Gait in cerebral small vessel disease, pre-dementia, and dementia: A systematic review

Clinical Phenotypes Associated With Cerebral Small Vessel Disease: An Overview of Systematic Reviews

BACKGROUND AND OBJECTIVES

Cerebral small vessel disease (cSVD) causes lacunar and hemorrhagic stroke and is an important contributor to vascular cognitive impairment. Other potential physical and psychological consequences of cSVD have been described across various body systems. Descriptions of cSVD are available in journals specific to those individual body systems, but a comprehensive assessment of clinical manifestations across this disparate literature is lacking. We conducted an overview of systematic reviews describing clinical cSVD phenotypes.

METHODS

We searched multidisciplinary databases from inception to December 2023. We included reviews describing concurrent clinical phenotypes in individuals with neuroimaging evidence of cSVD, defined using the STandards for ReportIng Vascular changes on nEuroimaging criteria. We broadly classified phenotypes into cognitive, mood and neuropsychiatric, respiratory, cardiovascular, renal-urinary, peripheral nervous system, locomotor, and gastrointestinal. We included both studies assessing multiple cSVD features and studies examining individual cSVD markers. We extracted risk factor-adjusted effect estimates, where possible, and assessed methodologic quality using the Assessment of Multiple Systematic Reviews-2 tool.

RESULTS

After screening 6,156 publications, we included 24 systematic reviews reporting on 685 original studies and 1,135,943 participants. Cognitive and neuropsychiatric phenotypes were examined most often, particularly in relation to white matter hyperintensities (range of risk ratios [RRs] for cognitive phenotypes 1.21-1.49, range of 95% CI 1.01-1.84; for neuropsychiatric, RR 1.02-5.71, 95% CI 0.96-19.69). Two reviews focused solely on perivascular spaces. No reviews assessed lacunes or small subcortical infarcts separately from other cSVD features. Reviews on peripheral nervous system, urinary, or gastrointestinal phenotypes were lacking. Fourteen reviews had high methodologic quality, 5 had moderate quality, and 5 had low quality. Heterogeneity in cSVD definitions and phenotypic assessments was substantial.

DISCUSSION

Neuroimaging markers of cSVD are associated with various clinical manifestations, suggesting a multisystem phenotype. However, features classically associated with cSVD, for example, gait, had limited supporting evidence, and for many body systems, there were no available reviews. Similarly, while white matter hyperintensities were relatively well studied, there were limited data on phenotypes associated with other cSVD features. Future studies should characterize the full clinical spectrum of cSVD and explore clinical associations beyond neurocognitive and neuropsychiatric presentations.

Vascular risk, gait, behavioral, and plasma indicators of VCID

INTRODUCTION

Cost-effective screening tools for vascular contributions to cognitive impairment and dementia (VCID) has significant implications. We evaluated non-imaging indicators of VCID using magnetic resonance imaging (MRI)-measured white matter (WM) damage and hypothesized that these indicators differ based on age.

METHODS

In 745 participants from the Mayo Clinic Study of Aging (≥50 years of age) with serial WM assessments from diffusion MRI and fluid-attenuated inversion recovery (FLAIR)-MRI, we examined associations between baseline non-imaging indicators (demographics, vascular risk factors [VRFs], gait, behavioral, plasma glial fibrillary acidic protein [GFAP], and plasma neurofilament light chain [NfL]) and WM damage across three age tertiles.

RESULTS

VRFs and gait were associated with diffusion changes even in low age strata. All measures (VRFs, gait, behavioral, plasma GFAP, plasma NfL) were associated with white matter hyperintensities (WMHs) but mainly in intermediate and high age strata.

DISCUSSION

Non-imaging indicators of VCID were related to WM damage and may aid in screening participants and assessing outcomes for VCID.

HIGHLIGHTS

Non-imaging indicators of VCID can aid in prediction of MRI-measured WM damage but their importance differed by age. Vascular risk and gait measures were associated with early VCID changes measured using diffusion MRI. Plasma markers explained variability in WMH across age strata. Most non-imaging measures explained variability in WMH and vascular WM scores in intermediate and older age groups. The framework developed here can be used to evaluate new non-imaging VCID indicators proposed in the future.

Stride length and cerebellar regulation: Key features of early gait disorder in cerebral small vessel disease

OBJECTIVES

Gait disorder (GD) is a common problem in cerebral small vessel disease (CSVD). This study aimed to determine (1) the early characteristics of GD in CSVD, (2) cerebellar neuroimaging features related to GD in CSVD, and (3) the association of cognitive impairment with GD.

METHODS

In total, 183 subjects were enrolled in this study: patients with CSVD with normal cognitive function (CSVD-NC) group (64 subjects), patients with CSVD with mild cognitive impairment (CSVD-MCI) group (66 subjects), and a healthy control (HC) group (53 subjects). The GD patterns were evaluated using the ReadyGo three-dimensional motion balance testing system. Meanwhile, we analyzed the cerebrum and cerebellum structurally and functionally. Correlation analyses were conducted among gait indicators, neuroimaging features, and neuropsychological tests.

RESULTS

Both the CSVD-NC and CSVD-MCI groups had a reduced stride length, cortical atrophy in the left cerebellum VIIIb, and decreased functional connectivity between the left cerebellum VIIIb and left SFGmed compared with the HC group. In the correlation analysis, the gray matter probability of the left cerebellum VIIIb was closely related to stride length in the HC group. In the CSVD-MCI group, linguistic function, memory, and attention were significantly correlated with gait performance.

