Identification of biomarkers of renal ischemia-reperfusion injury by bioinformatics analysis and single-cell sequencing analysis combined with in vivo validation

Abstract

Background: Renal ischemia-reperfusion injury (IRI) is a serious clinical complication of kidney injury. This research dealt with investigating the hub genes and pathways associated with renal IRI.

Methods: The transcriptome expression dataset of mouse renal ischemia samples (GSE39548) was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were filtered by R software for key genes utilized for gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and gene enrichment analysis (GSEA). The gene co-expression network was developed by WGCNA analysis to screen important modules. Hub genes from the intersection of DEGs and WGCNA were subjected to protein-protein interaction (PPI) network. The biomarkers obtained by SVM-REF and LASSO algorithm were validated by other datasets and subjected to GSEA analysis. The expression of biomarkers in renal IRI was detected by qRT-PCR and subjected to single-cell analysis.

Results: A total of 157 DEGs were discovered. Biological function analysis depicted that the DEGs were primarily involved in cytokine-cytokine receptor interaction, as well as the signaling pathways IL-17, MAPK, and TNF. The intersection of DEGs and the genes obtained by WGCNA analysis yielded 149 hubs genes. Based on SVM-REF and LASSO algorithm, cyp1a1 and pdk4 were determined as potential biomarkers in individuals with renal ischemia and showed good diagnostic value. qRT-PCR results depicted that cyp1a1 and pdk4 were significantly up-regulated in renal ischemia mice (P < 0.05). Finally, the single-cell analysis identified the expression of Cyp1a1 and Pdk4 in mice kidney tissue.

Conclusion: cyp1a1 and pdk4 were identified to play important roles in renal IRI. This research provides a new perspective and basis for studying the pathogenesis of renal IRI and developing new treatments.

Keywords: Ischemia-reperfusion injury; Renal; Single-cell sequencing analysis.