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Bartschi JG, Greenwood LM, Montgomery A, Dortants L, Weston-Green K, Huang XF, Pai N, Potter J, Schira MM, Croft R, Solowij N. Cannabidiol as a Treatment for Neurobiological, Behavioral, and Psychological Symptoms in Early-Stage Dementia: A Double-Blind, Placebo-Controlled Clinical Trial Protocol. Cannabis Cannabinoid Res 2022; 8:348-359. [PMID: 36040362 DOI: 10.1089/can.2021.0209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Rationale: The slowing of disease progression in dementia in the early stages of diagnosis is paramount to improving the quality of life for those diagnosed and their support networks. Accumulating evidence suggests that CBD, a constituent of Cannabis sativa, is associated with neuroprotective, neuroendocrine, and psychotherapeutic effects, suggesting that it may be beneficial to dementia treatment. However, no published human study to date has examined this possibility. This trial aims to determine whether daily treatment with CBD over a 12-week period is associated with improved neurobiological, behavioral, and psychological outcomes in individuals living with early-stage dementia. Methods: Sixty participants with early-stage dementia will be recruited for a randomized, double-blind, placebo-controlled clinical trial. Participants will be randomized into either 99.9% pure CBD or placebo treatment conditions and administered two capsules per day for 12 weeks. Participants will commence a 200 mg/day dose for 2 weeks before escalating to 300 mg/day for the remaining 10 weeks. Neuroimaging and blood-based neuroendocrine profiles will be assessed at baseline and post-treatment. Psychological and behavioral symptoms will be assessed at baseline, 6 weeks, and post-treatment. Monitoring of health and side-effects will be conducted through weekly home visits. Discussion: This study is among the first to investigate the effects of isolated CBD in improving neuroanatomical and neuroendocrine changes, alongside psychological symptoms, during the early stages of dementia diagnosis. The outcomes of this trial have the capacity to inform a potential novel and accessible treatment approach for individuals living with early-stage dementia, and in turn, improve quality of life, prognoses, and treatment outcomes. Trial Registration: This trial has been registered with the Therapeutic Goods Administration (CT-2020-CTN-03849-1v2) and the Australian and New Zealand Clinical Trials Registry (ACTRN12621001364864).
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Affiliation(s)
- Jessica G Bartschi
- School of Psychology, Faculty of the Arts, Social Sciences and Humanities, University of Wollongong, Wollongong, Australia.,Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, Australia.,Australian Center for Cannabinoid Clinical and Research Excellence (ACRE), New Lambton Heights, Australia
| | - Lisa-Marie Greenwood
- Australian Center for Cannabinoid Clinical and Research Excellence (ACRE), New Lambton Heights, Australia.,Research School of Psychology, The Australian National University, Canberra, Australia
| | - Amy Montgomery
- Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, Australia.,School of Nursing, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, Australia
| | - Lon Dortants
- School of Psychology, Faculty of the Arts, Social Sciences and Humanities, University of Wollongong, Wollongong, Australia.,Australian Center for Cannabinoid Clinical and Research Excellence (ACRE), New Lambton Heights, Australia
| | - Katrina Weston-Green
- Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, Australia.,Australian Center for Cannabinoid Clinical and Research Excellence (ACRE), New Lambton Heights, Australia.,School of Medicine and Molecular Horizons, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, Australia
| | - Xu-Feng Huang
- Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, Australia.,Australian Center for Cannabinoid Clinical and Research Excellence (ACRE), New Lambton Heights, Australia.,School of Medicine and Molecular Horizons, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, Australia
| | - Nagesh Pai
- Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, Australia.,School of Medicine and Molecular Horizons, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, Australia.,Southern Hospitals Network, Illawarra-Shoalhaven Local Health District, Warrawong, Australia
| | - Jan Potter
- Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, Australia.,School of Medicine and Molecular Horizons, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, Australia.,Southern Hospitals Network, Illawarra-Shoalhaven Local Health District, Warrawong, Australia
| | - Mark M Schira
- School of Psychology, Faculty of the Arts, Social Sciences and Humanities, University of Wollongong, Wollongong, Australia
| | - Rodney Croft
- School of Psychology, Faculty of the Arts, Social Sciences and Humanities, University of Wollongong, Wollongong, Australia.,Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, Australia
| | - Nadia Solowij
- School of Psychology, Faculty of the Arts, Social Sciences and Humanities, University of Wollongong, Wollongong, Australia.,Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, Australia.,Australian Center for Cannabinoid Clinical and Research Excellence (ACRE), New Lambton Heights, Australia
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Soshi T, Andersson M, Kawagoe T, Nishiguchi S, Yamada M, Otsuka Y, Nakai R, Abe N, Aslah A, Igasaki T, Sekiyama K. Prefrontal Plasticity after a 3-Month Exercise Intervention in Older Adults Relates to Enhanced Cognitive Performance. Cereb Cortex 2021; 31:4501-4517. [PMID: 34009242 DOI: 10.1093/cercor/bhab102] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 03/29/2021] [Accepted: 03/30/2021] [Indexed: 01/24/2023] Open
Abstract
This study examined exercise intervention effects on older adults' brain structures and function. Brain data were analyzed from 47 healthy adults between 61 and 82 years of age who, in a previous study, showed cognitive improvement following a 3-month intervention. The participants were assigned to a motor exercise intervention group (n = 24), performing exercise training programs for a 12-week period, or a waiting control group (n = 23), abstaining from any exercise program. Structural analysis of the frontal cortex and hippocampus revealed increased gray matter volume and/or thickness in several prefrontal areas in the intervention group and reduced hippocampal gray matter volume in the control group. Importantly, the volume increase in the middle frontal sulcus in the intervention group was associated with a general cognitive improvement after the intervention. Functional analysis showed that the prefrontal functional connectivity during a working memory task differently changed in response to the intervention or waiting in the two groups. The functional connectivity decreased in the intervention group, whereas the corresponding connectivity increased in the control group, which was associated with maintaining cognitive performance. The current longitudinal findings indicate that short-term exercise intervention can induce prefrontal plasticity associated with cognitive performance in older adults.
