Neural Mechanisms of Motor Dysfunction in Mild Cognitive Impairment and Alzheimer’s Disease: A Systematic Review

Alzheimer's disease biomarker burden in primary motor cortices is associated with poorer dexterity performance

INTRODUCTION

Motor function has correlated with longevity and functionality; however, there is limited research on those with Alzheimer's disease (AD). We studied the association between motor functionality and AD pathology in primary motor and medial temporal cortices.

METHODS

A total of 206 participants with a clinical diagnosis of cognitively healthy, AD, or mild cognitive impairment (MCI) underwent imaging and motor assessment. Linear regressions and analyses of variance were applied to test the prediction from AD imaging biomarkers to motor performance and the diagnosis group differences in motor performance.

RESULTS

Increased neurodegeneration was associated with worsening dexterity and lower walking speed, and increased amyloid and tau were associated with worsening dexterity. AD and MCI participants had lower motor performance than the cognitively healthy participants.

DISCUSSION

Increased AD pathology is associated with worsening dexterity performance. The decline in dexterity in those with AD pathology may offer an opportunity for non-pharmacological therapy intervention.

HIGHLIGHTS

Noted worsening dexterity performance was associated with greater Alzheimer's disease (AD) pathology (tau, amyloid beta, and neurodegeneration) in primary motor cortices. Similarly, increased neurodegeneration and tau pathology in parahippocampal, hippocampal, and entorhinal cortices is associated with worsening dexterity performance. Motor performance declined in those with clinical and preclinical AD among an array of motor assessments.

Development of a smartphone screening test for preclinical Alzheimer's disease and validation across the dementia continuum

BACKGROUND

Dementia prevalence is predicted to triple to 152 million globally by 2050. Alzheimer's disease (AD) constitutes 70% of cases. There is an urgent need to identify individuals with preclinical AD, a 10-20-year period of progressive brain pathology without noticeable cognitive symptoms, for targeted risk reduction. Current tests of AD pathology are either too invasive, specialised or expensive for population-level assessments. Cognitive tests are normal in preclinical AD. Emerging evidence demonstrates that movement analysis is sensitive to AD across the disease continuum, including preclinical AD. Our new smartphone test, TapTalk, combines analysis of hand and speech-like movements to detect AD risk. This study aims to [1] determine which combinations of hand-speech movement data most accurately predict preclinical AD [2], determine usability, reliability, and validity of TapTalk in cognitively asymptomatic older adults and [3], prospectively validate TapTalk in older adults who have cognitive symptoms against cognitive tests and clinical diagnoses of Mild Cognitive Impairment and AD dementia.

METHODS

Aim 1 will be addressed in a cross-sectional study of at least 500 cognitively asymptomatic older adults who will complete computerised tests comprising measures of hand motor control (finger tapping) and oro-motor control (syllabic diadochokinesis). So far, 1382 adults, mean (SD) age 66.20 (7.65) years, range 50-92 (72.07% female) have been recruited. Motor measures will be compared to a blood-based AD biomarker, phosphorylated tau 181 to develop an algorithm that classifies preclinical AD risk. Aim 2 comprises three sub-studies in cognitively asymptomatic adults: (i) a cross-sectional study of 30-40 adults to determine the validity of data collection from different types of smartphones, (ii) a prospective cohort study of 50-100 adults ≥ 50 years old to determine usability and test-retest reliability, and (iii) a prospective cohort study of ~1,000 adults ≥ 50 years old to validate against cognitive measures. Aim 3 will be addressed in a cross-sectional study of ~200 participants with cognitive symptoms to validate TapTalk against Montreal Cognitive Assessment and interdisciplinary consensus diagnosis.

DISCUSSION

This study will establish the precision of TapTalk to identify preclinical AD and estimate risk of cognitive decline. If accurate, this innovative smartphone app will enable low-cost, accessible screening of individuals for AD risk. This will have wide applications in public health initiatives and clinical trials.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT06114914, 29 October 2023. Retrospectively registered.

