Identification of Hub Genes Associated with the Development of Acute Kidney Injury by Weighted Gene Co-Expression Network Analysis

Abstract

Background: Acute kidney injury (AKI) is a severe clinical syndrome, causing a profound medical and socioeconomic burden worldwide. This study aimed to explore underlying molecular targets related to the progression of AKI. Methods: A public database originated from the NCBI GEO database (serial number: GSE121190) and a well-established and unbiased method of weighted gene co-expression network analysis (WGCNA) to identify hub genes and potential pathways were used. Furthermore, the unbiased hub genes were validated in 2 classic models of AKI in a rodent model: chemically established AKI by cisplatin- and ischemia reperfusion-induced AKI. Results: A total of 17 modules were finally obtained by the unbiased method of WGCNA, where the genes in turquoise module displayed strong correlation with the development of AKI. In addition, the results of gene ontology revealed that the genes in turquoise module were involved in renal injury and renal fibrosis. Thus, the hub genes were further validated by experimental methods and primarily obtained Rplp1 and Lgals1 as key candidate genes related to the progression of AKI by the advantage of quantitative PCR, Western blotting, and in situ tissue fluorescence. Importantly, the expression of Rplp1 and Lgals1 at the protein level showed positive correlation with renal function, including serum Cr and BUN. Conclusions: By the advantage of unbiased bioinformatic method and consequent experimental verification, this study lays the foundation basis for the pathogenesis and therapeutic agent development of AKI.

Keywords

• weighted gene co-expression network analysis
• acute kidney injury
• rplp1
• lgals1