Evidence mapPaperPMID 41347019Full record

ArticleFrontiers in physiology2025

Analysis of hub genes temporal dynamics in cardiac ischemia/reperfusion injury: a bioinformatics and experimental study.

Yu Zuo, Si-Yuan Yang, Xing-Kai Qian, Kun Liu

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Article in Frontiers in physiology, 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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0cells of the map it votes in
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

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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.

Yu ZuoCardiac Surgery Division, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Si-Yuan YangCardiac Surgery Division, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Xing-Kai QianGuizhou Medical University's Translational Medicine Research Institute, Guiyang, Guizhou, China.
Kun LiuCardiac Surgery Division, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Myocardial ischemia/reperfusion injury (MIRI) remains a major global health issue with rising morbidity and mortality. Blood flow restoration can worsen damage to oxygen-deprived cardiac tissue. This research aimed to identify hub genes linked to MIRI across various reperfusion stages, offering potential diagnostic indicators and therapeutic targets. Methods: Differentially expressed genes (DEGs) at 6, 24, and 72 h post-reperfusion based on the GSE160516 dataset via GEO2R were identified, and these genes were further analyzed using the DAVID database and online platforms for Gene Ontology Kyoto Encyclopedia of Genes and Genomes (KEGG) and Disease Ontology (DO) enrichment. Protein-protein interaction networks were constructed using STRING and visualized with Cytoscape, and the Degree algorithm within the CytoHubba plug-in identified the top ten hub genes at each time point. Additional analyses included miRNA-hub gene prediction, transcription factor-hub gene regulation, and drug-hub gene interactions via miRDB, TRRUST and DGIdb platforms. Receiver operating characteristic (ROC) curve analysis and immune cell infiltration assessment were performed using online analytical tools and CIBERSORT. Finally, an oxygen-glucose deprivation/reperfusion (OGD/R) model in HL-1 mouse cardiomyocytes and external datasets validated the expression of hub genes. Results: Totally, 341, 399 and 431 DEGs at 6, 24, and 72 h post-reperfusion were screened, enriched in functions, such as inflammatory pathways, cytokine-receptor interactions, and immune or inflammatory-related diseases. Degree algorithm analysis identified the top ten hub genes (Il1b, Cxcl2, Cd44, etc.) at 6h, (Il1b, Il6, Fn1, etc.), at 24 h and (Fcgr3, Ccl2, Cd68, etc.) at 72 h. Most hub genes showed notable interactions with specific microRNAs (mmu-let-7c-1-3p, mmu-miR-466L-3p), the transcription factor Nfkb1, and drugs with the highest drug-gene interaction scores (EMAPTICAP PEGOL, CARLUMAB, Compound 27 [PMID: 19854648]). ROC curve analyses demonstrated high diagnostic potential (AUC 0.889-1.000; sensitivity 100%; specificity 66.67%-100%) and immune infiltration analysis indicated increased resting dendritic cells and decreased neutrophils. Validation in HL-1 OGD/R models and external datasets confirmed elevated mRNA expression of Serpine1, Ccl2, Il6, and Fn1 at various reperfusion stages. Conclusion: Analysis across multiple datasets and HL-1 cell experimental models revealed four significantly altered genes-Serpine1, Ccl2, Il6 and Fn1-indicating their potential targets for MIRI.

Indexed as

bioinformatics analysisdifferential expression genesenrichment analysisgene expression omnibushub genesmyocardial ischemia/reperfusion injury

Identifiers

PMID41347019
PMCPMC12672348

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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.