# Mathematical Models of Tau-PET Measures and Cognitive Decline in Alzheimer's Disease Across the Lifespan

> **NIH AG R00** · BROWN UNIVERSITY · 2026 · $249,000

## Abstract

PROJECT SUMMARY/ ABSTRACT
Many specifics of the pathological process of Alzheimer’s disease (AD) remain unknown, such as the precise,
functional relationship between tau accumulation and cognitive decline as a function of age, as well as other
biomarkers that may modify these relationships. Conventional statistical approaches cannot easily answer
questions about the relationship between tau and cognition, due to their dynamic relationship, unknown time
lags, and complex measurement error structures. Mathematical modeling techniques—commonly used in
infectious disease epidemiology and computational biology—are specialized for the study of complex
relationships between biological variables, while incorporating prior knowledge about the relevant physiologic
system. The proposed project leverages my quantitative expertise from dissertation research on infectious
disease, using data from across the age span of AD onset to elucidate the relationship between tau-PET
measures and cognition.
As more tau-targeting drugs move through the pipeline, it is important to determine the optimal timing and
duration of treatment for trial design and for post-approval clinical guidelines. The ideal timing for tau-targeting
therapies may depend on factors such as age, amyloid, or vascular burden. Existing and emerging blood-
based biomarkers may offer important information about how tau spreads in the brain and the timing of
subsequent atrophy and cognitive decline longitudinally. A growing number of studies now perform tau-PET,
and including repeated neuroimaging, making it possible for an improved understanding of the dynamics of tau
and cognition in relation to other biomarkers.
We propose a biologically motivated, mathematical modeling approach to understand how neuroimaging and
other biomarkers can be used to better understand Alzheimer’s disease biology. We plan to fit mechanistic
models to data from three cohorts across the age span of AD diagnosis: Alzheimer’s Disease Neuroimagin

## Key facts

- **NIH application ID:** 11310831
- **Project number:** 5R00AG073454-06
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** Sarah  Ackley
- **Activity code:** R00 (R01, R21, SBIR, etc.)
- **Funding institute:** AG
- **Fiscal year:** 2026
- **Award amount:** $249,000
- **Award type:** 5
- **Project period:** 2022-05-01T00:00:00 → 2027-04-30T00:00:00

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11310831

## Citation

> US National Institutes of Health, RePORTER application 11310831, Mathematical Models of Tau-PET Measures and Cognitive Decline in Alzheimer's Disease Across the Lifespan (5R00AG073454-06). Retrieved via AI Analytics 2026-07-06 from https://api.ai-analytics.org/grant/nih/11310831. Licensed CC0.

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