1
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Wyman-Chick KA, Chaudhury P, Bayram E, Abdelnour C, Matar E, Chiu SY, Ferreira D, Hamilton CA, Donaghy PC, Rodriguez-Porcel F, Toledo JB, Habich A, Barrett MJ, Patel B, Jaramillo-Jimenez A, Scott GD, Kane JPM. Differentiating Prodromal Dementia with Lewy Bodies from Prodromal Alzheimer's Disease: A Pragmatic Review for Clinicians. Neurol Ther 2024; 13:885-906. [PMID: 38720013 PMCID: PMC11136939 DOI: 10.1007/s40120-024-00620-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 04/05/2024] [Indexed: 05/12/2024] Open
Abstract
This pragmatic review synthesises the current understanding of prodromal dementia with Lewy bodies (pDLB) and prodromal Alzheimer's disease (pAD), including clinical presentations, neuropsychological profiles, neuropsychiatric symptoms, biomarkers, and indications for disease management. The core clinical features of dementia with Lewy bodies (DLB)-parkinsonism, complex visual hallucinations, cognitive fluctuations, and REM sleep behaviour disorder are common prodromal symptoms. Supportive clinical features of pDLB include severe neuroleptic sensitivity, as well as autonomic and neuropsychiatric symptoms. The neuropsychological profile in mild cognitive impairment attributable to Lewy body pathology (MCI-LB) tends to include impairment in visuospatial skills and executive functioning, distinguishing it from MCI due to AD, which typically presents with impairment in memory. pDLB may present with cognitive impairment, psychiatric symptoms, and/or recurrent episodes of delirium, indicating that it is not necessarily synonymous with MCI-LB. Imaging, fluid and other biomarkers may play a crucial role in differentiating pDLB from pAD. The current MCI-LB criteria recognise low dopamine transporter uptake using positron emission tomography or single photon emission computed tomography (SPECT), loss of REM atonia on polysomnography, and sympathetic cardiac denervation using meta-iodobenzylguanidine SPECT as indicative biomarkers with slowing of dominant frequency on EEG among others as supportive biomarkers. This review also highlights the emergence of fluid and skin-based biomarkers. There is little research evidence for the treatment of pDLB, but pharmacological and non-pharmacological treatments for DLB may be discussed with patients. Non-pharmacological interventions such as diet, exercise, and cognitive stimulation may provide benefit, while evaluation and management of contributing factors like medications and sleep disturbances are vital. There is a need to expand research across diverse patient populations to address existing disparities in clinical trial participation. In conclusion, an early and accurate diagnosis of pDLB or pAD presents an opportunity for tailored interventions, improved healthcare outcomes, and enhanced quality of life for patients and care partners.
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Affiliation(s)
- Kathryn A Wyman-Chick
- Struthers Parkinson's Center and Center for Memory and Aging, Department of Neurology, HealthPartners/Park Nicollet, Bloomington, USA.
| | - Parichita Chaudhury
- Cleo Roberts Memory and Movement Center, Banner Sun Health Research Institute, Sun City, USA
| | - Ece Bayram
- Parkinson and Other Movement Disorders Center, University of California San Diego, San Diego, USA
| | - Carla Abdelnour
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Palo Alto, USA
| | - Elie Matar
- Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Shannon Y Chiu
- Department of Neurology, Mayo Clinic Arizona, Phoenix, USA
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institute, Solna, Sweden
- Department of Radiology, Mayo Clinic Rochester, Rochester, USA
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas, Spain
| | - Calum A Hamilton
- Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, UK
| | - Paul C Donaghy
- Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, UK
| | | | - Jon B Toledo
- Nantz National Alzheimer Center, Stanley Appel Department of Neurology, Houston Methodist Hospital, Houston, USA
| | - Annegret Habich
- Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institute, Solna, Sweden
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Matthew J Barrett
- Department of Neurology, Parkinson's and Movement Disorders Center, Virginia Commonwealth University, Richmond, USA
| | - Bhavana Patel
- Department of Neurology, College of Medicine, University of Florida, Gainesville, USA
- Norman Fixel Institute for Neurologic Diseases, University of Florida, Gainesville, USA
