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首页> 外文期刊>Balkan journal of medical genetics: BJMG >EXPLORING CANDIDATE GENES FOR EPILEPSY BY COMPUTATIONAL DISEASE-GENE IDENTIFICATION STRATEGY
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EXPLORING CANDIDATE GENES FOR EPILEPSY BY COMPUTATIONAL DISEASE-GENE IDENTIFICATION STRATEGY

机译：通过计算疾病基因鉴定策略探索癫痫候选基因

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Epilepsy is a complex disease with a strong genetic component. So far, studies have focused on experimental validation or genome-wide linkage scans for epilepsy susceptibility genes in multiple populations. We have used four bioinformatic tools (SNPs3D, PROSPECTR and SUSPECTS, GenWanderer, PosMed) to analyze 16 susceptibility loci selected from a literature search. Pathways and regulatory network analyses were performed using the Ingenuity Pathways Analysis (IPA) software. We identified a subset of 48 candidate epilepsy susceptibility genes. Five significant canonical pathways, in four typical networks, were identified: GABA receptor signaling, interleukin-6 (IL-6) signaling, G-protein coupled receptor signaling, type 2 diabetes mellitus signaling and airway inflammation in asthma. We concluded that online analytical tools provide a powerful way to reveal candidate genes which can greatly reduce experimental time. Our study contributes to further experimental tests for epilepsy susceptibility genes.
机译：癫痫病是一种复杂的疾病，具有很强的遗传成分。到目前为止，研究集中于对多个人群的癫痫易感基因进行实验验证或全基因组连锁扫描。我们使用了四种生物信息学工具（SNPs3D，PROSPECTR和SUSPECTS，GenWanderer，PosMed）来分析从文献检索中选择的16个易感基因座。使用Ingenuity Pathways Analysis（IPA）软件进行途径和监管网络分析。我们确定了48个候选癫痫易感基因的子集。在四个典型的网络中，确定了五个重要的经典途径：GABA受体信号传导，白介素6（IL-6）信号传导，G蛋白偶联受体信号传导，2型糖尿病信号传导和哮喘中的气道炎症。我们得出的结论是，在线分析工具提供了一种揭示候选基因的强大方法，可以大大减少实验时间。我们的研究有助于癫痫易感基因的进一步实验测试。

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