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Longitudinal cortical network reorganization in early relapsing–remitting multiple sclerosis
BACKGROUND: Network science provides powerful access to essential organizational principles of the brain. The aim of this study was to investigate longitudinal evolution of gray matter networks in early relapsing–remitting MS (RRMS) compared with healthy controls (HCs) and contrast network dynamics...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6482642/ https://www.ncbi.nlm.nih.gov/pubmed/31040880 http://dx.doi.org/10.1177/1756286419838673 |
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author | Fleischer, Vinzenz Koirala, Nabin Droby, Amgad Gracien, René-Maxime Deichmann, Ralf Ziemann, Ulf Meuth, Sven G. Muthuraman, Muthuraman Zipp, Frauke Groppa, Sergiu |
author_facet | Fleischer, Vinzenz Koirala, Nabin Droby, Amgad Gracien, René-Maxime Deichmann, Ralf Ziemann, Ulf Meuth, Sven G. Muthuraman, Muthuraman Zipp, Frauke Groppa, Sergiu |
author_sort | Fleischer, Vinzenz |
collection | PubMed |
description | BACKGROUND: Network science provides powerful access to essential organizational principles of the brain. The aim of this study was to investigate longitudinal evolution of gray matter networks in early relapsing–remitting MS (RRMS) compared with healthy controls (HCs) and contrast network dynamics with conventional atrophy measurements. METHODS: For our longitudinal study, we investigated structural cortical networks over 1 year derived from 3T MRI in 203 individuals (92 early RRMS patients with mean disease duration of 12.1 ± 14.5 months and 101 HCs). Brain networks were computed based on cortical thickness inter-regional correlations and fed into graph theoretical analysis. Network connectivity measures (modularity, clustering coefficient, local efficiency, and transitivity) were compared between patients and HCs, and between patients with and without disease activity. Moreover, we calculated longitudinal brain volume changes and cortical atrophy patterns. RESULTS: Our analyses revealed strengthening of local network properties shown by increased modularity, clustering coefficient, local efficiency, and transitivity over time. These network dynamics were not detectable in the cortex of HCs over the same period and occurred independently of patients’ disease activity. Most notably, the described network reorganization was evident beyond detectable atrophy as characterized by conventional morphometric methods. CONCLUSION: In conclusion, our findings provide evidence for gray matter network reorganization subsequent to clinical disease manifestation in patients with early RRMS. An adaptive cortical response with increased local network characteristics favoring network segregation could play a primordial role for maintaining brain function in response to neuroinflammation. |
format | Online Article Text |
id | pubmed-6482642 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-64826422019-04-30 Longitudinal cortical network reorganization in early relapsing–remitting multiple sclerosis Fleischer, Vinzenz Koirala, Nabin Droby, Amgad Gracien, René-Maxime Deichmann, Ralf Ziemann, Ulf Meuth, Sven G. Muthuraman, Muthuraman Zipp, Frauke Groppa, Sergiu Ther Adv Neurol Disord Advances in Neuroimaging BACKGROUND: Network science provides powerful access to essential organizational principles of the brain. The aim of this study was to investigate longitudinal evolution of gray matter networks in early relapsing–remitting MS (RRMS) compared with healthy controls (HCs) and contrast network dynamics with conventional atrophy measurements. METHODS: For our longitudinal study, we investigated structural cortical networks over 1 year derived from 3T MRI in 203 individuals (92 early RRMS patients with mean disease duration of 12.1 ± 14.5 months and 101 HCs). Brain networks were computed based on cortical thickness inter-regional correlations and fed into graph theoretical analysis. Network connectivity measures (modularity, clustering coefficient, local efficiency, and transitivity) were compared between patients and HCs, and between patients with and without disease activity. Moreover, we calculated longitudinal brain volume changes and cortical atrophy patterns. RESULTS: Our analyses revealed strengthening of local network properties shown by increased modularity, clustering coefficient, local efficiency, and transitivity over time. These network dynamics were not detectable in the cortex of HCs over the same period and occurred independently of patients’ disease activity. Most notably, the described network reorganization was evident beyond detectable atrophy as characterized by conventional morphometric methods. CONCLUSION: In conclusion, our findings provide evidence for gray matter network reorganization subsequent to clinical disease manifestation in patients with early RRMS. An adaptive cortical response with increased local network characteristics favoring network segregation could play a primordial role for maintaining brain function in response to neuroinflammation. SAGE Publications 2019-04-24 /pmc/articles/PMC6482642/ /pubmed/31040880 http://dx.doi.org/10.1177/1756286419838673 Text en © The Author(s), 2019 http://www.creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Advances in Neuroimaging Fleischer, Vinzenz Koirala, Nabin Droby, Amgad Gracien, René-Maxime Deichmann, Ralf Ziemann, Ulf Meuth, Sven G. Muthuraman, Muthuraman Zipp, Frauke Groppa, Sergiu Longitudinal cortical network reorganization in early relapsing–remitting multiple sclerosis |
title | Longitudinal cortical network reorganization in early relapsing–remitting multiple sclerosis |
title_full | Longitudinal cortical network reorganization in early relapsing–remitting multiple sclerosis |
title_fullStr | Longitudinal cortical network reorganization in early relapsing–remitting multiple sclerosis |
title_full_unstemmed | Longitudinal cortical network reorganization in early relapsing–remitting multiple sclerosis |
title_short | Longitudinal cortical network reorganization in early relapsing–remitting multiple sclerosis |
title_sort | longitudinal cortical network reorganization in early relapsing–remitting multiple sclerosis |
topic | Advances in Neuroimaging |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6482642/ https://www.ncbi.nlm.nih.gov/pubmed/31040880 http://dx.doi.org/10.1177/1756286419838673 |
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