| | - Alberto Jaramillo-Jimenez
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
- School of Medicine, Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellín, Colombia
| | - Gregory D Scott
- Department of Pathology and Laboratory Services, VA Portland Medical Center, Portland, USA
| | - Joseph P M Kane
- Centre for Public Health, Queen's University Belfast, Belfast, UK
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2
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Watanabe Y, Miyazaki Y, Hata M, Fukuma R, Aoki Y, Kazui H, Araki T, Taomoto D, Satake Y, Suehiro T, Sato S, Kanemoto H, Yoshiyama K, Ishii R, Harada T, Kishima H, Ikeda M, Yanagisawa T. A deep learning model for the detection of various dementia and MCI pathologies based on resting-state electroencephalography data: A retrospective multicentre study. Neural Netw 2024; 171:242-250. [PMID: 38101292 DOI: 10.1016/j.neunet.2023.12.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Revised: 11/12/2023] [Accepted: 12/04/2023] [Indexed: 12/17/2023]
Abstract
Dementia and mild cognitive impairment (MCI) represent significant health challenges in an aging population. As the search for noninvasive, precise and accessible diagnostic methods continues, the efficacy of electroencephalography (EEG) combined with deep convolutional neural networks (DCNNs) in varied clinical settings remains unverified, particularly for pathologies underlying MCI such as Alzheimer's disease (AD), dementia with Lewy bodies (DLB) and idiopathic normal-pressure hydrocephalus (iNPH). Addressing this gap, our study evaluates the generalizability of a DCNN trained on EEG data from a single hospital (Hospital #1). For data from Hospital #1, the DCNN achieved a balanced accuracy (bACC) of 0.927 in classifying individuals as healthy (n = 69) or as having AD, DLB, or iNPH (n = 188). The model demonstrated robustness across institutions, maintaining bACCs of 0.805 for data from Hospital #2 (n = 73) and 0.920 at Hospital #3 (n = 139). Additionally, the model could differentiate AD, DLB, and iNPH cases with bACCs of 0.572 for data from Hospital #1 (n = 188), 0.619 for Hospital #2 (n = 70), and 0.508 for Hospital #3 (n = 139). Notably, it also identified MCI pathologies with a bACC of 0.715 for Hospital #1 (n = 83), despite being trained on overt dementia cases instead of MCI cases. These outcomes confirm the DCNN's adaptability and scalability, representing a significant stride toward its clinical application. Additionally, our findings suggest a potential for identifying shared EEG signatures between MCI and dementia, contributing to the field's understanding of their common pathophysiological mechanisms.
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Affiliation(s)
- Yusuke Watanabe
- Institute for Advanced Co-creation Studies, Osaka University, Osaka, Japan
| | - Yuki Miyazaki
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Masahiro Hata
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Ryohei Fukuma
- Institute for Advanced Co-creation Studies, Osaka University, Osaka, Japan; Department of Neurosurgery, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Yasunori Aoki
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan; Department of Psychiatry, Nippon Life Hospital, Osaka, Japan
| | - Hiroaki Kazui
- Department of Neuropsychiatry, Kochi Medical School, Kochi University, Kochi, Japan
| | - Toshihiko Araki
- Department of Medical Technology, Osaka University Hospital, Osaka, Japan
| | - Daiki Taomoto
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Yuto Satake
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Takashi Suehiro
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Shunsuke Sato
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Hideki Kanemoto
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Kenji Yoshiyama
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Ryouhei Ishii
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan; Department of Occupational Therapy, Graduate School of Rehabilitation Science, Osaka Metropolitan University, Habikino, Japan
| | - Tatsuya Harada
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan; RIKEN, Tokyo, Japan
| | - Haruhiko Kishima
- Department of Neurosurgery, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Manabu Ikeda
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Takufumi Yanagisawa
- Institute for Advanced Co-creation Studies, Osaka University, Osaka, Japan; Department of Neurosurgery, Osaka University Graduate School of Medicine, Osaka, Japan.
