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Topological length of white matter connections predicts their rate of atrophy in premanifest Huntington's disease

McColgan, P; Seunarine, K; Gregory, S; Razi, A; Papoutsi, M; Long, J; Mills, J; ... Track-On HD Investigators, ; + view all (2017) Topological length of white matter connections predicts their rate of atrophy in premanifest Huntington's disease. JCI Insight , 2 (8) , Article e92641. 10.1172/jci.insight.92641. Green open access

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Abstract

We lack a mechanistic explanation for the stereotyped pattern of white matter loss seen in Huntington’s disease (HD). While the earliest white matter changes are seen around the striatum, within the corpus callosum, and in the posterior white matter tracts, the order in which these changes occur and why these white matter connections are specifically vulnerable is unclear. Here, we use diffusion tractography in a longitudinal cohort of individuals yet to develop clinical symptoms of HD to identify a hierarchy of vulnerability, where the topological length of white matter connections between a brain area and its neighbors predicts the rate of atrophy over 24 months. This demonstrates a new principle underlying neurodegeneration in HD, whereby brain connections with the greatest topological length are the first to suffer damage that can account for the stereotyped pattern of white matter loss observed in premanifest HD.

Type: Article
Title: Topological length of white matter connections predicts their rate of atrophy in premanifest Huntington's disease
Open access status: An open access version is available from UCL Discovery
DOI: 10.1172/jci.insight.92641
Publisher version: http://dx.doi.org/10.1172/jci.insight.92641
Language: English
Additional information: Copyright © 2017 McColgan et al. This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
UCL classification: UCL > School of Life and Medical Sciences
UCL > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Neurology
UCL > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Neurology > Imaging Neuroscience
UCL > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Neurology > Neurodegenerative Diseases
UCL > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Child Health
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URI: http://discovery.ucl.ac.uk/id/eprint/1545277
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