Gait Disturbances are Associated with Increased Cognitive Impairment and Cerebrospinal Fluid Tau Levels in a Memory Clinic Cohort

Progress on early diagnosing Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects both cognition and non-cognition functions. The disease follows a continuum, starting with preclinical stages, progressing to mild cognitive and behavioral impairment, ultimately leading to dementia. Early detection of AD is crucial for better diagnosis and more effective treatment. However, the current AD diagnostic tests of biomarkers using cerebrospinal fluid and/or brain imaging are invasive or expensive, and mostly are still not able to detect early disease state. Consequently, there is an urgent need to develop new diagnostic techniques with higher sensitivity and specificity during the preclinical stages of AD. Various non-cognitive manifestations, including behavioral abnormalities, sleep disturbances, sensory dysfunctions, and physical changes, have been observed in the preclinical AD stage before occurrence of notable cognitive decline. Recent research advances have identified several biofluid biomarkers as early indicators of AD. This review focuses on these non-cognitive changes and newly discovered biomarkers in AD, specifically addressing the preclinical stages of the disease. Furthermore, it is of importance to explore the potential for developing a predictive system or network to forecast disease onset and progression at the early stage of AD.

Predictive power of gait and gait-related cognitive measures in amnestic mild cognitive impairment: a machine learning analysis

Introduction

Gait disorders and gait-related cognitive tests were recently linked to future Alzheimer's Disease (AD) dementia diagnosis in amnestic Mild Cognitive Impairment (aMCI). This study aimed to evaluate the predictive power of gait disorders and gait-related neuropsychological performances for future AD diagnosis in aMCI through machine learning (ML).

Methods

A sample of 253 aMCI (stable, converter) individuals were included. We explored the predictive accuracy of four predictors (gait profile plus MMSE, DSST, and TMT-B) previously identified as critical for the conversion from aMCI to AD within a 36-month follow-up. Supervised ML algorithms (Support Vector Machine [SVM], Logistic Regression, and k-Nearest Neighbors) were trained on 70% of the dataset, and feature importance was evaluated for the best algorithm.

Results

The SVM algorithm achieved the best performance. The optimized training set performance achieved an accuracy of 0.67 (sensitivity = 0.72; specificity = 0.60), improving to 0.70 on the test set (sensitivity = 0.79; specificity = 0.52). Feature importance revealed MMSE as the most important predictor in both training and testing, while gait type was important in the testing phase.

Discussion

We created a predictive ML model that is capable of identifying aMCI at high risk of AD dementia within 36 months. Our ML model could be used to quickly identify individuals at higher risk of AD, facilitating secondary prevention (e.g., cognitive and/or physical training), and serving as screening for more expansive and invasive tests. Lastly, our results point toward theoretically and practically sound evidence of mind and body interaction in AD.

Predicting Ambulatory Capacity in Parkinson's Disease to Analyze Progression, Biomarkers, and Trial Design

BACKGROUND

In Parkinson's disease (PD), gait and balance is impaired, relatively resistant to available treatment and associated with falls and disability. Predictive models of ambulatory progression could enhance understanding of gait/balance disturbances and aid in trial design.

OBJECTIVES

To predict trajectories of ambulatory abilities from baseline clinical data in early PD, relate trajectories to clinical milestones, compare biomarkers, and evaluate trajectories for enrichment of clinical trials.

METHODS

Data from two multicenter, longitudinal, observational studies were used for model training (Tracking Parkinson's, n = 1598) and external testing (Parkinson's Progression Markers Initiative, n = 407). Models were trained and validated to predict individuals as having a "Progressive" or "Stable" trajectory based on changes of ambulatory capacity scores from the Movement Disorders Society Unified Parkinson's Disease Rating Scale parts II and III. Survival analyses compared time-to-clinical milestones and trial outcomes between predicted trajectories.

RESULTS

On external evaluation, a support vector machine model predicted Progressive trajectories using baseline clinical data with an accuracy, weighted-F1 (proportionally weighted harmonic mean of precision and sensitivity), and sensitivity/specificity of 0.735, 0.799, and 0.688/0.739, respectively. Over 4 years, the predicted Progressive trajectory was more likely to experience impaired balance, loss of independence, impaired function and cognition. Baseline dopamine transporter imaging and select biomarkers of neurodegeneration were significantly different between predicted trajectory groups. For an 18-month, randomized (1:1) clinical trial, sample size savings up to 30% were possible when enrollment was enriched for the Progressive trajectory versus no enrichment.

