Graph theoretical approach to brain remodeling in multiple sclerosis
Author(s) -
AmirHussein Abdolalizadeh,
Mohammad Amin Dabbagh Ohadi,
Amir Sasan Bayani Ershadi,
Mohammad Hadi Aarabi
Publication year - 2022
Publication title -
network neuroscience
Language(s) - English
Resource type - Journals
ISSN - 2472-1751
DOI - 10.1162/netn_a_00276
Subject(s) - multiple sclerosis , modularity (biology) , diffusion mri , tractography , cognition , neuroscience , lesion , graph , psychology , biomarker , connectome , medicine , computer science , magnetic resonance imaging , functional connectivity , biology , psychiatry , theoretical computer science , biochemistry , genetics , radiology
Multiple sclerosis (MS) is a neuroinflammatory disorder damaging structural connectivity. Natural remodeling processes of the nervous system can, to some extent, restore the damage caused. However, there is a lack of biomarkers to evaluate remodeling in MS. Our objective is to evaluate graph theory metrics (especially modularity) as a biomarker of remodeling and cognition in MS. We recruited 60 relapsing-remitting MS and 26 healthy controls. Structural and diffusion MRI, plus cognitive and disability evaluations, were done. We calculated modularity and global efficiency from the tractography-derived connectivity matrices. Association of graph metrics with T2 lesion load, cognition, and disability was evaluated using general linear models adjusting for age, gender, and disease duration wherever applicable. We showed that MS subjects had higher modularity and lower global efficiency compared with controls. In the MS group, modularity was inversely associated with cognitive performance but positively associated with T2 lesion load. Our results indicate that modularity increase is due to the disruption of intermodular connections in MS because of the lesions, with no improvement or preserving of cognitive functions.
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