Division of Life Sciences and Medicine, Department of Neurosurgery, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, China.
Anhui Province Key Laboratory of Brain Function and Brain Disease, Hefei, China.
J Parkinsons Dis. 2024;14(4):855-864. doi: 10.3233/JPD-240055.
Parkinson's disease (PD) is a common neurodegenerative disorder that is predominantly known for its motor symptoms but is also accompanied by non-motor symptoms, including anxiety.
The underlying neurobiological substrates and brain network changes associated with comorbid anxiety in PD require further exploration.
An analysis of oscillation-specific nodal properties in patients with and without anxiety was conducted using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory. We used a band-pass filtering approach to differentiate oscillatory frequency bands for subsequent functional connectivity (FC) and graph analyses.
The study included 68 non-anxiety PD (naPD) patients, 62 anxiety PD (aPD) patients, and 64 healthy controls (NC). Analyses of nodal betweenness centrality (BC), degree centrality (DC), and efficiency were conducted across multiple frequency bands. The findings indicated no significant differences in BC among naPD, aPD, and NC within the 0.01-0.08 Hz frequency range. However, we observed a specific reduction in BC at narrower frequency ranges in aPD patients, as well as differing patterns of change in DC and efficiency, which are believed to reflect the neurophysiological bases of anxiety symptoms in PD.
Differential oscillation-specific nodal characteristics have been identified in PD patients with anxiety, suggesting potential dysregulations in brain network dynamics. These findings emphasize the complexity of brain network alterations in anxiety-associated PD and identify oscillatory frequencies as potential biomarkers. The study highlights the importance of considering oscillatory frequency bands in the analysis of brain network changes.
帕金森病（PD）是一种常见的神经退行性疾病，主要以运动症状为特征，但也伴有非运动症状，包括焦虑。
需要进一步探讨与 PD 共病焦虑相关的潜在神经生物学基础和大脑网络变化。
使用静息态功能磁共振成像（rs-fMRI）和图论对伴或不伴焦虑的 PD 患者的振荡特定节点特性进行分析。我们使用带通滤波方法来区分振荡频率带，以便进行后续的功能连接（FC）和图分析。
该研究纳入了 68 名非焦虑 PD（naPD）患者、62 名焦虑 PD（aPD）患者和 64 名健康对照者（NC）。在多个频率波段上进行了节点介数中心性（BC）、度数中心性（DC）和效率的分析。结果表明，在 0.01-0.08 Hz 频率范围内，naPD、aPD 和 NC 之间的 BC 没有显著差异。然而，我们观察到 aPD 患者在更窄的频率范围内的 BC 特异性降低，以及 DC 和效率的不同变化模式，这被认为反映了 PD 中焦虑症状的神经生理基础。
在伴焦虑的 PD 患者中发现了具有差异的振荡特定节点特征，提示大脑网络动力学可能存在失调。这些发现强调了与焦虑相关的 PD 中大脑网络改变的复杂性，并确定了振荡频率作为潜在的生物标志物。该研究强调了在分析大脑网络变化时考虑振荡频率带的重要性。