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3
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Bejia I, Labidi J, Warniez A, Bayot M, Bourriez JL, Derambure P, Lebouvier T, Pasquier F, Delval A, Betrouni N. Multi-approach comparative study of EEG patterns associated with the most common forms of dementia. Neurobiol Aging 2023; 130:30-39. [PMID: 37433259 DOI: 10.1016/j.neurobiolaging.2023.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 05/30/2023] [Accepted: 06/10/2023] [Indexed: 07/13/2023]
Abstract
Electroencephalography's (EEG) sensitivity in discriminating dementia syndromes remains unclear. This study aimed to investigate EEG markers in patients with major cognitive disorders. The studied population included 4 groups of patients: Alzheimer's disease with associated vascular lesions, Alzheimer's disease without vascular lesions (AD-V), Lewy body disease and vascular dementia (VaD); and completed by a control group composed by cognitively unimpaired patients. EEGs were analysed quantitatively using spectral analysis, functional connectivity and micro-states. By comparison to the controls, expected slowing and alterations of functional connectivity were detected in patients with dementia. Among these patients, an overall increase in power in the alpha band was observed in the VaD group, mainly when compared to the 2 AD groups, while the Alzheimer's disease without vascular lesions group exhibited increased power in the beta-2 band and higher functional connectivity in the same frequency band. Micro-state analyses revealed differences in temporal dynamics for the VaD group. A number of EEG modifications reported as markers of some syndromes were found, but others were not reproduced.
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Affiliation(s)
- Ines Bejia
- Univ. Lille, INSERM, U1172 - LilNCog - Lille Neuroscience & Cognition, F-59000 Lille, France
| | - Jordan Labidi
- CHU Lille, Clinical Neurophysiology Department, F-59000 Lille, France
| | - Aude Warniez
- Univ. Lille, INSERM, U1172 - LilNCog - Lille Neuroscience & Cognition, F-59000 Lille, France
| | - Madli Bayot
- Univ. Lille, INSERM, U1172 - LilNCog - Lille Neuroscience & Cognition, F-59000 Lille, France; CHU Lille, Clinical Neurophysiology Department, F-59000 Lille, France
| | | | - Philippe Derambure
- Univ. Lille, INSERM, U1172 - LilNCog - Lille Neuroscience & Cognition, F-59000 Lille, France; CHU Lille, Clinical Neurophysiology Department, F-59000 Lille, France
| | - Thibaut Lebouvier
- Univ. Lille, INSERM, U1172 - LilNCog - Lille Neuroscience & Cognition, F-59000 Lille, France; CHU Lille, Centre Mémoire de Ressources et de Recherche (CMRR), F-59000 Lille, France
| | - Florence Pasquier
- Univ. Lille, INSERM, U1172 - LilNCog - Lille Neuroscience & Cognition, F-59000 Lille, France; CHU Lille, Centre Mémoire de Ressources et de Recherche (CMRR), F-59000 Lille, France
| | - Arnaud Delval
- Univ. Lille, INSERM, U1172 - LilNCog - Lille Neuroscience & Cognition, F-59000 Lille, France; CHU Lille, Clinical Neurophysiology Department, F-59000 Lille, France
| | - Nacim Betrouni
- Univ. Lille, INSERM, U1172 - LilNCog - Lille Neuroscience & Cognition, F-59000 Lille, France.
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4
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De Cock A, Van Ranst A, Costers L, Keytsman E, D'Hooghe MB, D'Haeseleer M, Nagels G, Van Schependom J. Reduced alpha2 power is associated with slowed information processing speed in multiple sclerosis. Eur J Neurol 2023; 30:2793-2800. [PMID: 37326133 DOI: 10.1111/ene.15927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Revised: 06/08/2023] [Accepted: 06/12/2023] [Indexed: 06/17/2023]
Abstract
OBJECTIVE Cognitive impairment is common in multiple sclerosis (MS), significantly impacts daily functioning, is time-consuming to assess, and is prone to practice effects. We examined whether the alpha band power measured with magnetoencephalography (MEG) is associated with the different cognitive domains affected by MS. METHODS Sixty-eight MS patients and 47 healthy controls underwent MEG, T1- and FLAIR-weighted magnetic resonance imaging (MRI), and neuropsychological testing. Alpha power in the occipital cortex was quantified in the alpha1 (8-10 Hz) and alpha2 (10-12 Hz) bands. Next, we performed best subset regression to assess the added value of neurophysiological measures to commonly available MRI measures. RESULTS Alpha2 power significantly correlated with information processing speed (p < 0.001) and was always retained in all multilinear models, whereas thalamic volume was retained in 80% of all models. Alpha1 power was correlated with visual memory (p < 0.001) but only retained in 38% of all models. CONCLUSIONS Alpha2 (10-12 Hz) power in rest is associated with IPS, independent of standard MRI parameters. This study stresses that a multimodal assessment, including structural and functional biomarkers, is likely required to characterize cognitive impairment in MS. Resting-state neurophysiology is thus a promising tool to understand and follow up changes in IPS.
