Population-Based Autism Genetics and Environment Study

项目摘要/摘要 虽然在了解自闭症的风险架构方面取得了很大进展，但仍有 关于自闭症的遗传和非遗传风险的性质的问题尚未得到回答。其中许多 以人口为基础的流行病学样本和详细的人口统计学样本可以最好地解决问题 和环境信息。到目前为止，几乎所有关于自闭症病因的研究都依赖于便利性 样本在捕捉遗传风险方面容易产生偏差，甚至可能更容易受到环境风险的影响。 基于流行病学的样本提供了一种独特的资源来确定遗传和非遗传原因 自闭症，同时允许准确地估计人口中的风险归因于每个风险来源。瑞典 受益于作为大规模流行病学研究基础的集中式医疗系统 精神障碍，特别是精神分裂症和双相情感障碍。在我们看来，这一点的意义 建议在于独特的、以人口为基础的流行病学样本的价值，其分析方式如下 解决自闭症的几个突出问题。这些措施包括：1)更好地估计遗传力和环境 在自闭症中？2)评估自闭症的复发风险CNV的比率？3)发现罕见的常备单核苷酸 自闭症的变异？4)非遗传发现与自闭症关联的潜在机制剖析-- 以及新的环境关联的发现？以及，5)交叉无序分析以更好地理解 自闭症和精神分裂症的共同风险。目标是：1)查明并保存至少1300个病例 与自闭症障碍和1000个额外的控制，为自闭症开发一个国际资源，并评估 选定的、可能的风险因素？2)使用高密度SNP阵列对所有样本进行分型，包括密集SNP 外显子组覆盖范围，并使用完整外显子组方法对所有三个组进行测序？以及，3)使用新方法来 评估遗传和从属变异在自闭症中的作用，并评估自闭症中罕见的常态变异， 同时整合关键环境变量。在后来的几年中，自闭症风险和 将对精神分裂症进行评估。在我们看来，拟议的研究是创新的，因为它确定了 以流行病学有效的方式提供自闭症样本，目标人群为基因相同的人群， 精神分裂症和躁郁症的样本已经收集完毕。该提案在使用 新的方法来估计遗传力和识别罕见的、具有自闭症风险的常备变异，而 为自闭症的遗传学和环境提供了一个完整的模型。最后，该应用程序是创新的，在 我们的观点是，它为理解自闭症和精神分裂症的共同风险提供了基础， 利用同质群体拥有更强的识别共同风险的能力。这一新的和实质性的 研究自闭症的不同方法，与在方便的样本中进行的研究相比， 自闭症研究中的许多悬而未决的问题，并提供了一条更好地理解风险的途径 自闭症的因素，并最终对自闭症进行更好的干预。

Project Summary/Abstract While there has been great progress in understanding the risk architecture of autism, there are still unanswered questions about the nature of the genetic and non­genetic risk for autism. Many of these questions can be best addressed with a population­-based epidemiological sample with detailed demographic and environmental information. To date, almost all studies on the etiology of autism relied on convenience samples, which are subject to biases in capturing genetic and, possibly even more so, environmental risk. Epidemiologically based samples provide a unique resource to identify genetic and non­genetic causes of autism, while allowing for a precise estimate of risk in the population attributed to each source of risk. Sweden benefits from a centralized medical system that has been the foundation of large­scale epidemiological studies in psychiatric disorders, particularly schizophrenia and bipolar disorder. In our opinion, the significance of this proposal lies in the value of a unique, population-­based epidemiological sample, analyzed in such a way as to address several outstanding issues in autism. These include: 1) Better estimates of heritability and environment in autism? 2) assessing the rate of recurrent risk CNV in autism? 3) discovery of rare standing single nucleotide variation in autism? 4) dissection of mechanisms underlying the association of non-genetic findings with autism – and the discovery of novel environmental associations? and, 5) cross-­disorder analyses to better understand shared liability to autism and schizophrenia. The aims are: 1) To ascertain and biobank at least 1300 cases with autistic disorder and 1000 additional controls, to develop an international resource for ASD, and to assess selected, putative risk factors? 2) To genotype all samples using high­-density SNP arrays, including dense exome coverage, and sequence all trios using whole ­exome approaches? and, 3) To use novel methods to assess the role of inherited and de novo variants in autism and to evaluate rare standing variation in autism, while integrating key environmental variables. In later years the relationship between autism risk and risk for schizophrenia will be assessed. The proposed research is innovative, in our opinion, because it ascertains autism samples in an epidemiologically-­valid manner, targeting a genetically homogenous population, for which schizophrenia and bipolar samples have already been collected. The proposal is also innovative in the use of novel methods to estimate heritability and to identify rare, standing ­variation conferring risk to autism, while providing an integrated model for genetics and environment in autism. Finally, the application is innovative, in our opinion, in that it provides the groundwork for understanding shared risk across autism and schizophrenia, making use of a homogenous group to have better power to identify shared risk. This new and substantively different approach to studying autism, compared to studies carried out in convenience samples, addresses many of the open questions in autism research and provides a path towards a better understanding of the risk factors for autism and ultimately to better interventions in autism.