Journal article
Cross-sectional and longitudinal voxel-based grey matter asymmetries in Huntington's disease
NeuroImage clinical, Vol.17, pp.312-324
01/01/2018
DOI: 10.1016/j.nicl.2017.10.023
PMCID: PMC5842644
PMID: 29527479
Abstract
Huntington's disease (HD) is a progressive neurodegenerative disorder that can be genetically confirmed with certainty decades before clinical onset. This allows the investigation of functional and structural changes in HD many years prior to disease onset, which may reveal important mechanistic insights into brain function, structure and organization in general. While regional atrophy is present at early stages of HD, it is still unclear if both hemispheres are equally affected by neurodegeneration and how the extent of asymmetry affects domain-specific functional decline. Here, we used whole-brain voxel-based analysis to investigate cross-sectional and longitudinal hemispheric asymmetries in grey matter (GM) volume in 56 manifest HD (mHD), 83 pre-manifest HD (preHD), and 80 healthy controls (HC). Furthermore, a regression analysis was used to assess the relationship between neuroanatomical asymmetries and decline in motor and cognitive measures across the disease spectrum. The cross-sectional analysis showed striatal leftward-biased GM atrophy in mHD, but not in preHD, relative to HC. Longitudinally, no net 36-month change in GM asymmetries was found in any of the groups. In the regression analysis, HD-related decline in quantitative-motor (Q-Motor) performance was linked to lower GM volume in the left superior parietal cortex. These findings suggest a stronger disease effect targeting the left hemisphere, especially in those with declining motor performance. This effect did not change over a period of three years and may indicate a compensatory role of the right hemisphere in line with recent functional imaging studies.
Details
- Title: Subtitle
- Cross-sectional and longitudinal voxel-based grey matter asymmetries in Huntington's disease
- Creators
- Lora Minkova - University of FreiburgSarah Gregory - Wellcome Centre for Human NeuroimagingRachael I. Scahill - University College LondonAhmed Abdulkadir - University of BernChristoph P. Kaller - University of FreiburgJessica Peter - University of BernJeffrey D. Long - University of IowaJulie C. Stout - Monash UniversityRalf Reilmann - University of TübingenRaymund A. Roos - Leiden UniversityAlexandra Durr - Assistance Publique – Hôpitaux de ParisBlair R. Leavitt - University of British ColumbiaSarah J. Tabrizi - University College LondonStefan Kloeppel - Univ Freiburg, Med Ctr, Dept Psychiat & Psychotherapy, Freiburg, GermanyTRACK-HD Investigators
- Resource Type
- Journal article
- Publication Details
- NeuroImage clinical, Vol.17, pp.312-324
- DOI
- 10.1016/j.nicl.2017.10.023
- PMID
- 29527479
- PMCID
- PMC5842644
- NLM abbreviation
- Neuroimage Clin
- ISSN
- 2213-1582
- eISSN
- 2213-1582
- Publisher
- Elsevier
- Number of pages
- 13
- Grant note
- UKDRI-1008/2 / MRC; UK Research & Innovation (UKRI); Medical Research Council UK (MRC) Albert-Ludwigs University Freiburg in the Open Access Publishing Funding Program CHDI/High Q Foundation Inc. German Research Foundation (DFG)
- Language
- English
- Date published
- 01/01/2018
- Academic Unit
- Psychiatry; Biostatistics
- Record Identifier
- 9984280880702771
Metrics
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