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.

Aim: Leukotrienes are important lipid inflammatory mediators that play a pivotal role in the pathogenesis of atherosclerosis. We aimed to construct a network of interactions between leukotrienes and inflammatory biomarkers and evaluate the expression of key members of the leukotriene pathway and leukotriene-induced inflammatory molecules in patients with coronary artery disease (CAD) and healthy controls. Methods: Leukotrienes and their regulatory inflammatory molecules reported in the literature were used to construct a biological network employing Gene spring GX v12.5. Key leukotriene genes and their closely interacting members were selected for expression study in 64 patients and 64 matched controls. Four single nucleotide polymorphisms (SNPs) (rs6538697, rs2660898, rs17525495 and rs1978331) in the leukotriene A4 hydrolase (LTA4H) gene were genotyped using SYBR green method, and plasma leukotriene B4 (LTB4) levels were measured using ELISA. Results: The expression levels of arachidonate 5-lipoxygenase (ALOX5), LTA4H, tumor necrosis factor (TNF) and interleukin-8 (IL-8) genes were significantly higher in patients than in the controls (p＜0.05). IL-8 (r

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.

The 9p21.3 locus is the best replicated region to date for coronary artery disease (CAD). We investigated the association of 9p21.3 common variants with CAD, candidate gene expression including ANRIL, a non-coding RNA, followed by in vitro validation. Five variants, rs10757278, rs10757274, rs2383206, rs1333049 and rs4977574 were genotyped in 1,034 cases and 1,034 controls. Gene expression of C9orf5, MTAP1, MTAP 2, p16INK4a, p14ARF, p15INK4b and two ANRIL splice variants, NR_003529 and EU741058, were measured in 100 cases and 100 controls. Human aortic smooth muscle cells (HuAoSMCs) were transfected with siRNA targeting ANRIL exon 19 (siRNA-1) or exon 2 (siRNA-2) and consequent effect determined. rs2383206 showed the highest association with CAD (odds ratio [OR] 2.02, 95% confidence interval [CI] 1.56 -2.62) and an adjusted OR of 2.55, 1.33-2.88 along with rs10757278. Conventional risk factors (conventional RFs), rs2383206 and rs10757278 variants together yielded a higher c index (OR 0.790, 95% CI 0.770 -0.810) as compared to conventional RFs (OR 0.783, 95% CI 0.763-0.803) or genetic variants (OR 0.561, 95% CI 0.536-0.586) alone. GAAAA haplotype showed significant protective association with CAD compared to CGGGG risk haplotype (OR 0.45, 95% CI 0.27-0.77). Expression of p16INK4a, p14ARF and p15INK4b as well as plasma CDKN2A levels were lower in cases than controls. GG genotype was associated with higher EU741058 expression and lower p16INK4a expression. HuAoSMCs transfected with siRNA-1 showed lower NR_003529, p16INK4aand p14ARFexpression. Our study provides further evidence on the significance of 9p21.3 locus for CAD wherein the risk allele regulate the expression of ANRIL and adjacent tumour suppressor genes which in turn alter smooth muscle proliferation, a fundamental process in atherosclerosis.