Understanding the relationship between gait and cognition in mild cognitive impairment subtypes and probable REM sleep behaviour disorder

Abstract

Introduction: Mild cognitive impairment (MCI) represents a transition state between normal cognition and dementia. Individuals with amnestic MCI (aMCI) are more likely to develop Alzheimer’s disease (AD), whereas individuals with non-amnestic MCI (naMCI) are more likely to progress to non-AD dementias. Individuals with multi-domain (MD-) MCI are more likely to develop dementia than individuals with single-domain (SD-) MCI. Previous research has demonstrated that individuals with MCI have slower gait compared to cognitively unimpaired (CU) older adults, but limited research has characterized gait differences across MCI subtypes over time in these groups. There is also growing evidence that specific gait characteristics are selectively associated with specific cognitive domains, but few studies have investigated these associations longitudinally in MCI. REM sleep behavior disorder (RBD) is a prodromal biomarker of α-synucleinopathies, particularly Parkinson’s disease (PD) and dementia with Lewy bodies (DLB). Individuals with RBD are more likely to develop MCI than healthy controls, and the presence of MCI in RBD is associated with greater risk for early phenoconversion. Recently, research has highlighted that individuals with isolated RBD exhibit subtle changes in gait. Despite this, no studies to date have explored how the presence of RBD influences gait characteristics in people with MCI. Therefore, this study aimed to a) characterize baseline and longitudinal gait characteristics across MCI subtypes, b) explore how the presence of RBD impacts gait characteristics in MCI, and c) assess whether baseline gait characteristics can predict future decline in specific cognitive domains in MCI. Methods: This study involved secondary data analysis of data from the Mayo Clinic Study of Aging. 382 individuals with MCI (180 SD-aMCI, 48 SD-naMCI, 134 MD-aMCI, 20 MD-naMCI), and 382 age-, sex- and education-matched CU individuals were included. Mean follow-up duration for the entire sample was 16.8 months. Participants completed gait assessment using an instrumented gait walkway. Informants completed the Mayo Sleep Questionnaire, which was used to determine probable RBD (pRBD) status. Cognition was measured using domain-specific z-scores for attention, memory, language, visuospatial function, as well as global cognition. Linear mixed effects models were used to compare gait outcomes over time between groups and by pRBD status. Principal component analysis and linear mixed effects models were used to derive gait components and assess if they predict change in cognitive domains from baseline to follow-up visits. Results: All individuals with MCI walked slower, with shorter steps, longer step time, and increased double support (%) compared to CU individuals. Variability of step length, stride velocity and swing time were increased in MD-aMCI compared to CU individuals. Over time, stride velocity and step length decreased, and step time increased in MD-aMCI. The presence of pRBD was associated with decreased stride velocity and step length, and increased stride width and double support (%), particularly in MD-naMCI. Swing time increased over time in people with MD-naMCI and pRBD. Principal component analysis identified three gait factors: pace and stability, timing and rhythm, and variability. The pace and stability factor was negatively associated with global cognition and attention. Surprisingly, the rhythm and timing factor was positively associated with memory. Variability was negatively associated with global cognition and visuospatial function, but this association weakened at follow-up. Conclusions: Gait analysis may be a helpful tool to distinguish MCI from normal aging. Gait variability and slowing of gait may be specific markers of multi-domain impairment. Gait is impacted by comorbid pRBD in MCI, particularly in MD-naMCI. These findings provide further support for the notion of selective associations between specific gait and cognitive domains in people with MCI. Importantly, further investigation with longer follow-up duration, larger sample sizes, and integration of neuroimaging and fluid biomarkers is needed to better understand the role of gait in predicting future progression to dementia in individuals at risk.