Applied Neuroscience Research Group, Central European Institute of Technology, Masaryk University (CEITEC MU), Brno, Czech Republic.
Faculty of Medicine, Masaryk University, Brno, Czech Republic.
J Alzheimers Dis. 2019;67(3):971-984. doi: 10.3233/JAD-180834.
Cognitive impairment in Parkinson's disease (PD) is associated with altered connectivity of the resting state networks (RSNs). Longitudinal studies in well cognitively characterized PD subgroups are missing.
To assess changes of the whole-brain connectivity and between-network connectivity (BNC) of large-scale functional networks related to cognition in well characterized PD patients using a longitudinal study design and various analytical methods.
We explored the whole-brain connectivity and BNC of the frontoparietal control network (FPCN) and the default mode, dorsal attention, and visual networks in PD with normal cognition (PD-NC, n = 17) and mild cognitive impairment (PD-MCI, n = 22) as compared to 51 healthy controls (HC). We applied regions of interest-based, partial least squares, and graph theory based network analyses. The differences among groups were analyzed at baseline and at the one-year follow-up visit (37 HC, 23 PD all).
The BNC of the FPCN and other RSNs was reduced, and the whole-brain analysis revealed increased characteristic path length and decreased average node strength, clustering coefficient, and global efficiency in PD-NC compared to HC. Values of all measures in PD-MCI were between that of HC and PD-NC. After one year, the BNC was further increased in the PD-all group; no changes were detected in HC. No cognitive domain z-scores deteriorated in either group.
As compared to HC, PD-NC patients display a less efficient transfer of information globally and reduced BNC of the visual and frontoparietal control network. The BNC increases with time and MCI status, reflecting compensatory efforts.
帕金森病(PD)患者的认知障碍与静息态网络(RSN)的连接改变有关。在认知特征良好的 PD 亚组中,缺乏纵向研究。
使用纵向研究设计和各种分析方法,评估认知特征良好的 PD 患者大尺度功能网络的全脑连接和网络间连接(BNC)的变化。
我们探索了认知正常 PD(PD-NC,n=17)和轻度认知障碍 PD(PD-MCI,n=22)患者与 51 名健康对照者(HC)的额顶控制网络(FPCN)和默认模式、背侧注意及视觉网络的全脑连接和 BNC。我们应用了基于感兴趣区的、偏最小二乘和基于图论的网络分析。在基线和一年随访(37 名 HC,23 名 PD 所有)时,分析组间差异。
FPCN 和其他 RSN 的 BNC 降低,全脑分析显示与 HC 相比,PD-NC 的特征路径长度增加,平均节点强度、聚类系数和全局效率降低。PD-MCI 的所有指标值均介于 HC 和 PD-NC 之间。一年后,PD-all 组的 BNC 进一步增加;HC 组未检测到变化。在任何一组中,都没有认知域 z 分数恶化。
与 HC 相比,PD-NC 患者的信息全局传输效率较低,视觉和额顶控制网络的 BNC 降低。BNC 随时间和 MCI 状态增加,反映了代偿努力。