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 罕见遗传性疾病（RGD）为认知功能障碍的遗传结构提供了一个重要的窗口。 和行为变异。他们还提出了关于特发性和 认知和行为障碍的综合征形式，以及遗传背景在RGD表达中的作用。 此外，迄今为止，大多数遗传学研究都集中在欧洲血统的人群上，这意味着很少有研究结果是正确的。 已知其他人群中的RGD表达和变异性。为了弥补这些差距，我们将利用 正在进行的NeuroDev南非收集，以遗传和表型表征1，000名年龄 2-17，确定为自闭症谱系障碍、智力残疾/全面发育迟缓，以及 注意力缺陷多动障碍在开普敦。该系列还包括1,000例父母和 1,000个没有血缘关系的匹配对照组我们将对所有3，000名NeuroDev参与者进行遗传特征分析， 为了识别和调查NeuroDev样本中估计的300例RGD病例。我们建议使用 病历数据，以进一步表征所有NeuroDev病例，结合详细的 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的表型比较（例如维度认知障碍） 和行为数据、脑成像、听力学数据）。通过汇总数据，我们将比较表型 基于RGD和特发性神经精神疾病的特征，并突出分歧点， 在未来的研究中，以及在最终的治疗试验中解决异质性是有用的。最后我们 考虑到遗传背景在神经精神病学涉及的RGDs的可变表达性中的作用， 行为障碍和祖先变异的全基因组遗传风险。这些分析将 解决了关于RGDs的生物学和表达的几个关键问题，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.