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