Novel approaches to measuring neurocognitive functions in Alzheimer's disease clinical trials.
Journal
Current opinion in neurology
ISSN: 1473-6551
Titre abrégé: Curr Opin Neurol
Pays: England
ID NLM: 9319162
Informations de publication
Date de publication:
01 04 2022
01 04 2022
Historique:
pubmed:
18
2
2022
medline:
15
4
2022
entrez:
17
2
2022
Statut:
ppublish
Résumé
We comprehensively examined recent advancements in developing novel cognitive measures that could significantly enhance detection of outcome changes in Alzheimer's disease clinical trials. Previously established measures were largely limited in their ability to detect subtle cognitive declines in preclinical stages of Alzheimer's disease, particularly due to weak psychometric properties (including practice effects and ceiling effects) and requirement of in-person visits that impacted ascertainment. We present novel cognitive measures that were designed to exhibit reduced practice effects and stronger correlations with Alzheimer's disease biomarkers. In addition, we summarized some recent efforts in developing remote testing measures protocols that are aimed to overcome the limitations and inconvenience of in-person testing, and digital phenotyping, which analyses subtle forms of digital behaviour indicative of cognitive phenotypes. We discuss each measure's prognostic accuracy and potential utility in Alzheimer's disease research while also commenting on their limitations. We also describe our study, the Development of Novel Measures for Alzheimer's Disease Prevention Trials (NoMAD), that employed a parallel group design in which novel measures and established measures are compared in a clinical trials armature. Overall, we believe that these recent developments offer promising improvements in accurately detecting clinical and preclinical cognitive changes in the Alzheimer's disease spectrum; however, further validation of their psychometric properties and diagnostic accuracies is warranted before reliably implementing these novel measures in Alzheimer's disease clinical trials.
Identifiants
pubmed: 35175975
doi: 10.1097/WCO.0000000000001041
pii: 00019052-202204000-00016
pmc: PMC10020887
mid: NIHMS1776321
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Review
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
240-248Subventions
Organisme : NIA NIH HHS
ID : R01 AG051346
Pays : United States
Organisme : NIMH NIH HHS
ID : T32 MH020004
Pays : United States
Informations de copyright
Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.
Références
2020 Alzheimer's disease facts and figures. Alzheimers Dement 2020; 16:391–460.
Jack CR Jr, Holtzman DM. Biomarker modeling of Alzheimer's disease. Neuron 2013; 80:1347–1358.
Goldberg TE, Goldman RS, Burdick KE, et al. Cognitive improvement after treatment with second-generation antipsychotic medications in first-episode schizophrenia: is it a practice effect? Arch Gen Psychiatry 2007; 64:1115–1122.
Goldberg TE, Harvey PD, Wesnes KA, et al. Practice effects due to serial cognitive assessment: implications for preclinical Alzheimer's disease randomized controlled trials. Alzheimers Dement (Amst) 2015; 1:103–111.
Calamia M, Markon K, Tranel D. Scoring higher the second time around: meta-analyses of practice effects in neuropsychological assessment. Clin Neuropsychol 2012; 26:543–570.
Machulda MM, Hagen CE, Wiste HJ, et al. [Formula: see text]Practice effects and longitudinal cognitive change in clinically normal older adults differ by Alzheimer imaging biomarker status. Clin Neuropsychol 2017; 31:99–117.
Schneider LS, Goldberg TE. Composite cognitive and functional measures for early stage Alzheimer's disease trials. Alzheimers Dement (Amst) 2020; 12:e12017.
Marshall GA, Rentz DM, Frey MT, et al. Executive function and instrumental activities of daily living in mild cognitive impairment and Alzheimer's disease. Alzheimers Dement 2011; 7:300–308.
Aizenstein HJ, Nebes RD, Saxton JA, et al. Frequent amyloid deposition without significant cognitive impairment among the elderly. Arch Neurol 2008; 65:1509–1517.
Song Z, Insel PS, Buckley S, et al. Brain amyloid-beta burden is associated with disruption of intrinsic functional connectivity within the medial temporal lobe in cognitively normal elderly. J Neurosci 2015; 35:3240–3247.
Duke Han S, Nguyen CP, Stricker NH, Nation DA. Detectable neuropsychological differences in early preclinical Alzheimer's disease: a meta-analysis. Neuropsychol Rev 2017; 27:305–325.
Mormino EC, Papp KV, Rentz DM, et al. Early and late change on the preclinical Alzheimer's cognitive composite in clinically normal older individuals with elevated amyloid beta. Alzheimers Dement 2017; 13:1004–1012.
