Rare genetic factors in epileptogenesis

导致遗传性广泛性癫痫（GGE）的因素在很大程度上是未知的，已知因素只能解释其高遗传性的一小部分。可能的解释是大量尚未确定的罕见变异和更常见的风险变异。常见的变体在项目P3中得到解决。在这里，我们将运行罕见变异基因发现的完整范围，从分析最大的外显子组序列集合- 6400个GGE和3200个癫痫性脑病（EE）病例-到癫痫发生背景下的功能解释。为此，我们将使用广泛的方法，从组学数据建模到细胞和动物模型中基因和变异的验证。首先，来自全球合作的全外显子组序列样本量的大幅增加将使我们能够从无假设分析中识别新的变异。罕见变异的识别将由最先进的统计模型作为负担或崩溃测试来运行。毫无疑问，癫痫的异质性导致了先前基因发现的失败，负担测试无法利用表型严重程度的信息。因此，我们将探索用于分析GGE的多效模型，以解决表型细节，但也包括与GGE相比的EE和局灶性癫痫（FE）。其次，我们将通过整合蛋白-蛋白相互作用、基因表达和基因变异富集来寻找介导GGE癫痫发生的基因网络。来自单细胞RNA-seq实验的新数据将使我们能够对单个细胞类型进行变异解释。在系统生物学方法中，这种网络的预测关键基因将与其他项目合作进行验证，例如在斑马鱼中。第三，将在细胞和小鼠模型中进行遗传变异的生理测试，以完成我们对其影响的理解。非洲爪蟾卵母细胞的自动筛选和哺乳动物细胞系的膜片钳研究将确定离子通道和受体变异的生物物理后果。尚未参与GGE的基因（如KCNA2、KCNQ5和KCND2）的因果变异将被研究。我们培育了一只携带人类gge相关GABRA5突变的敲入（KI）小鼠，将允许通过与其他癫痫小鼠模型杂交来评估修改效果。通过这种多方面、协调一致的方式，该项目将导致鉴定新的和经过验证的易感性变异，并对GGE癫痫发生进行深入的定性理解。

The factors contributing to genetic generalized epilepsies (GGE) are largely uncharted and known factors explain only a minor component of its high heritability. Possible explanations are large numbers of not yet identified contributing rare variants and also more common risk-conferring variants. Common variants are addressed in project P3. Here, we will run the complete gamut of gene discovery for rare variants, from analysing the largest assembled collection of exome sequences – 6400 GGE and 3200 epileptic encephalopathies (EE) cases – to functional interpretation in the context of epileptogenesis. To this end, we will use a broad spectrum of methods, from omics data modeling to validation of genes and variants in cellular and animal models. Firstly, substantially increased sample sizes of whole-exome sequences from global collaborations will put us in a position to identify new variants from hypothesis-free analyses. The identification of rare variants will be run by state-of-the-art statistical models as burden or collapsing tests. The heterogeneity of epilepsies is undoubtedly contributing to prior failures in gene discovery and burden tests are not able to utilize information on the severity of the phenotype. We will therefore explore pleiotropic models for analysing GGE addressing phenotype details but also including EE as well as focal epilepsies (FE) in comparison to GGE. Secondly, we will search for gene networks mediating epileptogenesis in GGE by integration of protein-protein interactions, gene expression and enrichment of genetic variants. New data from single-cell RNA-seq experiments will allow us to take variant interpretation to individual cell types. In a systems biology approach, predicted key genes of such networks will be validated in cooperation with other projects, e.g. in zebrafish. Thirdly, physiological testing of genetic variants in cellular and mouse models will be performed to complete our understanding of their impact. Automated screening in Xenopus oocytes and patch clamp studies in mammalian cell lines will identify biophysical consequences of variants in ion channels and receptors. Causal variants in genes not yet involved in GGE, such as KCNA2, KCNQ5, and KCND2, will be investigated. A knock-in (KI) mouse which we generated carrying a human GGE-associated mutation in GABRA5 will allow assessing modifying effects by cross-breeding with other epilepsy mouse models. In this multifaceted, concerted way, the project will lead to the identification of new and validated susceptibility variants and an in-depth qualitative understanding of GGE epileptogenesis.