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3/4 - The Autism Sequencing Consortium: Autism gene discovery in >20,000 exomes

3/4 - The Autism Sequencing Consortium: Autism gene discovery in >20,000 exomes
3/4 - 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
批准号:
8478295
负责人:
BERNIE DEVLIN
金额:
$27.65万
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 2016-07-31

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项目成果

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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取得了很大进展,但在被认为与ASD有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鉴定出来。下一代测序(NGS)已被证明可用于快速识别ASD的潜在变异,这种方法正在CA中进行。6,000个独立的ASD样本通过多项研究。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体为遗传咨询,了解发病机制和药物开发提供了机会。自闭症测序联盟(ASC)代表了20多个独立小组的协调努力,以快速识别和验证ASD风险基因,这些基因代表了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,同时将这些研究结果转化为临床实践。该提案的总体目标是快速鉴定ASD基因,这些基因代表高影响神经生物学研究和药物发现的主要靶点。我们的中心假设-基于SNV,indels和CNV的数据,以及对ASD中的医学遗传条件和ASD中的靶向测序的回顾-是多个独立的罕见变异占ASD风险的非常大的比例。我们提出这一建议的理由是,识别遗传变异赋予ASD和相关神经发育障碍的高风险风险,可以形成研究的基础,以了解发病机制以及新疗法的基础。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属有直接影响。这些目标将通过以下具体目标来实现:1)维护支持ASC目标的基础设施; 2)部署数据清理和协调以及变体调用的管道; 3)实施新的统计方法来识别ASD相关基因;以及4)对3,000名ASD受试者和父母进行全外显子组测序。这一贡献是重要的,因为它代表了研究的第一步,以了解ASD的发病机制和发展的药理学策略,治疗ASD的核心症状和病因相关的神经发育障碍。在我们看来,本申请中提出的研究是创新的,因为它涉及一种全新的出版前共享数据模型,使用最先进的方法来调用NGS数据中的不同类型的变体,采用更新变体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点。这是一种新的和实质上不同的方法来发现ASD中的基因,它与现状有很大的不同,并提供了实现这些重要目标的方法。
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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Fine-Mapping Genome-Wide Associated Loci using Multi-omics Data to Identify Mechanisms Affecting Serious Mental Illness
Fine-Mapping Genome-Wide Associated Loci using Multi-omics Data to Identify Mechanisms Affecting Serious Mental Illness
Fine-Mapping Genome-Wide Associated Loci using Multi-omics Data to Identify Mechanisms Affecting Serious Mental Illness
3/4 - The Autism Sequencing Consortium: Autism Gene Discovery in >50,000 Exomes
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