[Construction of sepsis-associated competing endogenous RNA network based on Gene Expression Omnibus datasets and bioinformatic analysis].

OBJECTIVE

To analyze the sepsis related long non-coding RNA (lncRNA) and mRNA expression profiles based on Gene Expression Omnibus (GEO) datasets and bioinformatic analysis, and to analyze the sepsis-associated competing endogenous RNA (ceRNA) network based on microRNA (miRNA) database.

METHODS

The sepsis-related lncRNA dataset was downloaded from the GEO database, and the differential expression analysis was conducted by Bioconductor on the sepsis dataset to obtain differentially expressed lncRNA (DElncRNA) and differentially expressed mRNA (DEmRNA), and cluster heat map was drawn. miRNA combined with DElncRNA were predicted by miRcode. mRNA targeted by miRNA was simultaneously met by three databases: TargetScan, miRDB, and mirTarBase. The interaction relationship of lncRNA-miRNA-mRNA was obtained. The regulatory network visualization software CytoScape was used to draw ceRNA networks. DEmRNA in the ceRNA networks were imported into the Search Tool for the Retrieval of Interacting Genes Database (STRING) online database to draw the protein-protein interaction (PPI) map. The gene ontology (GO) function annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEmRNA were performed.

RESULTS

Dataset GSE89376 and GSE145227 were found from GEO database. Difference analysis showed there were 14 DElncRNA and 359 DEmRNA in the elderly group of GSE89376; 8 DElncRNA and 153 DEmRNA in the adult group of GSE89376; 1 232 DElncRNA and 1 224 DEmRNA in the children group of GSE145227. Clustering heatmap showed that there were significant differences in the expression of lncRNA and mRNA between the sepsis group and the control group. The ceRNA networks were constructed with miRNA. Several DElncRNA and multiple DEmRNA participated in the ceRNA network of sepsis. The PPI diagram demonstrated that several genes encoding proteins interacted with each other and form a multi-node interaction network with multiple genes encoding proteins. Functional annotation and enrichment analysis demonstrated that there might be a crosstalk mechanism on functionally related genes such as nuclear receptor activity, ligand-activated transcription factor activity, and steroid hormone receptor activity, and played a role in the occurrence and development of diseases through forkhead box transcription factor O (FoxO) signaling pathway, Janus kinase/signal transducers and activators of transcription (JAK/STAT) signaling pathway, p53 signaling pathway, and phosphateidylinositol 3-kinase (PI3K)/Akt signaling pathway.

CONCLUSIONS

Through sepsis-related lncRNA-miRNA-mRNA ceRNA network and combining with KEGG pathway analysis, there were several lncRNA and mRNA participating in the ceRNA network related sepsis, which played an important role in several signal pathways.