Graph theoretical approach to brain remodeling in multiple sclerosis

Author:

Abdolalizadeh AmirHussein12ORCID,Ohadi Mohammad Amin Dabbagh12,Ershadi Amir Sasan Bayani12,Aarabi Mohammad Hadi3

Affiliation:

1. Students’ Scientific Research Program, Tehran University of Medical Sciences, Tehran, Iran

2. Interdisciplinary Neuroscience Research Program, Tehran University of Medical Sciences, Tehran, Iran

3. Department of Neuroscience, Padova Neuroscience Center, University of Padova, Padova, Italy

Abstract

Abstract 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.

Funder

euSNN European School of Network Neuroscience

Publisher

MIT Press

Subject

Applied Mathematics,Artificial Intelligence,Computer Science Applications,General Neuroscience

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