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Affiliation(s)
- Alexander De Cock
- Nationaal Multiple Sclerose Centrum, Melsbroek, Belgium
- Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Brussels, Belgium
- AIMS Lab, Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Brussels, Belgium
| | - Alexander Van Ranst
- Neurology Department, Universitair Ziekenhuis Brussel, Brussels, Belgium
- Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium
| | - Lars Costers
- AIMS Lab, Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Brussels, Belgium
| | - Eva Keytsman
- AIMS Lab, Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Brussels, Belgium
| | - Marie B D'Hooghe
- Nationaal Multiple Sclerose Centrum, Melsbroek, Belgium
- Neurology Department, Universitair Ziekenhuis Brussel, Brussels, Belgium
- Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium
| | - Miguel D'Haeseleer
- Nationaal Multiple Sclerose Centrum, Melsbroek, Belgium
- Neurology Department, Universitair Ziekenhuis Brussel, Brussels, Belgium
- Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium
| | - Guy Nagels
- Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Brussels, Belgium
- AIMS Lab, Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Brussels, Belgium
- Neurology Department, Universitair Ziekenhuis Brussel, Brussels, Belgium
- Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium
- St Edmund Hall, University of Oxford, Oxford, UK
| | - Jeroen Van Schependom
- AIMS Lab, Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Brussels, Belgium
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, Brussels, Belgium
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5
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Jaramillo-Jimenez A, Tovar-Rios DA, Ospina JA, Mantilla-Ramos YJ, Loaiza-López D, Henao Isaza V, Zapata Saldarriaga LM, Cadavid Castro V, Suarez-Revelo JX, Bocanegra Y, Lopera F, Pineda-Salazar DA, Tobón Quintero CA, Ochoa-Gomez JF, Borda MG, Aarsland D, Bonanni L, Brønnick K. Spectral features of resting-state EEG in Parkinson's Disease: A multicenter study using functional data analysis. Clin Neurophysiol 2023; 151:28-40. [PMID: 37146531 DOI: 10.1016/j.clinph.2023.03.363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 02/18/2023] [Accepted: 03/27/2023] [Indexed: 05/07/2023]
Abstract
OBJECTIVE This study aims 1) To analyse differences in resting-state electroencephalogram (rs-EEG) spectral features of Parkinson's Disease (PD) and healthy subjects (non-PD) using Functional Data Analysis (FDA) and 2) To explore, in four independent cohorts, the external validity and reproducibility of the findings using both epoch-to-epoch FDA and averaged-epochs approach. METHODS We included 169 subjects (85 non-PD; 84 PD) from four centres. Rs-EEG signals were preprocessed with a combination of automated pipelines. Sensor-level relative power spectral density (PSD), dominant frequency (DF), and DF variability (DFV) features were extracted. Differences in each feature were compared between PD and non-PD on averaged epochs and using FDA to model the epoch-to-epoch change of each feature. RESULTS For averaged epochs, significantly higher theta relative PSD in PD was found across all datasets. Also, higher pre-alpha relative PSD was observed in three of four datasets in PD patients. For FDA, similar findings were achieved in theta, but all datasets showed consistently significant posterior pre-alpha differences across multiple epochs. CONCLUSIONS Increased generalised theta, with posterior pre-alpha relative PSD, was the most reproducible finding in PD. SIGNIFICANCE Rs-EEG theta and pre-alpha findings are generalisable in PD. FDA constitutes a reliable and powerful tool to analyse epoch-to-epoch the rs-EEG.
