Rapid Phenotyping for Rare Variant Discovery in Autism

自闭症罕见变异发现的快速表型分析

• 批准号: 8926475
• 负责人: STANLEY F. NELSON
• 金额: $ 45.39万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8926475
• 关键词: Accounting; Affect; Age; Autistic Disorder; Behavioral; Bioinformatics; Biology; Blood; Candidate Disease Gene; Child; Clinic; Collaborations; Collection; Communities; Consent; Contracts; Copy Number Polymorphism; DNA; Data; Data Set; Databases; Detection; Developmental Delay Disorders; Disease; Ensure; Environment; Etiology; Event; Exons; Family; Family Planning; Frequencies; Funding; Future; Gene Frequency; Genes; Genetic; Genetic study; Genome; Genomic DNA; Genotype; Growth; Home environment; Individual; Instruction; Internet; Investigation; Lead; Massive Parallel Sequencing; Measurement; Minority; Molecular Abnormality; Monitor; Mutation; Nature; Online Systems; Parents; Phenotype; Policies; Population; Procedures; Process; Protocols documentation; Reading; Recontacts; Recruitment Activity; Relative (related person); Reporting; Research; Research Personnel; Resolution; Resources; Risk; Running; Sample Size; Sampling; Siblings; Site; Subgroup; Testing; Time; Variant; Work; autism spectrum disorder; base; computerized data processing; cost; cost effective; data sharing; database of Genotypes and Phenotypes; developmental disease; endophenotype; genetic analysis; genetic makeup; genetic risk factor; genetic variant; innovation; meetings; novel; proband; rare variant; risk variant; sample collection; targeted sequencing; web site

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.

描述（由申请人提供）：自闭症谱系障碍（ASD）是一组高度异质性的神经发育障碍。虽然强有力的家族证据支持自闭症谱系障碍（ASD）的病因学的重大遗传贡献，特定的遗传异常已被确定在所有情况下，只有一小部分。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性遗传成分，包括识别罕见和常见的变异，总体样本量比目前正在研究的样本量大一个数量级是非常必要的。这将需要快速和可扩展的受试者评估范例，其支持基于临床的时间密集型行为表型，这是一个限速步骤。这里提出的项目是使用基于网络的招募，网络实施和验证的表型测量，以及分布式血液收集的综合力量，以建立一个具有成本效益的招募受影响的ASD儿童。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型方法的准确性，我们在IAN中建立了一个功能齐全的自动化协议，从已经登记和新登记的家庭中招募，以电子方式同意他们，并指导他们在家中附近的1，600个签约抽血点之一进行采血。这项招募程序已经与IAN合作启动，我们预计，我们每年招募400个单胎四胞胎家庭的计划将在资助期的前三年内顺利实现（具体目标1）。使用收集的1200个四分体家族的样本集，我们将进行高灵敏度的靶向测序，以在基因集中搜索罕见的风险变体和罕见的CNV，该基因集中富集了先前研究中与自闭症相关的基因（具体目标2）。尽管本文提出的样本量仍然不足以检测所有罕见风险变异，但由于使用父母和未受影响的兄弟姐妹进行了严格控制，因此使用统计学上稳健的分析策略实现了筛查新型罕见突变的能力增加。此外，为了表达ASD的异质性，我们将对基因中心和表型中心亚组进行探索性子集分析（具体目标3）。在整个招募过程中，我们将仔细监测IAN人群，以确保未观察到显著的表型变化。这里发现的变异不仅将验证先前与自闭症相关的遗传发现，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个环境，在这个环境中，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，这样就可以对具有已知遗传风险因素的个体进行更深入的表型研究。所有收集的样本和序列数据将与其他研究人员共享，大大增加了自闭症遗传学研究的样本量。