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: 8239331
• 负责人: STANLEY F. NELSON
• 金额: $ 64.52万
• 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 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8239331
• 关键词: Accounting; Affect; Age; Alleles; Autistic Disorder; Behavioral; Bioinformatics; Biology; Blood; Candidate Disease Gene; Child; Clinic; Collaborations; Collection; Communities; Consent; Contracts; 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; Genome; Genomics; Genotype; Growth; Home environment; Individual; Instruction; Internet; Investigation; Lead; 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 risk factor; genetic variant; innovation; meetings; novel; proband; sample collection; 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. PUBLIC HEALTH RELEVANCE: This project is intended to use web-based recruiting to greatly expand DNA samples available for genetic analysis to determine the heterogeneous genetic causes of autism. A sample set of 1200 simplex tetrad families consisted of both parents; one affected child and the unaffected sibling will be collected, stored, and made available to researchers. Further, candidate gene re- sequencing will permit higher sensitivity detection of rare risk alleles for autism, identify potential new mutations that lead to autism and expand our understanding of autism.

描述（由申请人提供）：自闭症谱系障碍（ASD）是一群高度异质的神经发展疾病。尽管有强大的家族证据支持对自闭症谱系疾病（ASD）病因的实质性遗传贡献（ASD），但在所有病例中的一小部分中，已经确定了特定的遗传异常。当前的关键限制是相对缺乏可用于遗传分析的家庭。为了全面描绘自闭症的异质遗传成分，包括鉴定稀有和常见变体，总体样本量比当前正在研究的差异大的数量级。这将需要快速可扩展的受试者评估范例，以消除基于临床的时间密集的行为表型，这是限制速率的步骤。此处提出的项目是利用基于Web的招聘，经过Web的实施和经过验证的表型测量的合并能力，并分发血液收集血液来建立对ASD患有ASD的受影响儿童的具有成本效益的招聘。基于我们的初步分析，我们评估了在交互式自闭症网络（IAN）内实施的基于网络的自闭症表型方法的准确性，我们在IAN中建立了一个功能齐全的自动化协议，以从已经注册和新注册的家庭中招募招募，并以电子方式同意他们，并指导他们在1,600合同的血液中收集血液中的血液收集。该招聘程序已经与IAN合作启动，我们希望我们每年招募400个单纯Tetrad家庭的计划将在资助期的前三年很容易满足（特定的AIM 1）。使用收集的1200个四元家庭的样品集，我们将执行高度敏感的靶向测序，以搜索一个基因集中的罕见风险变体和稀有的CNV，该基因集富含与以前的研究相关的基因（特定目标2）。尽管此处提出的样本量仍然不足以检测所有罕见的风险变体，但由于使用父母和未受影响的兄弟姐妹的严格控制，通过统计上强大的分析策略，可以实现增加新型稀有突变的功率。此外，为了传达ASD的异质性质，我们将对以基因为中心和以表型为中心的亚组实施探索性子集分析（特定目标3）。在整个招聘过程中，我们将仔细监测IAN人群，以确保未观察到明显的表型变化。这里发现的变体不仅将验证与自闭症相关的先前遗传发现，而且还会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与全面的遗传危险因素相对于所有受影响的儿童遗传构成的环境，以便将更深层次的表型努力应用于具有已知遗传危险因素的个体。收集的所有样品和序列数据将与其他研究者共享，从而大大增加了可用于自闭症遗传研究的样本量。 公共卫生相关性：该项目旨在使用基于Web的招聘来大大扩展可用于遗传分析的DNA样本，以确定自闭症的异质遗传原因。一个样本的1200个单纯tetrad家族由父母双亲组成。一个受影响的孩子和未受影响的兄弟姐妹将被收集，存储并提供给研究人员。此外，候选基因补习将允许对自闭症的稀有风险等位基因的更高灵敏度检测，确定导致自闭症的潜在新突变并扩展我们对自闭症的理解。