Altered structural connectivity of the motor subnetwork in multiple system atrophy with cerebellar features

Objectives

To investigate the structural connectivity of the motor subnetwork in multiple system atrophy with cerebellar features (MSA-C), a distinct subtype of MSA, characterized by predominant cerebellar symptoms.

Methods

Twenty-three patients with MSA-C and 25 age- and gender-matched healthy controls were recruited for the study. Disease severity was quantified using the Unified Multiple System Atrophy Rating Scale (UMSARS). Diffusion MRI images were acquired and used to compute the structural connectomes (SCs) using probabilistic fiber tracking. The motor network with 12 brain regions and 26 cerebellar regions was extracted and was compared between the groups using analysis of variance at a global (network-wide), nodal (at each node), and edge (at each connection) levels, and was corrected for multiple comparisons. In addition, the acquired connectivity measures were correlated with duration of illness, total Unified MSA Rating Scale (UMSARS), and the motor component score.

Results

Significantly lower global network metrics—global density, transitivity, clustering coefficient, and characteristic path length—were observed in MSA-C (corrected p < 0.05). Reduced nodal strength was observed in the bilateral ventral diencephalon, the left thalamus, and several cerebellar regions. Network-based statistics revealed significant abnormal edge-wise connectivity in 40 connections (corrected p < 0.01), with majority of deficits observed in the cerebellum. Finally, significant negative correlations were observed between UMSARS scores and thalamic and cerebellar connectivity (p < 0.05) as well as between duration of illness and cerebellar connectivity.

Conclusions

Abnormal connectivity of the basal ganglia and cerebellar network may be causally implicated for the motor features observed in MSA-C.

Key Points

• Structural connectivity of the motor subnetwork was explored in patients with multiple system atrophy with cerebellar features (MSA-C) using probabilistic tractography.

• The motor subnetwork in MSA-C has significant alterations in both basal ganglia and cerebellar connectivity, with a higher extent of abnormality in the cerebellum.

• These findings may be causally implicated for the motor features of cerebellar dysfunction and parkinsonism observed in MSA-C.