Topological changes in white matter connectivity network in patients with Parkinson's disease and depression

Depression is the most common non-motor symptom accompanying Parkinson's disease (PD) with high prevalence but unclear pathophysiological mechanism. Relatively little is known about the topological patterns of white matter structural networks in depressed patients with PD. In this study, we used diffusion-tensor imaging (DTI) and graph theory approaches to explore the brain structural connectome in non-depressed patients with PD (n = 47), depressed patients with PD (n = 20) and healthy controls (n = 46). All three groups exhibited small-world topology. Compared with healthy controls, non-depressed patients with PD and depressed patients with PD showed a significant reduction of network efficiency in the cortico-subcortical circuits. Moreover, depressed patients with PD exhibited higher network efficiency in fronto-limbic system, compared to non-depressed patients with PD. To sum up, our data indicated a disrupted integrity in the large-scale brain systems in depressed patients with PD patients. The structural connectome provided a basis for functional alterations in depressed patients with PD that may advance our current understanding of pathophysiological mechanism underlying Parkinson's disease.