ArticleJournal of genetics2015
Understanding gene expression in coronary artery disease through global profiling, network analysis and independent validation of key candidate genes.
Article in Journal of genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 21 citations in OpenAlex.
- Identification of myocardial contractility-related genes as regenerative targets and diagnostic biomarkers in coronary artery disease.Regenerative therapy · 2026Article
- Comparative Analysis of Transcriptome Profiles in Patients with Thromboangiitis Obliterans.Genes · 2023Article
- Identification of diagnostic biomarkers and therapeutic targets in peripheral immune landscape from coronary artery disease.Journal of translational medicine · 2022Article
- Artificial Intelligence and Cardiovascular Genetics.Life (Basel, Switzerland) · 2022Review
- Identification of differentially expressed genes and the role of PDK4 in CD14+ monocytes of coronary artery disease.Bioscience reports · 2021Article
- Comparative study of gene expression profiles rooted in acute myocardial infarction and ischemic/reperfusion rat models.American journal of cardiovascular disease · 2020Article
- Article
- Gene expression profiling of coronary artery disease and its relation with different severities.Journal of genetics · 2018Article
- Integrative gene ontology and network analysis of coronary artery disease associated genes suggests potential role of ErbB pathway gene EGFR.Molecular medicine reports · 2018Article
- Dynamic Role of trans Regulation of Gene Expression in Relation to Complex Traits.American journal of human genetics · 2017Article
- Genomic translational research: Paving the way to individualized cardiac functional analyses and personalized cardiology.International journal of cardiology · 2017Review
- In-Cardiome: integrated knowledgebase for coronary artery disease enabling translational research.Database : the journal of biological databases and curation · 2017Article
- Differential gene expression profiles in peripheral blood in Northeast Chinese Han people with acute myocardial infarction.Genetics and molecular biologyArticle
- Integrated Network and Gene Ontology Analysis Identifies Key Genes and Pathways for Coronary Artery Diseases.Avicenna journal of medical biotechnologyArticle
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Molecular mechanism underlying the patho-physiology of coronary artery disease (CAD) is complex. We used global expression profiling combined with analysis of biological network to dissect out potential genes and pathways associated with CAD in a representative case-control Asian Indian cohort. We initially performed blood transcriptomics profiling in 20 subjects, including 10 CAD patients and 10 healthy controls on the Agilent microarray platform. Data was analysed with Gene Spring Gx12.5, followed by network analysis using David v 6.7 and Reactome databases. The most significant differentially expressed genes from microarray were independently validated by real time PCR in 97 cases and 97 controls. A total of 190 gene transcripts showed significant differential expression (fold change>2,P<0.05) between the cases and the controls of which 142 genes were upregulated and 48 genes were downregulated. Genes associated with inflammation, immune response, cell regulation, proliferation and apoptotic pathways were enriched, while inflammatory and immune response genes were displayed as hubs in the network, having greater number of interactions with the neighbouring genes. Expression of EGR1/2/3, IL8, CXCL1, PTGS2, CD69, IFNG, FASLG, CCL4, CDC42, DDX58, NFKBID and NR4A2 genes were independently validated; EGR1/2/3 and IL8 showed >8-fold higher expression in cases relative to the controls implying their important role in CAD. In conclusion, global gene expression profiling combined with network analysis can help in identifying key genes and pathways for CAD.
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