Increased structural white and grey matter network connectivity compensates for functional decline in early multiple...

Area of Science:

• Neuroscience
• Medical Imaging
• Systems Biology

Background:

• Multiple sclerosis (MS) involves early demyelination and neuronal injury, with remission phases suggesting repair mechanisms.
• The central nervous system's (CNS) capacity for homeostasis and counteracting clinical impairment in MS remains poorly understood.

Purpose of the Study:

• To analyze white matter (WM) and grey matter (GM) structural connectivity in relapsing-remitting MS.
• To understand how network organization prevents clinical decline during disease progression.

Main Methods:

• Investigated 138 relapsing-remitting MS patients and 32 healthy controls using 3-Tesla MRI.
• Employed graph theory on diffusion-tensor imaging (WM) and voxel-based morphometry (GM) to analyze network connectivity.

Main Results:

• Early in MS (first year), WM networks showed increased modularity, local connectivity, and clustering without clinical decline.
• Grey matter (GM) networks exhibited similar increased modularity, particularly in the cerebellum, cingulum, and temporo-parietal regions.
• Clinical impairment correlated with network pattern divergence at later disease stages.

Conclusions:

• MS network functionality is maintained by structural adaptations favoring increased local and modular connectivity.
• These adaptive patterns are associated with the CNS's ability to maintain homeostasis.