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Wang L, Nykänen NP, Western D, Gorijala P, Timsina J, Li F, Wang Z, Ali M, Yang C, Liu M, Brock W, Marquié M, Boada M, Alvarez I, Aguilar M, Pastor P, Ruiz A, Puerta R, Orellana A, Rutledge J, Oh H, Greicius MD, Le Guen Y, Perrin RJ, Wyss-Coray T, Jefferson A, Hohman TJ, Graff-Radford N, Mori H, Goate A, Levin J, Sung YJ, Cruchaga C. Proteo-genomics of soluble TREM2 in cerebrospinal fluid provides novel insights and identifies novel modulators for Alzheimer's disease. Mol Neurodegener 2024; 19:1. [PMID: 38172904 PMCID: PMC10763080 DOI: 10.1186/s13024-023-00687-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 11/28/2023] [Indexed: 01/05/2024] Open
Abstract
Triggering receptor expressed on myeloid cells 2 (TREM2) plays a critical role in microglial activation, survival, and apoptosis, as well as in Alzheimer's disease (AD) pathogenesis. We previously reported the MS4A locus as a key modulator for soluble TREM2 (sTREM2) in cerebrospinal fluid (CSF). To identify additional novel genetic modifiers of sTREM2, we performed the largest genome-wide association study (GWAS) and identified four loci for CSF sTREM2 in 3,350 individuals of European ancestry. Through multi-ethnic fine mapping, we identified two independent missense variants (p.M178V in MS4A4A and p.A112T in MS4A6A) that drive the association in MS4A locus and showed an epistatic effect for sTREM2 levels and AD risk. The novel TREM2 locus on chr 6 contains two rare missense variants (rs75932628 p.R47H, P=7.16×10-19; rs142232675 p.D87N, P=2.71×10-10) associated with sTREM2 and AD risk. The third novel locus in the TGFBR2 and RBMS3 gene region (rs73823326, P=3.86×10-9) included a regulatory variant with a microglia-specific chromatin loop for the promoter of TGFBR2. Using cell-based assays we demonstrate that overexpression and knock-down of TGFBR2, but not RBMS3, leads to significant changes of sTREM2. The last novel locus is located on the APOE region (rs11666329, P=2.52×10-8), but we demonstrated that this signal was independent of APOE genotype. This signal colocalized with cis-eQTL of NECTIN2 in the brain cortex and cis-pQTL of NECTIN2 in CSF. Overexpression of NECTIN2 led to an increase of sTREM2 supporting the genetic findings. To our knowledge, this is the largest study to date aimed at identifying genetic modifiers of CSF sTREM2. This study provided novel insights into the MS4A and TREM2 loci, two well-known AD risk genes, and identified TGFBR2 and NECTIN2 as additional modulators involved in TREM2 biology.
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Affiliation(s)
- Lihua Wang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Niko-Petteri Nykänen
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Daniel Western
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Priyanka Gorijala
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Fuhai Li
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA
| | - Zhaohua Wang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Muhammad Ali
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Chengran Yang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Menghan Liu
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - William Brock
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Marta Marquié
- Networking Research Center on Neurodegenerative Disease (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
- Research Center and Memory Clinic, ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Mercè Boada
- Networking Research Center on Neurodegenerative Disease (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
- Research Center and Memory Clinic, ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Ignacio Alvarez
- Memory Disorders Unit, Department of Neurology, University Hospital Mutua Terrassa, Terrassa, Spain
| | - Miquel Aguilar
- Memory Disorders Unit, Department of Neurology, University Hospital Mutua Terrassa, Terrassa, Spain
| | - Pau Pastor
- Unit of Neurodegenerative diseases, Department of Neurology, University Hospital Germans Trias i Pujol and The Germans Trias i Pujol Research Institute (IGTP) Badalona, Barcelona, Spain
| | - Agustín Ruiz
- Networking Research Center on Neurodegenerative Disease (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
- Research Center and Memory Clinic, ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Raquel Puerta
- Networking Research Center on Neurodegenerative Disease (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
- Research Center and Memory Clinic, ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Adelina Orellana
- Networking Research Center on Neurodegenerative Disease (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
- Research Center and Memory Clinic, ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Jarod Rutledge
- Wu-Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Hamilton Oh
- Wu-Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | | | - Yann Le Guen
- Wu-Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Richard J Perrin
- Department of Pathology & Immunology, Washington University School of Medicine, St. Louis, MO, USA
| | - Tony Wyss-Coray
- Wu-Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Angela Jefferson
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Timothy J Hohman
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | - Alison Goate
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Johannes Levin
- Department of Neurology, University Hospital of Munich, Ludwig-Maximilians-Universität (LMU) Munich, Munich, Germany
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Division of Biostatistics, Washington University School of Medicine, BJC Institute of Health, 425 S. Euclid Ave, Box 8134, St. Louis, MO, 63110, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA.
