Gait as a predictor for cognitive decline in Parkinson's disease

Abstract

Cognitive decline and dementia are core features of Parkinson’s disease (PD) with major personal and socioeconomic impact. Identifying individuals at risk of cognitive decline and dementia is vital in order to optimise clinical management and develop novel therapeutics. However, biomarkers for cognitive decline remain a major unmet need. A large structured review undertaken as part of this thesis revealed discrete gait characteristics predicted cognitive decline and dementia in older adults but to date no such study has been conducted in PD. Thus, the primary aim of this thesis was to investigate gait as a clinical biomarker for cognitive decline in PD. Newly diagnosed PD participants (n=118) and controls (n=184) completed a detailed quantitative gait assessment under single and dual task conditions at baseline. Additionally, a comprehensive battery of neuropsychological assessments were completed at baseline, 18 and 36 months later. Mixed-effects models identified significant gait predictors of cognitive decline over three years. Baseline cognition was also explored as a predictor for cognitive decline. Finally, gait was collected in the free-living environment using a body-worn monitor (BWM) and cross-sectional analysis explored free-living gait-cognition associations. Original contributions to knowledge were that gait characteristics under single and dual task in an incident cohort of PD predicted decline in discrete cognitive domains over three years. Critically, in comparison to gait, baseline neuropsychological assessment performance did not predict cognitive decline. Additionally, cross-sectional analysis in early PD revealed discrete gait-cognition associations in free-living signifying future clinical utility for gait as a clinical biomarker. This thesis provides the first evidence for gait as a clinical biomarker for cognitive decline in PD. Discrete gait characteristics may provide a low cost clinical biomarker and make an important contribution to prognostic models of dementia risk in PD.