# Disease pathways in the population determined by amyloid, tau, and neurodegeneration imaging biomarkers

> **NIH NIH R37** · MAYO CLINIC ROCHESTER · 2021 · $732,693

## Abstract

PROJECT SUMMARY / ABSTRACT
 In 2010 we proposed, and in 2013 revised, a hypothetical model of the temporal evolution of biomarkers
and clinical symptoms for individuals in the Alzheimer’s disease (AD) pathway. The biomarker model is based
on a hypothesized cause and effect sequence which can be summarized as: amyloidosis (A), promotes
tauopathy (T), which promotes neurodegeneration (N), which is the proximate cause of clinical symptoms (C).
For simplicity, we use this ATNC notation: A T  N  C. The current cycle of AG011378 was designed to
test aspects of this model that were testable using imaging; however, a major missing element when the
current cycle AG011378 began in 2013 was a method to measure fibrillar tau deposits with imaging. Tau PET
has recently become available and, consequently for the first time, imaging biomarkers exist to ascertain three
of the most important pathologic features of AD: amyloid, tau and neurodegeneration.
 An important insight gained from the current cycle of AG011378 was that modeling AD biomarkers on the
assumption that AD is the only pathological process present in the general aging population is conceptually
flawed. We argue that biomarker modeling within the general aging population should accommodate at least
three broad groups based on currently available biomarkers: (1) individuals with no biomarker abnormalities
whose future biomarker profiles are unknown; (2) individuals along the Alzheimer’s continuum; and (3) a
heterogeneous group with primarily suspected non-AD pathologies (SNAP).
 Our aims in this renewal are based on modeling longitudinal amyloid PET (A), tau PET (T), and MRI (N)
biomarkers. The overarching goals of the renewal are to empirically evaluate our hypothetical model of AD
biomarkers and to create complementary imaging biomarker models for individuals who are not in the
Alzheimer’s continuum. Our specific aims are:
Aim 1. To model the sequence of biomarker and clinical transitions over time across multiple pathways. Aim 1
employs hidden Markov models. 1a) To model the sequence of biomarker and clinical transitions in the
Alzheimer’s continuum, 1b) To model the sequence of biomarker and clinical transitions in SNAP pathways.
Aim 2. To model continuous biomarker and clinical trajectories over time across multiple pathways. Aim 2
analyses employ non-linear latent class mixed models. 2a) To model biomarker and clinical trajectories in the
Alzheimer’s continuum, 2b) To model biomarker and clinical trajectories in SNAP pathways.
Aim 3. To formulate mechanistic inferences about biomarker and clinical changes over time across multiple
pathways. 3a) inferences in the Alzheimer’s continuum, 3b) inferences in SNAP pathways.
Aim 4: To establish temporal ordering of topographic spread of A, T, and N within each modality, across
imaging modalities, and establish how these temporal orderings relate to cognitive impairment within (4a) the
Alzheimer’s continuum and (4b) the SNAP pathways. Aim 4 uses a c...

## Key facts

- **NIH application ID:** 10164686
- **Project number:** 5R37AG011378-29
- **Recipient organization:** MAYO CLINIC ROCHESTER
- **Principal Investigator:** CLIFFORD R. JACK
- **Activity code:** R37 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $732,693
- **Award type:** 5
- **Project period:** 1993-06-01 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10164686

## Citation

> US National Institutes of Health, RePORTER application 10164686, Disease pathways in the population determined by amyloid, tau, and neurodegeneration imaging biomarkers (5R37AG011378-29). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10164686. Licensed CC0.

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