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帕金森病运动波动的突触前机制:一个概率模型

Presynaptic mechanisms of motor fluctuations in Parkinson's disease: a probabilistic model.

作者信息

de la Fuente-Fernández Raúl, Schulzer Michael, Mak Edwin, Calne Donald B, Stoessl A Jon

机构信息

Pacific Parkinson's Research Centre, University of British Columbia, Vancouver, BC V6T 2B5, Canada.

出版信息

Brain. 2004 Apr;127(Pt 4):888-99. doi: 10.1093/brain/awh102. Epub 2004 Feb 11.

Abstract

Levodopa-treated Parkinson's disease is often complicated by the occurrence of motor fluctuations, which can be predictable ('wearing-off') or unpredictable ('on-off'). In contrast, untreated dopa-responsive dystonia (DRD) is usually characterized by predictable diurnal fluctuation. The pathogenesis of motor fluctuations in treated Parkinson's disease and diurnal fluctuation in untreated DRD is poorly understood. We have developed a mathematical model indicating that all these fluctuations in motor function can be explained by presynaptic mechanisms. The model is predicated upon the release of dopamine being subject to probabilistic variations in the quantity of dopamine released by exocytosis of vesicles. Specifically, we propose that the concentration of intravesicular dopamine undergoes dynamic changes according to a log-normal distribution that is associated with different probabilities of release failure. Changes in two parameters, (i) the proportion of vesicles that undergo exocytosis per unit of time and (ii) the proportion of dopamine subject to re-uptake from the synapse, allowed us to model different curves of levodopa response, for the same degree of nigrostriatal damage in Parkinson's disease. The model predicts the following periods of levodopa clinical benefit: 4 h for stable responders, 3 h for wearing-off fluctuators, and 1.5 h for on-off fluctuators. The model also predicts that diurnal fluctuation in untreated DRD should occur some 8 h after getting up in the morning. All these results fit well with clinical observations. Additionally, we calculated the probability of obtaining a second ON period after a single dose of levodopa in Parkinson's disease (the 'yo-yoing' phenomenon). The model shows that the yo-yoing phenomenon depends on how fast the curve crosses the threshold that separates ON and OFF states, which explains why this phenomenon is virtually exclusive to patients with on-off fluctuations. The model supports the idea that presynaptic mechanisms play a key role in both short-duration and long-duration responses encountered in Parkinson's disease. Dyskinesias may also be explained by the same mechanisms.

摘要

左旋多巴治疗的帕金森病常因运动波动的出现而复杂化,运动波动可分为可预测的(“剂末现象”)或不可预测的(“开-关”现象)。相比之下,未经治疗的多巴反应性肌张力障碍(DRD)通常以可预测的日间波动为特征。左旋多巴治疗的帕金森病中运动波动以及未经治疗的DRD中日间波动的发病机制尚不清楚。我们建立了一个数学模型,表明运动功能的所有这些波动都可以用突触前机制来解释。该模型基于多巴胺的释放受到囊泡胞吐释放多巴胺量的概率变化的影响。具体而言,我们提出囊泡内多巴胺的浓度根据对数正态分布进行动态变化,该分布与释放失败的不同概率相关。两个参数的变化,即(i)每单位时间发生胞吐作用的囊泡比例和(ii)从突触重新摄取的多巴胺比例,使我们能够针对帕金森病中相同程度的黑质纹状体损伤模拟不同的左旋多巴反应曲线。该模型预测了左旋多巴临床获益的以下时间段:稳定反应者为4小时,剂末波动者为3小时,开-关波动者为1.5小时。该模型还预测未经治疗的DRD中的日间波动应在早晨起床后约8小时出现。所有这些结果与临床观察结果非常吻合。此外,我们计算了帕金森病患者单次服用左旋多巴后获得第二个“开”期的概率(“溜溜球”现象)。该模型表明,“溜溜球”现象取决于曲线穿过区分“开”和“关”状态的阈值的速度,这解释了为什么这种现象实际上仅见于有开-关波动的患者。该模型支持突触前机制在帕金森病中遇到的短期和长期反应中都起关键作用的观点。异动症也可能由相同机制解释。

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