Wang Chunyi, Hu Jiajia, Li Puyu, Zhang Ming, Zhou Liche, Luo Ningdi, Zhu Xue, Yin Qianyi, Zhong Min, Zhou Xinyi, Wei Hongjiang, Li Yuanyuan, Li Biao, Liu Jun
Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Front Neurol. 2024 Aug 22;15:1442851. doi: 10.3389/fneur.2024.1442851. eCollection 2024.
Brain network dysfunction has been characterized by resting-state electroencephalography (EEG) and magnetic resonance imaging (MRI) in the prodromal stage. This study aimed to identify multi-modal electrophysiological and neuroimaging biomarkers for differential diagnosis in synucleinopathies and phenoconversion in isolated rapid eye movement sleep behavior disorder (iRBD).
We enrolled 35 patients with multiple system atrophy (MSA), 32 with Parkinson's disease (PD), 30 with iRBD and 30 matched healthy controls (HC). Power spectral density (PSD) was calculated in different frequency bands. EEG functional connectivity (FC) was calculated using the weighted Phase Lag Index (wPLI) after source localization. Significant network disruptions were further confirmed by MRI FC analysis.
Quantitative EEG analysis demonstrated that delta and theta power spectral density significantly differed among MSA, PD and HC. The increased PSD was correlated with cognitive decline and olfactory dysfunction in PD. Band-specific FC profiles were observed in theta, alpha, and gamma bands. The hypoconnected alpha network significantly correlated with motor dysfunction, while the gamma FC distinguished PD from MSA. By integrating EEG and MRI network analyses, we found that FC between the olfactory cortex and dorsolateral prefrontal cortex was significantly different between MSA and PD. A multimodal discriminative model for MSA and PD, integrating spectral and FC attributes of EEG and MRI, yielded an area under the receiver operating characteristic curve of 0.900. Simultaneously, we found the FC abnormalities were more prominent than spectral features in iRBD indicating prodromal dysfunction. The decreased FC between the angular gyrus and striatum was identified in α-synucleinopathies. This hypoconnectivity was associated with dopaminergic degeneration in iRBD examined by dopamine transporter imaging.
Our study demonstrated EEG spectral and functional profiles in prodromal and clinical-defined synucleinopathies. Multimodal EEG and MRI provided a novel approach to discriminate MSA and PD, and monitor neurodegenerative progression in the preclinical phase.
在疾病前驱期，静息态脑电图（EEG）和磁共振成像（MRI）已显示出脑网络功能障碍的特征。本研究旨在识别多模态电生理和神经影像生物标志物，用于突触核蛋白病的鉴别诊断以及孤立性快速眼动睡眠行为障碍（iRBD）的表型转化。
我们纳入了35例多系统萎缩（MSA）患者、32例帕金森病（PD）患者、30例iRBD患者以及30名匹配的健康对照（HC）。计算不同频段的功率谱密度（PSD）。在源定位后，使用加权相位滞后指数（wPLI）计算EEG功能连接（FC）。通过MRI FC分析进一步确认显著的网络破坏。
定量EEG分析表明，MSA、PD和HC之间的δ和θ功率谱密度存在显著差异。PD中PSD增加与认知衰退和嗅觉功能障碍相关。在θ、α和γ频段观察到特定频段的FC图谱。α网络连接减少与运动功能障碍显著相关，而γ FC可区分PD和MSA。通过整合EEG和MRI网络分析，我们发现MSA和PD之间嗅觉皮质与背外侧前额叶皮质之间的FC存在显著差异。一个整合EEG和MRI的频谱和FC属性的MSA和PD多模态判别模型，其受试者操作特征曲线下面积为0.900。同时，我们发现iRBD中的FC异常比频谱特征更突出，表明前驱期功能障碍。在α-突触核蛋白病中发现角回与纹状体之间的FC降低。通过多巴胺转运体成像检查发现，这种连接减少与iRBD中的多巴胺能变性有关。
我们的研究展示了前驱期和临床定义的突触核蛋白病中的EEG频谱和功能特征。多模态EEG和MRI提供了一种新方法来区分MSA和PD，并监测临床前期神经退行性进展。