- Hope Center for Neurologic Diseases, Washington University, St. Louis, MO, USA.
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Alegret M, García-Gutiérrez F, Muñoz N, Espinosa A, Ortega G, Lleonart N, Rodríguez I, Rosende-Roca M, Pytel V, Cantero-Fortiz Y, Rentz DM, Marquié M, Valero S, Ruiz A, Butler C, Boada M. FACEmemory®, an Innovative Online Platform for Episodic Memory Pre-Screening: Findings from the First 3,000 Participants. J Alzheimers Dis 2024; 97:1173-1187. [PMID: 38217602 DOI: 10.3233/jad-230983] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2024]
Abstract
BACKGROUND The FACEmemory® online platform comprises a complex memory test and sociodemographic, medical, and family questions. This is the first study of a completely self-administered memory test with voice recognition, pre-tested in a memory clinic, sensitive to Alzheimer's disease, using information and communication technologies, and offered freely worldwide. OBJECTIVE To investigate the demographic and clinical variables associated with the total FACEmemory score, and to identify distinct patterns of memory performance on FACEmemory. METHODS Data from the first 3,000 subjects who completed the FACEmemory test were analyzed. Descriptive analyses were applied to demographic, FACEmemory, and medical and family variables; t-test and chi-square analyses were used to compare participants with preserved versus impaired performance on FACEmemory (cut-off = 32); multiple linear regression was used to identify variables that modulate FACEmemory performance; and machine learning techniques were applied to identify different memory patterns. RESULTS Participants had a mean age of 50.57 years and 13.65 years of schooling; 64.07% were women, and 82.10% reported memory complaints with worries. The group with impaired FACEmemory performance (20.40%) was older, had less schooling, and had a higher prevalence of hypertension, diabetes, dyslipidemia, and family history of neurodegenerative disease than the group with preserved performance. Age, schooling, sex, country, and completion of the medical and family history questionnaire were associated with the FACEmemory score. Finally, machine learning techniques identified four patterns of FACEmemory performance: normal, dysexecutive, storage, and completely impaired. CONCLUSIONS FACEmemory is a promising tool for assessing memory in people with subjective memory complaints and for raising awareness about cognitive decline in the community.
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Affiliation(s)
- Montserrat Alegret
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | | | - Nathalia Muñoz
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Ana Espinosa
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Gemma Ortega
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Núria Lleonart
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Isabel Rodríguez
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Maitee Rosende-Roca
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Vanesa Pytel
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Yahveth Cantero-Fortiz
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Dorene M Rentz
- Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Marta Marquié
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Sergi Valero
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Agustín Ruiz
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Christopher Butler
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
- Department of Brain Sciences, Imperial College London, London, UK
| | - Mercè Boada
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
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Lü W, Zhang M, Yu W, Kuang W, Chen L, Zhang W, Yu J, Lü Y. Differentiating Alzheimer's disease from mild cognitive impairment: a quick screening tool based on machine learning. BMJ Open 2023; 13:e073011. [PMID: 38070931 PMCID: PMC10729043 DOI: 10.1136/bmjopen-2023-073011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 11/20/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Alzheimer's disease (AD) is a neurodegenerative disorder characterised by cognitive decline, behavioural and psychological symptoms of dementia (BPSD) and impairment of activities of daily living (ADL). Early differentiation of AD from mild cognitive impairment (MCI) is necessary. METHODS A total of 458 patients newly diagnosed with AD and MCI were included. Eleven batteries were used to evaluate ADL, BPSD and cognitive function (ABC). Machine learning approaches including XGboost, classification and regression tree, Bayes, support vector machines and logical regression were used to build and verify the new tool. RESULTS The Alzheimer's Disease Assessment Scale (ADAS-cog) word recognition task showed the best importance in judging AD and MCI, followed by correct numbers of auditory verbal learning test delay recall and ADAS-cog orientation. We also provided a selected ABC-Scale that covered ADL, BPSD and cognitive function with an estimated completion time of 18 min. The sensitivity was improved in the four models. CONCLUSION The quick screen ABC-Scale covers three dimensions of ADL, BPSD and cognitive function with good efficiency in differentiating AD from MCI.
