TY  - JOUR
A1  - Fleischer, Vinzenz
A1  - Koirala, Nabin
A1  - Droby, Amgad
A1  - Gracien, René-Maxime
A1  - Deichmann, Ralf
A1  - Ziemann, Ulf
A1  - Meuth, Sven
A1  - Muthuraman, Muthuraman
A1  - Zipp, Frauke
A1  - Groppa, Sergiu
T1  - Longitudinal cortical network reorganization in early relapsing–remitting multiple sclerosis
T2  - Therapeutic advances in neurological disorders
N2  - Background: Network science provides powerful access to essential organizational principles of the brain. The aim of this study was to investigate longitudinal evolution of gray matter networks in early relapsing–remitting MS (RRMS) compared with healthy controls (HCs) and contrast network dynamics with conventional atrophy measurements.
Methods: For our longitudinal study, we investigated structural cortical networks over 1 year derived from 3T MRI in 203 individuals (92 early RRMS patients with mean disease duration of 12.1 ± 14.5 months and 101 HCs). Brain networks were computed based on cortical thickness inter-regional correlations and fed into graph theoretical analysis. Network connectivity measures (modularity, clustering coefficient, local efficiency, and transitivity) were compared between patients and HCs, and between patients with and without disease activity. Moreover, we calculated longitudinal brain volume changes and cortical atrophy patterns.
Results: Our analyses revealed strengthening of local network properties shown by increased modularity, clustering coefficient, local efficiency, and transitivity over time. These network dynamics were not detectable in the cortex of HCs over the same period and occurred independently of patients’ disease activity. Most notably, the described network reorganization was evident beyond detectable atrophy as characterized by conventional morphometric methods.
Conclusion: In conclusion, our findings provide evidence for gray matter network reorganization subsequent to clinical disease manifestation in patients with early RRMS. An adaptive cortical response with increased local network characteristics favoring network segregation could play a primordial role for maintaining brain function in response to neuroinflammation.
KW  - graph theory
KW  - modularity
KW  - multiple sclerosis
KW  - network neuroscience
KW  - reorganization
KW  - structural covariance
Y1  - 2019
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/50357
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-503579
SN  - 1756-2864
SN  - 1756-2856
N1  - Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
VL  - 12
SP  - 1
EP  - 15
PB  - Sage
CY  - London [u. a.]
ER  -