ArticleFrontiers in cardiovascular medicine2022
Potential of immune-related genes as promising biomarkers for premature coronary heart disease through high throughput sequencing and integrated bioinformatics analysis.
Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 6 citations in OpenAlex.
- Predictive value of system immune-inflammation index for the severity of coronary stenosis in patients with coronary heart disease and diabetes mellitus.Scientific reports · 2024Article
- Expression Pattern and Molecular Mechanism of Oxidative Stress-Related Genes in Myocardial Ischemia-Reperfusion Injury.Journal of cardiovascular development and disease · 2023Article
- Worsening Thrombotic Complication of Atherosclerotic Plaques Due to Neutrophils Extracellular Traps: A Systematic Review.Biomedicines · 2023Review
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Authors and funding
13 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Coronary heart disease (CHD) is the most common progressive disease that is difficult to diagnose and predict in the young asymptomatic period. Our study explored a mechanistic understanding of the genetic effects of premature CHD (PCHD) and provided potential biomarkers and treatment targets for further research through high throughput sequencing and integrated bioinformatics analysis. Methods: High throughput sequencing was performed among recruited patients with PCHD and young healthy individuals, and CHD-related microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified by using R software. Enrichment analysis and CIBERSORT were performed to explore the enriched pathways of DEGs and the characteristics of infiltrating immune cells. Hub genes identified by protein-protein interaction (PPI) networks were used to construct the competitive endogenous RNA (ceRNA) networks. Potential drugs were predicted by using the Drug Gene Interaction Database (DGIdb). Results: A total of 35 DEGs were identified from the sequencing dataset and GEO database by the Venn Diagram. Enrichment analysis indicated that DEGs are mostly enriched in excessive immune activation pathways and signal transduction. CIBERSORT exhibited that resting memory CD4 T cells and neutrophils were more abundant, and M2 macrophages, CD8 T cells, and naïve CD4 T cells were relatively scarce in patients with PCHD. After the identification of 10 hub gens, three ceRNA networks of Conclusions: The immune dysfunction mainly contributes to the pathogenesis of PCHD, and three ceRNA networks of
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