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

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. 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. 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. 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.

Chen S ，Chen L ，Jiang H 《-》

Screening and Identification of Differentially Expressed Genes Between Diabetic Nephropathy Glomerular and Normal Glomerular via Bioinformatics Technology.

Diabetes is a chronic metabolic disease characterized by disorders of glucose and lipid metabolism. Its most serious microvascular complication is diabetic nephropathy (DN), which is characterized by varying degrees of proteinuria and progressive glomerulosclerosis, eventually progressing to end-stage renal failure. The aim of this research is to identify hub genes that might serve as genetic markers to enhance the diagnosis, treatment, and prognosis of DN. The procedures of the study include access to public data, identification of differentially expressed genes (DEGs) by GEO2R, and functional annotation of DEGs using enrichment analysis. Subsequently, the construction of the protein-protein interaction (PPI) network and identification of significant modules were performed. Finally, the hub genes were identified and analyzed, including clustering analysis, Pearson's correlation coefficient analysis, and multivariable linear regression analysis. Between the GSE30122 and GSE1009 datasets, a total of 142 DEGs were identified, which were mainly enriched in cell migration, platelet activation, glomerulus development, glomerular basement membrane development, focal adhesion, regulation of actin cytoskeleton, and the PI3K-AKT signaling pathway. The PPI network was composed of 205 edges and 142 nodes. A total of 10 hub genes (VEGFA, NPHS1, WT1, PODXL, TJP1, FYN, SULF1, ITGA3, COL4A3, and FGF1) were identified from the PPI network. The DEGs between DN and control glomeruli samples may be involved in the occurrence and development of DN. It was speculated that hub genes might be important inhibitory genes in the pathogenesis of diabetic nephropathy, therefore, they are expected to become the new gene targets for the treatment of DN.

Du J ，Yang J ，Meng L 《-》

Investigation of the Mechanism of Complement System in Diabetic Nephropathy via Bioinformatics Analysis.

Diabetic nephropathy (DN) is a major cause of end-stage renal disease (ESRD) throughout the world, and the identification of novel biomarkers via bioinformatics analysis could provide research foundation for future experimental verification and large-group cohort in DN models and patients. GSE30528, GSE47183, and GSE104948 were downloaded from Gene Expression Omnibus (GEO) database to find differentially expressed genes (DEGs). The difference of gene expression between normal renal tissues and DN renal tissues was firstly screened by GEO2R. Then, the protein-protein interactions (PPIs) of DEGs were performed by STRING database, the result was integrated and visualized via applying Cytoscape software, and the hub genes in this PPI network were selected by MCODE and topological analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out to determine the molecular mechanisms of DEGs involved in the progression of DN. Finally, the Nephroseq v5 online platform was used to explore the correlation between hub genes and clinical features of DN. There were 64 DEGs, and 32 hub genes were identified, enriched pathways of hub genes involved in several functions and expression pathways, such as complement binding, extracellular matrix structural constituent, complement cascade related pathways, and ECM proteoglycans. The correlation analysis and subgroup analysis of 7 complement cascade-related hub genes and the clinical characteristics of DN showed that C1QA, C1QB, C3, CFB, ITGB2, VSIG4, and CLU may participate in the development of DN. We confirmed that the complement cascade-related hub genes may be the novel biomarkers for DN early diagnosis and targeted treatment.

Xu B ，Wang L ，Zhan H ，Zhao L ，Wang Y ，Shen M ，Xu K ，Li L ，Luo X ，Zhou S ，Tang A ，Liu G ，Song L ，Li Y ... -  《-》

Seven basement membrane-specific expressed genes are considered potential biomarkers for the diagnosis and treatment of diabetic nephropathy.

