Objective:

This study employed an innovative method to assess myelin structure integrity in brain networks of patients with Multiple Sclerosis (pwMS). The goal was to investigate the alterations in myelin-weighted connectivity and their relationship with cognitive function and disability in pwMS.

Background:

Structural connectivity abnormalities in pwMS, as assessed by diffusion MRI, are associated with cognitive and motor dysfunction. However, diffusion MRI lacks myelin-specific sensitivity. To address this gap, we developed Myelin Streamlines Decomposition (MySD) to analyze brain network properties based on myelin content. Here, we retrospectively applied MySD for the first time in a Ph2 clinical trial.

Design/Methods:

We analyzed MTR-weighted connectomes from baseline MRI data in the SYNERGY trial: 112 relapsing-remitting (RR) (70 female, mean age 37.29±9.42, mean Expanded Disability Status Scale-EDSS 2.9±1.2) and 33 secondary progressive (SP) pwMS (20 female, mean age 48.06±6.96, mean EDSS 5.0±1.0). MySD was extended to incorporate MT values, accounting for signal loss in lesion-affected voxels, enabling MTR-weighted connectome calculation. We computed five global network metrics: density, mean strength-S, efficiency-E, modularity-M, and clustering coefficient-CC. We investigated (1) whether demyelination's impact on weighted global networks is different between RR and SP pwMS; and (2) if global myelin-weighted network metrics are associated with cognitive (Symbol Digit Modality Test-SDMT) and physical disability (EDSS).

Results:

We found higher S, E, and CC in RR compared to SP pwMS (p<0.03, R²>0.10). CC and S from myelin-weighted networks were negatively related to EDSS (p<0.03, R²>0.37), while SDMT was positively correlated with E, S, and CC (p<0.03, R²>0.37).

Conclusions:

It is possible to apply MySD to clinical trial data. CC and S –as obtained by MySD– were related to patients’ disability, whereas CC, S, and E were related to patients’ cognition.