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

基本信息

批准号：
10271123
负责人：
YADONG HUANG
金额：
$ 462.69万
依托单位：
J. DAVID GLADSTONE INSTITUTES
依托单位国家：
美国
项目类别：
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/10271123
关键词：
Address Algorithms Alzheimer like pathology Alzheimer&apos s Disease Alzheimer&apos s disease brain Alzheimer&apos 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

项目摘要

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 – 总结阿尔茨海默氏病（AD）是一个尚未解决的重大公共卫生问题。预防或阻止这种疾病的努力。失败了，很大程度上是因为对其复杂的发病机制了解不够。表明神经网络功能障碍可能是 AD 相关认知缺陷的基础或促进的原因，并有助于然而，这种功能障碍的原因和后果以及治疗潜力。因此，该计划的首要目标是解码。 AD 相关神经网络功能障碍的多因素病因学并利用新机制通过协作互动，我们将获得开发更好的治疗策略的见解。在四个项目和两个核心中，我们的计划将使用系统神经科学（神经生理学和行为）与系统生物学（单细胞转录组学和表观基因组学）以及神经病理学相结合并改进小鼠模型，以确定载脂蛋白 (apo) E4、淀粉样蛋白-b (Ab) 和 tau 蛋白会导致 AD 中的神经网络功能障碍和认知能力下降。项目 1-3 将协调所有活动，将使用新型散发性和家族性 AD 小鼠模型进行研究。不同 apoE 亚型与野生型 (WT) 人 tau（项目 1）或 APP/Ab（项目 2）或之间的相互作用 apoE4、Ab 和 tau 为 WT 或具有与疾病相关的氨基酸取代（项目 3）。对死后脑组织进行单核转录组和表观基因组分析对人类 AD 病例进行表型分析，以获得对人类状况的多因素病因学的新见解，验证小鼠研究的线索，并鼓励将其反向转化为综合数据科学。 Core 将帮助我们通过创新的统计模型整合所有项目的结果。揭示人类 AD 的哪些方面在小鼠模型中最忠实地再现，并帮助建立人体组织中细胞特异性改变的因果驱动因素，提高了细胞的机械解析能力后续研究将确定小鼠模型中的治疗干预是否会降低 apoE4 的表达。特定细胞类型可以阻断 apoE4 和 tau 对大脑功能的共致病作用（项目 1），调节特定中间神经元的活性可以抵消 apoE4 和 APP/Ab 的共致病作用（项目 2 和 4），敲低 tau 蛋白可以预防和逆转表达所有三种致病性的模型中的脑功能障碍通过这些高度凝聚力的努力，我们的计划将剖析多因素的相互作用。在 AD 相关致病因素中，定义它们对大脑复杂发病机制的相对贡献功能障碍，并有助于区分引起、导致或由其引起的神经病理学改变与神经网络功能障碍和认知能力下降同时发生的是共享我们将生成的各种数据集。传播我们计划为其分析开发的新颖的综合方法可以增强许多其他从事 AD 研究和药物开发或生物医学的其他团体的进展。