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

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.

Hand Motor Dysfunction Is Associated with Both Subjective and Objective Cognitive Impairment across the Dementia Continuum

INTRODUCTION

Motor dysfunction is an important feature of early-stage dementia. Gait provides a non-invasive biomarker across the dementia continuum. Gait speed and rhythm aid risk stratification of incident dementia in subjective cognitive impairment (SCI) and are associated with cognitive domains in mild cognitive impairment (MCI) and dementia. However, hand movement analysis, which may be more accessible, has never been undertaken in SCI and rarely in MCI or dementia. We aimed to address this gap and improve understanding of hand motor-cognitive associations across the dementia continuum.

METHODS

A total of 208 participants were recruited: 50 with dementia, 58 MCI, 40 SCI, and 60 healthy controls. Consensus diagnoses were made after comprehensive gold-standard assessments. A computer key-tapping test measured frequency, dwell-time, rhythm, errors, and speed. Associations between key-tapping and cognitive domains and diagnoses were analysed using regression. Classification accuracy was measured using area under receiver operating characteristic curves.

RESULTS

Hand frequency and speed were associated with memory and executive domains (p ≤ 0.001). Non-dominant hand rhythm was associated with all cognitive domains. Frequency, rhythm, and speed were associated with SCI, MCI, and dementia. Frequency and speed classified ≥94% of dementia and ≥88% of MCI from controls. Rhythm of the non-dominant hand classified ≥86% of dementia and MCI and 69% of SCI.

CONCLUSION

Our findings show hand motor dysfunction occurs across the dementia continuum and, similar to gait, is associated with executive and memory domains and with cognitive diagnoses. Key-tapping performance differentiated dementia and MCI from healthy controls. More research is required before recommending key-tapping as a non-invasive motor biomarker of cognitive impairment.

Classification of Mild Cognitive Impairment and Alzheimer's Disease Using Manual Motor Measures

INTRODUCTION

Manual motor problems have been reported in mild cognitive impairment (MCI) and Alzheimer's disease (AD), but the specific aspects that are affected, their neuropathology, and potential value for classification modeling is unknown. The current study examined if multiple measures of motor strength, dexterity, and speed are affected in MCI and AD, related to AD biomarkers, and are able to classify MCI or AD.

METHODS

Fifty-three cognitively normal (CN), 33 amnestic MCI, and 28 AD subjects completed five manual motor measures: grip force, Trail Making Test A, spiral tracing, finger tapping, and a simulated feeding task. Analyses included (1) group differences in manual performance; (2) associations between manual function and AD biomarkers (PET amyloid β, hippocampal volume, and APOE ε4 alleles); and (3) group classification accuracy of manual motor function using machine learning.

RESULTS

Amnestic MCI and AD subjects exhibited slower psychomotor speed and AD subjects had weaker dominant hand grip strength than CN subjects. Performance on these measures was related to amyloid β deposition (both) and hippocampal volume (psychomotor speed only). Support vector classification well-discriminated control and AD subjects (area under the curve of 0.73 and 0.77, respectively) but poorly discriminated MCI from controls or AD.

CONCLUSION

Grip strength and spiral tracing appear preserved, while psychomotor speed is affected in amnestic MCI and AD. The association of motor performance with amyloid β deposition and atrophy could indicate that this is due to amyloid deposition in and atrophy of motor brain regions, which generally occurs later in the disease process. The promising discriminatory abilities of manual motor measures for AD emphasize their value alongside other cognitive and motor assessment outcomes in classification and prediction models, as well as potential enrichment of outcome variables in AD clinical trials.

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.

Brief webcam test of hand movements predicts episodic memory, executive function, and working memory in a community sample of cognitively asymptomatic older adults

INTRODUCTION

Low-cost simple tests for preclinical Alzheimer's disease are a research priority. We evaluated whether remote unsupervised webcam recordings of finger-tapping were associated with cognitive performance in older adults.

METHODS

A total of 404 cognitively-asymptomatic participants (64.6 [6.77] years; 70.8% female) completed 10-second finger-tapping tests (Tasmanian [TAS] Test) and cognitive tests (Cambridge Neuropsychological Test Automated Battery [CANTAB]) online at home. Regression models including hand movement features were compared with null models (comprising age, sex, and education level); change in Akaike Information Criterion greater than 2 (ΔAIC > 2) denoted statistical difference.

RESULTS

Hand movement features improved prediction of episodic memory, executive function, and working memory scores (ΔAIC > 2). Dominant hand features outperformed nondominant hand features for episodic memory (ΔAIC = 2.5), executive function (ΔAIC = 4.8), and working memory (ΔAIC = 2.2).

DISCUSSION

This brief webcam test improved prediction of cognitive performance compared to age, sex, and education. Finger-tapping holds potential as a remote language-agnostic screening tool to stratify community cohorts at risk for cognitive decline.