A tale of two factors: What determines the rate of progression in Huntington's disease? A longitudinal MRI study§

Authors

  • H. Diana Rosas MD,

    Corresponding author
    1. Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    2. Center for Neuro-imaging of Aging and Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    3. MassGeneral Institute for Neurodegeneration, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    4. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    • Center for Neuro-imaging of Aging and Neurodegenerative Diseases, Massachusetts General Hospital, 149 13th Street, Room 2275, Charlestown, MA 02129, USA
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  • Martin Reuter PhD,

    1. Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    2. Center for Neuro-imaging of Aging and Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    3. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    4. Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA, and Harvard Medical School, Boston, Massachusetts, USA
    5. MIT Computer Science and AI Lab, Division of Health Sciences and Technology, Cambridge, Masschusetts, USA
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  • Gheorghe Doros PhD,

    1. Department of Biostatistics, Boston University, Boston, Massachusetts, USA
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  • Stephanie Y. Lee BS,

    1. Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    2. Center for Neuro-imaging of Aging and Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    3. MassGeneral Institute for Neurodegeneration, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    4. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
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  • Tyler Triggs BS,

    1. Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    2. Center for Neuro-imaging of Aging and Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    3. MassGeneral Institute for Neurodegeneration, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    4. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
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  • Keith Malarick BS,

    1. Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    2. Center for Neuro-imaging of Aging and Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    3. MassGeneral Institute for Neurodegeneration, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    4. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
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  • Bruce Fischl PhD,

    1. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    2. Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA, and Harvard Medical School, Boston, Massachusetts, USA
    3. MIT Computer Science and AI Lab, Division of Health Sciences and Technology, Cambridge, Masschusetts, USA
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  • David H. Salat PhD,

    1. Center for Neuro-imaging of Aging and Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    2. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    3. Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA, and Harvard Medical School, Boston, Massachusetts, USA
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  • Steven M. Hersch MD, PhD

    1. Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
    2. MassGeneral Institute for Neurodegeneration, Massachusetts General Hospital, Charlestown, Massachusetts, USA
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  • Funding agencies: Support for this research was provided in part by the National Institutes of Health, National Institute for Neurological Disorders and Stroke (R01 NS042861, NS058793, NS05792, NS052585, R21NS072652), National Institute of Nursing Research (NR010827), and the National Center for Research Resources (P41-RR14075, and the NCRR BIRN Morphometric Project BIRN002, U24-01). Additional support came from RR021382, the National Institute for Biomedical Imaging and Bioengineering (R01EB006758), and the National Institute on Aging (AG022381). Additional support was provided by CHDI and the Autism & Dyslexia Project, funded by the Ellison Medical Foundation.

  • Relevant conflicts of interest/financial disclosures: Nothing to report.

  • §

    Full financial disclosures and author roles may be found in the online version of this article.

Abstract

Over the past several years, increased attention has been devoted to understanding regionally selective brain changes that occur in Huntington's disease and their relationships to phenotypic variability. Clinical progression is also heterogeneous, and although CAG repeat length influences age of onset, its role, if any, in progression has been less clear. We evaluated progression in Huntington's disease using a novel longitudinal magnetic resonance imaging analysis. Our hypothesis was that the rate of brain atrophy is influenced by the age of onset of Huntington's disease. We scanned 22 patients with Huntington's disease at approximately 1-year intervals; individuals were divided into 1 of 3 groups, determined by the relative age of onset. We found significant differences in the rates of atrophy of cortex, white matter, and subcortical structures; patients who developed symptoms earlier demonstrated the most rapid rates of atrophy compared with those who developed symptoms during middle age or more advanced age. Rates of cortical atrophy were topologically variable, with the most rapid changes occurring in sensorimotor, posterior frontal, and portions of the parietal cortex. There were no significant differences in the rates of atrophy in basal ganglia structures. Although both CAG repeat length and age influenced the rate of change in some regions, there was no significant correlation in many regions. Rates of regional brain atrophy seem to be influenced by the age of onset of Huntington's disease symptoms and are only partially explained by CAG repeat length. These findings suggest that other genetic, epigenetic, and environmental factors play important roles in neurodegeneration in Huntington's disease. © 2011 Movement Disorder Society

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