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帕金森病的默认模式网络与认知:一种多模态静息态网络方法。

The default mode network and cognition in Parkinson's disease: A multimodal resting-state network approach.

机构信息

Department of Neurology, University Hospital of Marburg, Marburg, Germany.

Center for Mind, Brain, and Behavior-CMBB, Universities of Marburg and Gießen, Marburg, Germany.

出版信息

Hum Brain Mapp. 2021 Jun 1;42(8):2623-2641. doi: 10.1002/hbm.25393. Epub 2021 Feb 27.

Abstract

Involvement of the default mode network (DMN) in cognitive symptoms of Parkinson's disease (PD) has been reported by resting-state functional MRI (rsfMRI) studies. However, the relation to metabolic measures obtained by [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) is largely unknown. We applied multimodal resting-state network analysis to clarify the association between intrinsic metabolic and functional connectivity abnormalities within the DMN and their significance for cognitive symptoms in PD. PD patients were classified into normal cognition (n = 36) and mild cognitive impairment (MCI; n = 12). The DMN was identified by applying an independent component analysis to FDG-PET and rsfMRI data of a matched subset (16 controls and 16 PD patients) of the total cohort. Besides metabolic activity, metabolic and functional connectivity within the DMN were compared between the patients' groups and healthy controls (n = 16). Glucose metabolism was significantly reduced in all DMN nodes in both patient groups compared to controls, with the lowest uptake in PD-MCI (p < .05). Increased metabolic and functional connectivity along fronto-parietal connections was identified in PD-MCI patients compared to controls and unimpaired patients. Functional connectivity negatively correlated with cognitive composite z-scores in patients (r = -.43, p = .005). The current study clarifies the commonalities of metabolic and hemodynamic measures of brain network activity and their individual significance for cognitive symptoms in PD, highlighting the added value of multimodal resting-state network approaches for identifying prospective biomarkers.

摘要

静息态功能磁共振成像(rsfMRI)研究报道,默认模式网络(DMN)参与了帕金森病(PD)的认知症状。然而,其与[18F]-氟脱氧葡萄糖正电子发射断层扫描(FDG-PET)获得的代谢测量的关系在很大程度上尚不清楚。我们应用多模态静息态网络分析来阐明DMN内内在代谢和功能连接异常与 PD 认知症状之间的关系及其意义。将 PD 患者分为正常认知(n = 36)和轻度认知障碍(MCI;n = 12)。通过对 FDG-PET 和 rsfMRI 数据的匹配子集(总队列中的 16 名对照和 16 名 PD 患者)应用独立成分分析来识别 DMN。除代谢活性外,还比较了患者组和健康对照组(16 名)之间 DMN 内的代谢和功能连接。与对照组相比,两组患者的所有 DMN 节点的葡萄糖代谢均显著降低,而 PD-MCI 患者的摄取量最低(p <.05)。与对照组和未受损患者相比,PD-MCI 患者的额顶连接中存在代谢和功能连接增加。功能连接与患者的认知综合 z 评分呈负相关(r = -.43,p =.005)。本研究阐明了脑网络活动的代谢和血液动力学测量的共性及其对 PD 认知症状的个体意义,突出了多模态静息态网络方法在识别前瞻性生物标志物方面的附加价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e37a/8090788/8f1e24a67c95/HBM-42-2623-g004.jpg

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