| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 3075152 | NeuroImage: Clinical | 2015 | 12 Pages |
•Investigates characteristics of the connectome in Huntington's disease (HD).•HD patients showed longitudinal changes in their structural connectome.•Connectome dynamics correlated with changes in clinical and cognitive measures.•Connectomics provides novel insights into compensatory strategies of the diseased brain.
ObjectivesTo longitudinally investigate the connectome in different stages of Huntington's disease (HD) by applying graph theoretical analysis to diffusion MRI data.Experimental designWe constructed weighted structural networks and calculated their topological properties. Twenty-two premanifest (preHD), 10 early manifest HD and 24 healthy controls completed baseline and 2 year follow-up scans. We stratified the preHD group based on their predicted years to disease onset into a far (preHD-A) and near (preHD-B) to disease onset group. We collected clinical and behavioural measures per assessment time point.Principle observationsWe found a significant reduction over time in nodal betweenness centrality both in the early manifest HD and preHD-B groups as compared to the preHD-A and control groups, suggesting a decrease of importance of specific nodes to overall network organization in these groups (FDR adjusted ps < 0.05). Additionally, we found a significant longitudinal decrease of the clustering coefficient in preHD when compared to healthy controls (FDR adjusted p < 0.05), which can be interpreted as a reduced capacity for internodal information processing at the local level. Furthermore, we demonstrated dynamic changes to hub-status loss and gain both in preHD and early manifest HD. Finally, we found significant cross-sectional as well as longitudinal relationships between graph metrics and clinical and neurocognitive measures.ConclusionsThis study demonstrates divergent longitudinal changes to the connectome in (pre) HD compared to healthy controls. This provides novel insights into structural correlates associated with clinical and cognitive functions in HD and possible compensatory mechanisms at play in preHD.
