TAS Test: Online Motor-cognitive Tests for Early Detection of Alzheimer's Disease (TASTest)

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TAS Test: Online Motor-cognitive Tests for Early Detection of Alzheimer's Disease (TASTest)

Sponsor:

University of Tasmania

Collaborators:

National Health and Medical Research Council, Australia

University of Sydney

University of Leeds

Information provided by (Responsible Party):

Jane Alty, University of Tasmania

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Study Description

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Brief Summary:

Global dementia prevalence is rising. Alzheimer's disease (AD), the most common cause, has devastating effects on people's quality of life. AD has a preclinical (pre-AD) period of 10-20 years when brain pathology silently progresses before any cognitive symptoms appear. Current tests for pre-AD are invasive, costly and unsuitable for screening at population level. Similar to screening for pre-diabetes and carcinoma in situ, it is important to detect AD at the preclinical stage in order to offer early interventions before the pathology progresses to the irrerversible degenerative stage. In the study, research will develop a new scalable test (TAS Test) by combining two innovative ideas: hand-movement tests to detect pre-AD >10 years before cognitive symptoms begin; and computer vision so people can "self-test" online using home computers. This unique approach builds on recent discoveries that hand-movement patterns change in pre-AD. The research team will use exquisitely precise computer vision methods to automatically analyse movement data from thousands of participants, and combine this with machine learning of overall motor-cognitive performance. The project team has access to 3 well-phenotyped cohorts, >10,000 existing participants and a cutting-edge assay for a blood AD biomarker, ptau181. The research team will develop a TAS Test algorithm to classify hand-movement and cognitive test data for pre-AD risk (p-taua181 levels) and determine TAS Test's precision to prospectively predict 5-year risks of cognitive decline and AD.

Condition or disease	Intervention/treatment
Alzheimer Disease Dementia Age-related Cognitive Decline	Diagnostic Test: Cognitive test scores, clinical diagnosis and blood biomarkers

Detailed Description:

Sub-study 1: Cross-sectional study design: From two established cohorts with pre-existing datasets of up to 10 years of longitudinal cognitive, genetic and demographic data, the team will recruit 500 participants over 50 years old who are confirmed to have normal cognition. At baseline and months 3 and 6, the participants will be invited to complete TAS Test online at home, or in the research centre if preferred. The participants will also have a baseline blood test for ptau181 levels (and APOE4 if required). The research team will integrate movement data to develop a multivariable model that discriminates between pre-AD (positive p-tau181) and normal cognitive ageing (negative p-tau181).

Sub-study 2: Prospective 5-year cohort study design: The researchers will invite 10,000 adults from an established long-term (ISLAND Project) cohort to complete online tests at home: (i) TAS Test every 6 months, and (ii) Cambridge Neuropsychological Test Automated Battery (CANTAB) cognitive tests every 24 months. The prospective 'high risk' predictions of TAS Test at baseline will be validated against CANTAB scores, and also clinically (face to face gold standard consensus diagnosis of AD vs MCI vs normal) in a subsample of 300.

Study Design

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Study Type :	Observational
Estimated Enrollment :	3000 participants
Observational Model:	Cohort
Time Perspective:	Prospective
Official Title:	TAS Test: Determining the Feasibility and Validity of Online Motor-cognitive Testing for Early Detection of Alzheimer's Disease
Actual Study Start Date :	March 5, 2021
Estimated Primary Completion Date :	December 2025
Estimated Study Completion Date :	December 2030

The TAS Test project: a prospective longitudinal validation of new online motor-cognitive tests to detect preclinical Alzheimer’s disease and estimate 5-year risks of cognitive decline and dementia

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The TAS Test project: a prospective longitudinal validation of new online motor-cognitive tests to detect preclinical Alzheimer’s disease and estimate 5-year risks of cognitive decline and dementia

• Jane Alty,
• Quan Bai,
• Renjie Li,
• Katherine Lawler,
• Rebecca J. St George,
• Edward Hill,
• Aidan Bindoff,
• Saurabh Garg,
• Xinyi Wang,
• Guan Huang,
• Kaining Zhang,
• Kaylee D. Rudd,
• Larissa Bartlett,
• Lynette R. Goldberg,
• Jessica M. Collins,
• Mark R. Hinder,
• Sharon L. Naismith,
• David C. Hogg,
• Anna E. King &
• James C. Vickers 

BMC Neurology volume 22, Article number: 266 (2022) Cite this article

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Abstract

Background

The worldwide prevalence of dementia is rapidly rising. Alzheimer’s disease (AD), accounts for 70% of cases and has a 10–20-year preclinical period, when brain pathology covertly progresses before cognitive symptoms appear. The 2020 Lancet Commission estimates that 40% of dementia cases could be prevented by modifying lifestyle/medical risk factors. To optimise dementia prevention effectiveness, there is urgent need to identify individuals with preclinical AD for targeted risk reduction. Current preclinical AD tests are too invasive, specialist or costly for population-level assessments. We have developed a new online test, TAS Test, that assesses a range of motor-cognitive functions and has capacity to be delivered at significant scale. TAS Test combines two innovations: using hand movement analysis to detect preclinical AD, and computer-human interface technologies to enable robust ‘self-testing’ data collection. The aims are to validate TAS Test to [1] identify preclinical AD, and [2] predict risk of cognitive decline and AD dementia.

