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BMC Neurology
Published in: BMC Neurology 1/2024

Open Access 01-12-2024 | Alzheimer's Disease | Study Protocol

Development of a smartphone screening test for preclinical Alzheimer’s disease and validation across the dementia continuum

Authors: Jane Alty, Lynette R. Goldberg, Eddy Roccati, Katherine Lawler, Quan Bai, Guan Huang, Aidan D Bindoff, Renjie Li, Xinyi Wang, Rebecca J. St George, Kaylee Rudd, Larissa Bartlett, Jessica M. Collins, Mimieveshiofuo Aiyede, Nadeeshani Fernando, Anju Bhagwat, Julia Giffard, Katharine Salmon, Scott McDonald, Anna E. King, James C. Vickers

Published in: BMC Neurology | Issue 1/2024

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Abstract

Background

Dementia prevalence is predicted to triple to 152 million globally by 2050. Alzheimer’s disease (AD) constitutes 70% of cases. There is an urgent need to identify individuals with preclinical AD, a 10–20-year period of progressive brain pathology without noticeable cognitive symptoms, for targeted risk reduction. Current tests of AD pathology are either too invasive, specialised or expensive for population-level assessments. Cognitive tests are normal in preclinical AD. Emerging evidence demonstrates that movement analysis is sensitive to AD across the disease continuum, including preclinical AD. Our new smartphone test, TapTalk, combines analysis of hand and speech-like movements to detect AD risk. This study aims to [1] determine which combinations of hand-speech movement data most accurately predict preclinical AD [2], determine usability, reliability, and validity of TapTalk in cognitively asymptomatic older adults and [3], prospectively validate TapTalk in older adults who have cognitive symptoms against cognitive tests and clinical diagnoses of Mild Cognitive Impairment and AD dementia.

Methods

Aim 1 will be addressed in a cross-sectional study of at least 500 cognitively asymptomatic older adults who will complete computerised tests comprising measures of hand motor control (finger tapping) and oro-motor control (syllabic diadochokinesis). So far, 1382 adults, mean (SD) age 66.20 (7.65) years, range 50–92 (72.07% female) have been recruited. Motor measures will be compared to a blood-based AD biomarker, phosphorylated tau 181 to develop an algorithm that classifies preclinical AD risk. Aim 2 comprises three sub-studies in cognitively asymptomatic adults: (i) a cross-sectional study of 30–40 adults to determine the validity of data collection from different types of smartphones, (ii) a prospective cohort study of 50–100 adults ≥ 50 years old to determine usability and test-retest reliability, and (iii) a prospective cohort study of ~1,000 adults ≥ 50 years old to validate against cognitive measures. Aim 3 will be addressed in a cross-sectional study of ~200 participants with cognitive symptoms to validate TapTalk against Montreal Cognitive Assessment and interdisciplinary consensus diagnosis.

Discussion

This study will establish the precision of TapTalk to identify preclinical AD and estimate risk of cognitive decline. If accurate, this innovative smartphone app will enable low-cost, accessible screening of individuals for AD risk. This will have wide applications in public health initiatives and clinical trials.