CONCLUSION

Decreased stride length was the earliest characteristic of GD in CSVD. Structural and functional regulation of the left cerebellum VIIIb could play a particularly important role in early GD in CSVD.

Shifting From Active to Passive Monitoring of Alzheimer Disease: The State of the Research

Most research using digital technologies builds on existing methods for staff-administered evaluation, requiring a large investment of time, effort, and resources. Widespread use of personal mobile devices provides opportunities for continuous health monitoring without active participant engagement. Home-based sensors show promise in evaluating behavioral features in near real time. Digital technologies across these methodologies can detect precise measures of cognition, mood, sleep, gait, speech, motor activity, behavior patterns, and additional features relevant to health. As a neurodegenerative condition with insidious onset, Alzheimer disease and other dementias (AD/D) represent a key target for advances in monitoring disease symptoms. Studies to date evaluating the predictive power of digital measures use inconsistent approaches to characterize these measures. Comparison between different digital collection methods supports the use of passive collection methods in settings in which active participant engagement approaches are not feasible. Additional studies that analyze how digital measures across multiple data streams can together improve prediction of cognitive impairment and early-stage AD are needed. Given the long timeline of progression from normal to diagnosis, digital monitoring will more easily make extended longitudinal follow-up possible. Through the American Heart Association-funded Strategically Focused Research Network, the Boston University investigative team deployed a platform involving a wide range of technologies to address these gaps in research practice. Much more research is needed to thoroughly evaluate limitations of passive monitoring. Multidisciplinary collaborations are needed to establish legal and ethical frameworks for ensuring passive monitoring can be conducted at scale while protecting privacy and security, especially in vulnerable populations.

Gait Parameters can Reflect Cognitive Performance in Older Adults with Cerebral Small Vessel Disease: A Cross-sectional Research

BACKGROUND

Cerebral small vessel disease (CSVD) is a common chronic progressive disease. It remains unclear whether high gait variability is a marker of cognitive cortical dysfunction.

METHODS

This study included 285 subjects (aged from 60 to 85 years, 60.3% female) including 37 controls, 179 presented as Fazekas II, and 69 presented as Fazekas III. The severity of white matter hyperintensities was assessed by the Fazekas Rating Scale. Gait parameters were assessed using a vision-based artificial intelligent gait analyzer. Cognitive function was tested by MMSE, MoCA, DST, and VFT.

RESULTS

Three gait parameters including gait speed, gait length, and swing time were associated with cognitive performance in patients with CSVD. Gait speed was associated with cognitive performance, including MMSE (β 0.200; 95%CI 1.706-6.018; p <.001), MoCA (β 0.183; 95%CI 2.047-7.046; p <.001), DST (order) (β 0.204; 95%CI 0.563-2.093; p =.001) and VFT (β 0.162; 95%CI 0.753-4.865; p =.008). Gait length was associated with cognitive performance, including MMSE (β 0.193; 95%CI 3.475-12.845; p =.001), MoCA (β 0.213; 95%CI 6.098-16.942; p <.001), DST (order) (β 0.224; 95%CI 1.056-4.839; P <.001) and VFT (β 0.149; 95%CI 1.088- 10.114; p =.015). Swing time was associated with cognitive performance, including MMSE (β - 0.242; 95%CI -2.639 to -0.974; p<.001), MoCA (β -0.211; 95%CI -2.989 to -1.034; p <.001) and DST (reverse order) (β -0.140; 95%CI -0.568 to -0.049; p =.020).

CONCLUSION

This study revealed that the relationship between gait parameters and cognitive performance in patients with CSVD and the deteriorated gait parameters can reflect cognitive impairment and even dementia in older people with CSVD.

Abnormal whole-brain voxelwise structure-function coupling and its association with cognitive dysfunction in patients with different cerebral small vessel disease burdens

Cerebral small vessel disease (CSVD) is a universal neurological disorder in older adults that occurs in connection with cognitive dysfunction and is a chief risk factor for dementia and stroke. While whole-brain voxelwise structural and functional abnormalities in CSVD have been heavily explored, the degree of structure-function coupling abnormality possible in patients with different CSVD burdens remains largely unknown. This study included 53 patients with severe CSVD burden (CSVD-s), 108 patients with mild CSVD burden (CSVD-m) and 76 healthy controls. A voxelwise coupling metric of low frequency fluctuations (ALFF) and voxel-based morphometry (VBM) was used to research the important differences in whole-brain structure-function coupling among groups. The correlations between ALFF/VBM decoupling and cognitive parameters in CSVD patients were then investigated. We found that compared with healthy controls, CSVD-s patients presented notably decreased ALFF/VBM coupling in the bilateral caudate nuclei and increased coupling in the right inferior temporal gyrus (ITG). In addition, compared with the CSVD-m group, the CSVD-s group demonstrated significantly decreased coupling in the bilateral caudate nuclei, right putamen and inferior frontal gyrus (IFG) and increased coupling in the left middle frontal gyrus and medial superior frontal gyrus. Notably, the ALFF/VBM decoupling values in the caudate, IFG and ITG not only showed significant correlations with attention and executive functions in CSVD patients but also prominently distinguished CSVD-s patients from CSVD-m patients and healthy controls in receiver operating characteristic curve research. Our discoveries demonstrated that decreased ALFF/VBM coupling in the basal ganglia and increased coupling in the frontotemporal lobes were connected with more severe burden and worse cognitive decline in CSVD patients. ALFF/VBM coupling might serve as a novel effective neuroimaging biomarker of CSVD burden and provide new insights into the pathophysiological mechanisms of the clinical development of CSVD.

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.