# Characterizing sleep-wake activity patterns to detect early Alzheimer's disease in normal older individuals

> **NIH NIH F32** · STANFORD UNIVERSITY · 2022 · $69,674

## Abstract

PROJECT SUMMARY/ABSTRACT
Recent work has established a connection between disrupted sleep and Alzheimer’s disease that begins many
years before memory impairment or dementia. Many of the brain regions involved in regulating daily patterns of
sleep-wake behavior are also the earliest to be affected in the progression of Alzheimer’s disease. Therefore,
understanding how sleep-wake patterns change during the earliest stages of Alzheimer’s disease may lead to
better disease detection and treatment intervention strategies. Actigraphy watches, which use technology similar
to the accelerometers in our phones and smartwatches, can be used to collect sleep-wake activity data outside
the laboratory on a massive scale. By analyzing sleep-wake activity collected from thousands of cognitively
healthy older adults, this project will determine whether differences in daily activity patterns are able to forecast
subsequent memory decline and Alzheimer’s disease diagnosis. Additionally, in order to understand how early
Alzheimer’s disease-related changes in the brain affect sleep, we will collect brain imaging and fluid markers of
Alzheimer’s disease along with sleep-wake rhythm data from a local cohort of older adults. High-resolution
structural brain imaging, combined with sleep-wake activity phenotypes, will allow for the identification of sleep-
wake dysfunction signatures linked to specific pathological brain changes. This research proposal leverages big
data in parallel with rich neuroimaging in a multimodal approach which will advance our understanding of the
relationship between sleep and Alzheimer’s disease with important clinical implications.

## Key facts

- **NIH application ID:** 10480801
- **Project number:** 5F32AG074625-02
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Joseph Robert Winer
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $69,674
- **Award type:** 5
- **Project period:** 2021-08-24 → 2024-08-23

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10480801

## Citation

> US National Institutes of Health, RePORTER application 10480801, Characterizing sleep-wake activity patterns to detect early Alzheimer's disease in normal older individuals (5F32AG074625-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10480801. Licensed CC0.

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