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Affiliation(s)
- Takahiro Soshi
- Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, Sakyo-ku, Kyoto 606-8306, Japan
| | | | - Toshikazu Kawagoe
- College of Contemporary Psychology, Rikkyo University, Niiza, Saitama 352-8558, Japan
| | - Shu Nishiguchi
- NTT DATA Institute of Management Consulting, Inc., Chiyoda-ku, Tokyo 102-0093, Japan
| | - Minoru Yamada
- Graduate School of Comprehensive Human Sciences, University of Tsukuba, Bunkyo-ku, Tokyo 112-0012, Japan
| | - Yuki Otsuka
- Kokoro Research Center, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Ryusuke Nakai
- Kokoro Research Center, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Nobuhito Abe
- Kokoro Research Center, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Adibah Aslah
- Department of Human and Environmental Informatics, Kumamoto University, Chuo-ku, kumamoto 860-8555, Japan
| | - Tomohiko Igasaki
- Department of Human and Environmental Informatics, Kumamoto University, Chuo-ku, kumamoto 860-8555, Japan
| | - Kaoru Sekiyama
- Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, Sakyo-ku, Kyoto 606-8306, Japan
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Identifying Sensitive Measures of Cognitive Decline at Different Clinical Stages of Alzheimer's Disease. J Int Neuropsychol Soc 2021; 27:426-438. [PMID: 33046162 PMCID: PMC8041916 DOI: 10.1017/s1355617720000934] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Alzheimer's disease (AD) studies are increasingly targeting earlier (pre)clinical populations, in which the expected degree of observable cognitive decline over a certain time interval is reduced as compared to the dementia stage. Consequently, endpoints to capture early cognitive changes require refinement. We aimed to determine the sensitivity to decline of widely applied neuropsychological tests at different clinical stages of AD as outlined in the National Institute on Aging - Alzheimer's Association (NIA-AA) research framework. METHOD Amyloid-positive individuals (as determined by positron emission tomography or cerebrospinal fluid) with longitudinal neuropsychological assessments available were included from four well-defined study cohorts and subsequently classified among the NIA-AA stages. For each stage, we investigated the sensitivity to decline of 17 individual neuropsychological tests using linear mixed models. RESULTS 1103 participants (age = 70.54 ± 8.7, 47% female) were included: n = 120 Stage 1, n = 206 Stage 2, n = 467 Stage 3 and n = 309 Stage 4. Neuropsychological tests were differentially sensitive to decline across stages. For example, Category Fluency captured significant 1-year decline as early as Stage 1 (β = -.58, p < .001). Word List Delayed Recall (β = -.22, p < .05) and Trail Making Test (β = 6.2, p < .05) became sensitive to 1-year decline in Stage 2, whereas the Mini-Mental State Examination did not capture 1-year decline until Stage 3 (β = -1.13, p < .001) and 4 (β = -2.23, p < .001). CONCLUSIONS We demonstrated that commonly used neuropsychological tests differ in their ability to capture decline depending on clinical stage within the AD continuum (preclinical to dementia). This implies that stage-specific cognitive endpoints are needed to accurately assess disease progression and increase the chance of successful treatment evaluation in AD.
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Zwan MD, van der Flier WM, Cleutjens S, Schouten TC, Vermunt L, Jutten RJ, van Maurik IS, Sikkes SA, Flenniken D, Howell T, Weiner MW, Scheltens P, Prins ND. Dutch Brain Research Registry for study participant recruitment: Design and first results. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2021; 7:e12132. [PMID: 33614897 PMCID: PMC7882519 DOI: 10.1002/trc2.12132] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 11/11/2020] [Indexed: 12/12/2022]
Abstract
INTRODUCTION The Dutch Brain Research Registry aims to facilitate online recruitment of participants for brain disease studies. METHODS Registrants were primarily recruited through an online social media campaign. The registration process included a short questionnaire, which was subsequently used in the prescreening process to match participants to studies. RESULTS In the first 18 months, 17,218 registrants signed up (58±11 years old, 78% female). Out of 34,696 study invitations that were sent, 36% were accepted by registrants, of which 50% to 84% were finally enrolled, resulting in 10,661 participants in 28 studies. Compared to non-participants, study participants were more often older, male, more highly educated, retired or unemployed, non-smoking, healthier, and more often had a family member with dementia. DISCUSSION The Dutch Brain Research Registry facilitates effective matching of participants to brain disease studies. Participant factors related to study enrollment may reflect facilitators or barriers for participation, which is useful for improving recruitment strategies.
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Affiliation(s)
- Marissa D. Zwan
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam NeuroscienceAmsterdam University Medical CenterAmsterdamthe Netherlands
| | - Wiesje M. van der Flier
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam NeuroscienceAmsterdam University Medical CenterAmsterdamthe Netherlands
- Department of Epidemiology and BiostatisticsAmsterdam University Medical CenterAmsterdamthe Netherlands
| | - Solange Cleutjens
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam NeuroscienceAmsterdam University Medical CenterAmsterdamthe Netherlands
| | - Tamara C Schouten
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam NeuroscienceAmsterdam University Medical CenterAmsterdamthe Netherlands
| | - Lisa Vermunt
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam NeuroscienceAmsterdam University Medical CenterAmsterdamthe Netherlands
- Department of Clinical ChemistryNeurochemistry LaboratoryAmsterdam NeuroscienceAmsterdam University Medical CenterAmsterdamthe Netherlands
| | - Roos J. Jutten
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam NeuroscienceAmsterdam University Medical CenterAmsterdamthe Netherlands
| | - Ingrid S. van Maurik
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam NeuroscienceAmsterdam University Medical CenterAmsterdamthe Netherlands
- Department of Epidemiology and BiostatisticsAmsterdam University Medical CenterAmsterdamthe Netherlands
| | - Sietske A.M. Sikkes
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam NeuroscienceAmsterdam University Medical CenterAmsterdamthe Netherlands
| | - Derek Flenniken
- Center for Imaging of Neurodegenerative Diseases (CIND)San Francisco Veterans Affair Medical CenterSan FranciscoCaliforniaUSA
| | - Taylor Howell
- Center for Imaging of Neurodegenerative Diseases (CIND)San Francisco Veterans Affair Medical CenterSan FranciscoCaliforniaUSA
| | - Michael W. Weiner
- Center for Imaging of Neurodegenerative Diseases (CIND)San Francisco Veterans Affair Medical CenterSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Philip Scheltens
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam NeuroscienceAmsterdam University Medical CenterAmsterdamthe Netherlands
| | - Niels D. Prins
- Department of NeurologyAlzheimer Center AmsterdamAmsterdam NeuroscienceAmsterdam University Medical CenterAmsterdamthe Netherlands
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Romero-Ayuso D, Cuerda C, Morales C, Tesoriero R, Triviño-Juárez JM, Segura-Fragoso A, Gallud JA. Activities of Daily Living and Categorization Skills of Elderly with Cognitive Deficit: A Preliminary Study. Brain Sci 2021; 11:213. [PMID: 33578677 PMCID: PMC7916351 DOI: 10.3390/brainsci11020213] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 01/31/2021] [Accepted: 02/04/2021] [Indexed: 11/16/2022] Open
Abstract
Cognitive dysfunction affects the performance of Activities of Daily Living (ADL) and the quality of life of people with these deficits and their caregivers. To the knowledge of the authors, to date, there are few studies that focus on knowing the relationship between personal autonomy and deductive reasoning and/or categorization skills, which are necessary for the performance of the ADL. The aim of this study was to explore the relationships between ADL and categorization skills in older people. The study included 51 participants: 31 patients with cognitive impairment and 20 without cognitive impairment. Two tests were administered to assess cognitive functions: (1) the Montreal Cognitive Assessment (MoCA); and (2) the digital version of Riska Object Classification test (ROC-d). In addition, the Routine Tasks Inventory-2 (RTI-2) was applied to determine the level of independence in activities of daily living. People with cognitive impairment performed poorly in categorization tasks with unstructured information (p = 0.006). Also, the results found a high correlation between cognitive functioning and the performance of ADLs (Physical ADL: r = 0.798; p < 0.001; Instrumental ADL: r = 0.740; p < 0.001), a moderate correlation between Physical ADLs and categorization skills (unstructured ROC-d: r = 0.547; p < 0.001; structured ROC-d: r = 0.586; p < 0.001) and Instrumental ADLs and categorization skills in older people (unstructured ROC-d: r = 0.510; p < 0.001; structured ROC-d: r = 0.463; p < 0.001). The ROC-d allows the assessment of categorization skills to be quick and easy, facilitating the assessment process by OT, as well as the accuracy of the data obtained.
