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Abstract: PO0383

Identification of Hub Genes and Pathways of Ischemia-Reperfusion Injury and AKI by a Bioinformatics Method

Session Information

Category: Acute Kidney Injury

  • 103 AKI: Mechanisms

Authors

  • You, Ruilian, Peking Union Medical College Hospital, Dongcheng-qu, Beijing, China
  • Heyang, Zhige, Peking Union Medical College Hospital, Dongcheng-qu, Beijing, China
  • Ma, Yixin, Peking Union Medical College Hospital, Dongcheng-qu, Beijing, China
  • Zheng, Hua, Peking Union Medical College Hospital, Dongcheng-qu, Beijing, China
  • Lin, Jianfeng, Peking Union Medical College Hospital, Dongcheng-qu, Beijing, China
  • Ji, Peili, Peking Union Medical College Hospital, Dongcheng-qu, Beijing, China
  • Chen, Limeng, Peking Union Medical College Hospital, Dongcheng-qu, Beijing, China
Background

Ischemia/reperfusion injury (IRI) is the most common cause of acute kidney injury (AKI). However, mechanisms underlying the rapid loss in kidney function and tissue injury are not fully elucidated. We aimed to explore the potential crucial genes and pathways involved in the pathogenesis of IRI/AKI by the bioinformatics method.

Methods

We extracted two gene expression profiles (GSE87024 and GSE34351) from the GEO database of wild-type mice and the early onset of the IRI-AKI. Differentially expressed genes (DEGs) were identified from the two expression profiles, enriched with its gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the DEGs. Then we applied Gene set enrichment analysis (GSEA) methods to detect the potential crucial gene sets, the string network to identify PPI, and Cytoscape with plug-ins to find the hub genes and modules. We also used the robust rank aggregation (RRA) to the combined DEGs of the two datasets and analyzed the target genes for miRNA/TF, drug-gene interaction networks to find the potential therapeutic targets.

Results

We extracted a total of 239 and 384 DEGs in GSE87024 and GSE34351 separately, with the 73 same DEGs. GO and KEGG enrichment analysis of the DEGs and GSEA revealed that the significant pathways involve MAPK signaling pathway, IL-17 signaling pathway, and TNF signaling pathway. RRA analysis detected a total of 27 common DEGs. We identified JUN, ATF3, FOS, EGR1, HMOX1, DDIT3, JUNB, NFKBIZ, PPP1R15A, CXCL1, ATF4, and HSPA1B as hub genes. A total of 23 miRNAs interacted with the target genes and interact with curcumin, staurosporine, and deferoxamine by the drug-gene interaction networks analysis.

Conclusion

Our study focused on the early IRI-AKI by firstly adopted RRA analysis to combine DEGs in different datasets, identified hub genes and pathways. We further detected the potential therapeutic targets of the IRI-AKI such as curcumin and staurosporine.