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Affiliation(s)
- Wenqi Lü
- Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Department of Psychiatry, West China Hospital, Sichuan University, Chengdu, China
| | - Meiwei Zhang
- College of Electrical Engineering, Chongqing University, Chongqing, China
| | - Weihua Yu
- Institutes of Neuroscience, Chongqing Medical University, Chongqing, China
| | - Weihong Kuang
- Department of Psychiatry, West China Hospital, Sichuan University, Chengdu, China
| | - Lihua Chen
- Institutes of Neuroscience, Chongqing Medical University, Chongqing, China
| | - Wenbo Zhang
- Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Juan Yu
- College of Electrical Engineering, Chongqing University, Chongqing, China
| | - Yang Lü
- Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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Giannopoulou P, Vrahatis AG, Papalaskari MA, Vlamos P. The RODI mHealth app Insight: Machine-Learning-Driven Identification of Digital Indicators for Neurodegenerative Disorder Detection. Healthcare (Basel) 2023; 11:2985. [PMID: 37998477 PMCID: PMC10671821 DOI: 10.3390/healthcare11222985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 11/15/2023] [Accepted: 11/16/2023] [Indexed: 11/25/2023] Open
Abstract
Neurocognitive Disorders (NCDs) pose a significant global health concern, and early detection is crucial for optimizing therapeutic outcomes. In parallel, mobile health apps (mHealth apps) have emerged as a promising avenue for assisting individuals with cognitive deficits. Under this perspective, we pioneered the development of the RODI mHealth app, a unique method for detecting aligned with the criteria for NCDs using a series of brief tasks. Utilizing the RODI app, we conducted a study from July to October 2022 involving 182 individuals with NCDs and healthy participants. The study aimed to assess performance differences between healthy older adults and NCD patients, identify significant performance disparities during the initial administration of the RODI app, and determine critical features for outcome prediction. Subsequently, the results underwent machine learning processes to unveil underlying patterns associated with NCDs. We prioritize the tasks within RODI based on their alignment with the criteria for NCDs, thus acting as key digital indicators for the disorder. We achieve this by employing an ensemble strategy that leverages the feature importance mechanism from three contemporary classification algorithms. Our analysis revealed that tasks related to visual working memory were the most significant in distinguishing between healthy individuals and those with an NCD. On the other hand, processes involving mental calculations, executive working memory, and recall were less influential in the detection process. Our study serves as a blueprint for future mHealth apps, offering a guide for enhancing the detection of digital indicators for disorders and related conditions.
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Affiliation(s)
- Panagiota Giannopoulou
- Bioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, 49100 Corfu, Greece; (P.G.); (A.G.V.)
| | - Aristidis G. Vrahatis
- Bioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, 49100 Corfu, Greece; (P.G.); (A.G.V.)
| | | | - Panagiotis Vlamos
- Bioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, 49100 Corfu, Greece; (P.G.); (A.G.V.)
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Cano A, Esteban-de-Antonio E, Bernuz M, Puerta R, García-González P, de Rojas I, Olivé C, Pérez-Cordón A, Montrreal L, Núñez-Llaves R, Sotolongo-Grau Ó, Alarcón-Martín E, Valero S, Alegret M, Martín E, Martino-Adami PV, Ettcheto M, Camins A, Vivas A, Gomez-Chiari M, Tejero MÁ, Orellana A, Tárraga L, Marquié M, Ramírez A, Martí M, Pividori MI, Boada M, Ruíz A. Plasma extracellular vesicles reveal early molecular differences in amyloid positive patients with early-onset mild cognitive impairment. J Nanobiotechnology 2023; 21:54. [PMID: 36788617 PMCID: PMC9930227 DOI: 10.1186/s12951-023-01793-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 01/24/2023] [Indexed: 02/16/2023] Open
Abstract
In the clinical course of Alzheimer's disease (AD) development, the dementia phase is commonly preceded by a prodromal AD phase, which is mainly characterized by reaching the highest levels of Aβ and p-tau-mediated neuronal injury and a mild cognitive impairment (MCI) clinical status. Because of that, most AD cases are diagnosed when neuronal damage is already established and irreversible. Therefore, a differential diagnosis of MCI causes in these prodromal stages is one of the greatest challenges for clinicians. Blood biomarkers are emerging as desirable tools for pre-screening purposes, but the current results are still being analyzed and much more data is needed to be implemented in clinical practice. Because of that, plasma extracellular vesicles (pEVs) are gaining popularity as a new source of biomarkers for the early stages of AD development. To identify an exosome proteomics signature linked to prodromal AD, we performed a cross-sectional study in a cohort of early-onset MCI (EOMCI) patients in which 184 biomarkers were measured in pEVs, cerebrospinal fluid (CSF), and plasma samples using multiplex PEA technology of Olink© proteomics. The obtained results showed that proteins measured in pEVs from EOMCI patients with established amyloidosis correlated with CSF p-tau181 levels, brain ventricle volume changes, brain hyperintensities, and MMSE scores. In addition, the correlations of pEVs proteins with different parameters distinguished between EOMCI Aβ( +) and Aβ(-) patients, whereas the CSF or plasma proteome did not. In conclusion, our findings suggest that pEVs may be able to provide information regarding the initial amyloidotic changes of AD. Circulating exosomes may acquire a pathological protein signature of AD before raw plasma, becoming potential biomarkers for identifying subjects at the earliest stages of AD development.
