Alzheimer's Disease-Related Dementia Models by Precision Editing and Relevant Genetic x Environmental Exposures

项目总结 阿尔茨海默氏症是老年人痴呆症最常见的原因，但还有许多其他原因 相关痴呆在行为、认知和神经病理上表现出很大的重叠 这种疾病的表现。事实上，大多数痴呆症病例很可能是由一个共同发生的 或更多这样的AD和AD相关的病理，很少有人表现出‘纯粹的’阿尔茨海默氏症 病理学(例如，只有淀粉样斑块)。这种复杂性使得诊断和治疗的发展 具有挑战性的是，ADRD缺乏准确的动物模型，这加剧了这个问题 概述了这些疾病的分子、细胞、认知和行为病理的全部范围 痴呆症。作为对PAR-19-167的回应，我们将创建一个遗传多样性的转基因小鼠小组，这些小鼠拥有 使用精确的基因组编辑来确保与AD和几种相关痴呆相关的已知突变 与生物相关的基因表达模式和水平。在目标1中，我们将使用CRISPR/Cas9创建小鼠 携带App、PSEN1、MAPT、TardBP和SNCA致病突变的组合，以产生一组 我们希望能更好地捕捉到ADRD的复杂性。捕捉遗传背景的作用 在疾病风险方面，我们将把这些“核心”小鼠交叉到四个已知的遗传背景中，以促进 ADRD的易感性或恢复力(DBA/2J、FVB/NJ、WSB/EIJ和C57BL/6J)。然后我们将利用我们的 在高通量小鼠神经行为表型方面的专业知识，以筛选16个新的ADRD菌株进行鉴定 这些线条是ADRD最好的造型。在目标2中，我们将使用我们的深度表型管道来充分描述我们的 ADRD相关症状的整个范围内的顶级压力，包括认知和非认知 域名。我们还将使用高场磁共振、组织病理学测量和分子表型来 评估对大脑结构、神经病理程度的影响，以及对基因网络和通路的影响 与疾病相关的。最后，在目标3中，我们将验证我们的新模型在基础科学和 通过确定老鼠和人类数据之间的一致性并使用网络建模进行临床前研究 识别疾病的早期驱动因素的方法，预测人类的晚期结果。这个项目将 为AD和相关痴呆症制作急需的新模型，这将极大地提高我们对 这些疾病背后的病理机制。最后，这里生产的所有模型都将是 通过JAX存储库分发给社区。我们还将公开所有的表型数据 使用鼠标表现组数据库、GeneWeaver和Synapse等资源可用。

PROJECT SUMMARY Alzheimer’s disease is the most common cause of dementia in the elderly, but there are a number of other related dementias that exhibit substantial overlap in the behavioral, cognitive, and neuropathological manifestations of the disease. In fact, the majority of dementia cases likely arise from the co-occurrence of one or more of these AD and AD-related pathologies, with very few individuals exhibiting ‘pure’ Alzheimer’s pathology (e.g., only amyloid plaques). This complexity makes diagnosis and therapeutic development challenging, a problem exacerbated by a paucity of accurate animal models for ADRD that faithfully recapitulate the full spectrum of the molecular, cellular, cognitive, and behavioral pathologies of these dementias. In response to PAR-19-167, we will create a panel of genetically diverse knock-in mice harboring known mutations associated with AD and several related dementias using precise genomic editing to ensure biologically-relevant gene expression patterns and levels. In Aim 1, we will use CRISPR/Cas9 to create mice carrying combinations of disease-causing mutations in App, Psen1, Mapt, Tardbp, and Snca to produce a set of ‘core’ strains we expect to better capture the complexity of ADRD. To capture the role of genetic background in disease risk, we will then cross these ‘core’ mice to four genetic backgrounds known to promote susceptibility or resilience of ADRD (DBA/2J, FVB/NJ, WSB/EiJ, and C57Bl/6J). We will then leverage our expertise in high-throughput mouse neurobehavioral phenotyping to screen 16 new ADRD strains to identify the lines that best model ADRD. In Aim 2, we will use our deep phenotyping pipeline to fully characterize our top strains across the entire spectrum of ADRD-related symptoms, including both cognitive and non-cognitive domains. We will also use high-field MRI, histopathological measurements, and molecular phenotypes to assess effects on brain structure, extent of neuropathologies, and impact on gene networks and pathways associated with disease. Finally, in Aim 3, we will validate our new models for use in basic science and preclinical studies by determining concordance between mouse and human data and use network modeling approaches to identify early drivers of disease that predict late-stage outcomes in humans. This project will produce much-needed new models for AD and related dementias that will greatly enhance our understanding of the pathological mechanisms underlying these diseases. Finally, all of the models produced here will be distributed to the community via the JAX Repository. We will also make all of the phenotyping data publicly available using resources such as Mouse Phenome Database, GeneWeaver, and Synapse.