Spatiotemporal Mapping of Huntington's Disease Progression through Multimodal MRI-based Circuit Analysis - PROJECT ABSTRACT Huntington’s Disease (HD) is a progressive, autosomal dominant neurodegenerative disorder marked by motor, cognitive, and psychiatric disturbances. Although genetic testing allows identification of mutation carriers before symptom onset, the absence of sensitive and specific biomarkers to monitor disease progression, particularly in premanifest (PM) individuals, remains a major barrier to the development and evaluation of disease-modifying therapies. Previous imaging studies in HD predominantly focused on atrophy and iron deposition in the striatum, identifying changes on imaging that preceded the presence of symptoms and supported its crucial role in HD pathogenesis. However, growing evidence implicates HD as a whole-brain disorder, with alterations in brain structure and function beyond the striatum present in early disease stages. This proposal will develop a whole brain, circuit-based framework for characterizing and predicting spatial and temporal alterations of HD pathogenesis related to atrophy, structural and functional connectivity, iron deposition, myelin content, and striatal metabolism from multimodal MRI. We focus on the cortico-striato-thalamo-cortical (CSTC) and cerebello-thalamo-cortical (CTC) pathways, which underlie domain-specific symptoms and exhibit early vulnerability in HD. Our approach integrates structural and diffusion MRI, resting-state fMRI, quantitative susceptibility mapping (QSM), and spectroscopy-based metabolic imaging to measure brain atrophy, microstructural integrity, iron deposition, myelin content, and striatal metabolism. Aim 1 will identify regional and tract-based structural, functional, and metabolic characteristics of CSTC-CTC pathways across the disease spectrum of HD and healthy controls with publicly available HD datasets and prospectively acquired, multi-center 3T data, and characterize temporal dynamics of these imaging features through longitudinal evaluation. Aim 2 will define functional circuit-based, multimodal imaging predictors of domain-specific cognitive, motor, and behavioral symptoms present in HD patients, and evaluate their ability to predict subsequent decline. Aim 3 will then model spatiotemporal disease spread through brain networks during the course of HD based on atrophy, structural connectivity, and functional activity using large publicly available HD datasets and expand the model to include iron deposition, myelin content, and metabolism from prospectively acquired data. Individualized predictions of future brain state and symptom burden will also be tested. The proposed research will generate new insights into HD pathogenesis and symptom evolution, and provide a validated, multimodal imaging framework and individualized disease model to guide precision monitoring and clinical trial design.