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Affiliation(s)
- Amanda Cano
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain.
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Madrid, Spain.
| | - Ester Esteban-de-Antonio
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Mireia Bernuz
- Grup de Sensors I Biosensors, Departament de Química, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain
| | - Raquel Puerta
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Pablo García-González
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Itziar de Rojas
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Claudia Olivé
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Alba Pérez-Cordón
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Laura Montrreal
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Raúl Núñez-Llaves
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Óscar Sotolongo-Grau
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Emilio Alarcón-Martín
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Sergi Valero
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Montserrat Alegret
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Elvira Martín
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
| | - Pamela V Martino-Adami
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937, Cologne, Germany
| | - Miren Ettcheto
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Department of Pharmacology, Toxicology and Therapeutic Chemistry, Faculty of Pharmacy and Food Sciences, University of Barcelona, 08028, Barcelona, Spain
- Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Antonio Camins
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Department of Pharmacology, Toxicology and Therapeutic Chemistry, Faculty of Pharmacy and Food Sciences, University of Barcelona, 08028, Barcelona, Spain
- Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Assumpta Vivas
- Departament de Diagnòstic Per La Imatge, Clínica Corachan, Barcelona, Spain
| | - Marta Gomez-Chiari
- Departament de Diagnòstic Per La Imatge, Clínica Corachan, Barcelona, Spain
| | | | - Adelina Orellana
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Lluís Tárraga
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Marta Marquié
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Alfredo Ramírez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937, Cologne, Germany
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, 53127, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), 53127, Bonn, Germany
- Department of Psychiatry and Glenn, Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, TX, 78229, USA
- Cluster of Excellence Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, 50931, Cologne, Germany
| | - Mercè Martí
- Grup de Sensors I Biosensors, Departament de Química, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain
| | - María Isabel Pividori
- Grup de Sensors I Biosensors, Departament de Química, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain
- Biosensing and Bioanalysis Group, Institut de Biotecnologia I de Biomedicina (IBB-UAB), Mòdul B Parc de Recerca UAB, Campus Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain
| | - Mercè Boada
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Agustín Ruíz
- Ace Alzheimer Center Barcelona - International University of Catalunya (UIC), C/Marquès de Sentmenat, 57, 08029, Barcelona, Spain.
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Madrid, Spain.
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6
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Giaquinto F, Battista P, Angelelli P. Touchscreen Cognitive Tools for Mild Cognitive Impairment and Dementia Used in Primary Care Across Diverse Cultural and Literacy Populations: A Systematic Review. J Alzheimers Dis 2022; 90:1359-1380. [PMID: 36245376 DOI: 10.3233/jad-220547] [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: 12/14/2022]
Abstract
BACKGROUND Touchscreen cognitive tools opened new promising opportunities for the early detection of cognitive impairment; however, most research studies are conducted in English-speaking populations and high-income countries, with a gap in knowledge about their use in populations with cultural, linguistic, and educational diversity. OBJECTIVE To review the touchscreen tools used in primary care settings for the cognitive assessment of mild cognitive impairment (MCI) and dementia, with a focus on populations of different cultures, languages, and literacy. METHODS This systematic review was conducted following the PRISMA guidelines. Studies were identified by searching across MEDLINE, EMBASE, EBSCO, OVID, SCOPUS, SCIELO, LILACS, and by cross-referencing. All studies that provide a first-level cognitive assessment for MCI and dementia with any touchscreen tools suitable to be used in the context of primary care were included. RESULTS Forty-two studies reporting on 30 tools and batteries were identified. Substantial differences among the tools emerged, in terms of theoretical framework, clinical validity, and features related to the application in clinical practice. A small proportion of the tools are available in multiple languages. Only 7 out of the 30 tools have a multiple languages validation. Only two tools are validated in low-educated samples, e.g., IDEA and mSTS-MCI. CONCLUSION General practitioners can benefit from touchscreen cognitive tools. However, easy requirements of the device, low dependence on the examiner, fast administration, and adaptation to different cultures and languages are some of the main features that we need to take into consideration when implementing touchscreen cognitive tools in the culture and language of underrepresented populations.
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Affiliation(s)
- Francesco Giaquinto
- Department of History, Laboratory of Applied Psychology and Intervention, Society and Human Studies, University of Salento, Lecce, Italy
| | - Petronilla Battista
- Clinical and Scientific Institutes Maugeri Pavia, Scientific Institute of Bari, IRCCS, Italy
| | - Paola Angelelli
- Department of History, Laboratory of Applied Psychology and Intervention, Society and Human Studies, University of Salento, Lecce, Italy
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