Postural Control Characteristics in Alzheimer's Disease, Dementia With Lewy Bodies, and Vascular Dementia

BACKGROUND

Dementia often results in postural control impairment, which could signify central nervous system dysfunction. However, no studies have compared postural control characteristics among various types of dementia. This study aimed to compare static postural control in patients with Alzheimer's disease (AD), dementia with Lewy bodies (DLB), and vascular dementia (VaD).

METHODS

Cross-sectional relationship between the clinical diagnoses (AD, DLB, VaD, or normal cognition [NC]) of outpatients at a memory clinic and their upright postural control characteristics were examined. In the postural control test, participants were instructed to maintain a static upright standing on a stabilometer for 60 seconds under the eyes-open and eyes-closed conditions. Forty postural control parameters, including distance, position, and velocity in the anterior-posterior and medio-lateral directions, derived from the trajectory of the center of mass sway, were calculated. The characteristics of each type of dementia were compared to those of NC, and the differences among the 3 types of dementia were evaluated using linear regression models.

RESULTS

The study included 1 789 participants (1 206 with AD, 111 with DLB, 49 with VaD, and 423 with NC). Patients with AD exhibited distinct postural control characteristics, particularly in some distance and velocity parameters, only in the eyes-closed condition. Those with DLB exhibited features in the mean position in the anterior-posterior direction. In patients with VaD, significant differences were observed in most parameters, except the power spectrum.

CONCLUSIONS

Patients with AD, DLB, and VaD display disease-specific postural control characteristics when compared to cognitively normal individuals.

Utilizing graph convolutional networks for identification of mild cognitive impairment from single modal fMRI data: a multiconnection pattern combination approach

Mild cognitive impairment plays a crucial role in predicting the early progression of Alzheimer's disease, and it can be used as an important indicator of the disease progression. Currently, numerous studies have focused on utilizing the functional brain network as a novel biomarker for mild cognitive impairment diagnosis. In this context, we employed a graph convolutional neural network to automatically extract functional brain network features, eliminating the need for manual feature extraction, to improve the mild cognitive impairment diagnosis performance. However, previous graph convolutional neural network approaches have primarily concentrated on single modes of brain connectivity, leading to a failure to leverage the potential complementary information offered by diverse connectivity patterns and limiting their efficacy. To address this limitation, we introduce a novel method called the graph convolutional neural network with multimodel connectivity, which integrates multimode connectivity for the identification of mild cognitive impairment using fMRI data and evaluates the graph convolutional neural network with multimodel connectivity approach through a mild cognitive impairment diagnostic task on the Alzheimer's Disease Neuroimaging Initiative dataset. Overall, our experimental results show the superiority of the proposed graph convolutional neural network with multimodel connectivity approach, achieving an accuracy rate of 92.2% and an area under the Receiver Operating Characteristic (ROC) curve of 0.988.

Functional Connectivity Differences in Distinct Dentato-Cortical Networks in Alzheimer's Disease and Mild Cognitive Impairment

Recent research has implicated the cerebellum in Alzheimer's disease (AD), and cerebrocerebellar network connectivity is emerging as a possible contributor to symptom severity. The cerebellar dentate nucleus (DN) has parallel motor and non-motor sub-regions that project to motor and frontal regions of the cerebral cortex, respectively. These distinct dentato-cortical networks have been delineated in the non-human primate and human brain. Importantly, cerebellar regions prone to atrophy in AD are functionally connected to atrophied regions of the cerebral cortex, suggesting that dysfunction perhaps occurs at a network level. Investigating functional connectivity (FC) alterations of the DN is a crucial step in understanding the cerebellum in AD and in mild cognitive impairment (MCI). Inclusion of this latter group stands to provide insights into cerebellar contributions prior to diagnosis of AD. The present study investigated FC differences in dorsal (dDN) and ventral (vDN) DN networks in MCI and AD relative to cognitively normal participants (CN) and relationships between FC and behavior. Our results showed patterns indicating both higher and lower functional connectivity in both dDN and vDN in AD compared to CN. However, connectivity in the AD group was lower when compared to MCI. We argue that these findings suggest that the patterns of higher FC in AD may act as a compensatory mechanism. Additionally, we found associations between the individual networks and behavior. There were significant interactions between dDN connectivity and motor symptoms. However, both DN seeds were associated with cognitive task performance. Together, these results indicate that cerebellar DN networks are impacted in AD, and this may impact behavior. In concert with the growing body of literature implicating the cerebellum in AD, our work further underscores the importance of investigations of this region. We speculate that much like in psychiatric diseases such as schizophrenia, cerebellar dysfunction results in negative impacts on thought and the organization therein. Further, this is consistent with recent arguments that the cerebellum provides crucial scaffolding for cognitive function in aging. Together, our findings stand to inform future clinical work in the diagnosis and understanding of this disease.

