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

Abstract

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.

Keywords: bioinformatics analysis; biomarkers; ceRNA; diabetic neuropathy; mechanisms.

Figure 1

Research flow chart.

Figure 2

Differently expressed mRNAs in DN. (A) GSE30122. (B) GSE30529. Red and blue dots represent up- and downregulated genes, and gray dots represent no differential expression genes. (C) Coexpression of upregulated genes. (D) Coexpression of downregulated genes.

Figure 3

Enrichment analysis of the DEGs. (A) The top 10 enriched GO analysis results. (B) The top 20 KEGG pathways results. The size of the spots indicates the number of genes, and the color indicates the p-value.

Figure 4

PPI network analysis and gene cluster identification. (A) PPI network of DEGs. (B–E) Four modules extracted from the PPI network. The node represents the genes; the edge represents the relationship between them.

Figure 5

Screening of hub genes.

Figure 6

Differentially expressed miRNA in DN. (A) Red dots indicate upregulation, blue dots indicate downregulation, and gray dots indicate no differential expression. (B) Red represents upregulation, and blue represents downregulation.

Figure 7

The mRNA–miRNA network was constructed. (A) Screening of co-expressed miRNAs. (B) miRNA–mRNA regulatory network of hub genes. Green and red indicate mRNA and miRNA, respectively.

Figure 8

Differentially expressed lncRNA in DN. (A) Red dots represent upregulation, blue dots represent downregulation, and gray dots represent no differential expression. (B) Red represents upregulation, and blue represents downregulation.

Figure 9

The lncRNA–miRNA–mRNA ceRNA network in DN. The nodes colored in yellow, red, and green represent lncRNAs, miRNAs, and mRNAs, respectively.

Figure 10

Validation of hub genes. (A) ROC curve of the hub genes in GEO datasets. (B) The relative expression of hub genes was detected by RT-PCR. ^*p < 0.05, ^**p < 0.01.