ArticleAging2021
Identification of key genes in coronary artery disease: an integrative approach based on weighted gene co-expression network analysis and their correlation with immune infiltration.
Article in Aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 31 citations in OpenAlex.
- Identification and analysis of EphrinB2/EphB4 signaling pathway and angiogenesis related biomarkers in coronary artery disease based on bioinformatics.Journal of cardiothoracic surgery · 2026Article
- Development of immune-derived molecular markers for coronary heart disease via multimachine learning.iScience · 2026Article
- Identification and Analysis of PANoptosis Associated with Coronary Artery Disease Using Integrated Bioinformatics Methods.Iranian journal of biotechnology · 2026Article
- Twin pairs discordant for incident coronary artery disease reveal epigenetic and transcriptomic differences by gene region.Molecular genetics and genomics : MGG · 2025Article
- Genetic alterations in coronary cell lines exposed to sirolimus and paclitaxel.Archives of toxicology · 2025Article
- Identifying pyroptosis- and inflammation-related genes in spinal cord injury based on bioinformatics analysis.Scientific reports · 2025Article
- Immunophenotyping identifies key immune biomarkers for coronary artery disease through machine learning.PloS one · 2025Article
- Gene modules and genes associated with postoperative atrial fibrillation: weighted gene co-expression network analysis and circRNA-miRNA-mRNA regulatory network analysis.Journal of thoracic disease · 2023Article
- Identifying pyroptosis- and inflammation-related genes in intracranial aneurysms based on bioinformatics analysis.Biological research · 2023Article
- m6A regulator-mediated RNA methylation modification patterns are involved in the regulation of the immune microenvironment in ischaemic cardiomyopathy.Scientific reports · 2023Article
- Identification through machine learning of potential immune- related gene biomarkers associated with immune cell infiltration in myocardial infarction.BMC cardiovascular disorders · 2023Article
- An in vitro approach to understand contribution of kidney cells to human urinary extracellular vesicles.Journal of extracellular vesicles · 2023Article
- Identification and validation of potential hypoxia-related genes associated with coronary artery disease.Frontiers in physiology · 2023Article
- Integrating bulk and single-cell RNA sequencing data reveals epithelial-mesenchymal transition molecular subtype and signature to predict prognosis, immunotherapy efficacy, and drug candidates in low-grade gliomas.Frontiers in pharmacology · 2023Article
- Identifying patterns of immune related cells and genes in the peripheral blood of acute myocardial infarction patients using a small cohort.Journal of translational medicine · 2022Article
- Article
- Identification of molecular subtypes of coronary artery disease based on ferroptosis- and necroptosis-related genes.Frontiers in genetics · 2022Article
- Epithelial-mesenchymal transition-related genes in coronary artery disease.Open medicine (Warsaw, Poland) · 2022Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aimed to identify key genes related to coronary artery disease (CAD) and its association with immune cells infiltration. GSE20680 and GSE20681 were downloaded from GEO. We identified red and pink modules in WGCNA analysis and found 104 genes in these two modules. Next, least absolute shrinkage and selection operator (LASSO) logistic regression was used to screen and verify the diagnostic markers of CAD. We identified ASCC2, LRRC18, and SLC25A37 as the key genes in CAD diagnosis. We further studied the immune cells infiltration in CAD patients with CIBERSORT, and the correlation between key genes and infiltrating immune cells was analyzed. We also found immune cells, including macrophages M0, mast cells resting and T cells CD8, were associated with ASCC2, LRRC18 and SLC25A37. Gene enrichment analysis indicated that these genes mainly enriched in apoptotic signaling pathway for biological pathway analysis, riboflavin metabolism for KEGG analysis. The diagnostic efficiency of these key genes measured by AUC in the training set, testing set and validation cohort was 0.92, 0.96 and 0.83, respectively. In conclusion, ASCC2, LRRC18 and SLC25A37 can be used as diagnostic markers of CAD, and immune cell infiltration plays an important role in the onset and development of CAD.
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