Evidence map›Paper›PMID 40768057›Full record

ArticleClinical and experimental medicine2025

In-depth bioinformatics analysis uncovers the crosstalk genes and immune interactions among diagnostic markers linked to natural killer cells in patients with cirrhosis and sepsis.

Yue-Hua Wang, Xiao-Xiang Wang

Abstract read
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Article in Clinical and experimental medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Yue-Hua WangDepartment of Infectious Disease, Jinhua People's Hospital, Jinhua, 321000, China.
Xiao-Xiang WangDepartment of Neurology, Jinhua People's Hospital, NO.267 Danxi East Road, Jindong District, Jinhua City, Zhejiang Province, China. wxx13566782091@163.com.

Funding

Jinhua Science and Technology Bureau 2023-3-124
6 · The paper itself

Abstract

Patients with cirrhosis face an elevated risk of developing sepsis, leading to an escalating mortality rate. This study focuses on the link between natural killer (NK) cells, cirrhosis, and sepsis. Our goal is to identify NK cell-related genes that could serve as common diagnostic biomarkers for both conditions. The datasets pertaining to cirrhosis and sepsis were obtained from the Gene Expression Omnibus database. Initially, a single sample Gene set enrichment analysis (ssGSEA) concentrated on the NK cell gene set. Subsequently, the ssGSEA score was utilized as the phenotype data for the weighted gene co-expression network analysis (WGCNA). Feature genes for cirrhosis and sepsis were selected from a combination of cirrhosis differentially expressed genes (DEGs), sepsis DEGs, and key genes identified by WGCNA and screened using support vector machine-recursive feature elimination (SVM-RFE) and Random Forest machine learning algorithms. To rigorously validate the diagnostic significance of the feature genes, we performed receiver operating characteristic (ROC) curve and decision curve analysis (DCA) across both training and independent validation datasets. Additionally, CIBERSORT was employed to assess the infiltration of immune cells in cirrhosis and sepsis. qRT-PCR was further used to experimentally confirm the mRNA expression levels of candidate genes in peripheral blood samples. Finally, we conducted subtype identification of cirrhosis and sepsis based on the feature genes, and the infiltration of immune cells between subtypes was evaluated. Two genes associated with NK cells, MS4A4A and CD59, serve as biomarkers for diagnosing cirrhosis and sepsis. Additionally, the presence of MS4A4A and CD59 associated immune cells alongside naive B cells and dendritic cells (DCs) decrease, whereas M0 macrophages increases. Based on MS4A4A and CD59, cirrhosis and sepsis each comprise two distinct subtypes. This classification enables clear differentiation of immune cell infiltration patterns across the subtypes. The correlation between liver cirrhosis and sepsis is strongly associated with NK cells. Our multi-level bioinformatic and experimental validations demonstrate that MS4A4A and CD59 are robust diagnostic markers for both diseases, offering valuable insights into the shared immune mechanisms and interactions between cirrhosis and sepsis.

Indexed as

Computational BiologyKiller Cells, NaturalLiver CirrhosisSepsisBiomarkersDatabases, GeneticGene Expression ProfilingGene Regulatory NetworksHumansROC CurveBiomarkersCirrhosisDiagnostic markersImmune infiltrationNK cellsSepsis

Identifiers

PMID40768057
PMCPMC12328512

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.