Genetic Investigation of Minimally Verbal Children with ASD

项目摘要/摘要 自闭症谱系障碍(ASD)的临床表现具有高度的异质性，这使得 诊断、预后和治疗。随着人们对自闭症的遗传基础越来越了解，我们正在 面临理解遗传风险如何转化为特定表型、轨迹和机制的挑战。这个 对言语最少(MV)的儿童进行深入的表型和治疗提供了一个独特的机会 确定潜在的遗传风险因素或预测因素，这是本遗传学项目的主要目标。此外， 将MV ASD队列添加到可用于分子研究的更广泛的自闭症家族集合中将 从整体上加强我们对ASD背后的遗传异质性的理解。这个项目将是 由加州大学洛杉矶分校的丹尼尔·格施温德博士和他的同事们进行的。我们假设 MV儿童可能代表了具有特征遗传特征的ASD的遗传同质性更高的队列。 与ASD相关的特定症状有特定的行为和认知特征，包括语言 表型(Barnett和van Bon，2015；D‘Angelo等人，2016；DiStefano等人，2016；Nikraasson等人，2009； Penagarikano和Geschind，2012；van Bon等人，2010)。此外，罕见的大效应新基因突变 更可能与更严重的表型有关，包括低智商和严厉的语言 损害(Geschind和Konopka，2009；Robinson等人，2014；Sanders等人，2015)。基因检测 使用微阵列和全外显子测序(WES)在评估ASD的临床意义上被认为是可行的 鉴定大效应致病拷贝数变异(CNV)和从头蛋白中断突变(JEST) 和Geschind，2014；Miller等人，2010；Schaefer等人，2008)。鉴于CNV的流行率是 与严重程度相关，例如，低智商和语言障碍的人可能有CNV的频率为 高达25%(Jacquemont等人，2006)，WES的收益率可能为10-20%，我们将使用SNP微阵列来 确定可能导致CNV和WE的原因，从而为部分患者提供“分子诊断”。我们 将评估基因组范围内常见基因变异导致的ASD易感性与 口述运动和听觉功能的量化测量(项目1和项目2)；言语和语言能力 (核心B)；以及对干预的反应(项目3)。我们假设基因图谱可能与 对语言干预的反应(项目3)，未来的目标是迈出第一步，实现 可能对前瞻性地将儿童置于最适当的干预中有用的预测因素。

PROJECT SUMMARY/ ABSTRACT Autism Spectrum Disorder (ASD) is highly heterogeneous in its clinical presentation, which complicates diagnosis, prognosis and treatment. As the genetic basis for ASD becomes increasingly understood, we are challenged to understand how genetic risk translates to specific phenotypes, trajectories and mechanisms. The deep phenotyping and treatment of children who are minimally verbal (MV) provides a unique opportunity to identify potential genetic risk factors or predictors, which is the major aim of this genetics project. Moreover, the addition of the MV ASD cohort to the broader collection of autism families available for molecular study will enhance our understanding of the genetic heterogeneity underlying ASD as a whole. This project will be undertaken by Daniel Geschwind, MD, PhD, and his colleagues at UCLA. We hypothesize that subgroups of MV children may represent genetically more-homogeneous cohorts of ASD with characteristic genetic profiles. Specific syndromes associated with ASD have specific behavioral and cognitive profiles, including language phenotypes (Barnett and van Bon, 2015; D'Angelo et al., 2016; DiStefano et al., 2016; Niklasson et al., 2009; Penagarikano and Geschwind, 2012; van Bon et al., 2010). Further, rare, large effect size de novo mutations are more likely to be associated with more severe phenotypes, including low IQ and severe language impairment (Geschwind and Konopka, 2009; Robinson et al., 2014; Sanders et al., 2015). Genetic testing using microarrays and whole-exome sequencing (WES) is clinically indicated in the evaluation of ASD to identify large effect pathogenic copy number variants (CNV) and de novo protein disrupting mutations (Jeste and Geschwind, 2014; Miller et al., 2010; Schaefer et al., 2008). Given that the prevalence of CNV is associated with severity, e.g., those with low IQ and language impairment may have a frequency of CNV as high as 25% (Jacquemont et al., 2006) and the yield of WES is likely 10-20%, we will use SNP microarrays to identify likely causal CNVs and WES, thereby providing a “molecular diagnosis” for a subset of patients. We will evaluate the correlation between ASD liability due to common genetic variation genome-wide and quantitative measures of oromotor and auditory functioning (Projects 1 and 2); speech and language ability (Core B); and response to intervention (Project 3). We hypothesize that genetic profile may correlate with response to language intervention (Project 3), with the future goal of taking a first step toward generating predictors that may be useful to prospectively place children into the most appropriate interventions.