Methods

Aim 1 will be addressed through a cross-sectional study of 500 cognitively healthy older adults, who will complete TAS Test items comprising measures of motor control, processing speed, attention, visuospatial ability, memory and language. TAS Test measures will be compared to a blood-based AD biomarker, phosphorylated tau 181 (p-tau181). Aim 2 will be addressed through a 5-year prospective cohort study of 10,000 older adults. Participants will complete TAS Test annually and subtests of the Cambridge Neuropsychological Test Battery (CANTAB) biennially. 300 participants will undergo in-person clinical assessments. We will use machine learning of motor-cognitive performance on TAS Test to develop an algorithm that classifies preclinical AD risk (p-tau181-defined) and determine the precision to prospectively estimate 5-year risks of cognitive decline and AD.

Discussion

This study will establish the precision of TAS Test to identify preclinical AD and estimate risk of cognitive decline and AD. If accurate, TAS Test will provide a low-cost, accessible enrichment strategy to pre-screen individuals for their likelihood of AD pathology prior to more expensive tests such as blood or imaging biomarkers. This would have wide applications in public health initiatives and clinical trials.

Trial registration

ClinicalTrials.gov Identifier: NCT05194787, 18 January 2022. Retrospectively registered.

Estimating presymptomatic episodic memory impairment using simple hand movement tests: A cross-sectional study of a large sample of older adults

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Estimating presymptomatic episodic memory impairment using simple hand movement tests: A cross-sectional study of a large sample of older adults

Xinyi Wang, Rebecca J. St George, Aidan D. Bindoff, Alastair J. Noyce, Katherine Lawler, Eddy Roccati, Larissa Bartlett, Son N. Tran, James C. Vickers, Quan Bai, Jane Alty

First published: 30 July 2023

https://doi.org/10.1002/alz.13401

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Abstract

INTRODUCTION

Finding low-cost methods to detect early-stage Alzheimer's disease (AD) is a research priority for neuroprotective drug development. Presymptomatic Alzheimer's is associated with gait impairment but hand motor tests, which are more accessible, have hardly been investigated. This study evaluated how home-based Tasmanian (TAS) Test keyboard tapping tests predict episodic memory performance.

METHODS

1169 community participants (65.8 ± 7.4 years old; 73% female) without cognitive symptoms completed online single-key and alternate-key tapping tests and episodic memory, working memory, and executive function cognitive tests.

RESULTS

All single-key (R²_adj = 8.8%, ΔAIC = 5.2) and alternate-key (R²_adj = 9.1%, ΔAIC = 8.8) motor features predicted episodic memory performance relative to demographic and mood confounders only (R²_adj = 8.1%). No tapping features improved estimation of working memory.

DISCUSSION

Brief self-administered online hand movement tests predict asymptomatic episodic memory impairment. This provides a potential low-cost home-based method for stratification of enriched cohorts.

Highlights

• We devised two brief online keyboard tapping tests to assess hand motor function.
• 1169 cognitively asymptomatic adults completed motor- and cognitive tests online.
• Impaired hand motor function predicted reduced episodic memory performance.
• This brief self-administered test may aid stratification of community cohorts.

1 BACKGROUND

Dementia prevalence is predicted to triple to more than 150 million globally by 2050.^{1, 2} Most cases are caused by Alzheimer's disease (AD), which has a 10- to 20-year presymptomatic period of “silent” brain pathology (amyloid beta and tau deposition) before episodic memory symptoms emerge.³ To reduce dementia prevalence, there is an urgent need to identify at-risk individuals for early interventions. Up to 40% of dementia cases are attributable to modifiable risk factors,⁴ and the recent emergence of monoclonal therapies for AD may be most efficacious earlier in the disease course.^{5, 6} Dementia prevention and drug development are hindered by the lack of accessible, cost-effective tests to identify “at-risk” cohorts for specialist assessments, early recruitment to clinical trials, and targeted interventions. Current methods, such as neuropsychological assessments, blood- and cerebrospinal fluid (CSF)-based biomarkers, and positron emission tomography (PET) scans are too expensive, time-consuming, or invasive.³

Motor analysis holds strong potential to identify people at risk of AD. Gait slows down, with less rhythmic stepping, about 10 years before dementia diagnosis,⁷ but the need for specialist movement-sensing equipment and fall risk are barriers for translation to a population-level test. Though less explored than gait, hand motor function also declines in presymptomatic AD and has the advantage of accessible assessments through computer keyboards.⁸ Two recent studies found slower and less rhythmic tapping features in mild cognitive impairment (MCI) and AD, but both required laboratory-based equipment.^{9, 10} In 2019, Mollica et al. evaluated hand motor function in 72 older adults and found the speed and rhythm of repeatedly tapping a single computer key discriminated those with presymptomatic AD (n = 20, CSF Aβ-positive) from those with negative CSF biomarkers (n = 37).⁸ These promising findings have not yet been replicated in other at-risk groups or in larger samples.

This study builds upon Mollica et al.’s study by designing a self-administered keyboard tapping test to measure hand motor function at home. We aimed to evaluate (i) whether a single-key tapping test would help identify subtly impaired cognitive performance in episodic memory in a large community cohort of older cognitively asymptomatic adults, over and above a model that includes age, education, sex, level of education, anxiety, and depression; (ii) how a single-key motor performance test would compare with a more challenging alternate-key tapping test (based on the Bradykinesia Akinesia Incoordination [BRAIN] tap test¹¹); and (iii) which combination of motor features would best predict cognitive performance.

We hypothesized that impaired hand motor performance (defined as slower tapping frequency, arrhythmia, inaccurate target, or prolonged dwell time on each key) would associate with impairments in episodic memory but not in cognitive domains less sensitive to early AD (working memory, executive dysfunction)¹² and that the alternate-key test would have a stronger association due to greater cognitive loads required for key switching.

 

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