bioRxiv · 10.64898/2025.11.30.691364
Large Scale Functional and Effective Connectivity Alterations cross the Huntington's Disease Integrated Staging System
Abstract
Huntingtons disease (HD) is a progressive neurodegenerative disease with severe motor, cognitive and behavioral symptoms. There is a recent impetus to develop treatments that slow progression before clinical signs emerge. Such early interventions require biomarkers sensitive to the very earliest HD progression. Here we applied cutting-edge fMRI analysis on data collected in the Track-On HD study to evaluate whether functional and effective connectivity obtained from model-free and model-based approaches can produce useful biomarkers of HD progression. We analyzed data from 231 participants with up to three annual visits each and created five groups comprising normative controls and four HD groups according to the Huntingtons Disease Integrated Staging System (HD-ISS). We found significant differences across the HD-ISS stages but not in their longitudinal change. Specifically, we found attenuated functional and effective connectivity in the caudate nucleus in HD-ISS-2, and this effect extended to other corticostriatal connections in HD-ISS-3. Overall, most of the alterations were only evident in advanced HD stages, and we did not observe widespread alterations in cortical connectivity and graph topography. Although HD-ISS groups did not differ in the amount of in-scanner motion, we did find measures of functional and effective connectivity to be sensitive to motion. We conclude that fMRI can indeed capture attenuation of cortico-striatal functional and effective connectivity across HD progression. This is the first study to investigate fMRI alterations across the recently created HD-ISS stages within a novel framework of signal flow across the whole brain.
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Demirtas, M., Pustina, D., Wood, A., Sampaio, C., Vohryzek, J., Deco, G.. 2025-12-02. Large Scale Functional and Effective Connectivity Alterations cross the Huntington's Disease Integrated Staging System. https://doi.org/10.64898/2025.11.30.691364
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