Diabetic nephropathy (DN) is a diabetes-related chronic vasculitis. DN diminishes kidney function over time and, of course, leads to end stage renal disease in people (ESRD). In spite of the advances in diagnostic and treatment methods for DN, DN continues to impose a significant physical and psychological burden on patients, severely impacting their quality of life, making the hunt for novel therapeutic targets necessary. The Gene Expression Omnibus (GEO) microarray datasets GSE1009, GSE30122, GSE142153, and GSE96804 were downloaded to identify differentially expressed genes (DEGs) in kidney tissues from patients in the DN group and normal controls. These three datasets were examined for genes associated with basement membranes (BMs) with differential gene expression. The target genes were then subjected to gene ontology (GO) annotation and Kyoto Gene and Genome Encyclopedia (KEGG) pathway enrichment analysis. BM-related genes underwent PPI network analysis and screening of the top 10 hub genes, along with immune infiltration analysis and column line graph model development. Finally, we conducted DN therapeutic medication prediction and the creation of something like a miRNA network for genetic markers with BMs. Seven candidate BM-related genes (COL4A1, COL4A2, COL6A2, COL6A3, FN1, ITGQ4, and LAMB1) with acceptable helps the healthcare were discovered. Enrichment analysis of diabetes-related genes event occurred the role of biological processes including extracellular matrix organization, extracellular structural organization, and collagen-containing extracellular matrix, as well as the PI3K-Akt signaling pathway and the AGE-RAGE signaling pathway, in diabetic complications. These genes may also be associated in immune cells and autoimmune activities, such as Macrophages and MHC class I, in order to impact the immune process in DN. In the meanwhile, based on these seven BM-related genes, we discovered that Ginsenoside Rh1 was very significant for drug targeting. This research identified seven BM-related genes as possible diagnostic and therapeutic biomarkers for DN. Analysis of inflammatory infiltration indicated that these genes may be important in inflammatory processes through Macrophages and MHC class I, hence impacting the course and development of DN illness. The development of a correlated column line graph model for it also shown excellent predictive capabilities. In addition, we have found pharmaceuticals, such as Ginsenoside Rh1, that may provide fresh insights into the personalized management of patients with DN.

Gui H ，Chen X ，Ye L ，Ma H ... -  《-》

Bioinformatics Analysis of the Mechanisms of Diabetic Nephropathy via Novel Biomarkers and Competing Endogenous RNA Network.

Diabetic nephropathy (DN) is one of the common chronic complications of diabetes with unclear molecular mechanisms, which is associated with end-stage renal disease (ESRD) and chronic kidney disease (CKD). Our study intended to construct a competing endogenous RNA (ceRNA) network via bioinformatics analysis to determine the potential molecular mechanisms of DN pathogenesis. The microarray datasets (GSE30122 and GSE30529) were downloaded from the Gene Expression Omnibus database to find differentially expressed genes (DEGs). GSE51674 and GSE155188 datasets were used to identified the differentially expressed microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), respectively. The DEGs between normal and DN renal tissues were performed using the Linear Models for Microarray (limma) package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to reveal the mechanisms of DEGs in the progression of DN. The protein-protein interactions (PPI) of DEGs were carried out by STRING database. The lncRNA-miRNA-messenger RNA (mRNA) ceRNA network was constructed and visualized via Cytoscape on the basis of the interaction generated through the miRDB and TargetScan databases. A total of 94 significantly upregulated and 14 downregulated mRNAs, 31 upregulated and 121 downregulated miRNAs, and nine upregulated and 81 downregulated lncRNAs were identified. GO and KEGG pathways enriched in several functions and expression pathways, such as inflammatory response, immune response, identical protein binding, nuclear factor kappa b (NF-κB) signaling pathway, and PI3K-Akt signaling pathway. Based on the analysis of the ceRNA network, five differentially expressed lncRNAs (DElncRNAs) (SNHG6, KCNMB2-AS1, LINC00520, DANCR, and PCAT6), five DEmiRNAs (miR-130b-5p, miR-326, miR-374a-3p, miR-577, and miR-944), and five DEmRNAs (PTPRC, CD53, IRF8, IL10RA, and LAPTM5) were demonstrated to be related to the pathogenesis of DN. The hub genes were validated by using receiver operating characteristic curve (ROC) and real-time PCR (RT-PCR). Our research identified hub genes related to the potential mechanism of DN and provided new lncRNA-miRNA-mRNA ceRNA network that contributed to diagnostic and potential therapeutic targets for DN.

Guo M ，Dai Y ，Jiang L ，Gao J ... -  《Frontiers in Endocrinology》