Identification and Verification of Potential Biomarkers in Renal Ischemia-Reperfusion Injury by Integrated Bioinformatic Analysis

Abstract

Background. Renal ischemia-reperfusion injury (RIRI) plays an important role in the poor prognosis of patients with renal transplants. However, the potential targets and mechanism of IRI are still unclear. Method. Differential gene expression (DEG) analysis and weighted correlation network analysis (WGCNA) were performed on the GSE27274 dataset. Pathway enrichment analysis on the DEGs was performed. To identify the hub DEGs, we constructed a protein-protein interaction (PPI) network. Finally, the hub genes were verified, and candidate drugs were screened from the DsigDB database. Results. A hundred DEGs and four hub genes (Atf3, Psmb6, Psmb8, and Psmb10) were screened out. Pathway enrichment analysis revealed that 100 DEGs were mainly enriched in apoptosis and the TNF signaling pathway. The four hub genes were verified in animal models and another dataset (GSE148420). Thereafter, a PPI network was used to identify the four hub genes (Atf3, Psmb6, Psmb8, and Psmb10). Finally, eight candidate drugs were identified as potential drugs. Conclusion. Three hub genes (Psmb6, Psmb8, and Psmb10) were associated with RIRI and could be potential novel biomarkers for RIRI.