TapTalkTest Project:Development of a Non-invasive Screening Test to Detect Risk of Alzheimer's Disease Pathology

Study Overview
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Brief Summary
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This project aims to produce a solution for the rising incidence of dementia. This is particularly pertinent in Tasmania, Australia, with a rapidly ageing population and the oldest demographics of all Australian states. The team will develop TapTalk, a new screening test that detects risk of Alzheimer's disease (AD) pathology. TapTalk, will record a person's hand movements and speech patterns with a smartphone. Computer algorithms will learn which patterns of data are associated with AD pathology. This innovative test is based on: (i) emerging research that fine motor control required for hand and speech movements is sensitive to early AD pathology and (ii) the investigators' new machine learning methods.

Detailed Description
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This project aims to produce a solution for the rising incidence of dementia. This is particularly pertinent in Tasmania, with a rapidly ageing population. The investigators' will develop TapTalk, a new screening test that detects risk of Alzheimer's disease (AD) pathology. Accounting for 70% of all dementias, the brain pathology of AD progresses silently for more than 10 years before cognitive symptoms emerge (preclinical AD). It is possible to prevent 40% of dementia by modifying risk factors such as physical inactivity and smoking. However, the lack of a cost-effective screening tool means researchers and clinicians cannot target interventions, or recruit to drug trials, in early AD. Currently, cognitive tests lack sensitivity in preclinical AD, and specialist AD biomarker tests are invasive or costly. The investigators will address the hypothesis: Hand-speech movement patterns will detect the risk of Alzheimer's disease pathology in research and clinical cohorts through three aims: Develop and validate analytic algorithms for TapTalk by determining which combinations of hand-speech movement data most accurately detect preclinical AD Develop smartphone capability for TapTalk and determine usability and validity Prospectively validate TapTalk in people who have cognitive symptoms against gold-standard clinical diagnosis of Mild Cognitive Impairment (MCI) and AD dementia AIM 1 Problem: Identify which combination of hand-speech tests will be most discriminatory. Method: The investigators will develop software to video-record a 2-minute oral DDK (diadochokinesis) test, where participants make speech-like sounds repetitively e.g. pa-ta-ka. We already have software to collect hand movements (see TAS Test project). The research team will invite 500 ISLAND Project participants (>50 years old) with normal cognition to compete the hand-speech tests. All participants have provided blood samples for p-tau181 levels. This new assay quantifies AD pathology (using our ultrasensitive Simoa analyser) but the practicalities and cost of accessing the highly-specialist analytic equipment limit wide accessibility. We use ptau-181 as this is a highly predictive blood biomarkers of AD risk. Analysis: The investigators will use deep neural networks to automatically track video key points (e.g. finger/thumb tips) and audio features (e.g. pa-ta-ka). A sliding window approach extracts measures (e.g. speed/rhythm) as input data for developing an algorithm that that classifies p-tau181 levels. Outcome: TapTalk protocol and algorithm. AIM 2 Problem: Develop smartphone capabilities and age/cognitive status cut-offs Method We will develop a smartphone app. ISLAND Project participants (CANTAB cognitive tests every 24 months in-kind) will be invited to complete TapTalk online every 12 months. Analysis: Multi-level regression models will measure within-subject variability, and group differences on TapTalk and CANTAB at baseline, 12 and 24 months. Outcome: An externally validated TapTalk algorithm that produces AD risk scores across age and cognitive ranges. AIM 3 Problem: Validate TapTalk in people with cognitive symptoms. Method: The clinician researchers working at the Royal Hobart Hospital (RHH) will recruit 100 patients with cognitive symptoms (>3 months) from RHH acute medical/subacute units. The research assistant (RHHF funding requested) will complete a standard cognitive screening tool (MoCA) and smartphone TapTalk then invite patients to attend the new ISLAND cognitive clinic after discharge. This 'one-stop' interdisciplinary clinic provides bulk-billed neuropsychological and geriatrician, neurologist and physiotherapist assessments. The team will also recruit 100 consecutive patients referred to the clinic by their GPs and all patients will complete TapTalk. Analysis: The accuracy of TapTalk and MoCA will be compared to diagnosis using ROC analysis. Outcome: TapTalk prospectively clinically validated.

Official Title
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TapTalkTest: Development of a Non-invasive Screening Test to Detect Risk of Alzheimer's Disease Pathology

Conditions
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Alzheimer Disease, Dementia, Movement Abnormalities, Speech Disorders

Intervention / Treatment
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* Diagnostic Test: Tap Talk online program


Participation Criteria
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Eligibility Criteria
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AIM 1 AND AIM 2 Eligibility criteria Inclusion Criteria: Adults >50 years old who are participants in the ISLAND Project and who have provided a blood sample and have normal cognition and no persistent (>3 months) cognitive symptoms will be eligible. Exclusion Criteria: Impaired cognition, defined by a validated cut-off score >1.5 SD above the mean total errors adjusted for age and gender on the Paired Associates Learning sub-test of CANTAB. AIM 3 Eligibility criteria Inclusion Criteria: >3 months of persistent cognitive symptoms (patient- or family-reported) and >50 years old. Exclusion criteria: Acutely unwell, significant impairment of hand function, or known diagnosis of mild cognitive impairment (MCI) or 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

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| ISLAND cohort<br>About 1,000 participants completed hand motor and speech tests online and 150 will attend the research centre for usablity assessments | Diagnostic Test: Tap Talk online program<br>* Online hand and speech motor testing<br>|
| Clinical<br>The new app will be tested in about 100 patients at each of the ISLAND Cognitive Clinic or the Royal Hobart Hospital | Diagnostic Test: Tap Talk online program<br>* Online hand and speech motor testing<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Classification accuracy for blood biomarker of Alzheimer's disease, ptau181 in adults without cognitive symptoms | Area under a receiver operating characteristic (ROC) curve - AUC | 2024 | 
| Odds ratio of cognitive decline in adults without cognitive symptoms | Mixed effects logistic regression will be used to estimate the odds of a participant being confirmed as 'declining' at time T2 (24 months) conditioned on TapTalk score at time T1 (12 months), where the main measure of cogitive function is the CANTAB paired associate learning (PAL) test. | 2025 | 
| Classification accuracy for prospectively predicting risk of MCI and AD in adults with cognitive symptoms | The investigators will calculate AUC for TapTalk and MoCA. 95% confidence intervals will be obtained using bootstrapping. Covariates may include age, gender, APOE4, years of education, and handedness. The investigators will estimate cut-off scores for TapTalk and MoCA to differentiate between cognitively unimpaired vs MCI, and between cognitively unimpaired vs AD using the Youden index to optimise the trade-off between sensitivity and specificity. Classification accuracy (sensitivity and specificity) using these cut-offs will be compared using McNemar's test. | 2025 | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Alzheimer's disease, Dementia, preclinical, Artificial Intelligence, Machine learning