Rare genetic disorders in NeuroDev: Insight into the genetic and phenotypic heterogeneity of ID, ASD and ADHD in South African Populations

项目摘要 罕见遗传病(RGD)为研究认知能力的遗传结构提供了一扇重要的窗口 和行为变异。他们还对特发性和先天性心脏病之间的关系提出了疑问。 认知和行为障碍的症状形式，以及遗传背景在RGD表达中的作用。 此外，到目前为止，大多数基因研究都集中在欧洲血统的人群上，这意味着很少有 已知RGD在其他人群中的表达和变异性。为了解决这些差距，我们将利用 正在进行的NeuroDev南非收集将从基因和表型上表征1,000名儿童 2-17，确诊为自闭症谱系障碍、智力残疾/全球发育迟缓，以及 开普敦的注意力缺陷多动障碍。该收藏还包括1,000名案例父母和 1000名无血缘关系、血统匹配的对照。我们将对所有3,000名NeuroDev参与者进行基因特征分析 以确定和调查NeuroDev样本中估计的300例RGD病例。我们建议使用 医疗记录数据，以进一步表征所有NeuroDev病例，与详细的 作为核心收集活动的一部分收集的表型数据，将为 基于RGD的和特发性神经精神障碍(例如空间认知)的表型比较 和行为数据、脑成像、听力学数据)。利用聚合数据，我们将比较表型 基于RGD的和特发性神经精神障碍的特征和突出的分歧点，这将 有助于在未来的研究以及最终的治疗试验中解决异质性问题。最后，我们 考虑遗传背景在神经精神受累的RGDS的可变表达中的作用 行为障碍的全基因组遗传风险和祖先变异的术语。这些分析将 解决有关RGD的生物学和表现的几个关键问题，以及它们与 认知和行为障碍。这些数据的广泛共享将允许在实地进行进一步调查- 宽阔的水平。

Project Summary Rare genetic disorders (RGDs) have provided a significant window into the genetic architecture of cognitive and behavioral variation. They have also posed questions about the relationship between idiopathic and syndromic forms of cognitive and behavioral disorders, and the role of genetic background in RGD expression. Further, most genetic studies to date have focused on populations of European ancestry, meaning little is known about RGD expression and variability in other populations. To address these gaps, we will leverage the ongoing NeuroDev South Africa collection to genetically and phenotypically characterize 1,000 children aged 2-17, ascertained for Autism Spectrum Disorders, Intellectual Disability/Global Developmental Delay, and Attention Deficit Hyperactive Disorder in Cape Town. The collection also includes 1,000 case parents and 1,000 unrelated, ancestry-matched controls. We will genetically characterize all 3,000 NeuroDev participants in order to identify and investigate an estimated 300 RGD cases in the NeuroDev sample. We propose to use medical record data to further characterize all NeuroDev cases which, in conjunction with the detailed phenotype data collected as part of the core collection activity, will create uncommon opportunities for the phenotypic comparison of RGD-based and idiopathic neuropsychiatric disorders (e.g. dimensional cognitive and behavioral data, brain imaging, audiology data). With the aggregated data, we will compare the phenotypic features of RGD-based and idiopathic neuropsychiatric disorders and highlight points of divergence, which will be useful for addressing heterogeneity in future research, as well as in eventual treatment trials. Lastly, we consider the role of genetic background in the variable expressivity of neuropsychiatrically-involved RGDs, in terms of both genome-wide genetic risk for behavioral disorders and ancestral variation. These analyses will address several critical questions about the biology and presentation of RGDs, as well as their relationship to cognitive and behavioral disorders. The wide sharing of these data will permit further investigation at the field- wide level.