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Affiliation(s)
- Alberto Jaramillo-Jimenez
- Centre for Age-Related Medicine (SESAM), Stavanger University Hospital. Stavanger, Norway; Faculty of Health Sciences, University of Stavanger. Stavanger, Norway; Grupo de Neurociencias de Antioquia, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Grupo Neuropsicología y Conducta, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Semillero de Investigación SINAPSIS, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Semillero de Investigación NeuroCo, Universidad de Antioquia, School of Medicine & School of Engenieering. Medellín, Colombia.
| | - Diego A Tovar-Rios
- Centre for Age-Related Medicine (SESAM), Stavanger University Hospital. Stavanger, Norway; Faculty of Health Sciences, University of Stavanger. Stavanger, Norway; Universidad del Valle, Grupo de Investigación en Estadística Aplicada - INFERIR, Faculty of Engineering, Santiago de Cali, Colombia; Universidad del Valle, Prevención y Control de la Enfermedad Crónica - PRECEC, Faculty of Health, Santiago de Cali, Colombia
| | - Johann Alexis Ospina
- Facultad de Ciencias Básicas, Universidad Autónoma de Occidente, Santiago de Cali, Colombia
| | - Yorguin-Jose Mantilla-Ramos
- Grupo Neuropsicología y Conducta, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Semillero de Investigación NeuroCo, Universidad de Antioquia, School of Medicine & School of Engenieering. Medellín, Colombia
| | - Daniel Loaiza-López
- Grupo Neuropsicología y Conducta, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Semillero de Investigación NeuroCo, Universidad de Antioquia, School of Medicine & School of Engenieering. Medellín, Colombia
| | - Verónica Henao Isaza
- Grupo Neuropsicología y Conducta, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Semillero de Investigación NeuroCo, Universidad de Antioquia, School of Medicine & School of Engenieering. Medellín, Colombia
| | - Luisa María Zapata Saldarriaga
- Grupo Neuropsicología y Conducta, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Semillero de Investigación NeuroCo, Universidad de Antioquia, School of Medicine & School of Engenieering. Medellín, Colombia
| | - Valeria Cadavid Castro
- Grupo Neuropsicología y Conducta, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Semillero de Investigación NeuroCo, Universidad de Antioquia, School of Medicine & School of Engenieering. Medellín, Colombia
| | - Jazmin Ximena Suarez-Revelo
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Grupo Neuropsicología y Conducta, Universidad de Antioquia, School of Medicine. Medellín, Colombia
| | - Yamile Bocanegra
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Grupo Neuropsicología y Conducta, Universidad de Antioquia, School of Medicine. Medellín, Colombia
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, School of Medicine. Medellín, Colombia
| | - David Antonio Pineda-Salazar
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Grupo Neuropsicología y Conducta, Universidad de Antioquia, School of Medicine. Medellín, Colombia
| | - Carlos Andrés Tobón Quintero
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Grupo Neuropsicología y Conducta, Universidad de Antioquia, School of Medicine. Medellín, Colombia; Área Investigación e Innovación, Hospital Alma Mater de Antioquia. Medellín, Colombia
| | - John Fredy Ochoa-Gomez
- Grupo Neuropsicología y Conducta, Universidad de Antioquia, School of Medicine. Medellín, Colombia
| | - Miguel Germán Borda
- Centre for Age-Related Medicine (SESAM), Stavanger University Hospital. Stavanger, Norway; Faculty of Health Sciences, University of Stavanger. Stavanger, Norway; Semillero de Neurociencias y Envejecimiento, Pontificia Universidad Javeriana, Ageing Institute, Medical School. Bogotá, Colombia
| | - Dag Aarsland
- Centre for Age-Related Medicine (SESAM), Stavanger University Hospital. Stavanger, Norway; Faculty of Health Sciences, University of Stavanger. Stavanger, Norway; Department of Old Age Psychiatry, Institute of Psychiatry, Psychology, and Neuroscience, King's College London. London, UK
| | - Laura Bonanni
- Department of Medicine and Aging Sciences, G. d'Annunzio University. Chieti, Italy
| | - Kolbjørn Brønnick
- Centre for Age-Related Medicine (SESAM), Stavanger University Hospital. Stavanger, Norway; Faculty of Health Sciences, University of Stavanger. Stavanger, Norway
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6
