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4/4 The Autism Sequencing Consortium: Autism gene discovery in the >20,000 exomes (supplement)

4/4 The Autism Sequencing Consortium: Autism gene discovery in the >20,000 exomes (supplement)
4/4 自闭症测序联盟:在超过 20,000 个外显子组中发现自闭症基因(补充)
批准号:
9051994
负责人:
MATTHEW W. STATE
金额:
$92.0万
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-01 至 2017-07-31

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中文摘要
翻译
描述(由申请人提供):虽然在理解自闭症的基因组结构方面已经有了很大的进步,但在被认为与自闭症相关的数百个基因和基因组区域中,只有中等数量的基因和基因组区域被发现。下一代测序(NGS)已经证明了它在快速识别ASD潜在变异方面的效用,这种方法正在通过多项研究在大约6,000个独立的ASD样本中进行。迫切需要开发一个框架来整合和扩展这些当前的研究,并联合分析新出现的数据,以最大限度地识别有效的ASD基因座,因为经过验证的风险变量为遗传咨询、理解发病机制和药物开发提供了机会。自闭症测序联盟(ASC)代表着20多个独立小组的协调努力,以快速识别和验证自闭症风险基因,这些基因是神经生物学分析和药物发现的主要目标。ASC的长期目标是利用遗传学来确定ASD的治疗靶点,同时有助于将此类研究成果转化为临床实践。TIS建议的总体目标是快速识别代表高影响神经生物学研究和药物发现的领先靶点的ASD基因。我们的中心假设--基于SNV、INDELS和CNV的数据,以及ASD的医学遗传条件和ASD的靶向测序--是多种独立的罕见变异占ASD风险的很大比例。我们提出这一建议的理由是,识别导致ASD和相关神经发育障碍的高危基因变异可以形成研究的基础,以了解发病机制,并为新的治疗方法奠定基础。此外,这些变异在病因诊断、遗传咨询和患者护理方面对患者及其家人具有直接影响。这些目标将通过以下具体目标实现:1)维持支持ASC目标的基础设施;2)部署用于数据清理和协调以及变体调用的管道;3)采用新的统计方法来识别与ASD相关的基因;以及4)对3,000名ASD受试者和父母进行全外显子组测序。这一贡献意义重大,因为它是了解ASD发病机制的研究的第一步,也是开发治疗ASD核心症状和病因性神经发育障碍的药理学策略的第一步。在我们看来,这项申请中提出的研究是创新的,因为它涉及一种全新的在发布前共享数据的模式,使用最先进的方法调用NGS数据中的各种类型的变量,纳入更新变量调用和共享数据的新方法,并包括高度创新的统计方法来识别风险位置。这是一种在ASD中发现基因的新的、本质上不同的方法,它大大偏离了现状,并提供了实现这些重要目标的手段。
英文摘要
DESCRIPTION (provided by applicant): While there has been great progress in understanding the genomic architecture of autism, only a moderate number of the hundreds of genes and genomic regions thought to be involved in ASD have been identified. Next-generation sequencing (NGS) has proven its utility to rapidly identify variants underlying ASD, and this approach is being carried out in ca. 6,000 independent ASD samples through multiple studies. There is an urgent need to develop a framework to integrate and expand these current studies, and to jointly analyze emerging data to maximize the identification of valid ASD loci, because validated risk variants present opportunities for genetic counseling, understanding pathogenesis, and drug development. The Autism Sequencing Consortium (ASC) represents a coordinated effort by more than 20 independent groups to rapidly identify and validate ASD risk genes, which represent lead targets for neurobiological analyses and drug discovery. The long-term goal of the ASC is to make use of genetics to identify therapeutic targets in ASD, while contributing to translating such research findings to clinical practice. The overall objective of tis proposal is to rapidly identify ASD genes representing lead targets for high impact neurobiological studies and drug discovery. Our central hypothesis - formulated based on data with SNV, indels, and CNV, as well as review of medical genetic conditions in ASD and targeted sequencing in ASD - is that multiple independent rare variants account for a very significant proportion of risk to ASD. Our rationale for this proposal is that the identification of genetic variants conferring high-risk risk to ASD and associated neurodevelopmental disorders can form the bases of studies to understand pathogenesis as well as the bases for novel therapies. Moreover, such variants have direct implications for patients and their families in terms of etiological diagnosis, genetic counseling and patient care. These objectives will be accomplished with the following Specific Aims: 1) Maintain the infrastructure to support the ASC objectives; 2) Deploy pipelines for data cleaning and harmonization and variant calling; 3) Implement novel statistical methods for identifying ASD-associated genes; and, 4) Carry out whole-exome sequencing of 3,000 ASD subjects and parents. This contribution is significant because it represents the first step in research to understand pathogenesis of ASD and to the development of pharmacological strategies for treatment of core symptoms of ASD and etiologically related neurodevelopmental disorders. The research proposed in this application is innovative, in our opinion, because it involves an entirely new model of sharing data before publication, uses state-of-the-art methods for calling diverse types of variants in NGS data, incorporates novel methods for updating variant calling and sharing data, and includes highly innovative statistical methods to identify risk loci. This is a new and substantively different approach to gene discovery in ASD that departs significantly from the status quo and provides the means to achieve these important goals.
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