Evidence map›Paper›PMID 40091022›Full record

ArticleBMC medical genomics2025

Bioinformatics identification and validation of pyroptosis-related gene for ischemic stroke.

Xinying Shang, Rui Wei, Di Yang, Bawei Yu, Wei Zhang

Abstract read
In one paragraph

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

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Xinying Shang *Department of Emergency Medicine, The First Affiliated Hospital of Kunming Medical University, No. 295 Xichang Road, Wu Hua District, Kunming, Yunnan Province, 650032, China.
Rui Wei *Department of Emergency Medicine, The First Affiliated Hospital of Kunming Medical University, No. 295 Xichang Road, Wu Hua District, Kunming, Yunnan Province, 650032, China.
Di YangDepartment of Emergency Medicine, The First Affiliated Hospital of Kunming Medical University, No. 295 Xichang Road, Wu Hua District, Kunming, Yunnan Province, 650032, China.
Bawei YuDepartment of Emergency Medicine, The First Affiliated Hospital of Kunming Medical University, No. 295 Xichang Road, Wu Hua District, Kunming, Yunnan Province, 650032, China.
Wei ZhangDepartment of Emergency Medicine, The First Affiliated Hospital of Kunming Medical University, No. 295 Xichang Road, Wu Hua District, Kunming, Yunnan Province, 650032, China. zhangwei7222@kmmu.edu.cn.

Funding

Applied Basic Research Foundation of Yunnan Province 202101AY070001-021National Natural Science Foundation of China 82160374
6 · The paper itself

Abstract

backgroundIschemic stroke (IS) is one of the common and frequent diseases with extremely high lethality and disability in the world, and there is no effective treatment at present. This study aimed to screen hub genes involved in cerebral ischemia/reperfusion injury (CIRI) and pyroptosis, and explore promising intervention targets.

methodsCIRI-related genes (GSE202659 and GSE131193) and pyroptosis-related genes (PRGs) in mice were obtained from the Gene Expression Omnibus (GEO) and GeneCards database. We screened for LASSO regression to construct a prognostic model of GSE131193 and PRGs and examined by GSE137482. The functional enrichment analysis of Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were performed on pyroptosis-related differentially expressed genes (PRDEGs) of GSE202659.The key modules for CIRI and pyroptosis were identified by Weight Gene Co-expression Network Analysis (WGCNA). Subsequently, Protein-protein Interaction (PPI) network and the Cytoscape was constructed to screen out hub genes. Used the starBase to predict miRNA interacting with hub genes and constructed mRNA-miRNA-lncRNA interaction networks. CIRI-related Molecular Subtypes were constructed for hub genes. The relationship between immune cells and hub genes was verified via CIBERSORT. Finally, we selected C57BL/6 mice to construct models to confirm hub genes by enzyme linked immunosorbent assay (ELISA), reverse transcription-polymerase chain reaction (RT-PCR), western blot, and Immunofluorescence.

resultsA total of 272 PRGs and 35 PRDEGs were screened. An eight-gene risk prediction models were established (AUC = 0.868). GO, KEGG, GSEA and GSVA analyses revealed that PRDEGs were mainly involved in positive regulation of cytokine production, and NOD-like receptor signaling pathway. And then, seven hub genes (Irf1, Icam1, Tlr2, Tnf, Cebpb, Il1rn, and Casp8) were identified by PPI. Icam1, Tnf, Cebpb, Il1rn, and Casp8 had high expression profiles in Cluster2 by hierarchical clustering. The immune infiltration analysis results showed that among the hub genes, Cebpb, Il1rn, and Casp8, showed a significant positive correlation with the degree of NK.Actived, and Icam1 showed a significant negative correlation with B.Cells.Memory. The results of animal experiments significantly demonstrated an upregulation of Irf1, Icam1, Tlr2, Cebpb, and Il1rn.

conclusionOur finding indicated that Irf1, Icam1, Tlr2, Cebpb, and Il1rn are hub genes associated with pyroptosis, and these genes are all associated with different immune cells, so as to provide new targets for the prevention and treatment of IS from the perspective of pyroptosis.

Indexed as

Computational BiologyIschemic StrokePyroptosisAnimalsDatabases, GeneticGene Expression ProfilingGene OntologyGene Regulatory NetworksHumansMiceMicroRNAsProtein Interaction MapsReperfusion InjuryMicroRNAsCerebral ischemia reperfusion injuryImmune cell infiltrationIRF1Ischemic strokePyroptosis

Identifiers

PMID40091022
PMCPMC11912741

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.