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

Study Overview
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Brief Summary
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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.

Detailed Description
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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.

Official Title
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TAS Test: Determining the Feasibility and Validity of Online Motor-cognitive Testing for Early Detection of Alzheimer's Disease

Conditions
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Alzheimer Disease, Dementia, Age-related Cognitive Decline

Intervention / Treatment
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* Diagnostic Test: Cognitive test scores, clinical diagnosis and blood biomarkers


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: > 50years old Exclusion Criteria: established diagnosis of dementia

Ages Eligible for Study
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Minimum Age: 50 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Intervention/Treatment |
| --- |
|Diagnostic Test: Cognitive test scores, clinical diagnosis and blood biomarkers|Clinical diagnosis of Alzheimer's disease, mild cognitive impairment or normal ageing. Cognitive test score on CANTAB Blood biomarker (p-tau 181) level|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Develop and validate the optimal TAS Test protocol to detect pre-AD (p-tau 181 positivity) | Receiver Operating Characteristic (ROC) curves will be plotted against the positive p-tau181 cut-off to assess the sensitivity/specificity of TAS Test models to identify the pre-AD stage. | 3 years | 
| Prospectively validate TAS Test to predict risks of cognitive decline | Assess the sensitivity and specificity of TAS Test to predict cognitive trajectories (CANTAB scores) stable and declining using ROC curve analysis. | 5 years | 
| Prospectively validate TAS Test to predict risks of AD diagnosis | Multinomial logistic regression will estimate the (covariate adjusted) log-odds of being in each diagnostic category (AD, MCI and normal) at 5 years as predicted by baseline TAS Test results. | 5 years | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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pre-clinical, early detection, online tests, Artificial intelligence