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Authors: Fleischer, Vinzenz
Ciolac, Dumitru
Gonzalez-Escamilla, Gabriel
Grothe, Matthias
Strauss, Sebastian
Molina Galindo, Lara S.
Radetz, Angela
Salmen, Anke
Lukas, Carsten
Klotz, Luisa
Meuth, Sven G.
Bayas, Antonios
Paul, Friedemann
Hartung, Hans-Peter
Heesen, Christoph
Stangel, Martin
Wildemann, Brigitte
Then Bergh, Florian
Tackenberg, Björn
Kümpfel, Tania
Zettl, Uwe K.
Knop, Matthias
Tumani, Hayrettin
Wiendl, Heinz
Gold, Ralf
Bittner, Stefan
Zipp, Frauke
Groppa, Sergiu
Muthuraman, Muthuraman
Title: Subcortical volumes as early predictors of fatigue in multiple sclerosis
Online publication date: 5-Sep-2022
Year of first publication: 2022
Language: english
Abstract: Objective Fatigue is a frequent and severe symptom in multiple sclerosis (MS), but its pathophysiological origin remains incompletely understood. We aimed to examine the predictive value of subcortical gray matter volumes for fatigue severity at disease onset and after 4 years by applying structural equation modeling (SEM). Methods This multicenter cohort study included 601 treatment-naive patients with MS after the first demyelinating event. All patients underwent a standardized 3T magnetic resonance imaging (MRI) protocol. A subgroup of 230 patients with available clinical follow-up data after 4 years was also analyzed. Associations of subcortical volumes (included into SEM) with MS-related fatigue were studied regarding their predictive value. In addition, subcortical regions that have a central role in the brain network (hubs) were determined through structural covariance network (SCN) analysis. Results Predictive causal modeling identified volumes of the caudate (s [standardized path coefficient] = 0.763, p = 0.003 [left]; s = 0.755, p = 0.006 [right]), putamen (s = 0.614, p = 0.002 [left]; s = 0.606, p = 0.003 [right]) and pallidum (s = 0.606, p = 0.012 [left]; s = 0.606, p = 0.012 [right]) as prognostic factors for fatigue severity in the cross-sectional cohort. Moreover, the volume of the pons was additionally predictive for fatigue severity in the longitudinal cohort (s = 0.605, p = 0.013). In the SCN analysis, network hubs in patients with fatigue worsening were detected in the putamen (p = 0.008 [left]; p = 0.007 [right]) and pons (p = 0.0001). Interpretation We unveiled predictive associations of specific subcortical gray matter volumes with fatigue in an early and initially untreated MS cohort. The colocalization of these subcortical structures with network hubs suggests an early role of these brain regions in terms of fatigue evolution. ANN NEUROL 2022;91:192–202
DDC: 610 Medizin
610 Medical sciences
Institution: Johannes Gutenberg-Universität Mainz
Department: FB 04 Medizin
Place: Mainz
Version: Published version
Publication type: Zeitschriftenaufsatz
License: CC BY-NC-ND
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Journal: Annals of neurology
Pages or article number: 192
Publisher: Wiley-Blackwell
Publisher place: Hoboken, NJ
Issue date: 2022
ISSN: 1531-8249
Publisher DOI: 10.1002/ana.26290
Appears in collections:JGU-Publikationen

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