TapTalkTest: Development of a Non-invasive Screening Test to Detect Risk of Alzheimer's Disease Pathology
试验速览
- 阶段
- 不适用
- 状态
- Enrolling By Invitation
- 入组人数
- 1,000
- 试验地点
- 1
- 主要终点
- Classification accuracy for blood biomarker of Alzheimer's disease, ptau181 in adults without cognitive symptoms
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 50 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •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.
排除标准
- •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.
结局指标
主要结局
Classification accuracy for blood biomarker of Alzheimer's disease, ptau181 in adults without cognitive symptoms
时间窗: 2024
Area under a receiver operating characteristic (ROC) curve - AUC
Odds ratio of cognitive decline in adults without cognitive symptoms
时间窗: 2025
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.
Classification accuracy for prospectively predicting risk of MCI and AD in adults with cognitive symptoms
时间窗: 2025
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.
次要结局
未报告次要终点
研究者
Jane Alty
Associate Professor
University of Tasmania