# Assess Neural Circuits and Subtypes Underlying Dimensions of Neuropsychiatric Symptoms in Alzheimer's Disease

> **NIH NIH R21** · STANFORD UNIVERSITY · 2024 · $226,566

## Abstract

Project Abstract
Neuropsychiatric symptoms (NPS) are commonly observed in individuals with mild cognitive impairment or
Alzheimer’s disease (AD) dementia. These symptoms affect up to 97% of patients during the course of AD and
may cause accelerated declines in cognitive functions and conversion to dementia. Though numerous efforts
have been devoted to investigating the etiology of NPS, the neurobiological basis underlying NPS in AD dementia
remains unclear. There is an urgent need to advance the mechanistic understanding of these symptoms, which
is crucial for early detection and timely intervention to prevent AD progression. Increasing evidence has indicated
that differential NPS overlap substantially and are relevant to dysfunctions in distinctive brain networks.
Assessing NPS dimensionally and their associated circuit-level dysfunctions would therefore provide significant
benefits to deepen our understanding of neural circuits involved in the expression of NPS. In response to the
guidelines of the PAR-20-159, the overall objective of the project is to assess neural circuits and identify
neurophysiological subtypes (i.e., subtypes) underlying dimensions of NPS in dementia. We hypothesize that
distinct patterns of neural circuits will reflect latent dimensions of NPS domains that span from preclinical to
severe AD dementia, and interact to define neurophysiological subtypes that are predictive of clinical symptoms
and the rate of AD progression. In Aim 1, we will identify interpretable neural circuits and the linked latent
dimensions of NPS domains using a sparse multivariate correlation analysis. In Aim 2, we will identify
neurophysiological subtypes using statistical clustering with guidance from the NPS dimension-associated
circuitry characteristics. We will further evaluate and interpret the neurobiological meanings and clinical
relevance underlying these dimensions and subtypes. The proposed approaches will be developed and
evaluated by assessing resting-state functional MRI from two independent cohorts (OASIS-3 and ADNI) with
more than 1,800 subjects in total. Successful outcomes of the project will lead to an improved understanding of
the neurobiological mechanism underlying NPS and its clinical relevance, form a promising new avenue to
potentially guide the intervention of NPS and better the management of AD progression, and hence pave the
way towards precision medicine of AD dementia.

## Key facts

- **NIH application ID:** 11328568
- **Project number:** 7R21AG080425-03
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Yu Zhang
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $226,566
- **Award type:** 7
- **Project period:** 2023-09-20 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11328568

## Citation

> US National Institutes of Health, RePORTER application 11328568, Assess Neural Circuits and Subtypes Underlying Dimensions of Neuropsychiatric Symptoms in Alzheimer's Disease (7R21AG080425-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11328568. Licensed CC0.

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