Gutenberg Open Science: Gray matter integrity predicts white matter network reorganization in multiple sclerosis

Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-7188

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DC Field	Value	Language
dc.contributor.author	Radetz, Angela	-
dc.contributor.author	Koirala, Nabin	-
dc.contributor.author	Krämer, Julia	-
dc.contributor.author	Johnen, Andreas	-
dc.contributor.author	Fleischer, Vinzenz	-
dc.contributor.author	Gonzalez-Escamilla, Gabriel	-
dc.contributor.author	Cerina, Manuela	-
dc.contributor.author	Muthuraman, Muthuraman	-
dc.contributor.author	Meuth, Sven G.	-
dc.contributor.author	Groppa, Sergiu	-
dc.date.accessioned	2022-06-21T10:20:00Z	-
dc.date.available	2022-06-21T10:20:00Z	-
dc.date.issued	2020	-
dc.identifier.uri	https://openscience.ub.uni-mainz.de/handle/20.500.12030/7202	-
dc.description.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.	en_GB
dc.language.iso	eng	de
dc.rights	CC BY	*
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/	*
dc.subject.ddc	610 Medizin	de_DE
dc.subject.ddc	610 Medical sciences	en_GB
dc.title	Gray matter integrity predicts white matter network reorganization in multiple sclerosis	en_GB
dc.type	Zeitschriftenaufsatz	de
dc.identifier.doi	http://doi.org/10.25358/openscience-7188	-
jgu.type.dinitype	article	en_GB
jgu.type.version	Published version	de
jgu.type.resource	Text	de
jgu.organisation.department	FB 04 Medizin	de
jgu.organisation.number	2700	-
jgu.organisation.name	Johannes Gutenberg-Universität Mainz	-
jgu.rights.accessrights	openAccess	-
jgu.journal.title	Human brain mapping	de
jgu.journal.volume	41	de
jgu.journal.issue	4	de
jgu.pages.start	917	de
jgu.pages.end	927	de
jgu.publisher.year	2020	-
jgu.publisher.name	Wiley-Liss	de
jgu.publisher.place	New York, NY	de
jgu.publisher.issn	1097-0193	de
jgu.organisation.place	Mainz	-
jgu.subject.ddccode	610	de
jgu.publisher.doi	10.1002/hbm.24849	de
jgu.organisation.ror	https://ror.org/023b0x485
Appears in collections:	JGU-Publikationen

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