Trial registration

ClinicalTrials.gov identifier: NCT06114914, 29 October 2023. Retrospectively registered.
Appendix
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Literature
1.
Livingston G, Sommerlad A, Orgeta V, Costafreda SG, Huntley J, Ames D, et al. Dementia prevention, intervention, and care. Lancet. 2017;390(10113):2673–734.PubMedCrossRef
2.
3.
4.
5.
Livingston G, Huntley J, Sommerlad A, Ames D, Ballard C, Banerjee S, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020;396(10248):413–46.PubMedPubMedCentralCrossRef
6.
Chowdhary N, Barbui C, Anstey KJ, Kivipelto M, Barbera M, Peters R, et al. Reducing the risk of Cognitive decline and Dementia: WHO recommendations. Front Neurol. 2022;12:7.CrossRef
7.
Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, et al. Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7(3):280–92.PubMedCrossRef
8.
Scheltens P, Blennow K, Breteler MMB, de Strooper B, Frisoni GB, Salloway S, et al. Alzheimer’s disease. Lancet. 2016;388(10043):505–17.PubMedCrossRef
9.
Hassenstab J, Nicosia J, LaRose M, Aschenbrenner AJ, Gordon BA, Benzinger TLS, et al. Is comprehensiveness critical? Comparing short and long format cognitive assessments in preclinical Alzheimer disease. Alzheimers Res Ther. 2021;13(1):153.PubMedPubMedCentralCrossRef
10.
Spencer RJ, Wendell CR, Giggey PP, Katzel LI, Lefkowitz DM, Siegel EL, et al. Psychometric limitations of the mini-mental state examination among nondemented older adults: an evaluation of neurocognitive and magnetic resonance imaging correlates. Exp Aging Res. 2013;39(4):382–97.PubMedCrossRef
11.
Lista S, O’Bryant SE, Blennow K, Dubois B, Hugon J, Zetterberg H, et al. Biomarkers in sporadic and familial Alzheimer’s Disease. J Alzheimers Dis. 2015;47(2):291–317.PubMedCrossRef
12.
Janelidze S, Mattsson N, Palmqvist S, Smith R, Beach TG, Serrano GE, et al. Plasma P-tau181 in Alzheimer’s disease: relationship to other biomarkers, differential diagnosis, neuropathology and longitudinal progression to Alzheimer’s dementia. Nat Med. 2020;26(3):379–.PubMedCrossRef
13.
Baldacci F, Lista S, O’Bryant SE, Ceravolo R, Toschi N, Hampel H, et al. Blood-based Biomarker Screening with Agnostic Biological definitions for an Accurate diagnosis within the Dimensional Spectrum of neurodegenerative diseases. Methods Mol Biol. 2018;1750:139–55.PubMedCrossRef
14.
Hampel H, O’Bryant SE, Molinuevo JL, Zetterberg H, Masters CL, Lista S, et al. Blood-based biomarkers for Alzheimer disease: mapping the road to the clinic. Nat Rev Neurol. 2018;14(11):639–52.PubMedPubMedCentralCrossRef
15.
16.
Meiner Z, Ayers E, Verghese J. Motoric cognitive risk syndrome: a risk factor for cognitive impairment and dementia in different populations. Annals Geriatric Med Res. 2020;24(1):3–14.CrossRef
17.
Dumurgier J, Artaud F, Touraine C, Rouaud O, Tavernier B, Dufouil C, et al. Gait speed and decline in Gait Speed as predictors of Incident Dementia. Med Sci. 2017;72(5):655–61. Journals of Gerontology Series a-Biological Sciences.
18.
Rudd KD, Lawler K, Callisaya ML, Alty J. Investigating the associations between upper limb motor function and cognitive impairment: a scoping review. Geroscience. 2023:25.
19.
Wang XY, St George RJ, Bindoff AD, Noyce AJ, Lawler K, Roccati E et al. Estimating presymptomatic episodic memory impairment using simple hand movement tests: a cross-sectional study of a large sample of older adults. Alzheimers Dement. 2023:10.
20.
