Parallel Sequence Profiling of Ion Channels in Epilepsy

描述(申请人提供)：离子通道基因占人类基因组的1.5%，这些基因的遗传突变会导致大脑、神经、肌肉和心脏的一系列临床疾病。在大脑中，单基因通道病变是罕见的孟德尔特发性癫痫综合征的主要原因(13/14)，但它们对常见的散发性癫痫的贡献尚不清楚。高的从头突变率和复杂的多基因遗传(“共同疾病-共同变异”模式)是离子通道变异在散发性病例中作用的两个吸引人的解释。离子通道与其重要的致病作用一起，也是大多数抗癫痫药物的主要分子靶点，通道亚单位的遗传变异可能独立地参与了药物耐药性的产生。该项目将离子通道病和特定癫痫表型的基础和临床研究与贝勒人类基因组测序中心的大规模基因测序能力和突变分析资源相结合，以验证一个普遍假设，即对单个癫痫患者的大量通道基因的编码序列进行剖析可以揭示决定癫痫易感性和耐药性的常见等位基因变异的新突变和模式。我们将完成多重引物阵列的开发和优化，该阵列可以对500名具有特定临床癫痫表型的患者和500名种族匹配的对照组的100个候选离子通道基因进行快速和可扩展的并行外显子测序。将建立一个人类离子通道基因变异的公共数据库，以促进数据共享。这些数据将用于两种方式。首先，将在哺乳动物表达系统中分析具有预测的蛋白质编码变异的通道基因多态的子集的生物物理和药理学特性，以便定义与癫痫相关的人离子通道功能基因变体的有效子集。这份清单对于研究离子通道的特定病理生理学特性与癫痫相关模式的模型是必不可少的。其次，100个通道基因的序列将被组装成每个个体的简档(它们的“chnonotype”)，并用于测试不同chnonotype与癫痫表型的统计关联。对50名患者和50名对照的7个通道基因的所有外显子的初步分析发现了新的和以前报道的SNPs(编码和非编码)和微缺失，验证了数据收集管道的效率。使用机器人处理和自动突变检测算法，我们将衡量基因和患者的数量，以获得解决chnonotype-表型关联假说的统计能力。这项研究中确定的关联将解决癫痫复杂遗传学背后的一个主要假设，加快癫痫个性化临床风险评估的发展，并检查患有常见特发性疾病的儿童和成人对抗癫痫药物耐药的新机制。

DESCRIPTION (provided by applicant): Ion channel genes represent 1.5% of the human genome, and inherited mutations of these genes elicit a diverse array of clinical disorders of brain, nerve, muscle and heart. In brain, single gene channelopathies are the predominant cause (13/14) of rare mendelian idiopathic epilepsy syndromes, but their contribution to common sporadic epilepsy is unknown. High rates of de novo mutation and complex polygenic inheritance (the "common disease-common variant" model) are two attractive explanations for the role of ion channel variation in sporadic cases. Together with their important pathogenic role, ion channels are also the primary molecular targets of most antiepileptic drugs, and genetic variation in channel subunits may independently contribute to pharmacoresistance. This project combines basic and clinical research on ion channelopathy and specific epilepsy phenotypes with the large scale gene sequencing capacity and mutation analysis resources of the Baylor Human Genome Sequencing Center in order to test the general hypothesis that profiling the coding sequences of large numbers of channel genes in individual epilepsy patients can reveal novel mutations and patterns of common allelic variants that determine epilepsy susceptibility and pharmacoresistance. We will complete the development and optimization of a multiplex primer array that allows rapid and scalable parallel exon sequencing of 100 candidate ion channel genes in 500 patients with specific clinical epilepsy phenotypes and in 500 ethnically-matched controls. A public database of human ion channel gene variation will be generated to facilitate data-sharing. These data will be used in two ways. First, the biophysical and pharmacological properties of a subset of channel gene polymorphisms with predicted protein coding variation will be analyzed in mammalian expression systems in order to define a validated subset of functional gene variants of human ion channels relevant to epilepsy. This list is essential to examine models relating specific pathophysiological properties of ion channels to the patterns associated with epilepsy. Second, the sequence of the 100 channel genes will be assembled into a profile of each individual (their "channotype") and used to test the statistical association of different channotypes with epilepsy phenotypes. Preliminary analysis of all exons of 7 channel genes in 50 patients and 50 controls has detected novel and previously reported SNPs (coding and non-coding) and microdeletions, validating the efficiency of the data collection pipeline. Using robotic processing and automated mutation detection algorithms, we will scale the number of genes and patients to attain the statistical power to address the channotype-phenotype association hypotheses. The associations identified in this study will address a major hypothesis underlying the complex genetics of epilepsy, accelerate development of individualized clinical risk assessments for epilepsy, and examine a novel mechanism of resistance to antiepileptic drugs in children and adults with common idiopathic forms of the disorder.