Cross modal integration of molecular and physiological networks in ASD (2/2)

ASD 中分子和生理网络的跨模式整合 (2/2)

• 批准号: 9753368
• 负责人: Sergiu Pasca
• 金额: $ 79.59万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-21 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9753368
• 关键词: 3-Dimensional; Address; Animal Model; Area; Array tomography; Astrocytes; Autopsy; Behavior; Biological; Biological Assay; Biological Models; Biophysics; Brain; Brain Diseases; CRISPR/Cas technology; Calcium; Cells; Chromatin; Cognitive deficits; Collaborations; Complex; Computer Simulation; Data; Development; Disease model; Electric Stimulation; Electrodes; Engineering; Equilibrium; Face; Functional disorder; Gene Expression; Gene Proteins; Genes; Genetic; Genetic Engineering; Genetic Heterogeneity; Genetic Models; Genetic Risk; Genetic Transcription; Genetic Variation; Genomics; Glutamates; Human; Human Genetics; Image; Impairment; In Vitro; Individual; Interneurons; Investigation; Lead; Link; Measures; Mental disorders; Messenger RNA; Methodology; Modality; Modeling; Molecular; Morphology; Mutation; Nervous System Physiology; Neurobiology; Neuroglia; Neuronal Plasticity; Neurons; Optics; Organoids; Pathway interactions; Patients; Pattern; Phagocytosis; Phenotype; Physics; Physiological; Physiology; Principal Investigator; Property; Prosencephalon; Radial; Rattus; Research Personnel; Risk; Rodent; Rodent Model; Role; Stem cells; Structure; Synapses; Synaptosomes; Syndrome; System; Testing; Tissues; Untranslated RNA; Work; autism spectrum disorder; base; biophysical model; cell type; density; disorder risk; experimental study; fetal; flexibility; functional genomics; genetic approach; genetic architecture; genetic association; genetic risk factor; genetic variant; high risk; human disease; human model; human stem cells; immunocytochemistry; in vitro Model; in vivo; in vivo Model; induced pluripotent stem cell; innovation; migration; molecular pathology; network models; neurogenesis; neuropsychiatric disorder; novel; novel strategies; optogenetics; patch clamp; predictive modeling; predictive test; progenitor; relating to nervous system; risk variant; sequence learning; single cell analysis; synaptogenesis; theories; three dimensional cell culture; transcriptome sequencing; virtual reality

Genetic approaches have been successful in identifying causal genetic factors, both common and rare, that contribute to risk for autism spectrum disorder (ASD), providing a crucial starting point for mechanistic neurobiological investigations. However, moving towards an integrated mechanistic understanding of ASD at a molecular, cellular, and circuit level faces substantial challenges, such as extreme genetic heterogeneity and the lack of causal frameworks with which to connect different levels of analysis of nervous system function in model systems or patients. Nearly a decade ago, we reasoned that gene and protein networks would provide an organizing framework for understanding heterogeneous psychiatric disease genetic risk in a unified context and inform disease modeling; indeed there is now substantial evidence supporting convergence of major effect risk genes during mid-fetal cortical development. Furthermore, related functional genomic studies, including in those with a major gene form of ASD (dup)15q11-13, show shared patterns of transcriptional and chromatin dysregulation in post-mortem ASD brain, further supporting biological convergence. Where and how this occurs, and what biological mechanism(s) it reflects is not known. To address this, we propose an ambitious project that addresses several major challenges in establishing causal linkages between genetic risk and CNS structure and function in ASD. The work proposed in this multi-PI U01 involves a team of four principal investigators and co-investigators from UCLA and Stanford with the expertise necessary to perform this work using state of the art methodologies, ranging from developing and characterizing in vitro models of human brain development, stem cells, physiology, genomics, physics, and behavior. Through close collaboration, we will develop and analyze in vitro human stem cell based models that are differentiated from induced pluripotent stem cells and assembled into organized 3D brain cultures called human forebrain spheroids (hFS). These hFS contain the major cell classes of the developing forebrain, including progenitors, radial glia, cortical interneurons, glutamatergic neurons, and non-reactive astrocytes, and form functional synapses. We will model the effects of six major effect ASD risk loci in hFS with molecular, genomic, and physiological analyses to assess convergence at each level of analysis. We will also conduct comparisons of physiology using three rodent models based on the same genes modeled in vitro with the aim of integrating phenotypes to develop predictive models and compare with in vivo rodent models. We will analyze the relationship of molecular alterations and basic cellular and synaptic features with potential emergent or dynamic network features in control-derived hFS and compare these features with hFS harboring ASD risk mutations and test a subset of causal relationships based on network model predictions. Completion of these aims will lead to a more clear understanding of the power and limitations of model systems and computational models, while uncovering potential areas of convergence in different genetic forms of ASD.

遗传学方法已经成功地确定了常见和罕见的致病遗传因素， 有助于自闭症谱系障碍（ASD）的风险，为机械性 神经生物学研究然而，朝着ASD的综合机制理解， 分子、细胞和电路水平面临着巨大的挑战，如极端的遗传异质性 以及缺乏因果框架来连接神经系统的不同层次的分析 在模型系统或患者中发挥作用。大约十年前，我们推断基因和蛋白质网络 将提供一个组织框架，以了解异质性精神疾病的遗传风险， 统一的背景和通知疾病建模;事实上，现在有大量证据支持 在中期胎儿皮质发育过程中主要效应风险基因的会聚。此外，相关功能 基因组研究，包括ASD（dup）15 q11 -13主要基因形式的研究，显示了 转录和染色质失调在死后ASD大脑，进一步支持生物 收敛这种情况在哪里以及如何发生，以及它反映了什么生物学机制尚不清楚。到 为了解决这个问题，我们提出了一个雄心勃勃的项目，解决了建立因果关系的几个主要挑战， ASD中遗传风险与CNS结构和功能之间的联系。在此多PI U 01中提出的工作 包括来自加州大学洛杉矶分校和斯坦福大学的四名主要研究者和合作研究者， 有必要使用最先进的方法来执行这项工作，从开发和 表征人脑发育、干细胞、生理学、基因组学、物理学的体外模型， 行为通过密切合作，我们将开发和分析体外人类干细胞模型 从诱导多能干细胞分化而来，并组装成有组织的3D脑培养物， 称为人类前脑球状体（hFS）。这些hFS包含发育中的主要细胞类别， 前脑，包括祖细胞、放射状胶质细胞、皮质中间神经元、海马能神经元和非反应性神经元 星形胶质细胞，并形成功能性突触。我们将模拟六个主要影响ASD风险位点在hFS中的作用， 通过分子、基因组和生理分析来评估每个分析水平的收敛性。我们将 我还使用三种啮齿动物模型进行生理学比较，这些模型基于体外模拟的相同基因 目的是整合表型以开发预测模型并与体内啮齿动物模型进行比较。 我们将分析分子改变和基本的细胞和突触特征与潜在的 控制衍生hFS中的紧急或动态网络特征，并将这些特征与包含 ASD风险突变，并基于网络模型预测测试因果关系的子集。完成 这些目标的实现将使我们更清楚地了解模型系统的能力和局限性， 计算模型，同时揭示了不同遗传形式的ASD的潜在趋同领域。