Mollica MA, Tort-Merino A, Navarra J, Fernández-Prieto I, Valech N, Olives J, et al. Early detection of subtle motor dysfunction in cognitively normal subjects with amyloid-β positivity. Cortex. 2019;121:117–24.PubMedCrossRef
21.
Mollica MA, Navarra J, Fernández-Prieto I, Olives J, Tort A, Valech N, et al. Subtle visuomotor difficulties in preclinical Alzheimer’s disease. J Neuropsychol. 2017;11(1):56–73.PubMedCrossRef
22.
Andriuta D, Diouf M, Roussel M, Godefroy O. Is reaction time slowing an early sign of Alzheimer’s Disease? A Meta-analysis. Dement Geriatr Cogn Disord. 2019;47(4–6):281–8.PubMedCrossRef
23.
Ben-David BM, Icht M. The effect of practice and visual feedback on oral-diadochokinetic rates for younger and older adults. Lang Speech. 2018;61(1):113–34.PubMedCrossRef
24.
Kent RD, Kim Y, Chen LM. Oral and laryngeal diadochokinesis across the life span: a scoping review of methods, Reference Data, and clinical applications. J Speech Lang Hear Res. 2022;65(2):574–623.PubMedCrossRef
25.
Lancheros M, Friedrichs D, Laganaro M. What do differences between Alternating and Sequential Diadochokinetic Tasks Tell Us about the development of Oromotor skills? An insight from Childhood to Adulthood. Brain Sci. 2023;13(4):13.CrossRef
26.
Pierce JE, Cotton S, Perry A. Alternating and sequential motion rates in older adults. Int J Lang Communication Disorders. 2013;48(3):257–64.CrossRef
27.
Solomon NP, Brungart DS, Wince JR, Abramowitz JC, Eitel MM, Cohen J, et al. Syllabic diadochokinesis in adults with and without traumatic Brain Injury: Severity, Stability, and Speech considerations. Am J Speech-Language Pathol. 2021;30(3):1400–9.CrossRef
28.
Laguarta J, Subirana B. Longitudinal Speech biomarkers for automated Alzheimer’s detection. Front Comput Sci. 2021;3:12.CrossRef
29.
Wang YY, Gao K, Kloepper AM, Zhao YX, Kuruvilla-Dugdale M, Lever TE et al. DeepDDK: A Deep Learning based Oral-Diadochokinesis Analysis Software. 2019 Ieee Embs International Conference on Biomedical & Health Informatics (Bhi). 2019:4.
30.
Nadkarni NK, Perera S, Snitz BE, Mathis CA, Price J, Williamson JD, et al. Association of Brain Amyloid-β with slow gait in Elderly individuals without dementia influence of Cognition and Apolipoprotein E ε4 genotype. Jama Neurol. 2017;74(1):82–90.PubMedPubMedCentralCrossRef
31.
Ezzati A, Katz MJ, Lipton ML, Lipton RB, Verghese J. The association of brain structure with gait velocity in older adults: a quantitative volumetric analysis of brain MRI. Neuroradiology. 2015;57(8):851–61.PubMedPubMedCentralCrossRef
32.
Koppelmans V, Silvester B, Duff K. Neural mechanisms of motor dysfunction in mild cognitive impairment and Alzheimer’s Disease: a systematic review. J Alzheimers Dis Rep. 2022;6(1):307–44.PubMedPubMedCentralCrossRef
33.
Koppelmans V, Ruitenberg MFL, Schaefer SY, King JB, Hoffman JM, Mejia AF, et al. Delayed and more variable Unimanual and Bimanual Finger Tapping in Alzheimer’s Disease: associations with biomarkers and applications for classification. J Alzheimers Dis. 2023;95(3):1233–52.PubMedPubMedCentralCrossRef
34.
Zhang Z, Chan MY, Han L, Carreno CA, Winter-Nelson E, Wig GS, et al. Dissociable effects of Alzheimer’s Disease-related cognitive dysfunction and aging on functional Brain Network Segregation. J Neurosci. 2023;43(46):7879–92.PubMedPubMedCentralCrossRef
35.
36.
Huang G, Li R, Bai Q, Alty J. Multimodal learning of clinically accessible tests to aid diagnosis of neurodegenerative disorders: a scoping review. Health Inf Sci Syst. 2023;11(1):32.PubMedPubMedCentralCrossRef
37.