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Affiliation(s)
- Dulce Romero-Ayuso
- Department of Physical Therapy, Occupational Therapy Division, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain;
| | - Cristian Cuerda
- Computing Systems Department, University of Castilla-La Mancha, 02071 Albacete, Spain; (C.C.); (R.T.)
| | - Carmen Morales
- Department of Physical Therapy, Occupational Therapy Division, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain;
| | - Ricardo Tesoriero
- Computing Systems Department, University of Castilla-La Mancha, 02071 Albacete, Spain; (C.C.); (R.T.)
| | | | - Antonio Segura-Fragoso
- Faculty of Health Sciences, University of Castilla-La Mancha, Talavera de la Reina, 45600 Toledo, Spain;
| | - José A. Gallud
- Computing Systems Department, University of Castilla-La Mancha, 02071 Albacete, Spain; (C.C.); (R.T.)
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Cummings J. New approaches to symptomatic treatments for Alzheimer's disease. Mol Neurodegener 2021; 16:2. [PMID: 33441154 PMCID: PMC7805095 DOI: 10.1186/s13024-021-00424-9] [Citation(s) in RCA: 92] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 01/02/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Successful development of agents that improve cognition and behavior in Alzheimer's disease (AD) is critical to improving the lives of patients manifesting the symptoms of this progressive disorder. DISCUSSION There have been no recent approvals of cognitive enhancing agents for AD. There are currently 6 cognitive enhancers in Phase 2 trials and 4 in phase 3. They represent a variety of novel mechanisms. There has been progress in developing new treatments for neuropsychiatric symptoms in AD with advances in treatment of insomnia, psychosis, apathy, and agitation in AD. There are currently 4 AD-related psychotropic agents in Phase 2 trials and 7 in Phase 3 trials. Many novel mechanisms are being explored for the treatment of cognitive and behavioral targets. Progress in trial designs, outcomes measures, and population definitions are improving trial conduct for symptomatic treatment of AD. CONCLUSIONS Advances in developing new agents for cognitive and behavioral symptoms of AD combined with enhanced trial methods promise to address the unmet needs of patients with AD for improved cognition and amelioration of neuropsychiatric symptoms.
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Affiliation(s)
- Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV, USA.
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Palumbo R, Di Domenico A, Piras F, Bazzano S, Zerilli M, Lorico F, Borella E. Measuring global functioning in older adults with cognitive impairments using the Rasch model. BMC Geriatr 2020; 20:492. [PMID: 33228541 PMCID: PMC7685614 DOI: 10.1186/s12877-020-01886-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 11/10/2020] [Indexed: 11/30/2022] Open
Abstract
Background Cognitive and functional measures are often measured and interpreted separately during the clinical evaluation of patients with cognitive impairment. This can sometimes lead to a challenging interpretation when measures do not show concordance, especially after a clinical intervention. In this study, the development and evaluation of a new approach, using the Rasch model, that combines cognitive and functional measures in one single and more powerful measure (compared to stand-alone tests) to assess global functioning in older adults with cognitive impairment (including dementia) was presented. Methods Clinical data from 265 older adults’ subjects diagnosed with mild cognitive impairment, or dementia, included: The Mini-mental state examination (MMSE), the Esame Neuropsicologico Breve (ENB) – a neuropsychological battery used in Italy–, the Activities of Daily Living (ADL), and the Instrumental Activities of Daily Living (IADL) questionnaires. Results Patients with severe cognitive impairment showed lower global functioning score compared to patients with moderate impairment. Receiver Operating Characteristic (ROC) curve analyses were performed to determine sensitivity and specificity of the global functioning score resulting from the combined measure. Results showed that the global functioning score discriminates better between patients with severe and moderate cognitive impairment compared to the ENB, ADL, and IADL when considered separately. Conclusions The Rasch model was able to combine cognitive and functional measures into a single score (global functioning score). All together, these results suggest that the diverse cognitive and functional measures can be considered part of one single dimension (global functioning) and that this dimension can be measured as a single construct and score. This study offers an alternative perspective for future development of instruments that would help clinicians in measuring global functioning in older adults’ patients at different stages of cognitive impairments and different baseline level of performance.
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Affiliation(s)
- Rocco Palumbo
- Department of Psychological, Health and Territorial Sciences, University of Chieti, Via dei Vestini 31, 66100, Chieti, Italy. .,Department of Neurology, Boston University, School of Medicine, Boston, MA, USA.
| | - Alberto Di Domenico
- Department of Psychological, Health and Territorial Sciences, University of Chieti, Via dei Vestini 31, 66100, Chieti, Italy
| | - Federica Piras
- IRCCS Santa Lucia Foundation, Neuropsychiatry Laboratory, Clinical and Behavioral Neurology Department, Rome, Italy
| | - Salvatore Bazzano
- Centro Decadimento Cognitivo Asl7 di Bassano del Grappa, Bassano del Grappa, Italy
| | - Mario Zerilli
- Centro Decadimento Cognitivo Asl7 di Bassano del Grappa, Bassano del Grappa, Italy
| | - Fabio Lorico
- Centro Decadimento Cognitivo Asl7 di Bassano del Grappa, Bassano del Grappa, Italy
| | - Erika Borella
- Department of General Psychology, University of Padova, Padova, Italy
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Dubbelman MA, Jutten RJ, Tomaszewski Farias SE, Amariglio RE, Buckley RF, Visser PJ, Rentz DM, Johnson KA, Properzi MJ, Schultz A, Donovan N, Gatchell JR, Teunissen CE, Van Berckel BNM, Van der Flier WM, Sperling RA, Papp KV, Scheltens P, Marshall GA, Sikkes SAM. Decline in cognitively complex everyday activities accelerates along the Alzheimer's disease continuum. Alzheimers Res Ther 2020; 12:138. [PMID: 33121534 PMCID: PMC7597034 DOI: 10.1186/s13195-020-00706-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 10/12/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Impairment in daily functioning is a clinical hallmark of dementia. Difficulties with "instrumental activities of daily living" (IADL) seem to increase gradually over the course of Alzheimer's disease (AD), before dementia onset. However, it is currently not well established how difficulties develop along the preclinical and prodromal stages of AD. We aimed to investigate the trajectories of decline in IADL performance, as reported by a study partner, along the early stages of AD. METHODS In a longitudinal multicenter study, combining data from community-based and memory clinic cohorts, we included 1555 individuals (mean age 72.5 ± 7.8 years; 50% female) based on availability of amyloid biomarkers, longitudinal IADL data, and clinical information at baseline. Median follow-up duration was 2.1 years. All amyloid-positive participants (n = 982) were classified into the National Institute on Aging-Alzheimer's Association (NIA-AA) clinical stages ranging from preclinical AD (1) to overt dementia (4+). Cognitively normal amyloid-negative individuals (n = 573) served as a comparison group. The total scores of three study-partner reported IADL questionnaires were standardized. RESULTS The rate of decline in cognitively normal (stage 1) individuals with and without abnormal amyloid did not differ (p = .453). However, from stage 2 onwards, decline was significantly faster in individuals on the AD continuum (B [95%CI] = - 0.32 [- 0.55, - 0.09], p = .007). The rate of decline increased with each successive stage: one standard deviation (SD) unit per year in stage 3 (- 1.06 [- 1.27, - 0.85], p < .001) and nearly two SD units per year in stage 4+ (1.93 [- 2.19, - 1.67], p < .001). Overall, results were similar between community-based and memory clinic study cohorts. CONCLUSIONS Our results suggest that the rate of functional decline accelerates along the AD continuum, as shown by steeper rates of decline in each successive NIA-AA clinical stage. These results imply that incremental changes in function are a meaningful measure for early disease monitoring. Combined with the low-cost assessment, this advocates the use of these functional questionnaires for capturing the effects of early AD-related cognitive decline on daily life.
