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Dynamics of Cortical Degeneration Over a Decade in Huntington’s Disease

BACKGROUND: Characterizing changing brain structure in neurodegeneration is fundamental to understanding long-term effects of pathology and ultimately providing therapeutic targets. It is well established that Huntington’s disease (HD) gene carriers undergo progressive brain changes during the cours...

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Autores principales: Johnson, Eileanoir B., Ziegler, Gabriel, Penny, William, Rees, Geraint, Tabrizi, Sarah J., Scahill, Rachael I., Gregory, Sarah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7986936/
https://www.ncbi.nlm.nih.gov/pubmed/33500176
http://dx.doi.org/10.1016/j.biopsych.2020.11.009
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author Johnson, Eileanoir B.
Ziegler, Gabriel
Penny, William
Rees, Geraint
Tabrizi, Sarah J.
Scahill, Rachael I.
Gregory, Sarah
author_facet Johnson, Eileanoir B.
Ziegler, Gabriel
Penny, William
Rees, Geraint
Tabrizi, Sarah J.
Scahill, Rachael I.
Gregory, Sarah
author_sort Johnson, Eileanoir B.
collection PubMed
description BACKGROUND: Characterizing changing brain structure in neurodegeneration is fundamental to understanding long-term effects of pathology and ultimately providing therapeutic targets. It is well established that Huntington’s disease (HD) gene carriers undergo progressive brain changes during the course of disease, yet the long-term trajectory of cortical atrophy is not well defined. Given that genetic therapies currently tested in HD are primarily expected to target the cortex, understanding atrophy across this region is essential. METHODS: Capitalizing on a unique longitudinal dataset with a minimum of 3 and maximum of 7 brain scans from 49 HD gene carriers and 49 age-matched control subjects, we implemented a novel dynamical systems approach to infer patterns of regional neurodegeneration over 10 years. We use Bayesian hierarchical modeling to map participant- and group-level trajectories of atrophy spatially and temporally, additionally relating atrophy to the genetic marker of HD (CAG-repeat length) and motor and cognitive symptoms. RESULTS: We show, for the first time, that neurodegenerative changes exhibit complex temporal dynamics with substantial regional variation around the point of clinical diagnosis. Although widespread group differences were seen across the cortex, the occipital and parietal regions undergo the greatest rate of cortical atrophy. We have established links between atrophy and genetic markers of HD while demonstrating that specific cortical changes predict decline in motor and cognitive performance. CONCLUSIONS: HD gene carriers display regional variability in the spatial pattern of cortical atrophy, which relates to genetic factors and motor and cognitive symptoms. Our findings indicate a complex pattern of neuronal loss, which enables greater characterization of HD progression.
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spelling pubmed-79869362021-04-15 Dynamics of Cortical Degeneration Over a Decade in Huntington’s Disease Johnson, Eileanoir B. Ziegler, Gabriel Penny, William Rees, Geraint Tabrizi, Sarah J. Scahill, Rachael I. Gregory, Sarah Biol Psychiatry Archival Report BACKGROUND: Characterizing changing brain structure in neurodegeneration is fundamental to understanding long-term effects of pathology and ultimately providing therapeutic targets. It is well established that Huntington’s disease (HD) gene carriers undergo progressive brain changes during the course of disease, yet the long-term trajectory of cortical atrophy is not well defined. Given that genetic therapies currently tested in HD are primarily expected to target the cortex, understanding atrophy across this region is essential. METHODS: Capitalizing on a unique longitudinal dataset with a minimum of 3 and maximum of 7 brain scans from 49 HD gene carriers and 49 age-matched control subjects, we implemented a novel dynamical systems approach to infer patterns of regional neurodegeneration over 10 years. We use Bayesian hierarchical modeling to map participant- and group-level trajectories of atrophy spatially and temporally, additionally relating atrophy to the genetic marker of HD (CAG-repeat length) and motor and cognitive symptoms. RESULTS: We show, for the first time, that neurodegenerative changes exhibit complex temporal dynamics with substantial regional variation around the point of clinical diagnosis. Although widespread group differences were seen across the cortex, the occipital and parietal regions undergo the greatest rate of cortical atrophy. We have established links between atrophy and genetic markers of HD while demonstrating that specific cortical changes predict decline in motor and cognitive performance. CONCLUSIONS: HD gene carriers display regional variability in the spatial pattern of cortical atrophy, which relates to genetic factors and motor and cognitive symptoms. Our findings indicate a complex pattern of neuronal loss, which enables greater characterization of HD progression. Elsevier 2021-04-15 /pmc/articles/PMC7986936/ /pubmed/33500176 http://dx.doi.org/10.1016/j.biopsych.2020.11.009 Text en © 2020 Society of Biological Psychiatry. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Archival Report
Johnson, Eileanoir B.
Ziegler, Gabriel
Penny, William
Rees, Geraint
Tabrizi, Sarah J.
Scahill, Rachael I.
Gregory, Sarah
Dynamics of Cortical Degeneration Over a Decade in Huntington’s Disease
title Dynamics of Cortical Degeneration Over a Decade in Huntington’s Disease
title_full Dynamics of Cortical Degeneration Over a Decade in Huntington’s Disease
title_fullStr Dynamics of Cortical Degeneration Over a Decade in Huntington’s Disease
title_full_unstemmed Dynamics of Cortical Degeneration Over a Decade in Huntington’s Disease
title_short Dynamics of Cortical Degeneration Over a Decade in Huntington’s Disease
title_sort dynamics of cortical degeneration over a decade in huntington’s disease
topic Archival Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7986936/
https://www.ncbi.nlm.nih.gov/pubmed/33500176
http://dx.doi.org/10.1016/j.biopsych.2020.11.009
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