Abstract
Network analysis is a novel method to understand the complex pathogenesis of inflammation-driven atherosclerosis. Using this approach, we attempted to identify key inflammatory genes and their core transcriptional regulators in coronary artery disease (CAD). Initially, we obtained 124 candidate genes associated with inflammation and CAD using Polysearch and CADgene database for which protein-protein interaction network was generated using STRING 9.0 (Search Tool for the Retrieval of Interacting Genes) and visualized using Cytoscape v 2.8.3. Based on betweenness centrality (BC) and node degree as key topological parameters, we identified interleukin-6 (IL-6), vascular endothelial growth factor A (VEGFA), interleukin-1 beta (IL-1B), tumor necrosis factor (TNF) and prostaglandin-endoperoxide synthase 2 (PTGS2) as hub nodes. The backbone network constructed with these five hub genes showed 111 nodes connected via 348 edges, with IL-6 having the largest degree and highest BC. Nuclear factor kappa B1 (NFKB1), signal transducer and activator of transcription 3 (STAT3) and JUN were identified as the three core transcription factors from the regulatory network derived using MatInspector. For the purpose of validation of the hub genes, 97 test networks were constructed, which revealed the accuracy of the backbone network to be 0.7763 while the frequency of the hub nodes remained largely unaltered. Pathway enrichment analysis with ClueGO, KEGG and REACTOME showed significant enrichment of six validated CAD pathways - smooth muscle cell proliferation, acute-phase response, calcidiol 1-monooxygenase activity, toll-like receptor signaling, NOD-like receptor signaling and adipocytokine signaling pathways. Experimental verification of the above findings in 64 cases and 64 controls showed increased expression of the five candidate genes and the three transcription factors in the cases relative to the controls (p<0.05). Thus, analysis of complex networks aid in the prioritization of genes and their transcriptional regulators in complex diseases.
Highlights
Coronary Artery Disease (CAD) is a chronic inflammatory disease
Network analysis and characterization of the hub nodes The extended Protein-Protein interaction (PPI) network generated using the 124 seed genes in STRING resulted in 1234 interactions between 145 nodes, of which 21 new nodes were pulled out based on their proteinprotein interactions
IL-6 occupied the centre of the backbone network, having the largest degree and highest betweenness centrality (BC), which suggests that IL-6 could be considered as a super-hub gene
Summary
Coronary Artery Disease (CAD) is a chronic inflammatory disease. There is ample evidence on the role of inflammation in all stages of the atherosclerotic disease process [1,2]. Genetic studies have revealed many causal or susceptible inflammatory loci associated with CAD, the manifest form of atherosclerosis [3,4] Circulating inflammatory biomarkers such as C-reactive proteins (CRP) and certain cytokines are elevated in acute coronary syndrome, which reflect the extent of myocardial necrosis and ischemia/reperfusion damage [5]. Inflammation signaling show a cascade effect with some molecules acting as primary triggers that stimulate a secondary line of molecules and so on, eventually generating a strong inflammatory milieu Identification of such key inflammatory targets is critical from a translational aspect in order to treat the ‘inflammation’ component of the disease that can lead to slowing down or even arrest in its pathological and clinical progression
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