# Intraindividual Cognitive Variability as an Early Marker of Alzheimer's Disease

> **NIH NIH K23** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2022 · $183,713

## Abstract

ABSTRACT
 Alzheimer’s disease (AD) is the most common form of dementia, with neuropathology such as beta-
amyloid (Aβ) deposits and reduced hippocampal volume developing years before clinical cognitive impairment.
Early identification of these preclinical AD stages is imperative for improving prevention and treatment efforts.
Unfortunately, capturing the earliest subtle cognitive changes is difficult with traditional neuropsychological
tests, which 1) were developed to detect overt clinical cognitive impairment, and 2) measure peak performance
at a single, and potentially non-representative, time point in a well-controlled environment that is detached from
daily life. These limitations underscore the need for valid assessment tools that capture not only the range of
everyday cognition but also aspects of daily life, such as psychosocial factors, that signal resilience to AD
clinical symptomatology. Mobile health (mHealth) assessments that utilize common smartphone technology
may help overcome these limitations by sampling behavior multiple times per day in ‘real-time’, over the course
of several days. Repeated sampling enables characterization of the time-course of a person’s behavior, both in
terms of their cognition and their psychosocial context.
 The goal of this proposal is to examine the utility of a mHealth program to detect early markers of AD
cognitive vulnerability. The specific aims are to examine whether variability over time on mHealth cognitive
measures (i.e., intraindividual cognitive variability) is 1) a signature of AD neuropathologic risk, and 2) predicts
longitudinal cognitive decline on traditional neuropsychological tests. An exploratory aim proposes to examine
whether individuals with more AD neuropathology show stronger synchrony between their everyday
psychosocial context (interpersonal interactions, mood, loneliness) and everyday cognitive performance.
Participants will be cognitively normal Aβ positive and negative individuals recruited from ongoing longitudinal
studies that gather neuropsychological and neuroimaging (PET, MRI) markers of AD neuropathology.
Participants will undergo a 14-day mHealth protocol, twice over two years, that samples psychosocial factors
and cognitive performance. The proposed training aims include 1) building foundational mHealth skills and
specific expertise in using mHealth to measure cognition and psychosocial factors, 2) acquiring advanced
expertise in psychosocial factors that contribute to resistance and resilience to AD symptoms, and 3)
developing in-depth knowledge of PET and MRI imaging of AD neuropathologic risk factors.
 In summary, this proposed K23 award sets the foundation toward understanding whether individuals at
high AD neuropathologic risk show early markers of cognitive vulnerability on mHealth assessments. The
results of this study will establish the necessary groundwork for the PI’s development as an independent
neuropsychologist-investigator using cutting-edge approaches...

## Key facts

- **NIH application ID:** 10424752
- **Project number:** 1K23AG076663-01
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Andrea Weinstein
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $183,713
- **Award type:** 1
- **Project period:** 2022-08-01 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10424752

## Citation

> US National Institutes of Health, RePORTER application 10424752, Intraindividual Cognitive Variability as an Early Marker of Alzheimer's Disease (1K23AG076663-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10424752. Licensed CC0.

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