Abnormal walking patterns may be an early indicator of dementia caused by Alzheimer’s disease (AD) and may distinguish it from other neurodegenerative and cognitive disorders, new research suggests.
Results of a new study show that a high degree of variability in gait was associated with lower cognitive performance, and it accurately differentiated between AD and the other conditions studied.
“We found that across five different neurodegenerative conditions that can lead to dementia, there’s a motor signal that looks quite specific to AD, which is gait variability — an ‘arrhythmia of gait,’ ” senior author Manuel Montero-Odasso, MD, PhD, professor, Departments of Medicine and of Epidemiology and Biostatistics, University of Western Ontario, and director of the Gait and Brain Lab at Parkwood Institute, London, Ontario, Canada, told Medscape Medical News.
Gait can be a valuable marker “when a patient is coming to the clinic with memory concerns, and you don’t know whether this is due to the aging process or to the commencement of dementia,” said Montero-Odasso, who is also the team leader at the Canadian Consortium on Neurodegeneration in Aging and team co-leader at the Ontario Neurodegenerative Research Initiative.
The study was published online February 16 in Alzheimer’s and Dementia.
Predictor of Dementia
Many individuals with neurodegenerative and cognitive disorders experience gait impairment, most often gait variability, defined as “stride-by-stride fluctuations in distance and time,” the authors write.
Previous research has demonstrated an association between gait variability and neurodegenerative disorders. However, there is a “lack of systematic comparisons across the spectrum of neurodegenerative diseases that eventually affect cognition, including pre-dementia stages,” they note.
“We have longstanding evidence showing that cognitive problems, such as poor memory and executive dysfunction, can be predictors of dementia, and we aimed to see whether motor performance, specifically, gait variability, can also help diagnose different types of neurodegenerative conditions,” Montero-Odasso said.
The researchers assessed gait in 500 participants drawn from the COMPASS-ND Cohort and Gait Brain Study Cohort (mean [SD] age, 71.99 [7.51] years; 48.8% women).
Participants included cognitively intact individuals, as well as those with subjective cognitive impairment (SCI), mild cognitive impairment (MCI), PD and MCI (PD-MCI), AD, PD, PD-dementia, frontotemporal dementia (FTD), and Lewy body dementia (LBD).
The researchers divided the participants into three subgroups:
Normal global cognition: control persons (n = 91); PD (n = 41); SCO (n = 33)
MCI: MCI (n = 214); PD-MCI (n = 19)
Dementia: FTD (n = 10); LBD (n = 11); AD (n = 72); PDD (n = 9)
To measure gait, patients were asked to walk on a 6-meter electronic walkway. Four domains were assessed on the basis of factor analysis of 11 quantitative gait parameters: rhythm, pace, variability, and postural control.
Potential Red Flags
In comparison with the control group, differences in gait occurred only among the PD, AD, and PDD groups (all P < .006).
PD: Higher (ie, worse) variability and lower (ie, worse) postural control
AD: Higher variability and lower postural control
PDD: Higher variability
Each covariate that was entered into the MANOVA model (eg, age, number of comorbidities, gait speed) led to an attenuation in the group effect of >10% for ≥1 gait domain; age was the strongest covariate.
Gait variability was the only domain significantly associated with Montreal Cognitive Assessment (MoCA) score in the whole sample (unstandardized Beta = −.852; ‐1.229 to ‐.474; P < .0001). Moreover, in those with AD, gait variability was independently associated with MoCA score.
A “weak but significant association” was also found among PD participants between parkinsonian signs and gait variability, but only MoCA was significantly associated with gait variability.
Gait variability may be “a better motor marker of cognitive performance in PD than severity of parkinsonism,” the authors remark.
Gait variability was the only domain with “high accuracy” in identifying participants with AD (AUC = .82; P < .0001; AUC fully adjusted = .77, P < .0001).
The researchers further broke down the gait variability parameters into three domains that identified the presence of AD.
Stride time: specificity, 70%; sensitivity, 80%; variability, 2.3%
Stride length variability: specificity, 54%; sensitivity, 80%; variability, 2.58%
Double support time variability: specificity, 70%, sensitivity, 75%; variability, 6.2%
“The same areas of the brain that are important in maintaining cognition, memory, and executive function are key in regulating motor control of gait — for example, the frontotemporal and prefrontal cortex, the temporal area, and hippocampus,” said Montero-Odasso.
He advised that clinicians analyze gait of patients who present with memory concerns.
“Our study used electronic walkways, but you can do a gait analysis by walking down the hallway with the patient and observing their gait,” he suggested.
He also recommended asking the patient to walk the same distance while performing a cognitive task, such as naming animals. Gait slowing and greater asymmetry are potential flags for neurodegenerative conditions.
“Most people slow down a little — perhaps by 10% to 20% — when performing a cognitive task [while walking], but if the gait slows down by 30% or more, that is not normal,” Montero-Odasso said.
He added that memory problems are “common in age, although not everyone will get them; but impaired memory and executive function that also come with gait arrhythmia point to areas of the brain that are suffering not only with the aging process but also with degeneration.”
Wearable Devices Useful
Commenting on the study for Medscape Medical News, Jerry Hausdorff, PhD, director, Center for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel, said that gait variability and other gait parameters evaluated in this study “can be easily and quickly captured using electronic ‘gait mats,’ as was done in the present study, or using dedicated body-fixed sensors and wearable devices.”
Hausdorff, who is also a professor at Rush Alzheimer’s Disease Center and the Department of Surgery, Rush University Medical Center, Chicago, Illinois, was not involved with the study. He noted that “24/7 monitoring using wearable devices is emerging as a complementary approach for quantitatively assessing gait and mobility during daily living in ecological settings.”
The Canadian Consortium on Neurodegeneration in Aging (CCNA) is supported by a grant from the Canadian Institutes of Health Research, the Ontario Ministry of Research and Innovation, the Ontario Neurodegenerative Diseases Research Initiative, the CCNA, and the Department of Medicine Program of Experimental Medicine Research Award, University of Western Ontario. Montero-Odasso is the first recipient of the Schulich Clinician–Scientist Award. The authors and Hausdorff have disclosed no relevant financial relationships.
Alzheimers Dement. Published online February 16, 2021. Full text
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