Project 1: Identifying and optimizing monogenetic risk prediction for autism in newborns

项目总结 自闭症的遗传率估计为80%；因此，遗传学应该是治疗自闭症的有力工具。 预测患自闭症的风险。利用基因组测序进行新生儿筛查是一个平台，可以提供 在自闭症症状出现之前进行诊断--为早期干预提供机会，从而改善 自闭症的后果。除了这一提议，我们正在进行一项基因组的初步研究(卫报) 测序作为在纽约市多样化人口中进行传统新生儿筛查的新平台。在……里面 监护人，父母将可以选择接收至少100个单基因条件的结果，这些条件 基因变异对大脑和行为的影响具有很强的渗透性，平均约20% 携带风险变异的个体患有自闭症。患有单基因疾病和自闭症的人通常有 具有自我伤害行为的挑战，适应能力较差，独立性较差，并与 生活质量下降，家庭负担加重。目前还不清楚是什么因素决定了哪些人患有 单基因风险因素将发展为自闭症(包括其他罕见或常见的遗传变异或 其他因素)，以及是否有可能预测，在带有这些风险变异的婴儿中，谁会患上 自闭症，或许还能从行为干预中受益。用遗传学准确预测风险的关键是 识别所有风险基因和变异，并准确估计它们的影响大小。遗传的，罕见的，中等风险 个体小效应的变异和常见变异是聚集中自闭症风险的主要因素， 但这些基因或变异中的大多数还没有被识别出来。随着自闭症患者基因组数据的增加 包括斯帕克在内的队列，将有实质性的改进的能力，以更全面地理解 基因组结构，识别新的基因和变种，并量化这些变种的自闭症风险。在……里面 项目1，我们建议确定进展队列：一个多样化的新的自闭症高危新生儿 纽约市人口。我们将在《卫报》上对一大群(约100,000)新生儿进行筛查 并确定一组对高渗透性神经遗传具有单基因易感性的无偏见婴儿 增加自闭症风险的条件(IGR，N=400)，并在6小时内将这些遗传结果返回给父母 几个星期的生命。在卫报确认的这些婴儿中，240名将被同意参与项目2和3。我们将 确定120名无单基因风险(非IGR)婴儿的对照组。我们使用了大量的自闭症队列 将确定其他导致自闭症风险的基因和遗传变异，并测试遗传模型，包括 高、中、低风险基因变异和家族史，以开发综合基因组风险评分和 将其应用于我们对患有自闭症遗传风险(IGR)的新生儿的研究进展。未来者 对该队列的神经行为发育的评估(项目3)将为婴儿提供神经发育 将与复合基因组风险得分相结合的轨迹，以生成综合的自闭症风险 评分(项目1和项目3)。

PROJECT SUMMARY The heritability of autism has been estimated to be > 80%; therefore, genetics should be a powerful tool to predict risk of autism. Newborn screening using genomic sequencing is a platform that can deliver genetic diagnoses before autism symptoms emerge – providing the opportunity for early intervention which improves autism outcomes. Independent of this proposal, we are conducting a pilot study (GUARDIAN) of genome sequencing as a new platform for traditional newborn screening in a diverse New York City population. In GUARDIAN, parents will have the option to receive results for at least 100 monogenic conditions for which the genetic variants are highly penetrant for some impact on the brain and behavior, and on average ~20% of individuals with the risk variant have autism. The individuals with monogenic conditions and autism often have challenges with self-injurious behavior, have poorer adaptation, are less independent, and have associated lower quality of life and greater family burden. It is unclear what factors determine which of the individuals with the monogenic risk factor will develop autism (including other rare or common inherited genetic variants or other factors) and whether it is possible to predict, among infants with these risk variants, who will develop autism and perhaps benefit from behavioral interventions. The key to accurately predicting risk with genetics is to identify all risk genes and variants and precisely estimate their effect size. Inherited, rare, moderate-risk variants, and common variants of individually small effect are a major contributor to autism risk in aggregation, but the majority of these genes or variants have not been identified. As the genomic data increase in autism cohorts including SPARK, there will be substantially improved power to more completely understand the genomic architecture and identify new genes and variants and quantify the autism risk for these variants. In Project 1, we propose to identify the PROGRESS Cohort: newborns at high risk for autism in a diverse New York City population. We will screen a large (~100,000) population-based cohort of newborns in GUARDIAN and identify an unbiased group of infants with monogenic susceptibility to highly penetrant neurogenetic conditions that increase the risk of autism (IGR, N=400) and return these genetic results to parents within 6 weeks of life. Of these infants identified in GUARDIAN, 240 will be consented for Projects 2 and 3. We will identify a comparison group of 120 infants without monogenic risk (non-IGR). Using large autism cohorts we will identify additional genes and genetic variants that confer risk of autism and test genetic models including high, moderate, and low risk genetic variants and family history to develop a composite genomic risk score and apply it in our PROGRESS cohort of newborns at identified genetic risk (IGR) of autism. The prospective assessment of neurobehavioral development of this cohort (Project 3) will provide infant neurodevelopmental trajectories that will be combined with the composite genomic risk score to generate an integrated autism risk score (Projects 1 and 3).