Global and Subnetwork Changes of the Structural Connectome in de novo Parkinson’s Disease

Abstract

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by widespread neuropathological involvement of cortical and subcortical brain areas, which may therefore affect the structural brain network or ‘connectome’. Using diffusion tensor imaging (DTI) and graph analysis we studied the structural connectome of medication-naïve PD patients. DTI was acquired in 23 early-stage PD patients and 38 age, sex and education matched healthy controls. We studied global, subnetwork and local network topology using the Brainnetome atlas. At the subnetwork level we focused on the default-mode, frontoparietal, sensorimotor and attention networks. Graph measures included global efficiency, clustering coefficient and betweenness centrality. PD patients showed lower global efficiency and global clustering coefficient compared with healthy controls. This was also evident in all four subnetworks. These findings were largely replicated with the automated anatomical labeling (AAL) atlas and robust across a large range of thresholds. These results suggest that the wiring of the structural brain network of early-stage medication-naïve PD patients is altered relative to healthy controls in such a way that it allows for less integration (global efficiency) and segregation (clustering coefficient) of information processing.