Gait Analysis for Early Detection of Motor Symptoms in the 6-OHDA Rat Model of Parkinson's Disease - Boix, Jordi; von Hieber, Daniela; Connor, Bronwen (Frontiers in Behavioral Neuroscience, 2018)
Computer-supported gait analysis has proven to be effective for the comprehensive assessment of gait changes in rodent models of neurodegenerative and neurological disorders. However, full characterization of individual gait parameters is required for specific neurological or neurodegenerative disorders such as Parkinson’s disease (PD). Gait disturbances in particular present as the most constraining set of symptoms in PD, finally depriving patients from most activities of normal daily living. . In this study, we have characterized the gait pattern abnormalities observed in two rat models of PD: the medial forebrain bundle (MFB) 6-OHDA lesion model and the striatal 6-OHDA lesion model. Our data indicates significant changes in twenty-one different gait parameters in the MFB lesion cohort. We observed a steady decline in the overall walking speed and cadence, as well as significant alterations in the gait parameters stride length, initial dual stance, paw print position, step cycle, swing phase of the step cycle, stand index, phase dispersion, print length and print area in at least one of the paws. These alterations correlated with the extent of tyrosine hydroxylase (TH) neuronal loss observed in this group. These alterations were detected as early as 1 week post lesion. In contrast, limited gait dysfunction was detected in the striatal lesion cohort related to the low level of TH neuronal loss detected in this group. In this study we have demonstrated that gait analysis is a reliable method for the detection of motor deficiencies in a MFB 6-OHDA lesion model of PD and may prove a clinically relevant, low impact method of testing functional impairment as early as 1 week post lesion.