Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia.
School of Medicine, University of Tasmania, Hobart, Australia.
BMC Neurol. 2022 Jul 18;22(1):266. doi: 10.1186/s12883-022-02772-5.
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.
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.
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.
ClinicalTrials.gov Identifier: NCT05194787 , 18 January 2022. Retrospectively registered.
全球痴呆症的患病率正在迅速上升。阿尔茨海默病（AD）占病例的 70%，有 10-20 年的临床前阶段，在此期间，脑病理学在认知症状出现之前就悄悄进展。2020 年柳叶刀委员会估计，通过改变生活方式/医疗风险因素，40%的痴呆症病例可以预防。为了优化痴呆症预防效果，迫切需要确定有临床前 AD 的个体，以便进行有针对性的降低风险。目前的临床前 AD 测试对于人群水平的评估来说太具侵入性、专业性或昂贵。我们开发了一种新的在线测试 TAS Test，该测试评估一系列运动认知功能，并且具有大规模应用的能力。TAS Test 结合了两项创新：使用手部运动分析来检测临床前 AD，以及计算机人机界面技术，以实现强大的“自我测试”数据采集。其目的是验证 TAS Test 以[1]识别临床前 AD，以及[2]预测认知能力下降和 AD 痴呆的风险。
目标 1 将通过对 500 名认知健康的老年人进行横断面研究来解决，他们将完成包含运动控制、处理速度、注意力、视空间能力、记忆和语言在内的 TAS Test 项目。TAS Test 测量结果将与一种基于血液的 AD 生物标志物磷酸化 tau181（p-tau181）进行比较。目标 2 将通过对 10000 名老年人进行为期 5 年的前瞻性队列研究来解决。参与者将每年完成 TAS Test，每两年完成剑桥神经心理学测试电池（CANTAB）的子测试。300 名参与者将接受面对面的临床评估。我们将使用 TAS Test 上的运动认知表现的机器学习来开发一种算法，该算法可以对临床前 AD 风险（p-tau181 定义）进行分类，并确定前瞻性估计 5 年认知能力下降和 AD 风险的精度。
这项研究将确定 TAS Test 识别临床前 AD 和估计认知能力下降和 AD 风险的精度。如果准确，TAS Test 将提供一种低成本、可及的富集策略，以便在更昂贵的测试（如血液或成像生物标志物）之前对个体进行 AD 病理学的可能性进行预筛选。这将在公共卫生计划和临床试验中具有广泛的应用。
ClinicalTrials.gov 标识符：NCT05194787，2022 年 1 月 18 日。回顾性注册。
