Evidence map›Paper›PMID 39854580›Full record

ArticlePloS one2025

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

Hao Wang, Wei Xiong, Wu Zhong, Yingchun Hu

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Hao WangClinical Medical College, Southwest Medical University, Luzhou, People's Republic of China.
Wei XiongDepartment of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, People's Republic of China.
Wu ZhongDepartment of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, People's Republic of China.
Yingchun HuDepartment of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, People's Republic of China.ORCID 0000-0002-5465-4638

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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

objectiveTo screen novel biomarkers for sepsis.

methodsRaw 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.

resultsDifferential 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).

conclusionIn 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.

Indexed as

BiomarkersComputational BiologySepsisGene Expression ProfilingHumansPrognosisS100 ProteinsBiomarkersS100 Proteins

Identifiers

PMID39854580
PMCPMC11759385

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