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Affiliation(s)
- Mark A Dubbelman
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, location VUmc, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands.
| | - Roos J Jutten
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, location VUmc, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | | | - Rebecca E Amariglio
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Rachel F Buckley
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Pieter Jelle Visser
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, location VUmc, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Dorene M Rentz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Keith A Johnson
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael J Properzi
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Aaron Schultz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Nancy Donovan
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jennifer R Gatchell
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Bart N M Van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Wiesje M Van der Flier
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, location VUmc, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kathryn V Papp
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Philip Scheltens
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, location VUmc, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Gad A Marshall
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sietske A M Sikkes
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, location VUmc, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
- Department of Clinical, Neuro- & Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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de Vent NR, Agelink van Rentergem JA, Huizenga HM, van der Flier WM, Sikkes SAM, Murre JMJ, van den Bosch KA, Scheltens P, Schmand BA. An Operational Definition of 'Abnormal Cognition' to Optimize the Prediction of Progression to Dementia: What Are Optimal Cut-Off Points for Univariate and Multivariate Normative Comparisons? J Alzheimers Dis 2020; 77:1693-1703. [PMID: 32925072 PMCID: PMC7683061 DOI: 10.3233/jad-200811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Background: In neuropsychology and neurology, there is no consensus on the definition of abnormal cognition. Objective: To operationally define ‘abnormal cognition’ for optimally predicting progression to dementia in a memory clinic sample, and to test whether multivariate profile analysis of cognitive test results improves this prediction compared to standard clinical evaluation. Methods: We used longitudinal data from 835 non-demented patients of the Amsterdam Dementia Cohort. For 10 cognitive measures at baseline, we determined which number of abnormal tests and which magnitude of score deviations best predicted progression. Results: Predictive ability for progression to dementia of one, two, and three abnormal test scores out of 10 is highly similar (Cox hazard ratios: 3.7–4.1) provided cut-off values are adapted appropriately. Cut-offs have to be less stringent if the number of abnormal tests required increases: the optimal cut-off is z < –1.45 when one deviating score is required, z < –1.15 when two abnormal tests are required, and z < –0.70 when three abnormal tests are required. The profile analysis has similar predictive ability at the cut-off of p < 0.22 (hazard ratio 3.8). A likelihood ratio test showed that this analysis improves prediction of progression to dementia when added to standard clinical evaluation (p < 0.001). Conclusion: Abnormal cognition may be defined as one, two, or three abnormal test scores out of 10 if the magnitude of score deviations is adapted accordingly. An abnormal score profile predicts decline to dementia equally well, and improves the prediction when used complimentary to standard clinical evaluation.
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Affiliation(s)
- Nathalie R de Vent
- Brain and Cognition, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | | | - Hilde M Huizenga
- Developmental Psychology, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center, Department of Neurology, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands.,Department of Epidemiology & Biostatistics, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
| | - Sieske A M Sikkes
- Department of Epidemiology & Biostatistics, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
| | - Jaap M J Murre
- Brain and Cognition, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | - Karlijn A van den Bosch
- Alzheimer Center, Department of Neurology, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center, Department of Neurology, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
| | - Ben A Schmand
- Brain and Cognition, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
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10
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Jutten RJ, Harrison JE, Brunner A, Vreeswijk R, van Deelen R, de Jong FJ, Opmeer EM, Ritchie CW, Aleman A, Scheltens P, Sikkes SA. The Cognitive-Functional Composite is sensitive to clinical progression in early dementia: Longitudinal findings from the Catch-Cog study cohort. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2020; 6:e12020. [PMID: 32313832 PMCID: PMC7164406 DOI: 10.1002/trc2.12020] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 03/06/2020] [Indexed: 12/18/2022]
Abstract
INTRODUCTION In an attempt to capture clinically meaningful cognitive decline in early dementia, we developed the Cognitive-Functional Composite (CFC). We investigated the CFC's sensitivity to decline in comparison to traditional clinical endpoints. METHODS This longitudinal construct validation study included 148 participants with subjective cognitive decline, mild cognitive impairment, or mild dementia. The CFC and traditional tests were administered at baseline, 3, 6, and 12 months. Sensitivity to change was investigated using linear mixed models and r 2 effect sizes. RESULTS CFC scores declined over time (β = -.16, P < .001), with steepest decline observed in mild Alzheimer's dementia (β = -.25, P < .001). The CFC showed medium-to-large effect sizes at succeeding follow-up points (r 2 = .08-.42), exhibiting greater change than the Clinical Dementia Rating scale (r 2 = .02-.12). Moreover, change on the CFC was significantly associated with informant reports of cognitive decline (β = .38, P < .001). DISCUSSION By showing sensitivity to decline, the CFC could enhance the monitoring of disease progression in dementia research and clinical practice.