Bejanin A, Schonhaut DR, La Joie R, et al. Tau pathology and neurodegeneration contribute to cognitive impairment in Alzheimer's disease. Brain 2017; 140:3286–3300.
Nelson PT, Alafuzoff I, Bigio EH, et al. Correlation of Alzheimer disease neuropathologic changes with cognitive status: a review of the literature. J Neuropathol Exp Neurol 2012; 71:362–381.
Hanseeuw BJ, Betensky RA, Jacobs HIL, et al. Association of amyloid and tau with cognition in preclinical Alzheimer disease: a longitudinal study. JAMA Neurol 2019; 76:915–924.
Leuzy A, Smith R, Cullen NC, et al. Biomarker-based prediction of longitudinal tau positron emission tomography in Alzheimer disease. JAMA Neurol 2021; Published online December 20, 2021.
Calamia M, Weitzner DS, De Vito AN, et al. Feasibility and validation of a web-based platform for the self-administered patient collection of demographics, health status, anxiety, depression, and cognition in community dwelling elderly. PLoS One 2021; 16:e0244962.
Maruff P, Thomas E, Cysique L, et al. Validity of the CogState brief battery: relationship to standardized tests and sensitivity to cognitive impairment in mild traumatic brain injury, schizophrenia, and AIDS dementia complex. Arch Clin Neuropsychol 2009; 24:165–178.
Papp KV, Rentz DM, Maruff P, et al. The Computerized Cognitive Composite (C3) in an Alzheimer's disease secondary prevention trial. J Prev Alzheimers Dis 2021; 8:59–67.
Kirwan CB, Stark CE. Overcoming interference: an fMRI investigation of pattern separation in the medial temporal lobe. Learn Mem 2007; 14:625–633.
Vannini P, Hedden T, Becker JA, et al. Age and amyloid-related alterations in default network habituation to stimulus repetition. Neurobiol Aging 2012; 33:1237–1252.
Papp KV, Rentz DM, Maruff P, et al. Computerized Cognitive Composite (C3) performance differences between Abþ and Ab- normal older adults screened for the A4 (Anti-Amyloid in Asymptomatic AD) Study. Alzheimer's Association International Conference 2018. https://www.cogstate.com/wp-content/uploads/2018/08/A4_C3_AAICposter_2018.v1.pdf .
Buckley RF, Sparks KP, Papp KV, et al. Computerized cognitive testing for use in clinical trials: a comparison of the NIH Toolbox and Cogstate C3 batteries. J Prev Alzheimers Dis 2017; 4:3–11.
Scott EP, Sorrell A, Benitez A. Psychometric properties of the NIH Toolbox Cognition Battery in healthy older adults: reliability, validity, and agreement with standard neuropsychological tests. J Int Neuropsychol Soc 2019; 25:857–867.
Weintraub S, Dikmen SS, Heaton RK, et al. The cognition battery of the NIH toolbox for assessment of neurological and behavioral function: validation in an adult sample. J Int Neuropsychol Soc 2014; 20:567–578.
Snitz BE, Tudorascu DL, Yu Z, et al. Associations between NIH Toolbox Cognition Battery and in vivo brain amyloid and tau pathology in nondemented older adults. Alzheimers Dement (Amst) 2020; 12:e12018.
Trelle AN, Carr VA, Wilson EN, et al. Association of CSF biomarkers with hippocampal-dependent memory in preclinical Alzheimer disease. Neurology 2021; 96:e1470–e1481.
Braak H, Braak E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol 1991; 82:239–259.
Braak H, Braak E. Staging of Alzheimer's disease-related neurofibrillary changes. Neurobiol Aging 1995; 16:271–278. discussion 278-284.
Trelle AN, Carr VA, Guerin SA, et al. Hippocampal and cortical mechanisms at retrieval explain variability in episodic remembering in older adults. Elife 2020; 9:e55335.
Stark SM, Yassa MA, Lacy JW, Stark CE. A task to assess behavioral pattern separation (BPS) in humans: data from healthy aging and mild cognitive impairment. Neuropsychologia 2013; 51:2442–2449.
Stark SM, Kirwan CB, Stark CEL. Mnemonic similarity task: a tool for assessing hippocampal integrity. Trends Cogn Sci 2019; 23:938–951.
Crocco E, Curiel-Cid RE, Kitaigorodsky M, et al. A brief version of the LASSI-L detects prodromal Alzheimer's disease states. J Alzheimers Dis 2020; 78:789–799.
Loewenstein DA, Curiel RE, Greig MT, et al. A novel cognitive stress test for the detection of preclinical Alzheimer disease: discriminative properties and relation to amyloid load. Am J Geriatr Psychiatry 2016; 24:804–813.
