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

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:
10271123
负责人:
YADONG HUANG
金额:
$462.69万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-08-15 至 2026-07-31

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中文摘要
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英文摘要
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.
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Develop AD Connectivity Maps with Human iPSC-Derived Brain Cells and their Use
  • 批准号:
    10504728
  • 项目类别:
  • 资助金额:
    $94.18万
  • 财政年份:
    2022
  • 负责人:
    YADONG HUANG
  • 依托单位:
Develop AD Connectivity Maps with Human iPSC-Derived Brain Cells and their Use
  • 批准号:
    10686182
  • 项目类别:
  • 资助金额:
    $94.18万
  • 财政年份:
    2022
  • 负责人:
    YADONG HUANG
  • 依托单位:
Study Susceptibility and Resistance to ApoE4 in Alzheimer's Disease
  • 批准号:
    10418144
  • 项目类别:
  • 资助金额:
    $263.7万
  • 财政年份:
    2022
  • 负责人:
    YADONG HUANG
  • 依托单位:
Decoding the Multifactorial Etiology of Neural Network Dysfunction in Alzheimer's Disease
  • 批准号:
    10525204
  • 项目类别:
  • 资助金额:
    $9.17万
  • 财政年份:
    2021
  • 负责人:
    YADONG HUANG
  • 依托单位:
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