Objective: To determine whether outcomes extracted from a gait model can serve as markers of symptoms and neurodegeneration progression in Parkinson’s disease (PD).

Background: Longitudinal studies suggest that the decline observed in gait in PD could be a promising progression marker [1,2] that could track intervention-induced changes [3,4]. Gait speed has been proposed as progression marker [5,6], yet it does not holistically capture gait decline in PD [7,8], and previous efforts focused solely on its association with clinical scales of symptom progression [5]. Although sufficient for trials targeting symptoms [3], such an approach fails to assess the need to also reflect neurodegeneration for use in neuroprotective trials [3,4]. A recent gait model, derived via factor analysis, encompasses 11 gait outcomes reflecting overall PD-related gait decline [9,10] [figure 1]. It is unclear whether these outcomes could serve as progression markers during both symptoms and neuroprotective trials [4,8].

Method: A cross-sectional analysis is under way. Data from 167 participants with PD are being extracted from 5 studies [11–15]. The 11 outcomes will be obtained via FA. Associations between the 11 gait outcomes and clinical scales of PD symptoms progression (MDS-UPDRS and H&Y) will be examined in laboratory and home environments using correlation, covariate-adjusted linear models and restricted cubic spline models. Additionally, neuroimaging analyses will be employed to study the correlations between the 11 gait outcomes and neurodegeneration-related neural changes [16,17] [figure 2].

Results: Of the currently analyzed laboratory population (n=87/167), the gait model was successfully reproduced by FA and explained 76.09 % of the variance in gait performance. After adjusting for comorbidities and demographic factors, clinical scales of  PD progression were fairly associated with pace- and temporal variability-related outcomes [figure 3].

Conclusion: Preliminary results suggest that gait model outcomes related to pace- and temporal variability can serve as markers of symptoms progression. These initial results are in line with recent neuroimaging findings suggesting that both pace and temporal variability are controlled by two neurodegeneration-related brain “gait networks” [16]. Subsequent analyses should complement current results. This investigation could consolidate the idea of using gait as an indicator of participant response in clinical trials [6].

Figure 1

Figure 2

Figure 3

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