Zhao M, Marino M, Samogin J, Swinnen SP, Mantini D. Hand, foot and lip representations in primary sensorimotor cortex: a high-density electroencephalography study. Sci Rep. 2019;9(1):19464.PubMedPubMedCentralCrossRef
38.
Alty J, Bai Q, Li RJ, Lawler K, St George RJ, Hill E, et al. 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. BMC Neurol. 2022;22(1):13.CrossRef
39.
Wang XY, Garg S, Tran SN, Bai Q, Alty J. Hand tremor detection in videos with cluttered background using neural network based approaches. Health Inform Sci Syst. 2021;9(1):14.
40.
Williams S, Zhao ZB, Hafeez A, Wong DC, Relton SD, Fang H, et al. The discerning eye of computer vision: can it measure Parkinson’s finger tap bradykinesia? J Neurol Sci. 2020;416:7.CrossRef
41.
Williams S, Fang H, Relton SD, Wong DC, Alam T, Alty JE. Accuracy of Smartphone Video for Contactless Measurement of Hand Tremor frequency. Mov Disorders Clin Pract. 2021;8(1):69–75.CrossRef
42.
Huang G, Tran SN, Bai Q, Alty J. Real-time automated detection of older adults’ hand gestures in home and clinical settings. Neural Comput Appl. 2022:14.
43.
Li R, Lao CY, George RS, Lawler K, Garg S, Tran SN et al. Rapid-Motion-Track: Markerless Tracking of Fast Human Motion with Deeper Learning. 2023.
44.
Li RJ, Huang G, Wang XY, Chen YY, Tran SN, Garg S, et al. Parallel scale de-blur net for sharpening video images for remote clinical assessment of hand movements. Expert Syst Appl. 2024;235:9.CrossRef
45.
Bartlett L, Doherty K, Farrow M, Kim S, Hill E, King A, et al. Island Study linking aging and neurodegenerative disease (ISLAND) targeting dementia risk reduction: protocol for a prospective web-based Cohort Study. Jmir Res Protocols. 2022;11(3):14.CrossRef
46.
Bartlett L, Bindoff A, Doherty K, Kim S, Eccleston C, Kitsos A, et al. An online, public health framework supporting behaviour change to reduce dementia risk: interim results from the ISLAND study linking ageing and neurodegenerative disease. BMC Public Health. 2023;23(1):1886.PubMedPubMedCentralCrossRef
47.
Backx R, Skirrow C, Dente P, Barnett JH, Cormack FK. Comparing web-based and lab-based cognitive Assessment using the Cambridge Neuropsychological Test Automated Battery: a within-subjects counterbalanced study. J Med Internet Res. 2020;22(8):e16792.PubMedPubMedCentralCrossRef
48.
Chandler JM, Marsico M, Harper-Mozley L, Vogt R, Peng Y, Lesk V, et al. P3-111: cognitive assessment: discrimination of impairment and detection of decline in Alzheimer’s disease and mild cognitive impairment. Alzheimer’s Dement. 2008;4(4spart17):T551–2.
49.
Roccati E, Collins JM, Bindoff AD, Alty JE, Bartlett L, King AE, et al. Modifiable risk factors for dementia, cognition, and plasma phosphorylated tau 181 in a large-scale cohort of Australian older adults. Neurobiol Aging. 2023;131:106–14.PubMedCrossRef
50.
Brum WS, Ashton NJ, Simrén J, Molfetta Gd, Karikari TK, Benedet AL et al. Biological variation estimates of Alzheimer’s disease plasma biomarkers in healthy individuals. 2023.
51.
Mattsson N, Andreasson U, Zetterberg H, Blennow K. Alzheimer’s dis N. Association of plasma neurofilament light with neurodegeneration in patients with Alzheimer Disease. Jama Neurol. 2017;74(5):557–66.PubMedPubMedCentralCrossRef
52.
Yang ZS, Sreenivasan K, Strom ENT, Osse AML, Pasia LG, Cosme CG, et al. Clinical and biological relevance of glial fibrillary acidic protein in Alzheimer’s disease. Alzheimers Res Therapy. 2023;15(1):14.CrossRef
53.
Mancioppi G, Fiorini L, Rovini E, Zeghari R, Gros A, Manera V, et al. Innovative motor and cognitive dual-task approaches combining upper and lower limbs may improve dementia early detection. Sci Rep. 2021;11(1):9.CrossRef
