Rapid Phenotyping for Rare Variant Discovery in Autism

描述（由申请人提供）：自闭症谱系障碍（ASD）是一种高度异质性的神经发育障碍。虽然强有力的家族证据支持遗传对自闭症谱系障碍（ASD）病因的重要贡献，但仅在所有病例中的一小部分中确定了特定的遗传异常。目前的主要限制是相对缺乏可用于遗传分析的家庭。为了全面描述自闭症的异质遗传成分，包括罕见和常见变异的识别，迫切需要比目前正在研究的更大的总体样本量。这将需要快速和可扩展的受试者评估范式，以避免基于临床的时间密集型行为表型，这是一个限制速度的步骤。这里提出的项目是利用基于网络的招募、网络实施和验证的表型测量以及分布式血液采集的综合力量，建立一个具有成本效益的自闭症患儿招募方法。根据我们的初步分析，我们评估了在互动自闭症网络（IAN）中实施的基于网络的自闭症表型分析方法的准确性，我们在IAN中建立了一个功能齐全的自动化协议，从已经注册和新注册的家庭中招募，以电子方式同意他们，并指导他们在他们家附近的1600个签约抽血点之一采血。这一招募程序已经与IAN合作启动，我们预计我们每年招募400个单一四联体家庭的计划将在资助期的前三年很容易实现（具体目标1）。利用收集到的1200个四联体家族样本集，我们将执行高度敏感的靶向测序，以在先前研究中与自闭症相关的基因丰富的基因集中搜索罕见的风险变异和罕见的CNVs（特定目标2）。虽然这里提出的样本量仍然不够大，不足以检测所有罕见的风险变异，因为使用父母和未受影响的兄弟姐妹进行严格控制，但通过统计稳健的分析策略，增加了筛查新的罕见突变的能力。此外，为了传达ASD的异质性，我们将对基因中心亚群和表型中心亚群进行探索性亚群分析（具体目标3）。在整个招募过程中，我们将仔细监测IAN人群，以确保没有观察到显著的表型变化。这里发现的变异不仅将证实先前与自闭症相关的基因发现，而且还将导致识别新的突变并扩大基因列表。我们希望最终建立一种环境，在这种环境中，所有受影响的儿童的基因组成都是已知的，相对于一套全面的遗传风险因素，这样，更深入的表型研究就可以应用于已知遗传风险因素的个体。所有收集的样本和序列数据将与其他研究人员共享，从而大大增加自闭症基因研究的样本量。

DESCRIPTION (provided by applicant): Autism spectrum disorder (ASD) is a highly heterogeneous group of neuro-developmental disorders. While strong familial evidence supports a substantial genetic contribution to the etiology of autism spectrum disorders (ASD), specific genetic abnormalities have been identified in only a small minority of all cases. The key limitation currently is the relative lack of families available for genetic analysis. In order to comprehensively delineate the heterogeneous genetic components of autism including the identification of rare and common variants, overall sample sizes an order of magnitude larger than those currently under study are critically needed. This will require rapid and scalable subject assessment paradigms that obviate clinic-based time- intensive behavioral phenotyping, which is a rate-limiting step. The project proposed here is to use the combined power of web based recruiting, web-implemented and validated phenotypic measurements, and distributed blood collection to establish a cost-effective recruitment of affected children with ASD. Based on our preliminary analysis where we assessed the accuracy of a web-based approach to autism phenotyping implemented within the Interactive Autism Network (IAN), we have set up a fully functional and automated protocol in IAN to recruit from already registered and newly registered families, consent them electronically and instruct them for blood collection at one of the 1,600 contracted blood draw sites near their home. This recruitment procedure is already initiated in collaboration with IAN and we expect that our plan of recruiting 400 simplex tetrad families per year will be readily met in the first three year of the funding period (specific aim 1). Using the collected sample set of 1200 tetrad families, we will perform highly sensitive targeted sequencing to search for rare risk variants and rare CNVs within a gene set that is enriched for genes associated with autism from previous studies (specific aim 2). Although the sample size proposed here is still not large enough to detect all rare risk variants, because of the stringent control using parents and the unaffected siblings, increased power to screen for novel rare mutations is achieved with statistically robust analytical strategy. Additionally, to convey the heterogeneous nature of ASD, we will implement exploratory subset analysis of both the gene-centric and the phenotypic-centric subgroups (specific aim 3). Throughout the recruitment process, we will carefully monitor the IAN population to ensure that there is no significant phenotype shifts observed. The variants found here will not only validate the previous genetic findings associated with autism but also result in identifying novel mutations and expanding the gene list. We would hope to eventually establish an environment in which all affected children's genetic makeup is known, relative to a comprehensive set of genetic risk factors, so that deeper phenotypic efforts can be applied to individuals with known genetic risk factors. All of the samples collected and the sequence data will be shared with other investigators, substantially increasing the sample size available for autism genetic studies.