Time-course behavioral features are correlated with Parkinson's disease-associated pathology in a 6-hydroxydopamine hemiparkinsonian rat model

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Abstract

Parkinson's disease (PD) is one of the most common neurodegenerative diseases. For decades, the unilateral 6-hydroxydopamine (6-OHDA) rat model has been employed to investigate the pathogenesis and therapy of PD. However, the behavior and associated pathological features of the model long term have not previously been described dynamically. In the present study, the unilateral model was established by 6-OHDA injection in the striatum. The PD rat model was determined 2 weeks following surgery, according to the apomorphine (APO)-induced rotations, cylinder, rotarod and open field tests. TH-positive neurons and fibers in the substantia nigra pars compacta (SNpc) and striatum, respectively, and glial activation in the SNpc, determined by glial fibrillary acidic protein (GFAP) expression for astrocytes and CD11b (Mac1) expression for microglia, were detected by immunohistological staining. Correlation analysis was performed to understand the association between PD-associated behavior and pathology. The behavioral impairment progressively deteriorated during the process of experiment. In addition, the decrease in TH-positive neurons was associated with an increase in GFAP-and Mac1-positive cells in the SNpc. Linear regression analysis indicated the association between behavioral and pathological changes. The results of the present study indicate that the APO-induced rotation, cylinder and rotarod tests are all sensitive and reliable strategies to predict the loss of TH+ neurons. These results provide a potential intervention time-point and a comprehensive evaluation index system for assessment of PD therapeutic strategies using the hemiparkinsonian rat.

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Su, R. J., Zhen, J. L., Wang, W., Zhang, J. L., Zheng, Y., & Wang, X. M. (2018). Time-course behavioral features are correlated with Parkinson’s disease-associated pathology in a 6-hydroxydopamine hemiparkinsonian rat model. Molecular Medicine Reports, 17(2), 3356–3363. https://doi.org/10.3892/mmr.2017.8277

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