# Patient-tailored network prediction of neurodegenerative disease progression

> **NIH NIH K01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2021 · $130,211

## Abstract

PROJECT SUMMARY/ABSTRACT
 This is an application for a K01 award for Dr. Jesse Brown, a postdoctoral scholar in clinical
neuroimaging at the University of California, San Francisco (UCSF) in the Memory and Aging Center (MAC).
Dr. Brown is an early-career neuroscientist focusing on brain network neuroanatomy involved in
neurodegenerative disease. This K01 award will provide Dr. Brown with the support necessary to accomplish
the following goals: 1) gain experience in the network neuroanatomy of dementia, 2) achieve proficiency in
PET data analysis with an emphasis on tau imaging, 3) become an expert in longitudinal statistical modeling,
4) expand knowledge of new MRI neuroimaging methods, and 5) develop an independent research career. To
achieve these goals, Dr. Brown has assembled a mentorship team including a primary mentor, Dr. William
Seeley, a behavioral neurologist who conducts neuroimaging and neuropathological studies on selective
regional vulnerability in neurodegenerative disease; a co-mentor, Dr. Gil Rabinovici, a behavioral neurologist
who investigates how molecular brain imaging techniques can be used to improve diagnostic accuracy in
dementia; a collaborator, Dr. Howard Rosen, a behavioral neurologist who uses neuroimaging to track how
neurodegenerative diseases affect the brain over time; a collaborator, Dr. John Kornak, a biostatistician who is
an expert in longitudinal data analysis; and a collaborator, Dr. Christopher Hess, a neuroradiologist focused on
the translational application of MR imaging techniques to brain degeneration.
 This proposal describes a multimodal neuroimaging approach to predict neurodegenerative disease
progression in individual patients with frontotemporal dementia (FTD) and Alzheimer's disease (AD). The
central hypothesis of this proposal is that each of these diseases originates in a selectively vulnerable brain
region or “epicenter” and spreads outwards along network connections, with affected regions first showing
elevated tau protein binding, followed by an increased rate of gray matter loss, and eventually a high degree of
cumulative atrophy. We will first develop methods to detect patient-tailored epicenters in FTD/AD patients with
different clinical syndromes and use clustering methods to identify atrophy subtypes (Aim 1). We will then test
a model predicting that as disease spreads from an epicenter throughout the network, nodes that become
affected will show a greater longitudinal rate of atrophy before they show high cumulative atrophy (Aim 2).
Finally, we will use 18F-AV1451 PET imaging to examine the relative timing of tau spread and regional atrophy
spread from the epicenter. The goal of this project is to improve prognostic accuracy in individual dementia
patients. This proposal includes innovative imaging and statistical methods that will help us evaluate different
biomarkers of network-based neurodegenerative disease progression in a clinical trial. The K01 training will
prepare Dr. Brown to...

## Key facts

- **NIH application ID:** 10162458
- **Project number:** 5K01AG055698-05
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Jesse Aaron Brown
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $130,211
- **Award type:** 5
- **Project period:** 2017-07-01 → 2023-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10162458

## Citation

> US National Institutes of Health, RePORTER application 10162458, Patient-tailored network prediction of neurodegenerative disease progression (5K01AG055698-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10162458. Licensed CC0.

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