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首页> 外文期刊>Journal of genetics >Understanding gene expression in coronary artery disease through global profiling, network analysis and independent validation of key candidate genes
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Understanding gene expression in coronary artery disease through global profiling, network analysis and independent validation of key candidate genes

机译：通过全局分析，网络分析和关键候选基因的独立验证来了解冠状动脉疾病中的基因表达

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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.
机译：冠状动脉疾病（CAD）病理生理的潜在分子机制很复杂。我们使用了全局表达谱分析和生物网络分析相结合的方法，在一个有代表性的病例对照亚洲印度裔队列中，分析了与CAD相关的潜在基因和途径。我们最初在安捷伦微阵列平台上对20位受试者（包括10位CAD患者和10位健康对照）进行了血液转录组学分析。使用Gene Spring Gx12.5分析数据，然后使用David v 6.7和Reactome数据库进行网络分析。来自微阵列的最显着差异表达基因通过实时PCR独立验证了97例病例和97个对照。病例与对照组之间总共有190个基因转录本表现出显着的差异表达（倍数变化> 2，P <0.05），其中142个基因上调而48个基因下调。与炎症，免疫反应，细胞调节，增殖和凋亡途径相关的基因得到了丰富，而炎症和免疫反应基因则被展示为网络中的枢纽，与邻近基因的相互作用数量更多。独立验证了EGR1 / 2/3，IL8，CXCL1，PTGS2，CD69，IFNG，FASLG，CCL4，CDC42，DDX58，NFKBID和NR4A2基因的表达;相对于对照，EGR1 / 2/3和IL8的表达高出8倍以上，这表明它们在CAD中起重要作用。总之，整体基因表达谱分析与网络分析相结合可以帮助确定CAD的关键基因和途径。

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