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Graph theoretical approach to brain remodeling in multiple sclerosis.

AmirHussein Abdolalizadeh1,2, Mohammad Amin Dabbagh Ohadi1,2, Amir Sasan Bayani Ershadi1,2

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

Network Neuroscience (Cambridge, Mass.)
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Multiple sclerosis (MS) patients show altered brain network organization, with higher modularity linked to cognitive decline and lesion load. This suggests impaired brain repair in MS, highlighting modularity as a potential biomarker.

Keywords:
CognitionDiffusion MRIGraph theoryMultiple sclerosisRemodeling

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Network Science

Background:

  • Multiple sclerosis (MS) is a neuroinflammatory disease impacting the brain's structural connectivity.
  • While the brain has natural remodeling capabilities, effective biomarkers for assessing this in MS are lacking.
  • Understanding network changes is crucial for evaluating disease progression and recovery.

Purpose of the Study:

  • To investigate graph theory metrics, specifically modularity, as potential biomarkers for neural remodeling and cognitive function in MS.
  • To compare network organization between individuals with MS and healthy controls.
  • To explore the relationship between graph metrics, lesion load, and cognitive performance in MS.

Main Methods:

  • Recruited 60 relapsing-remitting MS patients and 26 healthy controls.
  • Acquired structural MRI, diffusion MRI, cognitive assessments, and disability evaluations.
  • Calculated graph theory metrics (modularity, global efficiency) from tractography-derived brain connectivity matrices.
  • Utilized general linear models to analyze associations, adjusting for relevant covariates.

Main Results:

  • Individuals with MS exhibited significantly higher modularity and lower global efficiency compared to healthy controls.
  • In the MS cohort, increased modularity correlated inversely with cognitive performance.
  • Higher modularity in MS patients was positively associated with T2 lesion load.

Conclusions:

  • Elevated modularity in MS appears to result from lesion-induced disruption of intermodular connections.
  • The observed increase in modularity does not correlate with improved or preserved cognitive function in MS.
  • Modularity shows promise as a biomarker for evaluating neural network disruption and impaired remodeling in multiple sclerosis.