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

> **NIH NIH P01** · J. DAVID GLADSTONE INSTITUTES · 2022 · $157,218

## Abstract

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 ne...

## Key facts

- **NIH application ID:** 10691620
- **Project number:** 3P01AG073082-02S1
- **Recipient organization:** J. DAVID GLADSTONE INSTITUTES
- **Principal Investigator:** YADONG HUANG
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $157,218
- **Award type:** 3
- **Project period:** 2021-08-15 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10691620

## Citation

> US National Institutes of Health, RePORTER application 10691620, Decoding the Multifactorial Etiology of Neural Network Dysfunction in Alzheimer's Disease (3P01AG073082-02S1). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10691620. Licensed CC0.

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