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TMS-evoked potentials unveil occipital network involvement in patients diagnosed with Parkinson’s disease within 5 years of inclusion
npj Parkinson's Disease ( IF 6.7 ) Pub Date : 2024-09-30 , DOI: 10.1038/s41531-024-00793-0
Noa Zifman, Ofri Levy-Lamdan, Tal Hiller, Avner Thaler, Iftach Dolev, Anat Mirelman, Hilla Fogel, Mark Hallett, Inbal Maidan

Distinguishing Parkinson’s disease (PD) subgroups may be achieved by observing network responses to external stimuli. We compared TMS-evoked potential (TEP) measures from stimulation of bilateral motor cortex (M1), dorsolateral prefrontal cortex (DLPFC), and visual cortex (V1) between 62 PD patients (age: 69.9 ± 7.5) and 76 healthy controls (age: 69.2 ± 4.3) using a TMS–EEG protocol. TEP measures were analyzed using two-way ANCOVA adjusted for MOCA. PD patients were divided into tremor dominant (TD), non-tremor dominant (NTD) and rapid disease progression (RDP) subgroups. PD patients showed lower wide-waveform adherence (wWFA) (p = 0.025) and interhemispheric connectivity (IHCCONN) (p < 0.001) compared to healthy controls. Lower occipital IHCCONN correlated with advanced disease stage (r = −0.37, p = 0.0039). The RDP and NTD groups showed lower wWFA in response to occipital stimulation than the TD group (p = 0.005). Occipital TEP measures identified RDP patients with 85% accuracy. These findings demonstrate occipital network involvement in early PD stages, suggesting that TEP measures offer insights into altered networks in PD subgroups.



中文翻译:


TMS 诱发电位揭示了入组后 5 年内被诊断患有帕金森病的患者的枕骨网络参与



区分帕金森病 (PD) 亚组可以通过观察网络对外部刺激的反应来实现。我们比较了 62 名 PD 患者 (年龄:69.9 ± 7.5) 和 76 名健康对照者 (年龄:69.2 ± 4.3) 刺激双侧运动皮层 (M1)、背外侧前额叶皮层 (DLPFC) 和视觉皮层 (V1) 的 TMS 诱发电位 (TEP) 测量值使用 TMS-EEG 方案。使用针对 MOCA 调整的双向 ANCOVA 分析 TEP 测量。将 PD 患者分为震颤显性 (TD) 、非震颤显性 (NTD) 和疾病快速进展 (RDP) 亚组。与健康对照相比,PD 患者的宽波形依从性 (wWFA) (p = 0.025) 和半球间连接 (IHC CONN) (p < 0.001) 较低。下枕 IHCCONN 与晚期疾病分期相关 (r = -0.37,p = 0.0039)。 RDP 和 NTD 组对枕骨刺激的响应 wWFA 低于 TD 组 (p = 0.005)。枕部 TEP 测量识别的 RDP 患者的准确率为 85%。这些发现表明枕骨网络参与早期 PD 阶段,表明 TEP 测量提供了对 PD 亚组中改变网络的见解。

更新日期:2024-09-30
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