Gray matter integrity predicts white matter network reorganization in multiple sclerosis

Area of Science:

• Neuroscience
• Radiology
• Neurology

Background:

• Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease.
• MS leads to gray matter atrophy and brain network reconfiguration.
• The relationship between white matter and gray matter changes in MS is not fully understood.

Purpose of the Study:

• To investigate whether white matter network reconfiguration follows gray matter damage or vice versa in early MS.
• To assess the predictive value of gray matter integrity for clinical outcomes.

Main Methods:

• MRI data from 83 patients with early MS were analyzed over a 1-year follow-up.
• White matter network integrity was assessed using graph theoretical analyses of diffusion-weighted data.
• Gray matter integrity was evaluated by measuring cortical thickness and deep gray matter volume.

Main Results:

• Significant atrophy was observed in the middle temporal cortex, thalamus, caudate, putamen, and brain stem.
• Deep gray matter volume changes predicted white matter network dynamics (modularity and distance measures).
• Initial white matter properties did not predict atrophy; however, baseline gray matter integrity predicted physical disability and cognitive performance.

Conclusions:

• Deep gray matter atrophy appears to drive white matter network adaptations in MS.
• Deep gray matter volume is a strong predictor of disability progression and cognitive impairment in early MS.