Brain function network abnormalities in Parkinson's disease patients at different disease stages

Wei Wei¹Xinhui Wang¹Chao Han²Yu Shen¹Panlong Li¹Yan Bai¹Shuo Liu¹Jingyao Xu¹Yanhong Shi¹Zhou Li²Meiyun Wang^1*

• ¹Henan Provincial People's Hospital, Zhengzhou, China
• ²General Hospital of Pingmei Shenma Medical Group, Pingdingshan, China

Parkinson's disease (PD) is a neurodegenerative disorder with some progressive impairment and an unclear pathogenesis.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.58 PD patients, with 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 functional brain networks among different disease stages of PD patients and HC participants. Furthermore, we also examined relationships between topological features with significant group effects and clinical characteristics, including Movement Disorder Society's Unified Parkinson's Disease Rating Scale III (MDS-UPDRS III) score and Hoehn and Yahr (H&Y) stage.At 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 brain regions related to the default mode network and frontoparietal control network relative 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 MDS-UPDRS III score and H&Y stage.This study found that the brain functional networks were disrupted at varying degree 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.