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Anatomical Covariance Analysis: Detection of Disrupted Correlation Network Related to Clinical Trait Fatigue in Multiple Sclerosis: A Pilot Study

BACKGROUND: Fatigue is one of the most distressing symptoms among persons with multiple sclerosis (PwMS). The experience of fatigue is inherently interoceptive, yet no study to date has explicitly investigated the insular cortex (IC) as a primary goal in the experience of fatigue in PwMS. In additio...

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Autores principales: Dacosta-Aguayo, Rosalia, Wylie, Glenn, DeLuca, John, Genova, Helen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775148/
https://www.ncbi.nlm.nih.gov/pubmed/32175581
http://dx.doi.org/10.1155/2020/5807496
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author Dacosta-Aguayo, Rosalia
Wylie, Glenn
DeLuca, John
Genova, Helen
author_facet Dacosta-Aguayo, Rosalia
Wylie, Glenn
DeLuca, John
Genova, Helen
author_sort Dacosta-Aguayo, Rosalia
collection PubMed
description BACKGROUND: Fatigue is one of the most distressing symptoms among persons with multiple sclerosis (PwMS). The experience of fatigue is inherently interoceptive, yet no study to date has explicitly investigated the insular cortex (IC) as a primary goal in the experience of fatigue in PwMS. In addition, it is unknown how brain regions such as IC play a role in state or trait fatigue. OBJECTIVE: Assess the involvement of the IC in trait fatigue and state fatigue in PwMS with and without clinical fatigue. METHODS: Trait and state fatigue, cognitive status, and structural MRI were assessed in 27 PwMS. PwMS were stratified into nonclinical fatigue (nF-MS, FSS ≤ 4.0) (n = 10) and clinical fatigue (F-MS, FSS ≥ 5.0) (n = 10). Voxel-based morphometry analysis (VBM) for the whole sample (n = 20) and for the two groups was performed. Anatomical covariance analysis (ACA) analysis was conducted by selecting different volumes included in the corticostriatal network (CoStN) and analyzing interhemispheric correlations between those volumes to explore the state of the CoStN in both groups. RESULTS: In the VBM analysis, when considering the whole sample of PwMS, higher levels of trait fatigue were negatively associated with grey matter (GM) volume in the left dorsal anterior insula (dAI) (rho = −0.647; p = 0.002; R(2) = 0.369). When comparing nF-MS versus F-MS, significant differences were found in the left dAI, where the F-MS group showed less GM volume in the left dAI. In the ACA analysis, the F-MS group showed fewer significant interhemispheric correlations in comparison with the Low-FSS group. CONCLUSIONS: The present results provide support to the interoceptive component of self-reported fatigue and suggest that changes in the relationship between the different anatomical regions involved in the CoStN are present even in nonclinical trait fatigue. Those changes might be responsible for the experience of trait fatigue in PwMS. Future studies with larger samples and multimodal MRI acquisitions should be considered to fully understand the changes in the CoStN and the specific role of the IC in trait fatigue.
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spelling pubmed-77751482021-01-07 Anatomical Covariance Analysis: Detection of Disrupted Correlation Network Related to Clinical Trait Fatigue in Multiple Sclerosis: A Pilot Study Dacosta-Aguayo, Rosalia Wylie, Glenn DeLuca, John Genova, Helen Behav Neurol Research Article BACKGROUND: Fatigue is one of the most distressing symptoms among persons with multiple sclerosis (PwMS). The experience of fatigue is inherently interoceptive, yet no study to date has explicitly investigated the insular cortex (IC) as a primary goal in the experience of fatigue in PwMS. In addition, it is unknown how brain regions such as IC play a role in state or trait fatigue. OBJECTIVE: Assess the involvement of the IC in trait fatigue and state fatigue in PwMS with and without clinical fatigue. METHODS: Trait and state fatigue, cognitive status, and structural MRI were assessed in 27 PwMS. PwMS were stratified into nonclinical fatigue (nF-MS, FSS ≤ 4.0) (n = 10) and clinical fatigue (F-MS, FSS ≥ 5.0) (n = 10). Voxel-based morphometry analysis (VBM) for the whole sample (n = 20) and for the two groups was performed. Anatomical covariance analysis (ACA) analysis was conducted by selecting different volumes included in the corticostriatal network (CoStN) and analyzing interhemispheric correlations between those volumes to explore the state of the CoStN in both groups. RESULTS: In the VBM analysis, when considering the whole sample of PwMS, higher levels of trait fatigue were negatively associated with grey matter (GM) volume in the left dorsal anterior insula (dAI) (rho = −0.647; p = 0.002; R(2) = 0.369). When comparing nF-MS versus F-MS, significant differences were found in the left dAI, where the F-MS group showed less GM volume in the left dAI. In the ACA analysis, the F-MS group showed fewer significant interhemispheric correlations in comparison with the Low-FSS group. CONCLUSIONS: The present results provide support to the interoceptive component of self-reported fatigue and suggest that changes in the relationship between the different anatomical regions involved in the CoStN are present even in nonclinical trait fatigue. Those changes might be responsible for the experience of trait fatigue in PwMS. Future studies with larger samples and multimodal MRI acquisitions should be considered to fully understand the changes in the CoStN and the specific role of the IC in trait fatigue. Hindawi 2020-12-23 /pmc/articles/PMC7775148/ /pubmed/32175581 http://dx.doi.org/10.1155/2020/5807496 Text en Copyright © 2020 Rosalia Dacosta-Aguayo et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Dacosta-Aguayo, Rosalia
Wylie, Glenn
DeLuca, John
Genova, Helen
Anatomical Covariance Analysis: Detection of Disrupted Correlation Network Related to Clinical Trait Fatigue in Multiple Sclerosis: A Pilot Study
title Anatomical Covariance Analysis: Detection of Disrupted Correlation Network Related to Clinical Trait Fatigue in Multiple Sclerosis: A Pilot Study
title_full Anatomical Covariance Analysis: Detection of Disrupted Correlation Network Related to Clinical Trait Fatigue in Multiple Sclerosis: A Pilot Study
title_fullStr Anatomical Covariance Analysis: Detection of Disrupted Correlation Network Related to Clinical Trait Fatigue in Multiple Sclerosis: A Pilot Study
title_full_unstemmed Anatomical Covariance Analysis: Detection of Disrupted Correlation Network Related to Clinical Trait Fatigue in Multiple Sclerosis: A Pilot Study
title_short Anatomical Covariance Analysis: Detection of Disrupted Correlation Network Related to Clinical Trait Fatigue in Multiple Sclerosis: A Pilot Study
title_sort anatomical covariance analysis: detection of disrupted correlation network related to clinical trait fatigue in multiple sclerosis: a pilot study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775148/
https://www.ncbi.nlm.nih.gov/pubmed/32175581
http://dx.doi.org/10.1155/2020/5807496
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