GERAD and Department of Chemical Engineering, École Polytechnique de Montréal, Montréal, QC, Canada H3T 1J4.
IET Syst Biol. 2012 Jun;6(3):65-72. doi: 10.1049/iet-syb.2011.0075.
Research into Parkinson's disease (PD) is difficult and time consuming. It is a complex condition that develops over many decades in the human brain. For such apparently intractable diseases, mathematical models can offer an additional means of investigation. As a contribution to this process, the authors have developed an ordinary differential equation model of the most important cellular processes that have been associated with PD. The model describes the following processes: (i) cellular generation and scavenging of reactive oxygen species; (ii) the possible damage and removal of the protein -synuclein and, (iii) feedback interactions between damaged α-synuclein and reactive oxygen species. Simulation results show that the Parkinsonian condition, with elevated oxidative stress and misfolded α-synuclein accumulation, can be induced in the model by known PD risk factors such as ageing, exposure to toxins and genetic defects. The significant outcome of the paper is the demonstration that it is possible to reproduce in silico the multi-factorial interactions that characterise the pathogenesis of PD. As such, the model provides a systematic explanation of the variability and heterogeneity of PD and provides the basis for computational studies of further facets of this complex multi-factorial condition. [Includes supplementary material].
帕金森病（PD）的研究既困难又耗时。它是一种在人类大脑中经过几十年发展的复杂疾病。对于这种明显难以解决的疾病，数学模型可以提供额外的研究手段。作为对这一过程的贡献，作者开发了一个与 PD 相关的最重要细胞过程的常微分方程模型。该模型描述了以下过程：（i）细胞产生和清除活性氧物质；（ii）可能对蛋白质 -突触核蛋白造成的损害和清除，以及（iii）受损α-突触核蛋白与活性氧物质之间的反馈相互作用。模拟结果表明，通过已知的 PD 风险因素（如老化、暴露于毒素和遗传缺陷），可以在模型中诱导具有升高的氧化应激和错误折叠α-突触核蛋白积累的帕金森病状态。本文的重要结果是证明可以在计算机中再现 PD 发病机制的多因素相互作用。因此，该模型为 PD 的可变性和异质性提供了系统的解释，并为进一步研究这种复杂多因素疾病的各个方面提供了计算研究的基础。[包括补充材料]。
