Altered Brain Functional Network in Subtypes of Parkinson's Disease: A Dynamic Perspective - Zhu, Junlan; Zeng, Qiaoling; Shi, Qiao; Li, Jiao; Dong, Shuwen; Lai, Chao; Cheng, Guanxun (Frontiers in Aging Neuroscience, 2021)
Background: Parkinson’s disease (PD) is a highly heterogeneous disease, especially in the clinical characteristics and prognosis. And subgroups of PD can be divided into tremor-dominant and nontremor-dominant. Previous studies suggest abnormal changes between two PD phenotypes by using static functional connectivity analysis. However, the dynamic properties of brain networks between two PD phenotypes are not yet clear. Therefore, we aimed to uncover dynamic functional network connectivity (dFNC) between the two PD phenotypes at subnetwork level, focused on temporal properties of dFNC and variability of network efficiency. Methods: We investigated resting-state functional magnetic resonance imaging (fMRI) data from 29 tremor-dominant PD patients (PDTD), 25 nontremor-dominant PD patients (PDNTD) and 20 healthy controls. Sliding window approach, k-means clustering, independent component analysis and graph theory analysis were applied to analyze the dFNC. Further the relationship between alterations in the dynamic properties and clincial features was assessed. Results: The dFNC analyses identified four reoccurring states, one of them showing sparse connections (State I). PDTD patients stayed longer time in State I and showed increased FNC between BG and vSMN in state IV. Both PD phenotypes exhibited higher FNC between dSMN and FPN in state II and in state III compared to the controls. PDNTD patients showed decreased FNC between BG and FPN but increased FNC in the bilateral FPN compared to both PDTD patients and controls. In addition, PDNTD patients exhibited greater variability in global network efficiency. Tremor scores were positively correlated with dwell time in state I along with increased FNC between BG and vSMN in state IV. Conclusions: This study explores dynamic functional network connectivity between the PDTD and PDNTD patients, which offers new evidences on the abnormal time-varying brain functional connectivity and their network destruction of the two PD phenotypes, and may help better understanding neural substrates underlying different types of PD.