Autoren:	Radetz, Angela Koirala, Nabin Krämer, Julia Johnen, Andreas Fleischer, Vinzenz Gonzalez-Escamilla, Gabriel Cerina, Manuela Muthuraman, Muthuraman Meuth, Sven G. Groppa, Sergiu
Titel:	Gray matter integrity predicts white matter network reorganization in multiple sclerosis
Online-Publikationsdatum:	21-Jun-2022
Erscheinungsdatum:	2020
Sprache des Dokuments:	Englisch
Zusammenfassung/Abstract:	Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease leading to gray matter atrophy and brain network reconfiguration as a response to increasing tissue damage. We evaluated whether white matter network reconfiguration appears subsequently to gray matter damage, or whether the gray matter degenerates following alterations in white matter networks. MRI data from 83 patients with clinically isolated syndrome and early relapsing–remitting MS were acquired at two time points with a follow-up after 1 year. White matter network integrity was assessed based on probabilistic tractography performed on diffusion-weighted data using graph theoretical analyses. We evaluated gray matter integrity by computing cortical thickness and deep gray matter volume in 94 regions at both time points. The thickness of middle temporal cortex and the volume of deep gray matter regions including thalamus, caudate, putamen, and brain stem showed significant atrophy between baseline and follow-up. White matter network dynamics, as defined by modularity and distance measure changes over time, were predicted by deep gray matter volume of the atrophying anatomical structures. Initial white matter network properties, on the other hand, did not predict atrophy. Furthermore, gray matter integrity at baseline significantly predicted physical disability at 1-year follow-up. In a sub-analysis, deep gray matter volume was significantly related to cognitive performance at baseline. Hence, we postulate that atrophy of deep gray matter structures drives the adaptation of white matter networks. Moreover, deep gray matter volumes are highly predictive for disability progression and cognitive performance.
DDC-Sachgruppe:	610 Medizin 610 Medical sciences
Veröffentlichende Institution:	Johannes Gutenberg-Universität Mainz
Organisationseinheit:	FB 04 Medizin
Veröffentlichungsort:	Mainz
ROR:	https://ror.org/023b0x485
DOI:	http://doi.org/10.25358/openscience-7188
Version:	Published version
Publikationstyp:	Zeitschriftenaufsatz
Nutzungsrechte:	CC BY
Informationen zu den Nutzungsrechten:	https://creativecommons.org/licenses/by/4.0/
Zeitschrift:	Human brain mapping 41 4
Seitenzahl oder Artikelnummer:	917 927
Verlag:	Wiley-Liss
Verlagsort:	New York, NY
Erscheinungsdatum:	2020
ISSN:	1097-0193
DOI der Originalveröffentlichung:	10.1002/hbm.24849
Enthalten in den Sammlungen:	JGU-Publikationen