2/3 Multidimensional investigation of the etiology of autism spectrum disorder

2/3 自闭症谱系障碍病因的多维调查

• 批准号: 9320767
• 负责人: KATHRYN M ROEDER
• 金额: $ 19.28万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9320767
• 关键词: 16p11.2; Affect; Autistic Disorder; Biological; Biological Models; Biological Process; Brain; Brain region; CRISPR/Cas technology; Cells; ChIP-seq; Clustered Regularly Interspaced Short Palindromic Repeats; Collaborations; Computing Methodologies; Copy Number Polymorphism; Data; Data Set; Development; Disease; Etiology; Female; Fetal Development; Functional disorder; Gene Expression; Gene Expression Regulation; Genes; Genetic; Genomics; Human; Human Genome; Impairment; Inherited; Investigation; Lead; Life; Literature; Methods; Molecular; Mus; Mutation; Neurodevelopmental Disorder; Pathology; Pathway interactions; Phenotype; Point Mutation; Population; Positioning Attribute; Prefrontal Cortex; Primates; Process; Public Health; Publishing; Risk; Seeds; Sex Bias; Source; Statistical Methods; Systems Biology; Technology; Testing; Transcript; Variant; Work; autism spectrum disorder; base; brain tissue; case control; cell type; convict; developmental neurobiology; early onset; exome sequencing; experimental study; gene discovery; genome editing; genome sequencing; genomic data; human female; human genomics; induced pluripotent stem cell; insight; interest; loss of function; male; novel; protein protein interaction; public health relevance; relating to nervous system; repetitive behavior; risk variant; sex; sexual dimorphism; social communication; spatiotemporal; statistics; targeted sequencing; transcriptome sequencing; whole genome

 DESCRIPTION (provided by applicant): Autism Spectrum Disorder (ASD) is characterized by impairments in social communication and restricted or repetitive behavior or interests. The application of genomic technologies has led to the identification of many of the genes underlying ASD, presenting the opportunity to assess the insight these risk genes can give into the etiology of ASD. In this proposal we aim to: 1) Generate a list of ASD-associated genes; 2) Identify points of convergence between these genes in biological data (e.g. gene regulation and expression); and 3) Validate these points of convergence in model systems. Since ASD is a human neurodevelopmental disorder we will prioritize biological data that is collected longitudinally across development from human brain tissue. In our prior work we have demonstrated that de novo mutations, specifically copy number variants (CNVs) and loss of function (LoF) point mutations, are strongly associated with ASD. Furthermore, these mutations cluster at ASD risk genes and loci in cases but not in controls. By comparing the distribution of these mutations between cases and controls we can identify the points of mutational clustering that represent ASD risk loci (e.g. CNVs at the 500kbp 16p11.2 locus and LoFs at the gene CHD8). We have developed a statistical framework to assess this clustering as well as incorporating evidence from inherited variants and case-control data. This framework is called the Transmitted and De novo Associated Test (TADA). In Aim 1 we will develop this test further to incorporate all the available CNV, exome, genome, and targeted sequencing data into a single ASD gene list, ranked by the degree of ASD association. Previously we used the top nine ASD risk genes as seeds for gene co-expression networks and assessed the validity of these networks by their ability to incorporate 120 independent ASD risk genes. By limiting the co- expression input data to narrow windows of development and specific brain regions we could identify the spatiotemporal networks with the greatest enrichment, for example pre-frontal cortex in mid-fetal development. In Aim 2, we propose a similar approach, but using the DAWN (Detecting Association With Networks) method developed by our group. DAWN uses the narrow windows of co-expression data as before, but is able to incorporate evidence from other datasets such as gene regulation, and protein-protein interaction (PPI). By seeding the DAWN networks with the highest confidence genes we will assess the spatiotemporal networks that best predict other ASD genes. ASD shows a significant sex bias implicating an interaction between ASD etiology and sexually dimorphic factors. Building on our work of identifying sexually dimorphic transcripts in the developing human brain we will test their enrichment within specific networks identified by DAWN. To validate the ASD-associated networks, in Aim 3 we will identify the gene that best represents each network and assess if disrupting it also disrupts the other genes within the network. We will disrupt each gene using CRISPR/Cas9 in both mice and human-derived iPSCs and assess the genes disrupted using RNA-Seq.

 描述（应用程序提供）：自闭症谱系障碍（ASD）的特征是社会交流和限制或重复行为或利益的损害。基因组技术的应用导致鉴定了ASD基因的许多基因，从而提供了评估这些风险基因的见解的机会，可以赋予ASD的病因。在此提案中，我们的目标是：1）生成与ASD相关基因的列表； 2）在生物学数据中识别这些基因之间的收敛点（例如基因调节和表达）； 3）在模型系统中验证这些收敛点。由于ASD是人类神经发育障碍，因此我们将优先考虑在人类脑组织中纵向收集的生物学数据。在我们的先前工作中，我们证明了从头突变，特别是拷贝数变体（CNV）和功能丧失（LOF）点突变与ASD密切相关。此外，这些突变聚集在ASD风险基因和基因座的情况下，但不在对照中。通过比较病例和对照之间的这些突变的分布，我们可以识别代表ASD风险位置的突变聚类点（例如，在500Kbp 16p11.2基因CHD8处的500Kbp 16p11.2基因座和LOFS）。我们已经开发了一个统计框架来评估这种聚类以及从继承的变体和病例对照数据中编码证据。该框架称为传输和从头相关的测试（TADA）。在AIM 1中，我们将进一步开发该测试，以将所有可用的CNV，外显子，基因组和靶向测序数据纳入单个ASD基因列表，并按ASD关联程度排名。以前，我们使用前九种ASD风险基因作为基因共表达网络的种子，并通过结合120个独立ASD风险基因的能力来评估这些网络的有效性。通过将共表达数据限制为狭窄的开发窗口和特定的大脑区域，我们可以识别具有最大富集的空间临时网络，例如中型开发中的前额叶皮层。在AIM 2中，我们提出了一种类似的方法，但是使用我们小组开发的黎明（检测与网络的检测关联）。黎明像以前一样使用狭窄的共表达数据窗口，但是ASD显示出明显的性偏见暗示了ASD病因与性二态因素之间的相互作用。在我们识别发展中人脑的性二态转录本的工作的基础上，我们将在黎明确定的特定网络中测试它们的富集。为了验证与ASD相关的网络，在AIM 3中，我们将确定最能代表每个网络的基因并评估它，如果破坏它也会破坏网络中的其他基因。我们将在小鼠和人类衍生的IPSC中使用CRISPR/CAS9破坏每个基因，并评估使用RNA-Seq中断的基因。