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Affiliation(s)
- Roos J. Jutten
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam Neuroscience, AmsterdamAmsterdam UMCthe Netherlands
| | - John E. Harrison
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam Neuroscience, AmsterdamAmsterdam UMCthe Netherlands
- Metis Cognition LtdWiltshireUK
- Institute of PsychiatryPsychology & NeuroscienceKing's College LondonLondonUK
| | - A.J. Brunner
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam Neuroscience, AmsterdamAmsterdam UMCthe Netherlands
| | - R. Vreeswijk
- Department of GeriatricsSpaarne GasthuisHaarlemthe Netherlands
| | | | - Frank Jan de Jong
- Department of NeurologyErasmus Medical CenterRotterdamthe Netherlands
| | - Esther M. Opmeer
- Department of NeurosciencesUniversity of GroningenUniversity Medical Center GroningenGroningenthe Netherlands
- Department of Health and Social WorkUniversity of Applied Sciences WindesheimZwollethe Netherlands
| | - Craig W. Ritchie
- Centre for Dementia PreventionUniversity of EdinburghEdinburghUK
| | - André Aleman
- Department of NeurosciencesUniversity of GroningenUniversity Medical Center GroningenGroningenthe Netherlands
| | - Philip Scheltens
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam Neuroscience, AmsterdamAmsterdam UMCthe Netherlands
| | - Sietske A.M. Sikkes
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam Neuroscience, AmsterdamAmsterdam UMCthe Netherlands
- Department of Clinical, Neuro‐ & Developmental PsychologyVrije Universiteit AmsterdamAmsterdamthe Netherlands
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11
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Giorgio J, Landau SM, Jagust WJ, Tino P, Kourtzi Z. Modelling prognostic trajectories of cognitive decline due to Alzheimer's disease. Neuroimage Clin 2020; 26:102199. [PMID: 32106025 PMCID: PMC7044529 DOI: 10.1016/j.nicl.2020.102199] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 01/24/2020] [Accepted: 01/25/2020] [Indexed: 01/13/2023]
Abstract
Alzheimer's disease (AD) is characterised by a dynamic process of neurocognitive changes from normal cognition to mild cognitive impairment (MCI) and progression to dementia. However, not all individuals with MCI develop dementia. Predicting whether individuals with MCI will decline (i.e. progressive MCI) or remain stable (i.e. stable MCI) is impeded by patient heterogeneity due to comorbidities that may lead to MCI diagnosis without progression to AD. Despite the importance of early diagnosis of AD for prognosis and personalised interventions, we still lack robust tools for predicting individual progression to dementia. Here, we propose a novel trajectory modelling approach based on metric learning (Generalised Metric Learning Vector Quantization) that mines multimodal data from MCI patients in the Alzheimer's disease Neuroimaging Initiative (ADNI) cohort to derive individualised prognostic scores of cognitive decline due to AD. We develop an integrated biomarker generation- using partial least squares regression- and classification methodology that extends beyond binary patient classification into discrete subgroups (i.e. stable vs. progressive MCI), determines individual profiles from baseline (i.e. cognitive or biological) data and predicts individual cognitive trajectories (i.e. change in memory scores from baseline). We demonstrate that a metric learning model trained on baseline cognitive data (memory, executive function, affective measurements) discriminates stable vs. progressive MCI individuals with high accuracy (81.4%), revealing an interaction between cognitive (memory, executive functions) and affective scores that may relate to MCI comorbidity (e.g. affective disturbance). Training the model to perform the same binary classification on biological data (mean cortical β-amyloid burden, grey matter density, APOE 4) results in similar prediction accuracy (81.9%). Extending beyond binary classifications, we develop and implement a trajectory modelling approach that shows significantly better performance in predicting individualised rate of future cognitive decline (i.e. change in memory scores from baseline), when the metric learning model is trained with biological (r = -0.68) compared to cognitive (r = -0.4) data. Our trajectory modelling approach reveals interpretable and interoperable markers of progression to AD and has strong potential to guide effective stratification of individuals based on prognostic disease trajectories, reducing MCI patient misclassification, that is critical for clinical practice and discovery of personalised interventions.
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Affiliation(s)
- Joseph Giorgio
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA USA
| | - Peter Tino
- School of Computer Science, University of Birmingham, Birmingham, United Kingdom
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom.
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12
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Naude JP, Gill S, Hu S, McGirr A, Forkert ND, Monchi O, Stys PK, Smith EE, Ismail Z. Plasma Neurofilament Light: A Marker of Neurodegeneration in Mild Behavioral Impairment. J Alzheimers Dis 2020; 76:1017-1027. [PMID: 32597801 PMCID: PMC7504997 DOI: 10.3233/jad-200011] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/09/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Assessing neuropsychiatric symptoms (NPS) in older adults is important for determining dementia risk. Mild behavioral impairment (MBI) is an at-risk state for cognitive decline and dementia, characterized by emergent NPS in later life. MBI has significantly higher dementia incidence than late life psychiatric conditions. However, its utility as a proxy for neurodegeneration has not been demonstrated. Plasma neurofilament light (NfL) is a validated biomarker of axonal damage, and has been shown to associate with hallmarks of neurodegeneration. OBJECTIVE The purpose of this investigation was to identify associations between NfL rate of change and the presence of MBI symptomatology. METHODS We evaluated the association of MBI with changes in NfL in a cohort (n = 584; MBI + n = 190, MBI- n = 394) of non-demented participants from the Alzheimer's Disease Neuroimaging Initiative. MBI was determined by transforming Neuropsychiatric Inventory Questionnaire items using a published algorithm. Change in NfL was calculated over 2 years. RESULTS Time*MBI status was the only significant interaction to predict change in NfL concentrations (F(1,574) = 4.59, p = 0.032), even after controlling for age, mild cognitive impairment, and demographics. Analyses reclassifying 64 participants with new onset MBI over 2 years similarly demonstrated greater increases in NfL (F(1,574) = 5.82, p = 0.016). CONCLUSION These findings suggest MBI is a clinical proxy of early phase neurodegeneration with putative utility in identifying those at dementia risk. MBI can be used as a case ascertainment approach to capture those at high risk for cognitive decline and dementia, and is an important construct for clinicians dealing with cognitive and neuropsychiatric symptomatology in older adults.
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Affiliation(s)
- James P. Naude
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Sascha Gill
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Sophie Hu
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Community Health Science, University of Calgary, Calgary, Alberta, Canada
| | - Alexander McGirr
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada
- Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, Alberta, Canada
| | - Nils D. Forkert
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Oury Monchi
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada
| | - Peter K. Stys
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Eric E. Smith
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Zahinoor Ismail
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
- Department of Community Health Science, University of Calgary, Calgary, Alberta, Canada
- Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada
- Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, Alberta, Canada
- O’Brien Institute for Public Health, University of Calgary
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13
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Zhao T, Wang D, Hu Y, Zhang N, Zang T, Wang Y. Identifying Alzheimer’s Disease-related miRNA Based on Semi-clustering. Curr Gene Ther 2019; 19:216-223. [DOI: 10.2174/1566523219666190924113737] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 06/05/2019] [Accepted: 06/12/2019] [Indexed: 01/14/2023]
Abstract
Background:
More and more scholars are trying to use it as a specific biomarker for Alzheimer’s
Disease (AD) and mild cognitive impairment (MCI). Multiple studies have indicated that
miRNAs are associated with poor axonal growth and loss of synaptic structures, both of which are early
events in AD. The overall loss of miRNA may be associated with aging, increasing the incidence of
AD, and may also be involved in the disease through some specific molecular mechanisms.
Objective:
Identifying Alzheimer’s disease-related miRNA can help us find new drug targets, early
diagnosis.
Materials and Methods:
We used genes as a bridge to connect AD and miRNAs. Firstly, proteinprotein
interaction network is used to find more AD-related genes by known AD-related genes. Then,
each miRNA’s correlation with these genes is obtained by miRNA-gene interaction. Finally, each
miRNA could get a feature vector representing its correlation with AD. Unlike other studies, we do not
generate negative samples randomly with using classification method to identify AD-related miRNAs.
