Preliminary screening of new biomarkers for sepsis using bioinformatics and experimental validation.

BACKGROUND

The morbidity and mortality of sepsis remain high, and so far specific diagnostic and therapeutic means are lacking.

OBJECTIVE

To screen novel biomarkers for sepsis.

METHODS

Raw sepsis data were downloaded from the Chinese National Genebank (CNGBdb) and screened for differentially expressed RNAs. Key genes with predictive value were identified through weighted correlation network analysis (WGCNA) and meta-analysis and survival analysis using multiple public databases. Core genes were analyzed for functional enrichment using Gene Set Enrichment Analysis(GSEA). The core genes were localized using single-cell sequencing. qPCR was used to validate the core genes.

RESULTS

Differential analysis yielded a total of 5125 mRNA. WGCNA identified 5 modules and screened 3 core genes (S100A11, QPCT, and IFITM2). The prognosis of sepsis patients was strongly linked to S100A11, QPCT, and IFITM2 based on meta-analysis and survival analysis(P < 0.05).GSEA analysis showed that S100A11, QPCT, and IFITM2 were significantly enriched in ribosome-related pathways. S100A11 and QPCT were widely distributed in all immune cells, and QPCT was mainly localized in the macrophage cell lineage. In the sepsis group, the qPCR results showed that S100A11, QPCT, and IFITM2 expression levels were significantly higher in the sepsis group(P < 0.05).

CONCLUSION

In this study, S100A11, QPCT, and IFITM2 were screened as new potential biomarkers for sepsis. Validated by bioinformatics analysis and qPCR, these genes are closely associated with the prognosis of sepsis patients and have potential as diagnostic and therapeutic targets.