CONCLUSIONS

It is possible to predict ambulatory abilities from clinical data that are associated with meaningful outcomes in people with early PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Objective Physical Function in the Alzheimer's Disease Continuum: Association with Cerebrospinal Fluid Biomarkers in the ALBION Study

Cognitive and physical decline, both indicators of aging, seem to be associated with each other. The aim of the present study was to investigate whether physical function parameters (walking time and handgrip strength) are related to cerebrospinal fluid (CSF) biomarkers (amyloid-beta Aβ42, Tau, PhTau) in individuals in the Alzheimer's disease (AD) continuum. The sample was drawn from the Aiginition Longitudinal Biomarker Investigation of Neurodegeneration study, comprising 163 individuals aged 40-75 years: 112 cognitively normal (CN) and 51 with mild cognitive impairment (MCI). Physical function parameters were measured at baseline, a lumbar puncture was performed the same day and CSF biomarkers were analyzed using automated methods. The association between walking time, handgrip strength and CSF biomarkers was evaluated by linear correlation, followed by multivariate linear regression models adjusted for age, sex, education and APOEe4 genotype. Walking time was inversely related to CSF Aβ42 (lower CSF values correspond to increased brain deposition) in all participants (p < 0.05). Subgroup analysis showed that this association was stronger in individuals with MCI and participants older than 60 years old, a result which remained statistically significant after adjustment for the aforementioned confounding factors. These findings may open new perspectives regarding the role of mobility in the AD continuum.

Cognitive-motor dual-task interference in Alzheimer's disease, Parkinson's disease, and prodromal neurodegeneration: A scoping review

BACKGROUND

Cognitive-motor interference (CMI) is a common deficit in Alzheimer's (AD) disease and Parkinson's disease (PD) and may have utility in identification of prodromal neurodegeneration. There is lack of consensus regarding measurement of CMI resulting from dual task paradigms.

RESEARCH QUESTION

How are individuals with AD, PD, and prodromal neurodegeneration impacted by CMI as measured by dual-task (DT) performance?

METHODS

A systematic literature search was performed in six datasets using the PRISMA guidelines. Studies were included if they had samples of participants with AD, PD, or prodromal neurodegeneration and reported at least one measure of cognitive-motor DT performance.

RESULTS

4741 articles were screened and 95 included as part of this scoping review. Articles were divided into three non-mutually exclusive groups based on diagnoses, with 26 articles in AD, 56 articles in PD, and 29 articles in prodromal neurodegeneration, and results presented accordingly.

SIGNIFICANCE

Individuals with AD and PD are both impacted by CMI, though the impact is likely different for each disease. We found a robust body of evidence regarding the utility of measures of DT performance in the detection of subtle deficits in prodromal AD and some signals of utility in prodromal PD. There are several key methodological challenges related to DT paradigms for the measurement of CMI in neurodegeneration. Overall, DT paradigms show good potential as a clinical method to probe specific brain regions, networks, and function; however, task selection and effect measurement should be carefully considered.

Relationship of Neural Correlates of Gait Characteristics and Cognitive Dysfunction in Patients with Mild Cognitive Impairment

Background: Some patients with mild cognitive impairment (MCI) experience gait disturbances. However, there are few reports on the relationship between gait disturbance and cognitive function in patients with MCI. Therefore, we investigated the neural correlates of gait characteristics related to cognitive dysfunction. Methods: Eighty patients diagnosed with MCI from three dementia centers in Gangwon-do, Korea, were recruited for this study. We defined MCI as a Clinical Dementia Rating global score of 0.5 or higher, with a memory domain score of 0.5 or greater. The patients were classified as having either higher or lower MMSE and the groups were based on their Mini Mental Status Examination z-scores. Multiple logistic regression analysis was performed to examine the association between the gait characteristics and cognitive impairment. Analyses included variables such as age, sex, years of education, number of comorbidities, body mass index, and height. Results: Gait velocity, step count, step length, heel-to-heel base support, swing and stance phase duration, and support time were associated with cognitive function. A decrease in gray matter volume in the right pericalcarine area was associated with gait characteristics related to cognitive dysfunction. An increase in the curvature of gray matter in the right entorhinal, right lateral orbitofrontal, right cuneus, and right and left pars opercularis areas was also associated with gait characteristics related to cognitive dysfunction. Conclusion: Since gait impairment is an important factor in determining activities of daily living in patients with mild cognitive impairment, the evaluation of gait and cognitive functions in patients with mild cognitive impairment is important.

