Decoding the Multifactorial Etiology of Neural Network Dysfunction in Alzheimer's Disease

解读阿尔茨海默病神经网络功能障碍的多因素病因

• 批准号: 10461839
• 负责人: YADONG HUANG
• 金额: $ 461.1万
• 依托单位: J. DAVID GLADSTONE INSTITUTES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-15 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10461839
• 关键词: Address; Algorithms; Alzheimer like pathology; Alzheimer' s Disease; Alzheimer' s disease brain; Alzheimer' s disease therapeutic; Amino Acid Sequence; Amino Acid Substitution; Amyloid beta-Protein; Apolipoprotein E; Autopsy; Behavior; Behavioral; Biochemical; Bioinformatics; Biological Assay; Brain; Cell Nucleus; Cells; Cognitive deficits; Communities; Complex; Data; Data Science Core; Data Set; Databases; Development; Disease; Disease Progression; Electrophysiology (science); Ensure; Epilepsy; Etiology; Experimental Designs; Functional disorder; Goals; Histopathology; Human; Hyperactivity; Impaired cognition; Infection; Interneurons; Intervention; Lead; Link; Modeling; Molecular; Mus; Nature; Neuroglia; Neurons; Neurosciences; Pathogenesis; Pathologic; Pathway interactions; Patients; Phenotype; Protein Isoforms; Public Health; Research; Research Activity; Role; Statistical Models; Stress; System; Systems Biology; Therapeutic; Therapeutic Intervention; Transgenic Organisms; Ursidae Family; Validation; Virulence Factors; apolipoprotein E-4; behavior test; brain dysfunction; brain tissue; cell type; cohesion; cohort; data harmonization; diverse data; drug development; epigenomics; experimental study; familial Alzheimer disease; human data; human tissue; improved; in vivo; innovation; insight; knock-down; mouse model; network dysfunction; neural network; neuromechanism; neuropathology; neurophysiology; novel; novel strategies; novel therapeutic intervention; overexpression; prevent; programs; research and development; tau Proteins; transcriptomics; working group

OVERALL – SUMMARY Alzheimer’s disease (AD) is a major unresolved public health problem. Efforts to prevent or stall this disease have failed, in good part because of inadequate understanding of its complex pathogenesis. Mounting evidence suggest that neural network dysfunction may underlie or promote AD-related cognitive deficits and contribute to disease progression. Yet, the causes and consequences of this dysfunction and the therapeutic potential of counteracting it remain sorely understudied. Therefore, the overarching goal of this program project is to decode the multifactorial etiology of AD-related neural network dysfunction and to leverage the novel mechanistic insights we will gain toward the development of better therapeutic strategies. Through collaborative interactions among four projects and two cores, our program will use systems neuroscience (neurophysiology and behavior) in combination with systems biology (single-cell transcriptomics and epigenomics), as well as neuropathology and improved mouse models, to determine how copathogenic interactions among apolipoprotein (apo) E4, amyloid-b (Ab), and tau cause neural network dysfunctions and cognitive decline in AD. An Administrative Core will coordinate all activities. Projects 1–3 will use novel mouse models of sporadic and familial AD to study interactions of different apoE isoforms with wildtype (WT) human tau (Project 1) or APP/Ab (Project 2), or among apoE4, Ab, and tau that is WT or bears disease-associated amino acid substitutions (Project 3). Project 4 will carry out single-nucleus transcriptomic and epigenomic analyses on postmortem brain tissues from deeply phenotyped human AD cases to gain novel insights into the multifactorial etiology of the human condition, validate leads from mouse studies, and encourage backtranslation into the models. An Integrative Data-Science Core will help us integrate results from all projects through innovative statistical modeling. This approach will reveal which aspects of human AD are most faithfully reproduced in the mouse models and help establish the causal drivers of cell-specific alterations in the human tissues, increasing the mechanistic resolving power of the latter studies. Therapeutic interventions in mouse models will determine whether reducing apoE4 expression in specific cell types can block copathogenic effects of apoE4 and tau on brain functions (Project 1), modulating the activity of specific interneurons can counteract copathogenic effects of apoE4 and APP/Ab (Projects 2 and 4), and knocking down tau can prevent and reverse brain dysfunction in models expressing all three pathogenic factors (Project 3). Through these highly cohesive efforts, our program will dissect the multifactorial interactions among AD-related pathogenic factors, define their relative contributions to the complex pathogenesis of brain dysfunctions, and help distinguish among neuropathological alterations that cause, result from, or are coincidental to neural network dysfunctions and cognitive decline. Sharing the diverse data sets we will generate and disseminating the novel integrative approaches we plan to develop for their analysis could enhance the progress of many other groups working in AD research and drug development or biomedicine in general.

总体--摘要 阿尔茨海默病(AD)是一个尚未解决的重大公共卫生问题。预防或延缓这种疾病的努力 都失败了，这在很大程度上是因为对其复杂的发病机制了解不足。越来越多的证据 提示神经网络功能障碍可能是AD相关认知缺陷的基础或促进因素，并有助于 疾病的发展。然而，这种功能障碍的原因和后果以及治疗潜力 对抗它的研究仍然严重不足。因此，这个程序项目的首要目标是解码 阿尔茨海默病相关神经网络功能障碍的多因素病因及新机制的作用 我们将获得对开发更好的治疗策略的见解。通过协作互动 在四个项目和两个核心中，我们的项目将使用系统神经科学(神经生理学和行为学) 与系统生物学(单细胞转录组和表观基因组学)以及神经病理学相结合 和改进的小鼠模型，以确定载脂蛋白(Apo)E4之间的共病相互作用， 淀粉样蛋白-b(Ab)和tau可导致AD的神经网络功能障碍和认知功能下降。一个行政核心 将协调所有活动。项目1-3将使用新的散发性和家族性阿尔茨海默病小鼠模型进行研究 不同载脂蛋白E亚型与野生型(WT)人tau(项目1)或APP/Ab(项目2)的相互作用 ApoE4、ApoE4、ApoE4、项目4将 从深部对死后脑组织进行单核转录和表观基因组分析 对人类阿尔茨海默病病例进行表型分析，以获得对人类疾病多因素病因的新见解， 验证来自小鼠研究的线索，并鼓励向后翻译到模型中。一种综合的数据科学 CORE将通过创新的统计模型帮助我们整合所有项目的成果。这一方法将 揭示人类阿尔茨海默病的哪些方面在小鼠模型中最真实地复制，并帮助建立 人体组织中细胞特异性改变的原因驱动因素，增加了 后期研究。在小鼠模型中的治疗干预将决定是否减少载脂蛋白E4的表达 特定的细胞类型可以阻断apoE4和tau对脑功能的共病效应(项目1)，调节 特定中间神经元的活动可以抵消apoE4和APP/Ab的共同致病效应(项目2和 4)，并且敲除tau可以预防和逆转表达这三种致病物质的模型的脑功能障碍 因素(项目3)。通过这些高度凝聚力的努力，我们的节目将剖析多因素相互作用 在与AD相关的致病因素中，确定它们在脑复杂发病机制中的相对贡献 功能障碍，并有助于区分引起、导致或 巧合的是神经网络功能障碍和认知能力下降。共享我们将生成的各种数据集 传播我们计划为他们的分析开发的新的综合方法可以增强 在AD研究和药物开发或生物医学方面工作的许多其他小组的进展。