Identifying of miRNA–mRNA Regulatory Networks Associated with Acute Kidney Injury by Weighted Gene Co-Expression Network Analysis

BACKGROUND: Acute kidney injury (AKI) is a clinical emergency characterized by a dramatic decline in renal function and the accumulation of metabolic waste products in the body, with a high morbidity and mortality rate. The pathogenesis of AKI remains unclear and there are no effective treatment options. METHODS: We aimed to identify critical genes involved in the pathogenesis of AKI and construct a miRNA–mRNA regulatory network using gene expression data downloaded from Gene Expression Omnibus (GSE85957) for 38 kidneys of AKI and 19 control rats and cisplatin treated kidneys of 3 AKI and 3 control rats. Data in GSE85957 were processed using weighted gene co-expression network analysis (WGCNA), and biological function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to analyze the functions associated with critical genes. RESULTS: Twenty-eight modules in the GSE85957 dataset were identified by WGCNA, of which 103 genes in the orange module and 30 genes in the black module were closely associated with AKI and dose. Biological function analysis of genes in the orange and black modules revealed that skeletal muscle cell differentiation, tissue development and organ development were involved in the pathological changes of AKI. Combining with our experimentally processed AKI rat kidney data, eight genes (Atf3, Egr1, Egr2, Fos, Fosb, Gdf15, Serpine1 and Nr1d1) were identified as potential biomarkers of AKI, and miRNA–mRNA regulatory networks were constructed based on the above eight critical genes. Further tissue validation revealed that Egr1 and Fos were highly expressed in AKI. CONCLUSION: Our study identified potential biomarkers of AKI and constructed an associated miRNA–mRNA regulatory network, which may provide new insights into the molecular pathogenesis of AKI.