Identification of Potential Biomarkers in Neonatal Sepsis by Establishing a Competitive Endogenous RNA Network.

Abstract

Neonatal sepsis is a serious and difficult-to-diagnose systemic infectious disease occurring during the neonatal period. This study aimed to identify potential biomarkers of neonatal sepsis and explore its underlying mechanisms. We downloaded the neonatal sepsis-related gene profile GSE25504 from the NCBI Gene Expression Omnibus (GEO) database. The differentially expressed RNAs (DERs) were screened and identified using LIMMA. Then, the functions of the DERs were evaluated using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Finally, a competing endogenous RNA (ceRNA) network was constructed and functional analyses were performed. The initial screening identified 444 differentially expressed (DE)-mRNAs and 45 DElncRNAs. GO analysis showed that these DE-mRNAs were involved in immune response, defense response, and positive regulation of immune system process. KEGG analysis showed that these DE-mRNAs were enriched in 30 activated pathways and 6 suppressed pathways, and those with the highest scores were the IL-17 signaling pathway and ribosome. Next, 722 miRNAs associated with the identified lncRNAs were predicted using miRWalk. A ceRNA network was constructed that included 6 lncRNAs, 11 mRNAs, and 55 miRNAs. In this network, HCP5, LINC00638, XIST and TP53TG1 were hub nodes. Functional analysis of this network identified some essential immune functions, hematopoietic functions, osteoclast differentiation, and primary immunodeficiency as associated with neonatal sepsis. HCP5, LINC00638, TP53TG1, ST20-AS1, and SERPINB9P1 may be potential biomarkers of neonatal sepsis and may be useful for rapid diagnosis; the biological process of the immune response was related to neonatal sepsis.