Integrated analysis of circRNA-miRNA-mRNA regulatory network identifies potential diagnostic biomarkers in diabetic foot ulcer

Abstract

Diabetic foot ulcer (DFU) is a common and serious complication of diabetes mellitus, which influences patients' quality of life. Recently, circRNA regulated the mRNA levels by functioning as miRNA sponge in various disease, including diabetes mellitus. Nevertheless, the circRNA-miRNA-mRNA regulatory network involved in DFU remains obscure. The aim of this study is to construct a competing endogenous RNA (ceRNA) network and screen biological indicators as diagnostic factors in DFU. All the differentially expressed circRNAs, miRNAs and mRNAs were derived from Gene Expression Omnibus database. Furthermore, circRNAs identified by cytoHubba analysis and miRNAs obtained by human miRNA-disease database were used to construct DFU-specific ceRNA network with intersection of mRNAs. Functional enrichment analysis displayed the function and pathway of dysregulated mRNAs. Hub genes with high diagnostic value were screened by ClusterONE, GO semantic similarity and receiver operating characteristic (ROC) curve. Here, the ceRNA network consisted of 8 circRNAs, 11 miRNAs and 91 mRNAs. Functional enrichment analysis demonstrated diabetic complications-related pathway including TGF-beta, FoxO and Wnt signaling pathway. GO semantic similarity and ROC curve analysis showed 6 hub genes with high diagnostic value (the area under the ROC curve ≥ 0.8) in patients with DFU, including BCL2, CCND1, IRAK4, SMAD4, SP1 and SUFU, which were identified as potential target genes for DFU diagnosis. In conclusion, the present study looked at a circRNA-miRNA-mRNA regulatory network with DFU and screened the potential function of mRNA, then identified novel diagnostic biomarkers and therapeutic targets for patients with DFU.

Keywords: Biomarkers; Diabetic foot ulcer; Diagnosis; ceRNA network.

Fig. 1

Volcano plots of differentially expressed circRNAs (A), miRNAs (B) and mRNAs (C) in GEO database. The red dots represent the upregulated genes with P-value < 0.05 and LogFC >1 as the threshold. The blue dots represent the downregulated genes with P-value < 0.05 and LogFC <1 as the cut-off criteria. The grey spots represent genes with no significant difference in expression. LogFC, Log2 (fold change); GEO, Gene Expression Omnibus.

Fig. 2

The DFU-specific circRNA-miRNA-mRNA ceRNA network. The competing endogenous RNA network were constructed based on ceRNA theory. Blue triangle indicates circRNAs; green hexagon indicates miRNAs; pink ellipse indicates mRNAs.

Fig. 3

Functional enrichment analysis of miRNAs and mRNAs in ceRNA network. A. DIANA mirPath analysis of 11 miRNAs in ceRNA network in patients with DFU. B. KEGG pathway enrichment analysis were performed using 91 differential target genes that were negatively associated with 11 miRNAs in ceRNA network. C. Gene Ontology (GO) analysis of differential expressed mRNAs in ceRNA network.

Fig. 4

Construction of protein‐protein interaction (PPI) network and ceRNA subnetworks. A. The PPI network was constructed for 80/91 differentially expressed mRNAs in ceRNA network. B. The modules were screened from the PPI network using “ClusterONE” algorithm containing 11 modules. Red dots represent upregulated mRNAs; blue dots represent downregulated mRNAs; grey dots represent mRNAs with no significant difference in expression. C. Interaction network of 16 hub genes. D. Sankey diagram for the circRNA-miRNA-hub gene subnetwork in diabetic foot ulcers, which was constructed using intersection between the top genes in the PPI network and potential genes that were associated with diabetic complication-related signaling pathways. Each rectangle indicates a gene. The size of the rectangle indicates the connection degree of each gene.

Fig. 5

Receiver operating characteristics (ROC) curve and GO semantic similarity analysis. A. ROC curve were performed in training (GSE80178) and test (GSE132187) dataset for hub genes with diagnostic values in DFU including BCL2, CCND1, IRAK4, SMAD4, SP1 and SUFU. B. Distributions of functional similarities between hub genes. The functional similarities were calculated using GO semantic similarity. C. KEGG enrichment analysis of hub genes with high diagnostic values in circRNA-miRNA-hub gene subnetwork.