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