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The shape of things to come. Mapping spatiotemporal progression of striatal morphology in Huntington disease : The IMAGE-HD study

Wilkes, Fiona A.
Jakabek, David
Walterfang, Mark
Velakoulis, Dennis
Poudel, Govinda R.
Stout, Julie C.
Chua, Phyllis
Egan, Gary F.
Looi, Jeffrey C. L.
Georgiou-Karistianis, Nellie
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Abstract
Mapping the spatiotemporal progression of neuroanatomical change in Huntington's Disease (HD) is fundamental to the development of bio-measures for prognostication. Statistical shape analysis to measure the striatum has been performed in HD, however there have been a limited number of longitudinal studies. To address these limitations, we utilised the Spherical Harmonic Point Distribution Method (SPHARM-PDM) to generate point distribution models of the striatum in individuals, and used linear mixed models to test for localised shape change over time in pre-manifest HD (pre-HD), symp-HD (symp-HD) and control individuals. Longitudinal MRI scans from the IMAGE-HD study were used (baseline, 18 and 30 months). We found significant differences in the shape of the striatum between groups. Significant group-by-time interaction was observed for the putamen bilaterally, but not for caudate. A differential rate of shape change between groups over time was observed, with more significant deflation in the symp-HD group in comparison with the pre-HD and control groups. CAG repeats were correlated with bilateral striatal shape in pre-HD and symp-HD. Robust statistical analysis of the correlates of striatal shape change in HD has confirmed the suitability of striatal morphology as a potential biomarker correlated with CAG-repeat length, and potentially, an endophenotype.
Keywords
striatum, endophenotype, biomarker, Huntington’s disease
Date
2023
Type
Journal article
Journal
Psychiatry Research: Neuroimaging
Book
Volume
335
Issue
Page Range
1-7
Article Number
Article 111717
ACU Department
Mary MacKillop Institute for Health Research
Faculty of Health Sciences
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Open Access Status
Published as ‘gold’ (paid) open access
License
CC BY-NC-ND 4.0
File Access
Open
Notes
© 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).