Reducing polypyrimidine tract‑binding protein 1 fails to promote neuronal transdifferentiation on HT22 and mouse astrocyte cells under physiological conditions

In contrast to prior findings that have illustrated the conversion of non-neuronal cells into functional neurons through the specific targeting of polypyrimidine tract-binding protein 1 (PTBP1), accumulated evidence suggests the impracticality of inducing neuronal transdifferentiation through suppressing PTBP1 expression in pathological circumstances. Therefore, the present study explored the effect of knocking down PTBP1 under physiological conditions on the transdifferentiation of mouse hippocampal neuron HT22 cells and mouse astrocyte (MA) cells. A total of 20 µM negative control small interfering (si)RNA and siRNA targeting PTBP1 were transfected into HT22 and MA cells using Lipo8000™ for 3 and 5 days, respectively. The expression of early neuronal marker βIII-Tubulin and mature neuronal markers NeuN and microtubule-associated protein 2 (MAP2) were detected using western blotting. In addition, βIII-tubulin, NeuN and MAP2 were labeled with immunofluorescence staining to evaluate neuronal cell differentiation in response to PTBP1 downregulation. Under physiological conditions, no significant changes in the expression of βIII-Tubulin, NeuN and MAP2 were found after 3 and 5 days of knockdown of PTBP1 protein in both HT22 and MA cells. In addition, the immunofluorescence staining results showed no apparent transdifferentiation in maker levels and morphology. The results suggested that the knockdown of PTBP1 failed to induce neuronal differentiation under physiological conditions.

EEG Reveals Alterations in Motor Imagery in People With Amnestic Mild Cognitive Impairment

OBJECTIVES

Motor imagery has been used to investigate the cognitive mechanism of motor control. Although behavioral and electrophysiological changes in motor imagery in people with amnestic mild cognitive impairment (aMCI) have been reported, deficits in different types of imagery remain unclear. To explore this question, we used electroencephalography (EEG) to study neural correlates of visual imagery (VI) and kinesthetic imagery (KI) and their relationship to cognitive function in people with aMCI.

METHODS

A hand laterality judgment task was used to induce implicit motor imagery in 29 people with aMCI and 40 healthy controls during EEG recording. Mass univariate and multivariate EEG analysis was applied to explore group differences in a data-driven manner.

RESULTS

Modulation of stimuli orientation to event-related potential (ERP) amplitudes differed significantly between groups at 2 clusters located in the posterior-parietal and frontal areas. Multivariate decoding revealed sufficient representation of VI-related orientation features in both groups. Relative to healthy controls, the aMCI group lacked accurate representation of KI-related biomechanical features, suggesting deficits in automatic activation of KI strategy. Electrophysiological correlates were associated with episodic memory, visuospatial function, and executive function. Higher decoding accuracy of biomechanical features predicted better executive function via longer response time in the imagery task in the aMCI group.

DISCUSSION

These findings reveal electrophysiological correlates related to motor imagery deficits in aMCI, including local ERP amplitudes and large-scale activity patterns. Alterations in EEG activity are related to cognitive function in multiple domains, including episodic memory, suggesting the potential of these EEG indices as biomarkers of cognitive impairment.

