Research into Parkinson's disease (PD) is intensely difficult and time consuming. It is a complex condition that develops over many years in the human brain. For such apparently intractable diseases, mathematical models can offer an additional means for investigating the unknown mechanisms of PD. As a contribution to this process, we have developed an ordinary differential equation model of the most important cellular processes that have been associated with PD pathogenesis. The model describes the following processes: (i) cellular generation and scavenging of reactive oxygen species, (ii) the possible damage to the protein α-synuclein by oxidative stress, or mutation, and removal of the damaged protein 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 aging, 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. Specifically, the modeling and simulation show in a logical manner how both multi-factorial interactions and modifications of regulatory feedbacks can jointly, and in various ways, contribute to the pathogenesis of Parkinson's disease. 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.
Published December 2012 , 24 pages