Mobility and associations with levels of cerebrospinal fluid amyloid β and tau in a memory clinic cohort

Background

Mobility impairments, in terms of gait and balance, are common in persons with dementia. To explore this relationship further, we examined the associations between mobility and cerebrospinal fluid (CSF) core biomarkers for Alzheimer's disease (AD).

Methods

In this cross-sectional study, we included 64 participants [two with subjective cognitive decline (SCD), 13 with mild cognitive impairment (MCI) and 49 with dementia] from a memory clinic. Mobility was examined using gait speed, Mini-Balance Evaluation Systems test (Mini-BESTest), Timed Up and Go (TUG), and TUG dual-task cost (TUG DTC). The CSF biomarkers included were amyloid-β 42 (Aβ₄₂), total-tau (t-tau), and phospho tau (p-tau₁₈₁). Associations between mobility and biomarkers were analyzed through correlations and multiple linear regression analyses adjusted for (1) age, sex, and comorbidity, and (2) SCD/MCI vs. dementia.

Results

Aβ₄₂ was significantly correlated with each of the mobility outcomes. In the adjusted multiple regression analyses, Aβ₄₂ was significantly associated with Mini-BESTest and TUG in the fully adjusted model and with TUG DTC in step 1 of the adjusted model (adjusting for age, sex, and comorbidity). T-tau was only associated with TUG DTC in step 1 of the adjusted model. P-tau₁₈₁ was not associated with any of the mobility outcomes in any of the analyses.

Conclusion

Better performance on mobility outcomes were associated with higher levels of CSF Aβ₄₂. The association was strongest between Aβ₄₂ and Mini-BESTest, suggesting that dynamic balance might be closely related with AD-specific pathology.

Effects of Brain Pathologies on Spatiotemporal Gait Parameters in Patients with Mild Cognitive Impairment

BACKGROUND

Impaired gait can precede dementia. The associations between gait parameters and brain pathologies are therefore of interest.

OBJECTIVE

To explore how different brain pathologies (i.e., vascular and Alzheimer's) are associated with specific gait parameters from various gait components in persons with mild cognitive impairment (MCI), who have an increased risk of developing dementia.

METHODS

This cross-sectional study included 96 patients with MCI (mean 72, ±7.5 years; 52% women). Gait was evaluated by using an electronic walkway, GAITRite®. Four gait parameters (step velocity variability; step length; step time; stance time asymmetry) were used as dependent variables in multivariable linear regression analyses. Independent variables included Alzheimer's disease pathologies (amyloid-β and tau) by using PET imaging and white matter hyperintensities (WMH) by using MRI. Covariates included age, sex, comorbidities (and intracranial volume in analyses that includedWMH).

RESULTS

Increased tau-PET (Braak I-IV region of interest [ROI]) was associated with step velocity variability (standardized regression coefficient, β= 0.383, p < 0.001) and step length (β= 0.336, p < 0.001), which remained significant when using different Braak ROIs (I-II, III-IV, V-VI). The associations remained significant when adjusting for WMH (p < 0.001). When also controlling for gait speed, tau was no longer significantly (p = 0.168) associated with an increased step length. No significant associations between gait and Aβ-PET load or WMH were identified.

CONCLUSIONS

The results indicate that one should pay specific attention to assess step velocity variability when targeting single task gait in patients with MCI. Future studies should address additional gait variability measures and dual tasking in larger cohorts.

Gait dysfunction in Alzheimer disease

Alzheimer's disease (AD) is the most common cause of age-associated dementia and will exponentially rise in prevalence in the coming decades, supporting the parallel development of the early stage detection and disease-modifying strategies. While primarily considered as a cognitive disorder, AD also features motor symptoms, primarily gait dysfunction. Such gait abnormalities can be phenotyped across classic clinical syndromes as well as by quantitative kinematic assessments to address subtle dysfunction at preclinical and prodromal stages. As such, certain measures of gait can predict the future cognitive and functional decline. Moreover, cross-sectional and longitudinal studies have associated gait abnormalities with imaging, biofluid, and genetic markers of AD across all stages. This suggests that gait assessment is an important tool in the clinical assessment of patients across the AD spectrum, especially to help identify at-risk individuals.