Neuroimaging modalities in the detection of Alzheimer's disease-associated biomarkers

Alzheimer's disease (AD) is the most common cause of dementia. Neuropathological changes in AD patients occur up to 10-20 years before the emergence of clinical symptoms. Specific diagnosis and appropriate intervention strategies are crucial during the phase of mild cognitive impairment (MCI) and AD. The detection of biomarkers has emerged as a promising tool for tracking the efficacy of potential therapies, making an early disease diagnosis, and prejudging treatment prognosis. Specifically, multiple neuroimaging modalities, including magnetic resonance imaging (MRI), positron emission tomography, optical imaging, and single photon emission-computed tomography, have provided a few potential biomarkers for clinical application. The MRI modalities described in this review include structural MRI, functional MRI, diffusion tensor imaging, magnetic resonance spectroscopy, and arterial spin labelling. These techniques allow the detection of presymptomatic diagnostic biomarkers in the brains of cognitively normal elderly people and might also be used to monitor AD disease progression after the onset of clinical symptoms. This review highlights potential biomarkers, merits, and demerits of different neuroimaging modalities and their clinical value in MCI and AD patients. Further studies are necessary to explore more biomarkers and overcome the limitations of multiple neuroimaging modalities for inclusion in diagnostic criteria for AD.

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.

Delayed and More Variable Unimanual and Bimanual Finger Tapping in Alzheimer's Disease: Associations with Biomarkers and Applications for Classification

BACKGROUND

Despite reports of gross motor problems in mild cognitive impairment (MCI) and Alzheimer's disease (AD), fine motor function has been relatively understudied.

OBJECTIVE

We examined if finger tapping is affected in AD, related to AD biomarkers, and able to classify MCI or AD.

METHODS

Forty-seven cognitively normal, 27 amnestic MCI, and 26 AD subjects completed unimanual and bimanual computerized tapping tests. We tested 1) group differences in tapping with permutation models; 2) associations between tapping and biomarkers (PET amyloid-β, hippocampal volume, and APOEɛ4 alleles) with linear regression; and 3) the predictive value of tapping for group classification using machine learning.

RESULTS

AD subjects had slower reaction time and larger speed variability than controls during all tapping conditions, except for dual tapping. MCI subjects performed worse than controls on reaction time and speed variability for dual and non-dominant hand tapping. Tapping speed and variability were related to hippocampal volume, but not to amyloid-β deposition or APOEɛ4 alleles. Random forest classification (overall accuracy = 70%) discriminated control and AD subjects, but poorly discriminated MCI from controls or AD.

CONCLUSIONS

MCI and AD are linked to more variable finger tapping with slower reaction time. Associations between finger tapping and hippocampal volume, but not amyloidosis, suggest that tapping deficits are related to neuropathology that presents later during the disease. Considering that tapping performance is able to differentiate between control and AD subjects, it can offer a cost-efficient tool for augmenting existing AD biomarkers.

Reduction in manual asymmetry and decline in fine manual dexterity in right-handed older adults with mild cognitive impairment

Research in Parkinson's or Alzheimer's disease suggests that hand function is affected by neurodegenerative diseases. However, little is known about the relationship between hand function and mild cognitive impairment (MCI). Therefore, we conducted a kinematic analysis of unimanual hand movements in MCI patients to answer whether manual asymmetries and manual dexterity are affected or preserved in this condition. Forty-one MCI patients and fifty healthy controls were tested with the Purdue Pegboard test. All participants were right-handed. Kinematic analyses (by hand) were calculated for path length, angle, and linear and angular velocities during reaching, grasping, transport and inserting. Group differences were tested by with factorial MANOVAs and laterality indexes (LI) were assessed. Groups were compared on "Right-Left" hand correlations to identify kinematics that best single-out patients. Kinematics from grasping and inserting were significantly more deteriorated in the MCI group, while outcomes for reaching and transport denoted superior performance. LIs data showed symmetry of movements in the MCI group, during reaching and transport. Comparisons of "Right-Left" hand correlations revealed that kinematics in reaching and transport were more symmetrical in patients. This study showed a deterioration of fine manual dexterity, an enhancement in gross dexterity of upper-limbs, and symmetrical movements in MCI patients.