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The association between white matter tract structural connectivity and information processing speed in relapsing-remitting multiple sclerosis
BACKGROUND: Information processing speed (IPS) deterioration is common in relapsing-remitting multiple sclerosis (RRMS) patients [1] and might severely affect quality of life and occupational activity. However, understanding of its neural substrate is not fully elucidated. We aimed to investigate th...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415523/ https://www.ncbi.nlm.nih.gov/pubmed/37103603 http://dx.doi.org/10.1007/s10072-023-06817-6 |
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author | Chylińska, Magdalena Karaszewski, Bartosz Komendziński, Jakub Wyszomirski, Adam Hałas, Marek Szurowska, Edyta Sabisz, Agnieszka |
author_facet | Chylińska, Magdalena Karaszewski, Bartosz Komendziński, Jakub Wyszomirski, Adam Hałas, Marek Szurowska, Edyta Sabisz, Agnieszka |
author_sort | Chylińska, Magdalena |
collection | PubMed |
description | BACKGROUND: Information processing speed (IPS) deterioration is common in relapsing-remitting multiple sclerosis (RRMS) patients [1] and might severely affect quality of life and occupational activity. However, understanding of its neural substrate is not fully elucidated. We aimed to investigate the associations between MRI-derived metrics of neuroanatomical structures, including the tracts, and IPS. METHODS: Symbol Digit Modalities Test (SDMT), Paced Auditory Serial Addition Test (PASAT), and Color Trails Test (CTT) were used to evaluate IPS in 73 RRMS consecutive patients, all undergoing only interferon beta (IFN-β) therapy during the study. At the same time, 1.5T MRI including diffusion tensor imaging (DTI) data was acquired for each recruited subject. We analyzed volumetric and diffusion MRI measures (FreeSurfer 6.0) including normalized brain volume (NBV), cortical thickness (thk), white matter hypointensities (WMH), volume (vol), diffusion parameters: mean (MD), radial (RD), axial (AD) diffusivities, and fractional anisotropy (FA) of 18 major white-matter (WM) tracts. Multiple linear regression model with interaction resulted in distinguishing the neural substrate of IPS deficit in the IPS impaired subgroup of patients. RESULTS: The most significant tract abnormalities contributing to IPS deficit were right inferior longitudinal fasciculus (R ILF) FA, forceps major (FMAJ) FA, forceps minor (FMIN) FA, R uncinate fasciculus (UNC) AD, R corticospinal tract (CST) FA, and left superior longitudinal fasciculus FA (L SLFT). Among volumetric MRI metrics, IPS deficit was associated with L and R thalamic vol. and cortical thickness of insular regions. CONCLUSION: In this study, we showed that disconnection of the selected WM tracts, in addition to cortical and deep gray matter (GM) atrophy, might underlie IPS deficit in RRMS patients but more extensive studies are needed for precise associations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10072-023-06817-6. |
format | Online Article Text |
id | pubmed-10415523 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-104155232023-08-12 The association between white matter tract structural connectivity and information processing speed in relapsing-remitting multiple sclerosis Chylińska, Magdalena Karaszewski, Bartosz Komendziński, Jakub Wyszomirski, Adam Hałas, Marek Szurowska, Edyta Sabisz, Agnieszka Neurol Sci Original Article BACKGROUND: Information processing speed (IPS) deterioration is common in relapsing-remitting multiple sclerosis (RRMS) patients [1] and might severely affect quality of life and occupational activity. However, understanding of its neural substrate is not fully elucidated. We aimed to investigate the associations between MRI-derived metrics of neuroanatomical structures, including the tracts, and IPS. METHODS: Symbol Digit Modalities Test (SDMT), Paced Auditory Serial Addition Test (PASAT), and Color Trails Test (CTT) were used to evaluate IPS in 73 RRMS consecutive patients, all undergoing only interferon beta (IFN-β) therapy during the study. At the same time, 1.5T MRI including diffusion tensor imaging (DTI) data was acquired for each recruited subject. We analyzed volumetric and diffusion MRI measures (FreeSurfer 6.0) including normalized brain volume (NBV), cortical thickness (thk), white matter hypointensities (WMH), volume (vol), diffusion parameters: mean (MD), radial (RD), axial (AD) diffusivities, and fractional anisotropy (FA) of 18 major white-matter (WM) tracts. Multiple linear regression model with interaction resulted in distinguishing the neural substrate of IPS deficit in the IPS impaired subgroup of patients. RESULTS: The most significant tract abnormalities contributing to IPS deficit were right inferior longitudinal fasciculus (R ILF) FA, forceps major (FMAJ) FA, forceps minor (FMIN) FA, R uncinate fasciculus (UNC) AD, R corticospinal tract (CST) FA, and left superior longitudinal fasciculus FA (L SLFT). Among volumetric MRI metrics, IPS deficit was associated with L and R thalamic vol. and cortical thickness of insular regions. CONCLUSION: In this study, we showed that disconnection of the selected WM tracts, in addition to cortical and deep gray matter (GM) atrophy, might underlie IPS deficit in RRMS patients but more extensive studies are needed for precise associations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10072-023-06817-6. Springer International Publishing 2023-04-27 2023 /pmc/articles/PMC10415523/ /pubmed/37103603 http://dx.doi.org/10.1007/s10072-023-06817-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Chylińska, Magdalena Karaszewski, Bartosz Komendziński, Jakub Wyszomirski, Adam Hałas, Marek Szurowska, Edyta Sabisz, Agnieszka The association between white matter tract structural connectivity and information processing speed in relapsing-remitting multiple sclerosis |
title | The association between white matter tract structural connectivity and information processing speed in relapsing-remitting multiple sclerosis |
title_full | The association between white matter tract structural connectivity and information processing speed in relapsing-remitting multiple sclerosis |
title_fullStr | The association between white matter tract structural connectivity and information processing speed in relapsing-remitting multiple sclerosis |
title_full_unstemmed | The association between white matter tract structural connectivity and information processing speed in relapsing-remitting multiple sclerosis |
title_short | The association between white matter tract structural connectivity and information processing speed in relapsing-remitting multiple sclerosis |
title_sort | association between white matter tract structural connectivity and information processing speed in relapsing-remitting multiple sclerosis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415523/ https://www.ncbi.nlm.nih.gov/pubmed/37103603 http://dx.doi.org/10.1007/s10072-023-06817-6 |
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