A Review of the Measurement of the Neurology of Gait in Cognitive Dysfunction or Dementia, Focusing on the Application of fNIRS during Dual-Task Gait Assessment

Poor motor function or physical performance is a predictor of cognitive decline. Additionally, slow gait speed is associated with poor cognitive performance, with gait disturbances being a risk factor for dementia. Parallel declines in muscular and cognitive performance (resulting in cognitive frailty) might be driven primarily by muscle deterioration, but bidirectional pathways involving muscle–brain crosstalk through the central and peripheral nervous systems are likely to exist. Following screening, early-stage parallel declines may be manageable and modifiable through simple interventions. Gait–brain relationships in dementia and the underlying mechanisms are not fully understood; therefore, the current authors critically reviewed the literature on the gait–brain relationship and the underlying mechanisms and the feasibility/accuracy of assessment tools in order to identify research gaps. The authors suggest that dual-task gait is involved in concurrent cognitive and motor activities, reflecting how the brain allocates resources when gait is challenged by an additional task and that poor performance on dual-task gait is a predictor of dementia onset. Thus, tools or protocols that allow the identification of subtle disease- or disorder-related changes in gait are highly desirable to improve diagnosis. Functional near-infrared spectroscopy (fNIRS) is a non-invasive, cost-effective, safe, simple, portable, and non-motion-sensitive neuroimaging technique, widely used in studies of clinical populations such as people suffering from Alzheimer’s disease, depression, and other chronic neurological disorders. If fNIRS can help researchers to better understand gait disturbance, then fNIRS could form the basis of a cost-effective means of identifying people at risk of cognitive dysfunction and dementia. The major research gap identified in this review relates to the role of the central/peripheral nervous system when performing dual tasks.

Dual-Task Gait as a Predictive Tool for Cognitive Impairment in Older Adults: A Systematic Review

The use of the dual-task model as a cognitive-motor interface has been extensively investigated in cross-sectional studies as a training task in cognitive impairment. However, few existing longitudinal studies prove the usefulness of this tool as a clinical marker of cognitive impairment in older people. What is the evidence in prospective studies about dual-task gait as a predictor of cognitive impairment in older adults? This study aims to review and discuss the current state of knowledge in prospective studies on the use of dual-task gait as a predictive tool for cognitive impairment in older adults. The methodology used was a systematic review, according to the PRISMA criteria for the search, summarize and report. A search in 3 databases (Pubmed, Web of Science, and Scopus) was carried out until April 2021. The search terms used were: "(gait OR walking) AND (cognitive decline) AND (dual-task) AND (follow-up OR longitudinal OR long-term OR prospective OR cohort OR predict)." We included prospective research articles with older people with cognitive evaluation at the beginning and the end of the follow-up and dual-task gait paradigm as initial evaluation associated with the presentation of cognitive impairment prediction using any dual-task gait parameters. After exclusion criteria, 12 studies were reviewed. The results indicate that eight studies consider dual-task gait parameters a useful cognitive-motor tool, finding that some of the evaluated parameters of dual-task gait significantly correlate with cognitive impairment over time. The most promising DT parameters associated with cognitive impairment prediction seem to be gait speed, speed cost, DT time, numbers of words during DT, among others. In sum, this study reviews the variety of dual-task gait parameters and their relevance as a simple tool for early cognitive impairment screening, opening a diagnostic window for the screening of cognitive impairment in older people.

Aging-related Alzheimer's disease-like neuropathology and functional decline in captive vervet monkeys (Chlorocebus aethiops sabaeus)

Age-related neurodegeneration characteristic of late-onset Alzheimer's disease (LOAD) begins in middle age, well before symptoms. Translational models to identify modifiable risk factors are needed to understand etiology and identify therapeutic targets. Here, we outline the evidence supporting the vervet monkey (Chlorocebus aethiops sabaeus) as a model of aging-related AD-like neuropathology and associated phenotypes including cognitive function, physical function, glucose handling, intestinal physiology, and CSF, blood, and neuroimaging biomarkers. This review provides the most comprehensive multisystem description of aging in vervets to date. This review synthesizes a large body of evidence that suggests that aging vervets exhibit a coordinated suite of traits consistent with early AD and provide a powerful, naturally occurring model for LOAD. Notably, relationships are identified between AD-like neuropathology and modifiable risk factors. Gaps in knowledge and key limitations are provided to shape future studies to illuminate mechanisms underlying divergent neurocognitive aging trajectories and to develop interventions that increase resilience to aging-associated chronic disease, particularly, LOAD.

