Nonhuman primate models of Parkinson's disease

Nonhuman primate (NHP) models of Parkinson's disease (PD) play an essential role in the understanding of PD pathophysiology and the assessment of PD therapies. NHP research enabled the identification of environmental risk factors for the development of PD. Electrophysiological studies in NHP models of PD identified the neural circuit responsible for PD motor symptoms, and this knowledge led to the development of subthalamic surgical ablation and deep brain stimulation. Similar to human PD patients, parkinsonian monkeys are responsive to dopamine replacement therapies and present complications associated with their long-term use, a similarity that facilitated the assessment of new symptomatic treatments, such as dopaminergic agonists. New generations of compounds and novel therapies that use directed intracerebral delivery of drugs, cells, and viral vectors benefit from preclinical evaluation in NHP models of PD. There are several NHP models of PD, each with characteristics that make it suitable for the study of different aspects of the disease or potential new therapies. Investigators who use the models and peer scientists who evaluate their use need information about the strengths and limitations of the different PD models and their methods of evaluation. This article provides a critical review of available PD monkey models, their utilization, and how they compare to emerging views of PD as a multietiologic, multisystemic disease. The various models are particularly useful for representing different aspects of PD at selected time points. This conceptualization provides clues for the development of new NHP models and facilitates the clinical translation of findings. As ever, successful application of any model depends on matching the model to the scientific question to be answered. Adequate experimental designs, with multiple outcome measures of clinical relevance and an appropriate number of animals, are essential to minimize the limitations of models and increase their predictive clinical validity.