Abnormal topological organization of structural covariance networks in early-stage Parkinson's disease patients with autonomic dysfunction.

Background: Autonomic dysfunction is a universal nonmotor symptom in Parkinson's disease (PD). Several magnetic resonance (MR) studies have shown that the abnormality of the central neural network is involved in the occurrence and development of autonomic nerve dysfunction in PD. This study aimed to investigate the network topological alteration in early-stage PD patients with autonomic dysfunction by structural covariance networks (SCNs) established via brain gray matter volume (GMV). Methods: The alterations of topological organization of GMV-based SCN in PD patients were analyzed, comparing patients with the highest (n=73) and lowest (n=89) quartile scores in a questionnaire assessing autonomic dysfunction in PD named Scales for Outcomes in Parkinson's Disease-Autonomic (SCOPA-AUT), obtained from a larger pool of patients (n=279). All analyses excluded the interference of age, sex, the Movement Disorders Society sponsored revision of Unified Parkinson's Disease Rating Scale (MDS-UPDRS-III) scores, and individual total intracranial volume (TIV). Results: Compared with PD patients with a lower burden of autonomic symptoms, those with a higher burden of autonomic symptoms had worsened motor symptoms, decreased small-world index (P<0.001) and normalized clustering coefficient (P<0.001), decreased nodal betweenness centrality (BC) in the right thalamus proper [P<0.0001, false discovery rate (FDR) corrected], increased nodal BC in the cerebellar vermal lobules VI-VII (P<0.0001, FDR corrected), and enhanced nodal efficiency (Ne) in the left middle temporal gyrus (P<0.0001, FDR corrected). Conclusions: Our study revealed abnormal global and local topological properties in the GMV-based SCN of early-stage PD patients with autonomic dysfunction and provided novel network-level evidence for elucidating the pathophysiological mechanisms of dysautonomia in early PD.