Integrative genomics to map risk genes and pathways in autism and epilepsy

项目总结 自闭症谱系障碍(ASD)影响1%的普通人群，癫痫(EPI)在AT 至少三分之一的自闭症患者。伴有癫痫的ASD(ASD-EPI)通常更严重，治疗 拖延对结果有负面影响。癫痫和自闭症表型之间的频繁联系 这表明他们有共同的易感基因。事实上，近些年来，基因已经变得很明显 与ASD和EPI有关，以及其他神经发育障碍，在功能上是相互联系的 网络。引人注目的是，在每一种紊乱中，受影响的网络都有相当大的重叠，这引发了一些问题 关于这些常见网络的中断如何产生如此表型多样性的问题。 尽管正在进行大规模的努力来识别ASD的危险基因，并在较小程度上识别儿科EPI，但 诊断效率仍然很低，大多数因果基因和风险变量尚未确定。新的队列是 还需要在先前识别的候选基因中发现更多的变异，并将它们提升到 ASD-EPI危险基因的研究现状。我们的研究与以前的研究不同，我们的研究集中在550个患有 特定的ASD-EPI亚型将导致较少的表型异质性，以增加发现能力 这一特定亚型的变种。对于每个家族，我们将对完整的外显子组以及非编码进行测序 与ASD和/或EPI相关的基因附近的调节区，具有强有力的先前证据。我们将表演 ASD-EPI中罕见从头和遗传基因干扰事件的负担分析及其与临床的相关性 表型变量(早发性与晚发性癫痫、性别、智商和核磁共振异常)，并将其纳入 用于基因集和网络分析的现有ASD/EPI数据集，以及将SNV和CNV集成到 共同框架(目标1)。我们还将识别非编码监管要素中的风险变体，包括顺式- ASD和EPI(ASD/EPI-)相关、高置信度和/或候选基因附近的调控元件 相关基因)、内含子RBFox结合靶标和miRNA结合靶标，使用新的统计框架 然后是负担分析(目标2)。最后，我们将从功能上描述8种高影响力的变种，它们将 通过CRISPR基因组编辑引入同基因的人诱导多能干细胞(IPSCs)，并 进一步分化为前脑神经前体细胞和神经元。功能分析将包括 核糖核酸序列、神经元连接和形态，以及使用多电极阵列的活动(目标3)。这个 更多突变的鉴定和功能描述将有助于确定基因的优先顺序并揭示新的 ASD-EPI基础通路的组成部分，并提供对它们如何相互关联的机械性洞察 其他的。我们的系统方法也提供了对ASD/EPI分子亚型进行分类的机会 区分ASD-EPI背后的遗传子网络与通路框架有何不同 与每一种疾病相关联，作为实现量身定制的干预和治疗的必要步骤。我们的建议将 为ASD和相关神经发育障碍的快速和大规模筛查设立标准。

PROJECT SUMMARY Autism spectrum disorders (ASDs) affect 1% of the general population, and epilepsy (EPI) is observed in at least one-third of ASD individuals. ASDs with epilepsy (ASD-EPI) are typically more severe and treatment delay has a negative impact on outcome. The frequent association between epileptic and autistic phenotypes suggests that they share predisposing genes. Indeed, in recent years it has become clear that genes implicated in ASD and EPI, as well as other neurodevelopmental disorders, are interconnected in functional networks. Strikingly, there is a considerable overlap in the networks affected in each disorder, raising questions on how disruptions of these common networks can give rise to such phenotypical diversity. Despite ongoing large-scale efforts to identify risk genes for ASD, and to a lesser extent for pediatric EPI, the diagnostic yield remains low and most causal genes and risk variants are yet to be identified. New cohorts are also needed to discover additional variants in previously identified candidate genes and elevate them to the status of ASD-EPI risk genes. Our study differs from previous efforts by focusing on a set of 550 families with a specific ASD-EPI sub-phenotype that will result in less phenotypic heterogeneity to increase power to find variants in this specific subtype. For each family we will sequence the complete exome, as well as noncoding regulatory regions near genes with strong prior evidence for association with ASD and/or EPI. We will perform burden analysis of rare de novo and inherited gene-disruptive events in ASD-EPI, and correlate with clinical phenotype variables (early vs late-onset epilepsy, gender, IQ, and MRI abnormalities), and incorporate this into existing ASD/EPI datasets for gene-set and network analyses, as well as integrating SNVs and CNVs in a common framework (Aim 1). We will also identify risk variants in noncoding regulatory elements, including cis- regulatory elements near implicated, high confidence, and/or candidate genes for ASD and EPI (ASD/EPI- relevant genes), intronic RBFOX binding targets, and miRNA binding targets, using a new statistical framework followed by burden analyses (Aim 2). Finally, we will functionally characterize 8 high-impact variants, which will be introduced by CRISPR genome editing into isogenic human induced pluripotent stem cells (iPSCs) and further differentiated into forebrain neuronal progenitor cells (NPCs) and neurons. Functional assays will include RNA-Seq, neuronal connectivity and morphology, as well as activity using Multi-Electrode Arrays (Aim 3). The identification and functional characterization of additional mutations will help prioritize genes and reveal novel components of the pathways underlying ASD-EPI, and provide mechanistic insight into how they relate to each other. Our systematic approach also provides the opportunity to classify molecular subtypes of ASD/EPI and to distinguish how the genetic subnetworks underlying ASD-EPI differ from the framework of pathways associated with each disorder, as necessary steps toward tailored intervention and treatment. Our proposal will set a standard for rapid and large-scale screening for ASD and related neurodevelopmental disorders.