54.
Montero-Odasso M, Oteng-Amoako A, Speechley M, Gopaul K, Beauchet O, Annweiler C, et al. The Motor signature of mild cognitive impairment: results from the Gait and Brain Study. Sci Med Sci. 2014;69(11):1415–21. Journals of Gerontology Series a-Biological.
55.
Tatebe H, Kasai T, Ohmichi T, Kishi Y, Kakeya T, Waragai M, et al. Quantification of plasma phosphorylated tau to use as a biomarker for brain Alzheimer pathology: pilot case-control studies including patients with Alzheimer’s disease and down syndrome. Mol Neurodegeneration. 2017;12:11.CrossRef
56.
Wolff RF, Moons KGM, Riley RD, Whiting PF, Westwood M, Collins GS, et al. PROBAST: A Tool to assess the risk of Bias and Applicability of Prediction Model studies. Ann Intern Med. 2019;170(1):51–.PubMedCrossRef
57.
Shenoy P, Sompur V, Skm V. Methods for Measurement and Analysis of Full hand Angular Kinematics using Electromagnetic Tracking sensors. Ieee Access. 2022;10:42673–89.CrossRef
58.
Noccaro A, Eden J, Di Pino G, Formica D, Burdet E. Human performance in three-hands tasks. Sci Rep. 2021;11(1):8.CrossRef
59.
Islam N, Hashem R, Gad M, Brown A, Levis B, Renoux C, et al. Accuracy of the Montreal Cognitive Assessment tool for detecting mild cognitive impairment: a systematic review and meta-analysis. Alzheimers Dement. 2023;19(7):3235–43.PubMedCrossRef
60.
Dong YH, Lee WY, Basri NA, Collinson SL, Merchant RA, Venketasubramanian N, et al. The Montreal Cognitive Assessment is superior to the Mini-mental State examination in detecting patients at higher risk of dementia. Int Psychogeriatr. 2012;24(11):1749–55.PubMedCrossRef
61.
Storey JE, Rowland JTJ, Conforti DA, Dickson HG. The Rowland Universal Dementia Assessment Scale (RUDAS): a multicultural cognitive assessment scale. Int Psychogeriatr. 2004;16(1):13–31.PubMedCrossRef
62.
Alty J, Lawler K, Salmon K, McDonald S, Stuart K, Cleary A, et al. A new one-stop interdisciplinary cognitive clinic model tackles rural health inequality and halves the time to diagnosis: benchmarked against a national dementia registry. Int J Geriatr Psychiatry. 2023;38(8):10.CrossRef
63.
Roalf DR, Moberg PJ, Xie SX, Wolk DA, Moelter ST, Arnold SE. Comparative accuracies of two common screening instruments for classification of Alzheimer’s disease, mild cognitive impairment, and healthy aging. Alzheimers Dement. 2013;9(5):529–37.PubMedCrossRef
64.
Economic Cost of Dementia in. Australia 2016–2056. The National Centre for Social and Economic Modelling NATSEM; 2016.
65.
Commerford T. Why timely diagnosis of dementia matters. Med J Australia. 2017.
66.
Naismith SL, Michaelian JC, Santos C, Mehrani I, Robertson J, Wallis K, et al. Tackling dementia together via the Australian Dementia Network (ADNeT): a Summary of initiatives, Progress and Plans. J Alzheimers Dis. 2023;96(3):913–25.PubMedPubMedCentralCrossRef
Metadata
Title
Development of a smartphone screening test for preclinical Alzheimer’s disease and validation across the dementia continuum
Authors
Jane Alty
Lynette R. Goldberg
Eddy Roccati
Katherine Lawler
Quan Bai
Guan Huang
Aidan D Bindoff
Renjie Li
Xinyi Wang
Rebecca J. St George
Kaylee Rudd
Larissa Bartlett
Jessica M. Collins
Mimieveshiofuo Aiyede
Nadeeshani Fernando
Anju Bhagwat
Julia Giffard
Katharine Salmon
Scott McDonald
Anna E. King
James C. Vickers
Publication date
01-12-2024
Publisher
BioMed Central
Published in
BMC Neurology / Issue 1/2024
Electronic ISSN: 1471-2377
DOI
https://doi.org/10.1186/s12883-024-03609-z

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