Brain functional network abnormalities in Parkinson’s disease patients at different disease stages - Wei, Wei; Wang, Xinhui; Han, Chao; Shen, Yu; Li, Panlong; Bai, Yan; Liu, Shuo; Xu, Jingyao; Shi, Yanhong; Li, Zhou; Wang, Meiyun (Frontiers in Neuroscience, 2025)
BackgroundParkinson’s disease (PD) is a neurodegenerative disorder with some progressive impairment and an unclear pathogenesis.PurposeThis study aimed to use resting-state functional magnetic resonance imaging (rs-fMRI) and graph analysis approaches to compare changes in brain functional network topology in PD at different disease stages.Materials and methodsA total of 58 PD patients, comprising 29 early-stage PD (PD-E) and 29 middle-to-late stage PD (PD-M), and 29 age- and sex-matched healthy control (HC) participants, were recruited. All subjects underwent clinical assessments and magnetic resonance imaging (MRI) scanning. We analyzed alterations in the global, regional, and modular topological characteristics of brain functional networks among different disease stages of PD patients and HC participants. Furthermore, we also examined the relationship between topological features with significant group effects and clinical characteristics, including the Movement Disorder Society’s Unified Parkinson’s Disease Rating Scale III (MDS-UPDRS III) score and Hoehn and Yahr (H&Y) stage.ResultsAt the global level, PD-M and PD-E exhibited lower clustering coefficient, and PD-M also exhibited lower local efficiency and normalized characteristic path length relative to HC. At the regional level, PD-M and PD-E showed lower nodal centrality in temporal-occipital regions and higher centrality in brain regions related to the default mode network and the frontoparietal control network compared to HC. Notably, nodal centrality metrics of the left middle frontal gyrus and the temporal pole of the right middle temporal gyrus were associated with the MDS-UPDRS III score and H&Y stage.ConclusionThis study found that the brain functional networks were disrupted at varying degrees in patients with PD at different disease stages. These findings contribute to our understanding of the topological changes in the neural networks associated with the severity of PD.