Evidence map›Paper›PMID 39348809›Full record

ArticleInternational archives of allergy and immunology2025

Identification of Immune-Related Genes as Potential Biomarkers in Early Septic Shock.

Beibei Liu, Yonghua Fan, Xianjing Zhang, Huaqing Li, Fei Gao, Wenli Shang, Juntao Hu, Zhanhong Tang

Abstract read
In one paragraph

Article in International archives of allergy and immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Beibei LiuDepartment of Intensive Care Unit, The Second Affiliated Hospital of Shandong First Medical University, Taian, China.
Yonghua FanDepartment of Emergency Intensive Care Unit, The Second Affiliated Hospital of Shandong First Medical University, Taian, China.
Xianjing ZhangDepartment of Emergency Intensive Care Unit, The Second Affiliated Hospital of Shandong First Medical University, Taian, China.
Huaqing LiDepartment of Intensive Care Unit, The Second Affiliated Hospital of Shandong First Medical University, Taian, China.
Fei GaoDepartment of Intensive Care Unit, The Second Affiliated Hospital of Shandong First Medical University, Taian, China.
Wenli ShangDepartment of Intensive Care Unit, The Second Affiliated Hospital of Shandong First Medical University, Taian, China.
Juntao HuDepartment of Intensive Care Unit, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Zhanhong TangDepartment of Intensive Care Unit, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSeptic shock, a severe manifestation of infection-induced systemic immune response, poses a critical threat resulting in life-threatening multi-organ failure. Early diagnosis and intervention are imperative due to the potential for irreversible organ damage. However, specific and sensitive detection tools for the diagnosis of septic shock are still lacking.

methodsGene expression files of early septic shock were obtained from the Gene Expression Omnibus (GEO) database. CIBERSORT analysis was used to evaluate immune cell infiltration. Genes related to immunity and disease progression were identified using weighted gene co-expression network analysis (WGCNA), followed by enrichment analysis. CytoHubba was then employed to identify hub genes, and their relationships with immune cells were explored through correlation analysis. Blood samples from healthy controls and patients with early septic shock were collected to validate the expression of hub genes, and an external dataset was used to validate their diagnostic efficacy.

resultsTwelve immune cells showed significant infiltration differences in early septic shock compared to control, such as neutrophils, M0 macrophages, and natural killer cells. The identified immune and disease-related genes were mainly enriched in immune, cell signaling, and metabolism pathways. In addition, six hub genes were identified (PECAM1, F11R, ITGAL, ICAM3, HK3, and MCEMP1), all significantly associated with M0 macrophages and exhibiting an area under curve of over 0.7. These genes exhibited abnormal expression in patients with early septic shock. External datasets and real-time qPCR validation supported the robustness of these findings.

conclusionSix immune-related hub genes may be potential biomarkers for early septic shock.

introductionSeptic shock, a severe manifestation of infection-induced systemic immune response, poses a critical threat resulting in life-threatening multi-organ failure. Early diagnosis and intervention are imperative due to the potential for irreversible organ damage. However, specific and sensitive detection tools for the diagnosis of septic shock are still lacking.

methodsGene expression files of early septic shock were obtained from the Gene Expression Omnibus (GEO) database. CIBERSORT analysis was used to evaluate immune cell infiltration. Genes related to immunity and disease progression were identified using weighted gene co-expression network analysis (WGCNA), followed by enrichment analysis. CytoHubba was then employed to identify hub genes, and their relationships with immune cells were explored through correlation analysis. Blood samples from healthy controls and patients with early septic shock were collected to validate the expression of hub genes, and an external dataset was used to validate their diagnostic efficacy.

resultsTwelve immune cells showed significant infiltration differences in early septic shock compared to control, such as neutrophils, M0 macrophages, and natural killer cells. The identified immune and disease-related genes were mainly enriched in immune, cell signaling, and metabolism pathways. In addition, six hub genes were identified (PECAM1, F11R, ITGAL, ICAM3, HK3, and MCEMP1), all significantly associated with M0 macrophages and exhibiting an area under curve of over 0.7. These genes exhibited abnormal expression in patients with early septic shock. External datasets and real-time qPCR validation supported the robustness of these findings.

conclusionSix immune-related hub genes may be potential biomarkers for early septic shock.

Indexed as

BiomarkersShock, SepticDisease ProgressionHumansKiller Cells, NaturalMacrophagesNeutrophilsTranscriptomeBiomarkersBiomarkersImmune infiltrationSeptic shockWeighted gene co-expression network analysis

Identifiers

PMID39348809
PMCPMC11887992

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.