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

Abstract

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.

Fig 1. Flowchart of this study.

Exploration of new biomarkers for sepsis using bioinformatics and qPCR experimental validation methods. NC, normal control; WGCNA, Weighted Gene Co-Expression Network Analysis; GSEA, Gene Set Enrichment Analysis; scRNA-Seq, Single-Cell RNA Sequencing.

Fig 2. Displays the analysis of RNAs with varying expression levels.

A: PCA plot demonstrates distinct clustering between the NC and SEPSIS categories, with no samples that deviate from the expected pattern. B: The volcano plot displays RNAs that are up-regulated in red and down-regulated in blue.

Fig 3. WGCNA as well as the co-expression network.

A: Module topology fit gradually increases with increasing soft threshold. B: Average connectivity gradually decreases with increasing soft threshold. C: Modules based on overlapping co-expression topologies of different colored mRNAs (module size > 50). The blue module is significantly associated with the clinical features of sepsis. D: There are 30 genes in this network, with S100A11, QPCT, and IFITM2 located in the center of the network.

Fig 4. Displays the prognostic analysis and expression of important genes, with survival time in days on the horizontal axis and survival rate on the vertical axis.

A–C: Low mRNA samples are indicated by the green line, while high mRNA samples are represented by the red line, both with p-values below 0.005. D–F: S100A11, QPCT, and IFITM2 were highly expressed in the sepsis group.

Fig 5. Meta-analysis results.

A meta-analysis was conducted comparing the levels of S100A11, IFITM2, and QPTC expression between the sepsis survivors and non-survivors using the GSE54514, GSE95233, and GSE63042 datasets. The I² value is 44% for the S100A11 and 15% and 0% for the QPCT and IFITM2, respectively.

Fig 6. Results of GSEA enrichment analysis.

A-F: The spikes in the enrichment score (ES) curves reveal a tendency for these gene sets to concentrate in the sequenced gene list, suggesting their potential activity in the study state. The results of the GSEA enrichment analysis indicate that S100A11, QPCT, and IFITM2 are closely related to ribosome function.

Fig 7. The localization of important genes in cell lineage is depicted.

A: Macrophages are found in Groups 3 and 5, natural killer cells in Group 4, T cells in Groups 1, 2, 6, and 8, B cells in Group 7, and platelets in Group 9. B-E: The distribution of S100A11 and IFITM2 is widespread among all immune cells, while QPCT is mainly found in macrophages. F: Each bubble in the figure represents the average gene expression in a specific cell population, with the size of the bubble indicating the percentage of cells expressing the gene in that population.

Fig 8. Results of qPCR experiments. qPCR detects the expression of three core genes in the sepsis cell model.

The blue color indicates the control group and the red color indicates sepsis. *p < 0.05; **p < 0.01.