs was significantly enriched in kidney development. PI3K-Akt signaling pathway, focal adhesion, complement and coagulation cascades were significantly enriched KEGG pathways. The identified top10 hub genes were VEGFA, NPHS1, WT1, TJP1, CTGF, FYN, SYNPO, PODXL, TNNT2, and BMP2. VEGFA, NPHS1, WT1, CTGF, SYNPO, PODXL, and TNNT2 were significantly downregulated in DN. VEGFA, NPHS1, WT1, CTGF, SYNPO, and PODXL were positively correlated with glomerular filtration rate. The targeted drugs or molecular compounds were enalapril, sildenafil, and fenofibrate target for VEGFA; losartan target for NPHS1; halofuginone, deferoxamine, curcumin, and sirolimus target for WT1; and purpurogallin target for TNNT2.

Conclusions

VEGFA, NPHS1, WT1, CTGF, SYNPO, and PODXL are promising biomarkers for diagnosing and evaluating the progression of DN. The drug-gene interaction analyses provide a list of candidate drugs for the precise treatment of DN.