Background: Sepsis is a complex clinical syndrome caused by a dysregulated host immune response to infection. This study aimed to identify a competing endogenous RNA (ceRNA) network that can greatly contribute to understanding the pathophysiological process of sepsis and determining sepsis biomarkers. Methods: The GSE100159, GSE65682, GSE167363, and GSE94717 datasets were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene coexpression network analysis was performed to find modules possibly involved in sepsis. A long noncoding RNA-microRNA-messenger RNA (lncRNA-miRNA-mRNA) network was constructed based on the findings. Single-cell analysis was performed. Human umbilical vein endothelial cells were treated with lipopolysaccharide (LPS) to create an in vitro model of sepsis for network verification. Reverse transcription-polymerase chain reaction, fluorescence in situ hybridization, and luciferase reporter genes were used to verify the bioinformatic analysis. Result: By integrating data from three GEO datasets, we successfully constructed a ceRNA network containing 18 lncRNAs, 7 miRNAs, and 94 mRNAs based on the ceRNA hypothesis. The lncRNA ZFAS1 was found to be highly expressed in LPS-stimulated endothelial cells and may thus play a role in endothelial cell injury. Univariate and multivariate Cox analyses showed that only SLC26A6 was an independent predictor of prognosis in sepsis. Overall, our findings indicated that the ZFAS1/hsa-miR-449c-5p/SLC26A6 ceRNA regulatory axis may play a role in the progression of sepsis. Conclusion: The sepsis ceRNA network, especially the ZFAS1/hsa-miR-449c-5p/SLC26A6 regulatory axis, is expected to reveal potential biomarkers and therapeutic targets for sepsis management.
Keywords: bioinformatics; ceRNA; lncRNA; sepsis.