Gait Kinematic and Kinetic Characteristics of Older Adults With Mild Cognitive Impairment and Subjective Cognitive Decline: A Cross-Sectional Study

Background

Older adults with mild cognitive impairment (MCI) have slower gait speed and poor gait performance under dual-task conditions. However, gait kinematic and kinetic characteristics in older adults with MCI or subjective cognitive decline (SCD) remain unknown. This study was designed to explore the difference in gait kinematics and kinetics during level walking among older people with MCI, SCD, and normal cognition (NC).

Methods

This cross-sectional study recruited 181 participants from July to December 2019; only 82 met the inclusion criteria and consented to participate and only 79 completed gait analysis. Kinematic and kinetic data were obtained using three-dimensional motion capture system during level walking, and joint movements of the lower limbs in the sagittal plane were analyzed by Visual 3D software. Differences in gait kinematics and kinetics among the groups were analyzed using multivariate analysis of covariance (MANCOVA) with Bonferroni post-hoc analysis. After adjusting for multiple comparisons, the significance level was p < 0.002 for MANCOVA and p < 0.0008 for post-hoc analysis.

Results

Twenty-two participants were MCI [mean ± standard deviation (SD) age, 71.23 ± 6.65 years], 33 were SCD (age, 72.73 ± 5.25 years), and 24 were NC (age, 71.96 ± 5.30 years). MANCOVA adjusted for age, gender, body mass index (BMI), gait speed, years of education, diabetes mellitus, and Geriatric Depression Scale (GDS) revealed a significant multivariate effect of group in knee peak extension angle (F = 8.77, p < 0.0001) and knee heel strike angle (F = 8.07, p = 0.001) on the right side. Post-hoc comparisons with Bonferroni correction showed a significant increase of 5.91° in knee peak extension angle (p < 0.0001) and a noticeable decrease of 6.21°in knee heel strike angle (p = 0.001) in MCI compared with NC on the right side. However, no significant intergroup difference was found in gait kinetics, including dorsiflexion, plantar flexion, knee flexion, knee extension, hip flexion, and hip extension(p > 0.002).

Conclusion

An increase of right knee peak extension angle and a decrease of right knee heel strike angle during level walking were found among older adults with MCI compared to those with NC.

Gait and balance disturbances are common in young urbanites and associated with cognitive impairment. Air pollution and the historical development of Alzheimer's disease in the young

To determine whether gait and balance dysfunction are present in young urbanites exposed to fine particular matter PM2.5 ≥ annual USEPA standard, we tested gait and balance with Tinetti and Berg tests in 575 clinically healthy subjects, age 21.0 ± 5.7 y who were residents in Metropolitan Mexico City, Villahermosa and Reynosa. The Montreal Cognitive Assessment was also applied to an independent cohort n:76, age 23.3 ± 9.1 y. In the 575 cohort, 75.4% and 34.4% had abnormal total Tinetti and Berg scores and high risk of falls in 17.2% and 5.7% respectively. BMI impacted negatively Tinetti and Berg performance. Gait dysfunction worsen with age and males performed worse than females. Gait and balance dysfunction were associated with mild cognitive impairment MCI (19.73%) and dementia (55.26%) in 57/76 and 19 cognitively intact subjects had gait and balance dysfunction. Seventy-five percent of urbanites exposed to PM2.5 had gait and balance dysfunction. For MMC residents-with historical documented Alzheimer disease (AD) and CSF abnormalities, these findings suggest Alzheimer Continuum is in progress. Early development of a Motoric Cognitive Risk Syndrome ought to be considered in city dwellers with normal cognition and gait dysfunction. The AD research frame in PM2.5 exposed young urbanites should include gait and balance measurements. Multicity teens and young adult cohorts are warranted for quantitative gait and balance measurements and neuropsychological and brain imaging studies in high vs low PM2.5 exposures. Early identification of gait and balance impairment in young air pollution-exposed urbanites would facilitate multidisciplinary prevention efforts for modifying the course of AD.