Comprehensive Bioinformatics Method to Explore Immune-Related Genes in the Pathogenesis of Myocardial Infarction DOI Creative Commons
Xin Zhang, Yi-Ren Yao, Ying Ding

и другие.

Cardiovascular Innovations and Applications, Год журнала: 2025, Номер 10(1)

Опубликована: Янв. 1, 2025

Objective: This study was aimed at exploring immune-related genes and their expression changes in myocardial infarction (MI) through comprehensive bioinformatics methods validating these as potential diagnostic therapeutic targets. Methods: Gene data were analyzed from three datasets: GSE29111 GSE66360, which combined a training set, GSE48060, served the validation set. We performed differential gene analysis, GO/KEGG enrichment protein-protein interaction (PPI) network weighted co-expression analysis (WGCNA), set immune infiltration studies to identify core associated with MI. The capabilities of assessed receiver operating characteristic curves, RT-PCR used verify levels between patients MI controls. relationships BCL6 inflammatory response oxidative stress explored detection factors TNF-α, IL-1, IL-6; NADPH oxidase subunits p67 gp91; SOD activity; MDA content. Results: Ninety-one differentially expressed identified. Enrichment analyses highlighted involvement lipopolysaccharide IL-17 signaling pathway. From PPI genes, four initially recognized, WGCNA further identified 13 genes. Intersection finalized identification S100A12 key biomarkers. Both showed significant control groups (P < 0.01), AUCs 0.809 0.837, respectively. These findings corroborated by similarly favorable AUCs. Furthermore, revealed positive correlation cell markers. After knockdown, an exacerbated observed, indicated higher subunits, lower activity, group than 0.01). Conclusion: might serve candidate biomarkers for early have promise new

Язык: Английский

Comprehensive Bioinformatics Method to Explore Immune-Related Genes in the Pathogenesis of Myocardial Infarction DOI Creative Commons
Xin Zhang, Yi-Ren Yao, Ying Ding

и другие.

Cardiovascular Innovations and Applications, Год журнала: 2025, Номер 10(1)

Опубликована: Янв. 1, 2025

Objective: This study was aimed at exploring immune-related genes and their expression changes in myocardial infarction (MI) through comprehensive bioinformatics methods validating these as potential diagnostic therapeutic targets. Methods: Gene data were analyzed from three datasets: GSE29111 GSE66360, which combined a training set, GSE48060, served the validation set. We performed differential gene analysis, GO/KEGG enrichment protein-protein interaction (PPI) network weighted co-expression analysis (WGCNA), set immune infiltration studies to identify core associated with MI. The capabilities of assessed receiver operating characteristic curves, RT-PCR used verify levels between patients MI controls. relationships BCL6 inflammatory response oxidative stress explored detection factors TNF-α, IL-1, IL-6; NADPH oxidase subunits p67 gp91; SOD activity; MDA content. Results: Ninety-one differentially expressed identified. Enrichment analyses highlighted involvement lipopolysaccharide IL-17 signaling pathway. From PPI genes, four initially recognized, WGCNA further identified 13 genes. Intersection finalized identification S100A12 key biomarkers. Both showed significant control groups (P < 0.01), AUCs 0.809 0.837, respectively. These findings corroborated by similarly favorable AUCs. Furthermore, revealed positive correlation cell markers. After knockdown, an exacerbated observed, indicated higher subunits, lower activity, group than 0.01). Conclusion: might serve candidate biomarkers for early have promise new

Язык: Английский

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