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.

PSRC1 in the cholesterol gene cluster shows a significant association with CAD by virtue of the two SNPs, rs646776 and rs599839 that also regulate plasma cholesterol levels.

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Venous thromboembolism (VTE), a multi-factorial disease, is the third most common cardiovascular disease. Established genetic and acquired risk factors are responsible for the onset of VTE. High altitude (HA) also poses as an additional risk factor, predisposing individuals to VTE; however, its molecular mechanism remains elusive. This study aimed to identify genes/pathways associated with the pathophysiology of deep vein thrombosis (DVT) at HA. Gene expression profiling of DVT patients, who developed the disease, either at sea level or at HA-DVT locations, resulted in differential expression of 378 and 875 genes, respectively. Gene expression profiles were subjected to bioinformatic analysis, followed by technical and biological validation of selected genes using quantitative reverse transcription-polymerase chain reaction. Both gene ontology and pathway analysis showed enrichment of genes involved in haemostasis and platelet activation in HA-DVT patients with the most relevant pathway being 'response to hypoxia'. Thus, given the environmental condition the differential expression of hypoxia-responsive genes (angiogenin, ribonuclease, RNase A family, 5; early growth response 1; lamin A; matrix metallopeptidase 14 [membrane-inserted]; neurofibromin 1; PDZ and LIM domain 1; procollagen-lysine 1, 2-oxoglutarate 5-dioxygenase 1; solute carrier family 6 [neurotransmitter transporter, serotonin], member 4; solute carrier family 9 [sodium/hydrogen exchanger], member 1; and TEK tyrosine kinase, endothelial) in HA-DVT could be a determining factor to understand the pathophysiology of DVT at HA.

Low vitamin D level was associated with an enhanced risk for incident CAD. VDR genotypes did not show any association with either vitamin D levels or CAD.