Here we use a semi-clustering method ‘one-class SVM’. AD-related miRNAs are considered as outliers
and our aim is to identify the miRNAs that are similar to known AD-related miRNAs (outliers).
Results and Conclusion:
We identified 257 novel AD-related miRNAs and compare our method with
SVM which is applied by generating negative samples. The AUC of our method is much higher than
SVM and we did case studies to prove that our results are reliable.
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Affiliation(s)
- Tianyi Zhao
- Department of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Donghua Wang
- Department of General Surgery, General Hospital of Heilongjiang Province Land Reclamation Bureau, Harbin, China
| | - Yang Hu
- School of life Science and Tenchnology, Harbin Institute of Technology, Harbin, China
| | - Ningyi Zhang
- Department of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Tianyi Zang
- Department of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Yadong Wang
- Department of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
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14
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Jutten RJ, Harrison JE, Lee Meeuw Kjoe PR, Ingala S, Vreeswijk R, van Deelen RAJ, de Jong FJ, Opmeer EM, Aleman A, Ritchie CW, Scheltens P, Sikkes SAM. Assessing cognition and daily function in early dementia using the cognitive-functional composite: findings from the Catch-Cog study cohort. ALZHEIMERS RESEARCH & THERAPY 2019; 11:45. [PMID: 31092277 PMCID: PMC6521452 DOI: 10.1186/s13195-019-0500-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Accepted: 04/28/2019] [Indexed: 12/15/2022]
Abstract
Background The cognitive-functional composite (CFC) was designed to improve the measurement of clinically relevant changes in predementia and early dementia stages. We have previously demonstrated its good test-retest reliability and feasibility of use. The current study aimed to evaluate several quality aspects of the CFC, including construct validity, clinical relevance, and suitability for the target population. Methods Baseline data of the Capturing Changes in Cognition study was used: an international, prospective cohort study including participants with subjective cognitive decline (SCD), mild cognitive impairment (MCI), Alzheimer’s disease (AD) dementia, and dementia with Lewy bodies (DLB). The CFC comprises seven existing cognitive tests focusing on memory and executive functions (EF) and the informant-based Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL-Q). Construct validity and clinical relevance were assessed by (1) confirmatory factor analyses (CFA) using all CFC subtests and (2) linear regression analyses relating the CFC score (independent) to reference measures of disease severity (dependent), correcting for age, sex, and education. To assess the suitability for the target population, we compared score distributions of the CFC to those of traditional tests (Alzheimer’s Disease Assessment Scale–Cognitive subscale, Alzheimer’s Disease Cooperative Study–Activities of Daily Living scale, and Clinical Dementia Rating scale). Results A total of 184 participants were included (age 71.8 ± 8.4; 42% female; n = 14 SCD, n = 80 MCI, n = 78 AD, and n = 12 DLB). CFA showed that the hypothesized three-factor model (memory, EF, and IADL) had adequate fit (CFI = .931, RMSEA = .091, SRMR = .06). Moreover, worse CFC performance was associated with more cognitive decline as reported by the informant (β = .61, p < .001), poorer quality of life (β = .51, p < .001), higher caregiver burden (β = − .51, p < .001), more apathy (β = − .36, p < .001), and less cortical volume (β = .34, p = .02). Whilst correlations between the CFC and traditional measures were moderate to strong (ranging from − .65 to .83, all p < .001), histograms showed floor and ceiling effects for the traditional tests as compared to the CFC. Conclusions Our findings illustrate that the CFC has good construct validity, captures clinically relevant aspects of disease severity, and shows no range restrictions in scoring. It therefore provides a more useful outcome measure than traditional tests to evaluate cognition and function in MCI and mild AD. Electronic supplementary material The online version of this article (10.1186/s13195-019-0500-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Roos J Jutten
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - John E Harrison
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Metis Cognition Ltd, Park House, Kilmington Common, Wiltshire, UK.,Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Philippe R Lee Meeuw Kjoe
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Silvia Ingala
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Radiology and Nuclear Medicine Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - R Vreeswijk
- Department of Geriatrics, Spaarne Gasthuis, Haarlem, The Netherlands
| | - R A J van Deelen
- Department of Geriatrics, Spaarne Gasthuis, Haarlem, The Netherlands
| | - Frank Jan de Jong
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Esther M Opmeer
- Department of Biomedical Sciences, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.,Department of Health and Social Work, University of Applied Sciences Windesheim, Zwolle, The Netherlands
| | - André Aleman
- Department of Biomedical Sciences, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Craig W Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, UK
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Sietske A M Sikkes
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Epidemiology & Biostatistics, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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15
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Marizzoni M, Ferrari C, Macis A, Jovicich J, Albani D, Babiloni C, Cavaliere L, Didic M, Forloni G, Galluzzi S, Hoffmann KT, Molinuevo JL, Nobili F, Parnetti L, Payoux P, Pizzini F, Rossini PM, Salvatore M, Schönknecht P, Soricelli A, Del Percio C, Hensch T, Hegerl U, Tsolaki M, Visser PJ, Wiltfang J, Richardson JC, Bordet R, Blin O, Frisoni GB. Biomarker Matrix to Track Short Term Disease Progression in Amnestic Mild Cognitive Impairment Patients with Prodromal Alzheimer’s Disease. J Alzheimers Dis 2019; 69:49-58. [DOI: 10.3233/jad-181016] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Moira Marizzoni
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Clarissa Ferrari
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Ambra Macis
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Jorge Jovicich
- Center for Mind/Brain Sciences, University of Trento, Italy
| | - Diego Albani
- Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Claudio Babiloni
- Department of Physiology and Pharmacology “V. Erspamer”, Sapienza University of Rome, Rome, Italy
- Hospital San Raffaele Cassino, Cassino (FR), Italy
| | - Libera Cavaliere
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Mira Didic
- Aix-Marseille Université, Inserm, INS UMR_S 1106, Marseille, France
- APHM, Timone, Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
| | - Gianluigi Forloni
- Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Samantha Galluzzi
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | | | - José Luis Molinuevo
- Alzheimer’s Disease Unit and Other Cognitive Disorders Unit, Hospital Clínic de Barcelona, and Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalunya, Spain
| | - Flavio Nobili
- Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy
- Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Lucilla Parnetti
- Clinica Neurologica, Università di Perugia, Ospedale Santa Maria della Misericordia, Perugia, Italy
| | - Pierre Payoux
- INSERM; Imagerie cérébrale et handicaps neurologiques UMR 825, Toulouse, France
| | - Francesca Pizzini
- Department of Diagnostics and Pathology, Neuroradiology, Verona University Hospital, Italy
| | - Paolo Maria Rossini
- Department of Gerontology, Area of Neuroscience, Neurosciences & Orthopedics, Catholic University, Policlinic A. Gemelli Foundation Rome, Italy
| | | | - Peter Schönknecht
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | | | | | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | - Ulrich Hegerl
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | - Magda Tsolaki
- 3rd Neurologic Clinic, Medical School, G. Papanikolaou Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Centre, VU Medical Centre, Amsterdam, The Netherlands
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, LVR-Hospital Essen, Faculty of Medicine, University of Duisburg-Essen, Essen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August-University, Goettingen, Germany
- iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Jill C. Richardson
- Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, UK
| | - Régis Bordet
- University of Lille, Inserm, CHU Lille, U1171-Degenerative and vascular cognitive disorders, Lille, France
| | - Olivier Blin
- Aix Marseille University, UMR-CNRS 7289, Service de Pharmacologie Clinique, AP-HM, Marseille, France
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
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16
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Abstract
A key message from the review of cognitive dysfunction in psychiatry published by Millan et al (2012) was not just that cognitive skills are often compromised in patients with psychiatric disorders, but that deficits in specific domains are common to a number of conditions. The review also highlighted that the magnitude of the observed deficits varied across disorders. A helpful element of the Millan et al study was the inclusion of a table in which the authors sought to convey the domains of cognition and a categorization of the magnitude of the observed deficits.In previous articles, we have considered best practice for the assessment of cognition. In these contributions, we have argued not for the use of specific tests, but instead for measures that meet acceptable standards of reliability, validity, and sensitivity. In the course of our discussions, we have included reference to test validity in the context of considering whether selected measures index appropriate domains of cognition. In this article, we begin with a brief discussion of the requirements for good test selection, especially with respect to issues of sensitivity, reliability, and validity. Thereafter the focus of this article is on the issue of domain validity. We will critically review the specification of the cognitive domains proposed by Millan et al, as well as those selected by authors of meta-analyses characterizing cognitive deficits in major depressive disorders. This focus is solely to make the discussion tractable, though we propose that the issues raised will be applicable across all psychiatric and neurological disorders.
