Integrative gene ontology and network analysis of coronary artery disease associated genes suggests potential role of ErbB pathway gene EGFR
Autor: | Ankit Sharma, Madankumar Ghatge, Jiny Nair, Rajani Kanth Vangala |
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Rok vydání: | 2017 |
Předmět: |
0301 basic medicine
Oncology Adult Male Cancer Research medicine.medical_specialty ERBB signaling pathway Coronary Artery Disease Biochemistry Polymorphism Single Nucleotide network topology Coronary artery disease protein-protein interaction 03 medical and health sciences Disease Ontology ErbB Risk Factors Internal medicine Databases Genetic Genetics Odds Ratio Medicine Humans Gene Regulatory Networks Genetic Predisposition to Disease Myocardial infarction Molecular Biology Regulation of gene expression business.industry hubs Gene Expression Profiling Computational Biology Molecular Sequence Annotation Odds ratio Articles Middle Aged medicine.disease Gene expression profiling ErbB Receptors 030104 developmental biology Gene Ontology Gene Expression Regulation Molecular Medicine Female disease ontology business Biomarkers |
Zdroj: | Molecular Medicine Reports |
ISSN: | 1791-3004 |
Popis: | Coronary artery disease (CAD) is a major cause of mortality in India, more importantly the young Indians. Combinatorial and integrative approaches to evaluate pathways and genes to gain an improved understanding and potential biomarkers for risk assessment are required. Therefore, 608 genes from the CADgene database version 2.0, classified into 12 functional classes representing the atherosclerotic disease process, were analyzed. Homology analysis of the unique list of gene ontologies (GO) from each functional class gave 8 GO terms represented in 11 and 10 functional classes. Using disease ontology analysis 80 genes belonging to 8 GO terms, using FunDO suggested that 29 of them were identified to be associated with CAD. Extended network analysis of these genes using STRING version 9.1 gave 328 nodes and 4,525 interactions of which the top 5% had a node degree of ≥75 associated with pathways including the ErbB signaling pathway with epidermal growth factor receptor (EGFR) gene as the central hub. Evaluation of EFGR protein levels in age and gender-matched 342 CAD patients vs. 342 control subjects demonstrated significant differences [controls=149.76±2.47 pg/ml and CAD patients stratified into stable angina (SA)=161.65±3.40 pg/ml and myocardial infarction (MI)=171.51±4.26 pg/ml]. Logistic regression analysis suggested that increased EGFR levels exhibit 3-fold higher risk of CAD [odds ratio (OR) 3.51, 95% confidence interval [CI] 1.96–6.28, P≤0.001], upon adjustment for hypertension, diabetes and smoking. A unit increase in EGFR levels increased the risk by 2-fold for SA (OR 2.58, 95% CI 1.25–5.33, P=0.01) and 3.8-fold for MI (OR 3.82, 95% CI 1.94–7.52, P≤0.001) following adjustment. Thus, the use of ontology mapping and network analysis in an integrative manner aids in the prioritization of biomarkers of complex disease. |
Databáze: | OpenAIRE |
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