Curiel Cid RE, Loewenstein DA, Rosselli M, et al. A cognitive stress test for prodromal Alzheimer's disease: multiethnic generalizability. Alzheimers Dement (Amst) 2019; 11:550–559.
Loewenstein DA, Curiel RE, Wright C, et al. Recovery from proactive semantic interference in mild cognitive impairment and normal aging: relationship to atrophy in brain regions vulnerable to Alzheimer's disease. J Alzheimers Dis 2017; 56:1119–1126.
Bell SA, Cohen HR, Lee S, et al. Development of novel measures for Alzheimer's disease prevention trials (NoMAD). Contemp Clin Trials 2021; 106:106425.
Pratap A, Neto EC, Snyder P, et al. Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants. NPJ Digit Med 2020; 3:21.
Geddes MR, O’Connell ME, Fisk JD, et al. Alzheimer Society of Canada Task Force on Dementia Care Best Practices for C. Remote cognitive and behavioral assessment: report of the Alzheimer Society of Canada Task Force on dementia care best practices for COVID-19. Alzheimers Dement (Amst) 2020; 12:e12111.
Wong L, Martin-Khan M, Rowland J, et al. The Rowland Universal Dementia Assessment Scale (RUDAS) as a reliable screening tool for dementia when administered via videoconferencing in elderly postacute hospital patients. J Telemed Telecare 2012; 18:176–179.
Newkirk LA, Kim JM, Thompson JM, et al. Validation of a 26-point telephone version of the Mini-Mental State Examination. J Geriatr Psychiatry Neurol 2004; 17:81–87.
Pendlebury ST, Welch SJ, Cuthbertson FC, et al. Telephone assessment of cognition after transient ischemic attack and stroke: modified telephone interview of cognitive status and telephone Montreal Cognitive Assessment versus face-to-face Montreal Cognitive Assessment and neuropsychological battery. Stroke 2013; 44:227–229.
Rebchuk AD, Deptuck HM, O’Neill ZR, et al. Validation of a novel telehealth administration protocol for the NIH Toolbox-Cognition Battery. Telemed J E Health 2019; 25:237–242.
Perin S, Buckley RF, Pase MP, et al. Unsupervised assessment of cognition in the Healthy Brain Project: implications for web-based registries of individuals at risk for Alzheimer's disease. Alzheimers Dement (N Y) 2020; 6:e12043.
Sliwinski MJ. Measurement-burst designs for social health research. Soc Person Psychol Compass 2008; 2:245–261.
Sliwinski MJ, Mogle JA, Hyun J, et al. Reliability and validity of ambulatory cognitive assessments. Assessment 2018; 25:14–30.
Hassenstab J. Presentation: remote assessment approaches in the Dominantly Inherited Alzheimer Network (DIAN). Alzheimer's Association International Conference 2020. https://alz.confex.com/alz/20amsterdam/meetingapp.cgi/Paper/38144 .
Samaroo A, Amariglio RE, Burnham S, et al. Diminished Learning Over Repeated Exposures (LORE) in preclinical Alzheimer's disease. Alzheimers Dement (Amst) 2020; 12:e12132.
Duff K, Hammers DB, Dalley BCA, et al. Short-term practice effects and amyloid deposition: providing information above and beyond baseline cognition. J Prev Alzheimers Dis 2017; 4:87–92.
Baker JE, Bruns L Jr, Hassenstab J, et al. Use of an experimental language acquisition paradigm for standardized neuropsychological assessment of learning: a pilot study in young and older adults. J Clin Exp Neuropsychol 2020; 42:55–65.
Buegler M, Harms R, Balasa M, et al. Digital biomarker-based individualized prognosis for people at risk of dementia. Alzheimers Dement (Amst) 2020; 12:e12073.
Rentz DM, Papp KV, Mayblyum DV, et al. Association of digital clock drawing with PET amyloid and tau pathology in normal older adults. Neurology 2021; 96:e1844–e1854.
Chen R, Jankovic F, Marsinek N. Developing measures of cognitive impairment in the real world from consumer-grade multimodal sensor streams. 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Anchorage, AK; 2019.
Bayat S, Babulal GM, Schindler S E, et al. GPS driving: a digital biomarker for preclinical Alzheimer disease. Alzheimers Res Ther 2021; 13:115.
Zhou H, Lee H, Lee J, et al. Motor planning error: toward measuring cognitive frailty in older adults using wearables. Sensors (Basel) 2018; 18:926.
Husebo BS, Heintz HL, Berge LI, et al. Sensing technology to monitor behavioral and psychological symptoms and to assess treatment response in people with dementia. A systematic review. Front Pharmacol 2019; 10:1699.