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17
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Sabbagh MN, Hendrix S, Harrison JE. FDA position statement "Early Alzheimer's disease: Developing drugs for treatment, Guidance for Industry". ALZHEIMERS & DEMENTIA-TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS 2019; 5:13-19. [PMID: 31650002 PMCID: PMC6804505 DOI: 10.1016/j.trci.2018.11.004] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Despite billions of dollars invested in clinical trials to develop novel therapeutics for Alzheimer's disease, no approved treatments have been developed in the past 15 years. In that span, new classes of drugs have been developed and tested, including monoclonal antibodies, γ-secretase modulators, γ-secretase inhibitors, BACE inhibitors, RAGE inhibitors, nicotinic agonists, 5HT6 antagonists, and others. The one constant for all of these clinical trials programs is the use of the ADAS-cog as the primary scale to determine efficacy. The question that needs to be considered is whether it is the target engagement of the drug or the clinical trial measure testing the efficacy. The FDA put out a new position statement in 2018 informing the field on possible considerations for demonstrating efficacy to open the path for approval. Here, we propose and comment on a variety of approaches that are alternatives to the ADAS for FDA-specified stage 3 and 4 Alzheimer's disease. These novel outcomes are being validated in current clinical trials and could be used as efficacy measures moving forward.
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Affiliation(s)
- Marwan N Sabbagh
- Cleveland Clinic, Lou Ruvo Center for Brain Health, Las Vegas, NV, USA
| | | | - John E Harrison
- Principal Consultant at Metis Cognition Ltd, Kilmington, UK.,Associate Professor at the Alzheimer Center, VUmc, Amsterdam, The Netherlands.,Visiting Professor Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London
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18
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Malek-Ahmadi M, Chen K, Perez SE, He A, Mufson EJ. Cognitive composite score association with Alzheimer's disease plaque and tangle pathology. ALZHEIMERS RESEARCH & THERAPY 2018; 10:90. [PMID: 30205840 PMCID: PMC6134796 DOI: 10.1186/s13195-018-0401-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Accepted: 07/02/2018] [Indexed: 11/10/2022]
Abstract
BACKGROUND Cognitive composite scores are used as the primary outcome measures for Alzheimer's disease (AD) prevention trials; however, the extent to which these composite measures correlate with AD pathology has not been fully investigated. Since many on-going AD prevention studies are testing therapies that target either amyloid or tau, we sought to establish an association between a cognitive composite score and the underlying pathology of AD. METHODS Data from 192 older deceased and autopsied persons from the Rush Religious Order Study were used in this study. All participants were classified at their initial evaluations with a clinical diagnosis of no cognitive impairment (NCI). Of these individuals, 105 remained NCI at the time of their death while the remaining 87 progressed to mild cognitive impairment (MCI) or AD. A cognitive composite score composed of eight cognitive tests was used as the outcome measure. Individuals were classified into groups based on Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropathological diagnosis and Braak stage. RESULTS The rate of annualized composite score decline was significantly greater for the high CERAD (p < 0.001, d = 0.56) and Braak (p < 0.001, d = 0.55) groups compared with the low CERAD and Braak groups, respectively. Mixed-model repeated measure (MMRM) analyses revealed a significantly greater difference in composite score change from baseline for the high CERAD group relative to the low CERAD group after 5 years (Δ = -2.74, 95% confidence interval (CI) -5.01 to -0.47; p = 0.02). A similar analysis between low and high Braak stage groups found no significant difference in change from baseline (Δ = -0.69, 95% CI -3.03 to 1.66; p = 0.56). CONCLUSIONS These data provide evidence that decreased cognitive composite scores were significantly associated with increased AD pathology and provide support for the use of cognitive composite scores in AD prevention trials.
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Affiliation(s)
| | - Kewei Chen
- Banner Alzheimer's Institute, 901 E. Willetta St, Phoenix, AZ, USA
| | - Sylvia E Perez
- Department of Neurobiology and Neurology, Barrow Neurological Institute, 350 W. Thomas Rd, Phoenix, AZ, 85013, USA
| | - Anna He
- Banner Alzheimer's Institute, 901 E. Willetta St, Phoenix, AZ, USA
| | - Elliott J Mufson
- Department of Neurobiology and Neurology, Barrow Neurological Institute, 350 W. Thomas Rd, Phoenix, AZ, 85013, USA.
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19
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Robillard JM, Lai JA, Wu JM, Feng TL, Hayden S. Patient perspectives of the experience of a computerized cognitive assessment in a clinical setting. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2018; 4:297-303. [PMID: 30090850 PMCID: PMC6077833 DOI: 10.1016/j.trci.2018.06.003] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
INTRODUCTION Computerized assessments are becoming widely accepted in the clinical setting and as a potential outcome measure in clinical trials. To gain patient perspectives of this experience, the aim of the present study was to investigate patient attitudes and perceptions of the Cognigram [Cogstate], a computerized cognitive assessment. METHODS Semi-structured interviews were conducted with 19 older adults undergoing a computerized cognitive assessment at the University of British Columbia Hospital Clinic for Alzheimer Disease and Related Disorders. Thematic analysis was applied to identify key themes and relationships within the data. RESULTS The analysis resulted in three categories: attitudes toward computers in healthcare, the cognitive assessment process, and evaluation of the computerized assessment experience. The results show shared views on the need for balance between human and computer intervention, as well as room for improvement in test design and utility. DISCUSSION Careful design and user-testing should be made a priority in the development of computerized assessment interfaces, as well as reevaluating the cognitive assessment process to minimize patient anxiety and discomfort. Future research should move toward continuous data capture within clinical trials and ensuring instruments of high reliability to reduce variance.
