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：
10670331
负责人：
YADONG HUANG
金额：
$ 465.72万
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/10670331
关键词：
Address Algorithms Alzheimer like pathology Alzheimer&apos s Disease Alzheimer&apos s disease brain Amino Acid Sequence Amino Acid Substitution Amyloid beta-Protein Apolipoprotein E Apolipoproteins 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 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 Validation Virulence Factors apolipoprotein E-4 behavior test brain dysfunction brain tissue cell type cohort data harmonization diverse data drug development epigenomics epileptiform 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 - 摘要阿尔茨海默氏病（AD）是一个主要无法解决的公共卫生问题。预防或陷入这种疾病的努力失败了，在很大程度上是因为对其复杂发病机理的理解不足。越来越多的证据表明神经网络功能障碍可能是基础或促进与广告相关的认知定义并有助于疾病进展。然而，这种功能障碍的原因和后果以及抵消它仍然是深知的。因此，该计划项目的总体目标是解码广告相关神经网络功能障碍的多因素病因，并利用新型机械我们将获得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，我们的计划将使用系统神经科学（神经生理学和行为）结合系统生物学（单细胞转录组学和表观基因组学）以及神经病理学和改进的小鼠模型，以确定载脂蛋白（APO）E4之间的共同疾病相互作用如何淀粉样蛋白-B（AB）和Tau引起AD的神经网络功能障碍和认知能力下降。行政核心将协调所有活动。项目1–3将使用新颖的零星和家庭广告的鼠标模型来学习不同APOE同工型与野生型（WT）人tau（项目1）或APP/AB（项目2）或中间的相互作用 APOE4，AB和TAU是WT或带有与疾病相关的氨基酸取代的（项目3）。项目4 Will 从深层进行死后脑组织进行单核转录组和表观基因组分析表型的人类AD病例以对人类状况的多因素病因的新颖见解，从小鼠研究中验证铅，并鼓励对模型进行倒退。集成数据科学核心将通过创新的统计建模帮助我们整合所有项目的结果。这种方法会揭示人类广告的哪些方面在鼠标模型中最忠实地复制并帮助建立人体组织中细胞特异性改变的因果驱动因素，增加了机械解析器的能力后一个研究。小鼠模型中的治疗干预措施将确定是否降低了APOE4表达特定的细胞类型可以阻止APOE4和TAU对脑功能的共同致病作用（项目1），调整特定中间神经元的活性可以抵消APOE4和APP/AB的共同致病作用（项目2和ABS/AB（项目2和AB） 4），击倒tau可以预防和逆转大脑功能障碍，以表达这三种病原体因素（项目3）。通过这些高度凝聚力的努力，我们的计划将剖析多因素互动在与广告相关的致病因素中，定义其对大脑复杂发病机理的相对贡献功能障碍，并有助于区分导致，或从神经网络功能障碍和认知能力下降的巧合。分享我们将生成的潜水员数据集并传播我们计划开发的新型综合方法以进行分析可以增强许多其他从事广告研究和药物开发或生物医学的群体的进展。