# Robust Precision Mapping of Cortical and Subcortical Brain Metabolic Signatures in AD

> **NIH NIH R01** · UNIVERSITY OF KANSAS MEDICAL CENTER · 2024 · $786,778

## Abstract

PROJECT SUMMARY/ABSTRACT
Treating and caring for the more than 6.5 million older adults in the U.S. living with Alzheimer’s disease (AD)
presents the largest burden from a single disease on the healthcare system, with costs exceeding $320 billion
per year for AD and related dementias (AD/ADRD). While deaths due to major diseases (e.g., stroke, heart
disease, and cancers) have declined, AD and AD-related deaths have increased substantially, with a projected
cost of about $1 trillion per year to the US economy by 2050. Although AD is currently irreversible, new
therapeutic approaches and prevention strategies are under extensive investigation. Over 50% of the
pharmacologic agents currently being tested for AD target aberrant brain metabolism. Thus, it is essential to
establish a concrete relationship between metabolic dysfunction and pathologic features of AD brains.
However, comprehensive whole-brain metabolic mapping, including cortical and subcortical brain regions that
are highly relevant to AD pathology, has not been achieved, due to substantial technical challenges in
acquiring high-quality magnetic resonance (MR) spectroscopic imaging data with sufficient spatial resolution
across the entire brain in clinically acceptable scan time. In this regard, we propose to generate a robust and
reliable metabolic mapping of the whole brain, including the cortical regions, by establishing technical
capabilities for three-dimensional echo-planar spectroscopic imaging (3D-EPSI). Building on our team’s
pioneering work in MR technical development and an existing collaboration, we are ideally positioned to make
integrative technical advances in nuisance signal reduction, improved spatial encoding, and real-time motion
and B0 correction, to create a state-of-the-art metabolic imaging approach. Accurate anatomy-based regional
data analysis tools (namely MetaSurfer) will also be developed to provide a novel surface-based approach to
processing whole brain metabolic imaging data. Thus, this project offers comprehensive whole-brain metabolic
imaging packages for a full end-to-end solution from robust data acquisition to novel data analysis. Using the
developed packages, we will create population-averaged normative whole-brain metabolic atlases in the aging
population after stratifying amyloid status (Aβ- and Aβ+), which will provide a statistical basis for assessing
metabolic alterations in AD. In our pilot clinical study of early AD, we will investigate the relationship between
brain metabolic imaging outcomes and molecular, genetic, morphological, clinical, and cognitive measures in
people with early AD, leveraging the available data from NIA AD Research Center (ADRC) resources and
ongoing AD clinical studies. This study will provide critical data for future large-scale clinical trials evaluating
new AD-treatment strategies as a part of the emerging field of metabolic and bioenergetic medicine for
AD/ADRD.

## Key facts

- **NIH application ID:** 10914263
- **Project number:** 5R01AG079422-02
- **Recipient organization:** UNIVERSITY OF KANSAS MEDICAL CENTER
- **Principal Investigator:** Phil Lee
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $786,778
- **Award type:** 5
- **Project period:** 2023-09-01 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10914263

## Citation

> US National Institutes of Health, RePORTER application 10914263, Robust Precision Mapping of Cortical and Subcortical Brain Metabolic Signatures in AD (5R01AG079422-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10914263. Licensed CC0.

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