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Affiliation(s)
- Julie M. Robillard
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
- BC Women's and Children's Hospital, Vancouver, BC, Canada
| | - Jen-Ai Lai
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Julia M. Wu
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Tanya L. Feng
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
| | - Sherri Hayden
- Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada
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20
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Harrison JE. Cognition comes of age: comments on the new FDA draft guidance for early Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2018; 10:61. [PMID: 29958538 PMCID: PMC6026341 DOI: 10.1186/s13195-018-0386-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Background The FDA have recently published draft guidance for the development of treatments for early Alzheimer’s disease. Key features of this guidance are the advocacy of sensitive cognitive measures and a taxonomy of disease severity. Whilst desirable patterns of cognitive-functional improvement are included, specific measures, and the magnitude of required effects, are not described. Main section We describe key elements of the guidance content, especially with regard targeting key cognitive domains and the means by which they might be efficiently indexed in the disease stages included in the guidance. We discuss also the opportunities to assess cognitive performance in ‘Stage 2’ and ‘Stage 3’ patients, as well as the possibilities for effectively assessing function in the latter category. In this section we review candidate cognitive assessments that we judge are capable of delivering on the guidance specification for sensitive neuropsychological measures. This includes detailed consideration of the ADCS-PACC and Catch-Cog initiatives. With respect to the magnitude of effects, we propose that standardised effect sizes of 0.3 represent a reasonable level of efficacy based on the observation that already marketed drugs on average deliver this level of improvement. Conclusions We propose the use of cognitive measures in stage 2 patients to index the cognitive skills known to be compromised early in the Alzheimer’s disease process. We recommend extending the traditional interest in episodic memory to include sensitive, reliable and valid measures of attention, working memory and aspects of executive function. We propose a focus on these additional cognitive abilities based on evidence that performance on tests of these domains is moderately well related to functional skills.
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Affiliation(s)
- John E Harrison
- Metis Cognition Ltd., Kilmington Common, Wiltshire, BA12 6QY, UK. .,Alzheimer Center, Amsterdam, The Netherlands. .,IoPPN, King's College London, London, UK.
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21
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Weintraub S, Carrillo MC, Farias ST, Goldberg TE, Hendrix JA, Jaeger J, Knopman DS, Langbaum JB, Park DC, Ropacki MT, Sikkes SAM, Welsh-Bohmer KA, Bain LJ, Brashear R, Budur K, Graf A, Martenyi F, Storck MS, Randolph C. Measuring cognition and function in the preclinical stage of Alzheimer's disease. ALZHEIMERS & DEMENTIA-TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS 2018; 4:64-75. [PMID: 29955653 PMCID: PMC6021264 DOI: 10.1016/j.trci.2018.01.003] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The Alzheimer's Association's Research Roundtable met in November 2016 to explore how best to measure changes in cognition and function in the preclinical stage of Alzheimer's disease. This review will cover the tools and instruments currently available to identify populations for prevention trials, and measure subtle disease progression in the earliest stages of Alzheimer's disease, and will include discussions of suitable cognitive, behavioral, functional, composite, and biological endpoints for prevention trials. Current prevention trials are reviewed including TOMMOROW, Alzheimer's Prevention Initiative Autosomal Dominant Alzheimer's Disease Trial, the Alzheimer's Prevention Initiative Generation Study, and the Anti-Amyloid Treatment in Asymptomatic Alzheimer's to compare current approaches and tools that are being developed.
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Affiliation(s)
- Sandra Weintraub
- Cognitive Neurology and Alzheimer's Disease Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.,Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | | | | | | | - Judith Jaeger
- Cognition Metrics, LLC, Wilmington, DE, USA.,Albert Einstein College of Medicine, Bronx, NY, USA
| | | | | | | | | | - Sietske A M Sikkes
- Alzheimer Center, VU University Medical Center, Amsterdam, Netherlands.,Amsterdam Neuroscience, Amsterdam, Netherlands
| | | | - Lisa J Bain
- Independent Science Writer, Elverson, PA, USA
| | - Robert Brashear
- Janssen Research and Development, Titusville, New Jersey, USA
| | | | - Ana Graf
- Novartis Pharma AG, Basel, Switzerland
| | | | | | - Christopher Randolph
- MedAvante-Prophase, Hamilton, NJ, USA.,Department of Neurology, Loyola University Medical Center, Maywood, IL, USA
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22
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Jutten RJ, Harrison J, Lee Meeuw Kjoe PR, Opmeer EM, Schoonenboom NSM, de Jong FJ, Ritchie CW, Scheltens P, Sikkes SAM. A novel cognitive-functional composite measure to detect changes in early Alzheimer's disease: Test-retest reliability and feasibility. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2017; 10:153-160. [PMID: 29780863 PMCID: PMC5956799 DOI: 10.1016/j.dadm.2017.12.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Introduction To improve the detection of changes in Alzheimer's disease (AD), we designed the cognitive-functional composite (CFC). As a first validation step, we investigated its test–retest reliability and feasibility of use. Methods We performed a test–retest study with 2–3 weeks between assessments, including patients with mild cognitive impairment (MCI) or mild AD dementia and cognitively healthy participants. We calculated intraclass correlation coefficients (ICCs) type absolute agreement for all CFC measures and compared baseline and retest scores using paired-samples t-tests. We evaluated feasibility by interviewing participants. Results Forty-three patients (40% female, mean age = 69.9) and 30 controls (50% female, mean age = 65) were included. Subtest intraclass correlation coefficients ranged from .70 to .96. We found negligible improvements after retesting on only two subtests. Overall, patients perceived the administration of the CFC as feasible. Discussion The CFC is a stable and feasible measure in MCI and mild AD dementia, and thereby meets important quality metrics for clinically meaningful outcome measures. We investigated stability and feasibility of the cognitive-functional composite (CFC). We demonstrated good test–retest reliability for all CFC subtests. We only found negligible practice effects on two CFC subtests. Overall, patients experienced the administration of the CFC as feasible.
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Affiliation(s)
- Roos J Jutten
- Alzheimer Center, Department of Neurology, VU University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - John Harrison
- Alzheimer Center, Department of Neurology, VU University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands.,Metis Cognition Ltd, Park House, Kilmington Common, Wiltshire, United Kingdom.,Institute of Psychiatry, Psychology & Neuroscience, King's College, London, United Kingdom
| | - Philippe R Lee Meeuw Kjoe
- Alzheimer Center, Department of Neurology, VU University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Esther M Opmeer
- Department of Neurosciences, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | | | - Frank Jan de Jong
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Craig W Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, United Kingdom
| | - Philip Scheltens
- Alzheimer Center, Department of Neurology, VU University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Sietske A M Sikkes
- Alzheimer Center, Department of Neurology, VU University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands.,Department of Epidemiology & Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
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