Washington University Intellectual and Developmental Disabilities Research Center-Administrative Down Syndrome Supplement

摘要 唐氏综合征(DS，21三体)是智力和发育最常见的遗传原因 残疾(IDD)，但导致特定认知缺陷的细胞和分子异常不是 定义得很清楚。虽然DS患者都有相同的智力残疾的遗传原因(21三体)， 在患者群体中，认知功能有相当大的变异性。此外，虽然几十年来 数据表明，皮质中间神经元是人类DS中一个脆弱的神经元群体，它们的 干扰可能与DS患者的认知功能改变有关，关于如何改变的数据非常有限 中间神经元特征的改变和功能障碍导致DS。在这里，为了应对这些挑战，我们 建议从深表型DS建立患者来源的诱导多能干细胞(IPSC)模型 根据认知能力进行分层的个人(目标1)。这些模型将提供有价值的 DS研究社区的资源，将用于表型和数据的跨站点复制 两个智力和发育障碍的细胞模型单元进行的Meta分析 研究中心(IDDCs)，提高整个网络中IDD细胞建模的严密性和重复性。 在目标2和目标3中，我们将识别反映认知能力差异的细胞和分子签名： 从这些DS患者的IPSCs分化出的中间神经元将被分析以寻找特定的细胞缺陷，以及 通过探索性转录分析，鉴定细胞表型和分子特征 区分高认知功能和低认知功能的DS患者。这些实验的结果将 确定可在未来项目中利用的与患者相关的做作贡献者，以确定潜在的 DS的治疗靶点。 这项工作综合了IDDRC@WUSTL Parent U54授权的主要指令，以阐明 IDDS的中间表型，趋同致病机制的功能基因组发现，以及 在IDDRC@WUSTL和整个IDDRC建设IDDS细胞模型的能力 网络。这一合作还有助于正在进行的由这些联合调查员领导的跨国际发展研究中心倡议， 为IDD研究建立共享的细胞建模资源，包括交叉IDDRC校准方法和 基准、新的IDD模型，以及IDDRC支持的IDD细胞模型的生物和数据存储库。 这些举措将在国际数据和发展中心之间建立国际数据共享和数据综合分析的能力 整个网络的调查人员，增强了这一项目和其他研究项目的影响，并将 促进融合的中间表型、途径和分子靶标的识别 不同的IDD型号。这些模型提供了一种可再生的、可共享的资源，由此改变的过程， 在本项目中确定的路径和目标可以作为使用这些模型的未来工作的基础 与化学和分子筛选相结合，以确定潜在的干预措施。

ABSTRACT Down syndrome (DS, trisomy 21) is the most common genetic cause of intellectual and developmental disability (IDD), but the cellular and molecular abnormalities that contribute to specific cognitive deficits are not well defined. Although DS individuals all have the same genetic cause of intellectual disability (trisomy 21), there is considerable variability in cognitive function across the patient population. In addition, while decades of data indicate that cortical interneurons are a vulnerable neuronal population in human DS and that their perturbation may be linked to altered cognitive function in DS patients, there is very limited data regarding how altered interneuron characteristics and dysfunction contribute to DS. Here, to address these challenges, we propose to build patient-derived induced pluripotent stem cell (iPSC) models from deeply phenotyped DS individuals who have been stratified based on cognitive ability (Aim 1). These models will provide a valuable resource for the DS research community, and will be used for cross-site replication of phenotypes and data meta-analyses conducted by the Cellular Modeling Units of two Intellectual and Developmental Disabilities Research Centers (IDDRCs), enhancing rigor and reproducibility of IDD cellular modeling across the network. In Aims 2 and 3, we will identify cellular and molecular signatures that reflect differences in cognitive ability: interneurons differentiated from these DS patient iPSCs will be analyzed for specific cellular defects, as well as through exploratory transcriptomic analysis, to identify cellular phenotypes and molecular signatures that distinguish DS individuals with high versus low cognitive functioning. Results from these experiments will define patient-relevant contributors to affectation that can be exploited in future projects to identify potential therapeutic targets for DS. This work integrates major directives of the IDDRC@WUSTL parent U54 grant in elucidation of intermediate phenotypes for IDDs, functional genomic discovery of convergent pathogenic mechanisms, and building of capacity for cellular modeling of IDDs, both at the IDDRC@WUSTL and throughout the IDDRC network. This collaboration also contributes to ongoing cross-IDDRC initiatives, led by these co-Investigators, to build shared cellular modeling resources for IDD research, including cross-IDDRC calibrated methods and benchmarks, new IDD models, and IDDRC-supported bio- and data-repositories for IDD cellular models. These initiatives will build capacity for IDD resource sharing and meta-analysis of data among IDDRC investigators throughout the network, enhancing the impact of this and other research projects, and will facilitate identification of convergent intermediate phenotypes, pathways, and molecular targets across different IDD models. These models provide a renewable, sharable resource, whereby the altered processes, pathways, and targets that are identified in this project can serve as a basis for future work using these models in combination with chemical and molecular screening to identify potential interventions.