Literature DB >> 32302946

Early diagnosis of Alzheimer's disease: the role of biomarkers including advanced EEG signal analysis. Report from the IFCN-sponsored panel of experts.

P M Rossini1, R Di Iorio2, F Vecchio3, M Anfossi4, C Babiloni5, M Bozzali6, A C Bruni4, S F Cappa7, J Escudero8, F J Fraga9, P Giannakopoulos10, B Guntekin11, G Logroscino12, C Marra13, F Miraglia3, F Panza12, F Tecchio14, A Pascual-Leone15, B Dubois16.   

Abstract

Alzheimer's disease (AD) is the most common neurodegenerative disease among the elderly with a progressive decline in cognitive function significantly affecting quality of life. Both the prevalence and emotional and financial burdens of AD on patients, their families, and society are predicted to grow significantly in the near future, due to a prolongation of the lifespan. Several lines of evidence suggest that modifications of risk-enhancing life styles and initiation of pharmacological and non-pharmacological treatments in the early stage of disease, although not able to modify its course, helps to maintain personal autonomy in daily activities and significantly reduces the total costs of disease management. Moreover, many clinical trials with potentially disease-modifying drugs are devoted to prodromal stages of AD. Thus, the identification of markers of conversion from prodromal form to clinically AD may be crucial for developing strategies of early interventions. The current available markers, including volumetric magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebral spinal fluid (CSF) analysis are expensive, poorly available in community health facilities, and relatively invasive. Taking into account its low cost, widespread availability and non-invasiveness, electroencephalography (EEG) would represent a candidate for tracking the prodromal phases of cognitive decline in routine clinical settings eventually in combination with other markers. In this scenario, the present paper provides an overview of epidemiology, genetic risk factors, neuropsychological, fluid and neuroimaging biomarkers in AD and describes the potential role of EEG in AD investigation, trying in particular to point out whether advanced analysis of EEG rhythms exploring brain function has sufficient specificity/sensitivity/accuracy for the early diagnosis of AD.
Copyright © 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  AD biomarkers; Alzheimer’s disease; Dementia; EEG analysis; EEG rhythms; Early diagnosis; Event-related responses; Mild cognitive impairment

Year:  2020        PMID: 32302946     DOI: 10.1016/j.clinph.2020.03.003

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  28 in total

1.  Neuronavigated Magnetic Stimulation combined with cognitive training for Alzheimer's patients: an EEG graph study.

Authors:  Fabrizio Vecchio; Davide Quaranta; Francesca Miraglia; Chiara Pappalettera; Riccardo Di Iorio; Federica L'Abbate; Maria Cotelli; Camillo Marra; Paolo Maria Rossini
Journal:  Geroscience       Date:  2021-12-31       Impact factor: 7.713

2.  DWI-based MR thermometry: could it discriminate Alzheimer's disease from mild cognitive impairment and healthy subjects?

Authors:  Berrak Barutcu Asfuroğlu; Tuğberk Andaç Topkan; Nesrin Erdoğan Kaydu; Koji Sakai; Ali Yusuf Öner; Yahya Karaman; Kei Yamada; E Turgut Tali
Journal:  Neuroradiology       Date:  2022-05-10       Impact factor: 2.995

3.  Exploring the Alterations in the Distribution of Neural Network Weights in Dementia Due to Alzheimer's Disease.

Authors:  Marcos Revilla-Vallejo; Jesús Poza; Javier Gomez-Pilar; Roberto Hornero; Miguel Ángel Tola-Arribas; Mónica Cano; Carlos Gómez
Journal:  Entropy (Basel)       Date:  2021-04-22       Impact factor: 2.524

Review 4.  Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: Recommendations of an expert panel.

Authors:  Claudio Babiloni; Xianghong Arakaki; Hamed Azami; Karim Bennys; Katarzyna Blinowska; Laura Bonanni; Ana Bujan; Maria C Carrillo; Andrzej Cichocki; Jaisalmer de Frutos-Lucas; Claudio Del Percio; Bruno Dubois; Rebecca Edelmayer; Gary Egan; Stephane Epelbaum; Javier Escudero; Alan Evans; Francesca Farina; Keith Fargo; Alberto Fernández; Raffaele Ferri; Giovanni Frisoni; Harald Hampel; Michael G Harrington; Vesna Jelic; Jaeseung Jeong; Yang Jiang; Maciej Kaminski; Voyko Kavcic; Kerry Kilborn; Sanjeev Kumar; Alice Lam; Lew Lim; Roberta Lizio; David Lopez; Susanna Lopez; Brendan Lucey; Fernando Maestú; William J McGeown; Ian McKeith; Davide Vito Moretti; Flavio Nobili; Giuseppe Noce; John Olichney; Marco Onofrj; Ricardo Osorio; Mario Parra-Rodriguez; Tarek Rajji; Petra Ritter; Andrea Soricelli; Fabrizio Stocchi; Ioannis Tarnanas; John Paul Taylor; Stefan Teipel; Federico Tucci; Mitchell Valdes-Sosa; Pedro Valdes-Sosa; Marco Weiergräber; Gorsev Yener; Bahar Guntekin
Journal:  Alzheimers Dement       Date:  2021-04-15       Impact factor: 16.655

Review 5.  Therapy for Alzheimer's disease: Missing targets and functional markers?

Authors:  Milan Stoiljkovic; Tamas L Horvath; Mihály Hajós
Journal:  Ageing Res Rev       Date:  2021-03-09       Impact factor: 11.788

6.  Resting state EEG biomarkers of cognitive decline associated with Alzheimer's disease and mild cognitive impairment.

Authors:  Amir H Meghdadi; Marija Stevanović Karić; Marissa McConnell; Greg Rupp; Christian Richard; Joanne Hamilton; David Salat; Chris Berka
Journal:  PLoS One       Date:  2021-02-05       Impact factor: 3.240

7.  Selecting the most important self-assessed features for predicting conversion to mild cognitive impairment with random forest and permutation-based methods.

Authors:  Jaime Gómez-Ramírez; Marina Ávila-Villanueva; Miguel Ángel Fernández-Blázquez
Journal:  Sci Rep       Date:  2020-11-26       Impact factor: 4.379

8.  Reliability of P3 Event-Related Potential During Working Memory Across the Spectrum of Cognitive Aging.

Authors:  Hannes Devos; Jeffrey M Burns; Ke Liao; Pedram Ahmadnezhad; Jonathan D Mahnken; William M Brooks; Kathleen Gustafson
Journal:  Front Aging Neurosci       Date:  2020-10-19       Impact factor: 5.750

Review 9.  microRNA-Based Biomarkers in Alzheimer's Disease (AD).

Authors:  Yuhai Zhao; Vivian Jaber; Peter N Alexandrov; Andrea Vergallo; Simone Lista; Harald Hampel; Walter J Lukiw
Journal:  Front Neurosci       Date:  2020-10-30       Impact factor: 4.677

10.  Psycho-Electrophysiological Benefits of Forest Therapies Focused on Qigong and Walking with Elderly Individuals.

Authors:  Jiyune Yi; Seul Gee Kim; Taegyu Khil; Minja Shin; Jin-Hee You; Sookja Jeon; Gue Hong Park; Ah Young Jeong; Youngsuwn Lim; Kahye Kim; Jingun Kim; Byunghoon Kang; Jueun Lee; Jeong Hwan Park; Boncho Ku; Jungmi Choi; Wonseok Cha; Hwa-Jin Lee; Changseob Shin; Wonsop Shin; Jaeuk U Kim
Journal:  Int J Environ Res Public Health       Date:  2021-03-15       Impact factor: 3.390

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