Population-Based Autism Genetics and Environment Study

虽然在阐明自闭症谱系障碍的遗传因素方面取得了巨大的进展，但它 遗传和非遗传风险因素如何结合以及它们如何塑造社会严重程度在很大程度上是未知的 沟通和认知缺陷。这一差距可以通过发展全面责任来弥补。 模型使用基于人群的流行病学样本，具有密集的遗传和表型数据。为了填满这个 GAP，我们开发了基于人群的自闭症遗传学和环境研究(PAGE)，涉及 瑞典流行病学队列通过确定患有DSM-IV自闭症(AD)的样本而获得， 捕获受影响更严重的个体，从7000多个基于人口的全国性样本中挑选出来 活着的个体。对AD流行病学样本中的风险进行建模提供了对 由常见和罕见的基因变异传递的风险。这项研究还显示，~40%的人仍然 下落不明。结合关键环境变量(父亲和母亲的年龄、孕产史) 而表型数据(智商、自闭症严重程度、家族精神病史)和遗传性的测量是完全 了解自闭症的易感性。我们现在建议通过追求以下具体目标来加强PAGE：1) 对至少1 500例新增病例进行招募、分型和排序，其中包括1 350例受影响较轻的病例 2)研究常见和罕见的基因变异与自闭症严重程度和认知功能的关系；3) 确定ASD的其他假定风险来源如何分布与ASD严重程度和 认知功能，以及，4)通过分析全外显子序列数据发现ASD的危险基因和 通过全基因组关联研究确定常见的风险变异。我们希望承担责任 整合遗传和环境风险因素并考虑表型复杂性的模型 沿着两个核心维度：社会缺陷的严重性和认知功能。在我们看来，这一点意义重大 因为它允许我们：1)研究表型群体在所有尺度上罕见的遗传变异；2)理解 多基因风险和高渗透性罕见变异在表型组之间的相互作用；3)测量 遗传力和环境影响根据表型变异；以及，4)定义家庭负担， 包括遗传性和非遗传性。在我们看来，我们的研究是创新的，因为它探索了 风险，包括遗传和非遗传，在基于人群的队列中，并引入表型变异性作为 额外的维度。它也是创新的，因为它结合了遗传(加性和罕见的遗传)变异， 父母年龄和精神障碍家族史来评估家庭负担，同时介绍小说 基因分析的工具和方法。这是处理自闭症责任的全新方式，与 目前的研究将为自闭症风险因素及其相互作用提供新的见解，以确定 表型，从而为临床风险评估、预防和临床护理开辟了新的途径。

While enormous progress has been made in elucidating genetic factors underlying autism spectrum disorder, it is largely unknown how genetic and non-genetic risk factors integrate and how they shape severity of social communication and cognitive deficits. This gap can be addressed by developing comprehensive liability models using a population-based epidemiological sample with dense genetic and phenotypic data. To fill this gap, we have developed the Population-based Autism Genetics and Environment Study (PAGES), involving a Swedish epidemiological cohort obtained by ascertaining samples with DSM-IV autistic disorder (AD), which captures more severely affected individuals, chosen from a national, population-based sample of over 7,000 living individuals. Modeling liability in the epidemiological sample of AD has provided accurate estimates of the risk conveyed by common and rare genetic variation. This study has also revealed that ~40% is still unaccounted for. Combining critical environmental variables (paternal and maternal age, gestational history) and phenotyping data (IQ, autism severity, family psychiatric history) with measures of heritability is key to fully understand autism liability. We now propose to strengthen PAGES by pursuing the following specific aims: 1) To recruit, genotype and sequence at least 1,500 additional cases, including 1,350 less severely affected individuals; 2) To study common and rare genetic variation in relation to ASD severity and cognitive function; 3) To determine how other sources of putative risk for ASD are distributed in relation to ASD severity and cognitive function, and, 4) To discover risk genes for ASD by analysis of whole-exome sequence data and identify common risk variation by genome-wide association study (GWAS). We expect to contribute liability models that integrate genetic and environmental risk factors and take into account the phenotypic complexity along two core dimensions: severity of social deficits and cognitive function. In our opinion, this is significant because it allows us to: 1) study rare genetic variation at all scales across phenotypic groups; 2) understand the interplay between polygenic risk and highly penetrant rare variants across phenotypic groups; 3) measure heritability and environmental influences in light of phenotypic variability; and, 4) define the familial burden, both genetic and non-genetic. In our opinion, our study is innovative because it probes specific components of risk, both genetic and non-genetic, in a population-based cohort and introduces phenotypic variability as an additional dimension. It is also innovative because it combines genetic (additive and rare inherited) variation, parental age, and family history of psychiatric disorder to assess the familial burden, while introducing novel tools and approaches to genetic analyses. This radically new way of tackling ASD liability, compared with current studies, will provide novel insights into autism risk factors and their interactions in determining phenotype, thus opening new avenues for clinical assessment of risk, prevention and clinical care.