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The TAS Test project: a prospective longitudinal validation of new online motor-cognitive tests to detect preclinical Alzheimer's disease and estimate 5-year risks of cognitive decline and dementia.
Alty, Jane; Bai, Quan; Li, Renjie; Lawler, Katherine; St George, Rebecca J; Hill, Edward; Bindoff, Aidan; Garg, Saurabh; Wang, Xinyi; Huang, Guan; Zhang, Kaining; Rudd, Kaylee D; Bartlett, Larissa; Goldberg, Lynette R; Collins, Jessica M; Hinder, Mark R; Naismith, Sharon L; Hogg, David C; King, Anna E; Vickers, James C.
Afiliación
  • Alty J; Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia. Jane.Alty@utas.edu.au.
  • Bai Q; School of Medicine, University of Tasmania, Hobart, Australia. Jane.Alty@utas.edu.au.
  • Li R; Royal Hobart Hospital, Hobart, Tasmania, Australia. Jane.Alty@utas.edu.au.
  • Lawler K; School of Information and Communication Technologies, University of Tasmania, Hobart, Australia.
  • St George RJ; School of Information and Communication Technologies, University of Tasmania, Hobart, Australia.
  • Hill E; Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia.
  • Bindoff A; Royal Hobart Hospital, Hobart, Tasmania, Australia.
  • Garg S; Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia.
  • Wang X; School of Psychological Sciences, University of Tasmania, Hobart, Australia.
  • Huang G; Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia.
  • Zhang K; Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia.
  • Rudd KD; School of Information and Communication Technologies, University of Tasmania, Hobart, Australia.
  • Bartlett L; School of Information and Communication Technologies, University of Tasmania, Hobart, Australia.
  • Goldberg LR; School of Information and Communication Technologies, University of Tasmania, Hobart, Australia.
  • Collins JM; School of Information and Communication Technologies, University of Tasmania, Hobart, Australia.
  • Hinder MR; Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia.
  • Naismith SL; Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia.
  • Hogg DC; Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia.
  • King AE; Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia.
  • Vickers JC; School of Psychological Sciences, University of Tasmania, Hobart, Australia.
BMC Neurol ; 22(1): 266, 2022 Jul 18.
Article en En | MEDLINE | ID: mdl-35850660
ABSTRACT

BACKGROUND:

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.

METHODS:

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.

DISCUSSION:

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. TRIAL REGISTRATION ClinicalTrials.gov Identifier NCT05194787 , 18 January 2022. Retrospectively registered.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedad de Alzheimer / Disfunción Cognitiva Tipo de estudio: Diagnostic_studies / Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Humans Idioma: En Revista: BMC Neurol Asunto de la revista: NEUROLOGIA Año: 2022 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedad de Alzheimer / Disfunción Cognitiva Tipo de estudio: Diagnostic_studies / Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Humans Idioma: En Revista: BMC Neurol Asunto de la revista: NEUROLOGIA Año: 2022 Tipo del documento: Article País de afiliación: Australia