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Liu H, Huang Z, Deng B, Chang Z, Yang X, Guo X, Yuan F, Yang Q, Wang L, Zou H, Li M, Zhu Z, Jin K, Wang Q. QEEG Signatures are Associated with Nonmotor Dysfunctions in Parkinson's Disease and Atypical Parkinsonism: An Integrative Analysis. Aging Dis 2023; 14:204-218. [PMID: 36818554 PMCID: PMC9937709 DOI: 10.14336/ad.2022.0514] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Accepted: 05/14/2022] [Indexed: 11/18/2022] Open
Abstract
Parkinson's disease (PD) and atypical parkinsonism (AP), including progressive supranuclear palsy (PSP) and multiple system atrophy (MSA), share similar nonmotor symptoms. Quantitative electroencephalography (QEEG) can be used to examine the nonmotor symptoms. This study aimed to characterize the patterns of QEEG and functional connectivity (FC) that differentiate PD from PSP or MSA, and explore the correlation between the differential QEEG indices and nonmotor dysfunctions in PD and AP. We enrolled 52 patients with PD, 31 with MSA, 22 with PSP, and 50 age-matched health controls to compare QEEG indices among specific brain regions. One-way analysis of variance was applied to assess QEEG indices between groups; Spearman's correlations were used to examine the relationship between QEEG indices and nonmotor symptoms scale (NMSS) and mini-mental state examination (MMSE). FCs using weighted phase lag index were compared between patients with PD and those with MSA/PSP. Patients with PSP revealed higher scores on the NMSS and lower MMSE scores than those with PD and MSA, with similar disease duration. The delta and theta powers revealed a significant increase in PSP, followed by PD and MSA. Patients with PD presented a significantly lower slow-to-fast ratio than those with PSP in the frontal region, while patients with PD presented significantly higher EEG-slowing indices than patients with MSA. The frontal slow-to-fast ratio showed a negative correlation with MMSE scores in patients with PD and PSP, and a positive correlation with NMSS in the perception and mood domain in patients with PSP but not in those with PD. Compared to PD, MSA presented enhanced FC in theta and delta bands in the posterior region, while PSP revealed decreased FC in the delta band within the frontal-temporal cortex. These findings suggest that QEEG might be a useful tool for evaluating the nonmotor dysfunctions in PD and AP. Our QEEG results suggested that with similar disease duration, the cortical neurodegenerative process was likely exacerbated in patients with PSP, followed by those with PD, and lastly in patients with MSA.
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Affiliation(s)
- Hailing Liu
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.,Department of Neurology, Maoming People's Hospital, Maoming, Guangdong, China.
| | - Zifeng Huang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Bin Deng
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Zihan Chang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Xiaohua Yang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Xingfang Guo
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Feilan Yuan
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Qin Yang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Liming Wang
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
| | - Haiqiang Zou
- Department of Neurosurgery, General Hospital of Southern Theater Command of PLA, Guangdong, China.
| | - Mengyan Li
- Department of Neurology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China.
| | - Zhaohua Zhu
- Clinical Research Centre, Orthopedic Centre, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - Kunlin Jin
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
| | - Qing Wang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.,Correspondence should be addressed to: Dr. Qing Wang, Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong 510282, China. .
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7
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Jin L, Nawaz H, Ono K, Nowell J, Haley E, Berman BD, Mukhopadhyay ND, Barrett MJ. One Minute of EEG Data Provides Sufficient and Reliable Data for Identifying Lewy Body Dementia. Alzheimer Dis Assoc Disord 2023; 37:66-72. [PMID: 36413637 PMCID: PMC9974530 DOI: 10.1097/wad.0000000000000536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 10/05/2022] [Indexed: 11/23/2022]
Abstract
OBJECTIVE To determine the minimum duration of electroencephalography (EEG) data necessary to differentiate EEG features of Lewy body dementia (LBD), that is, dementia with Lewy bodies and Parkinson disease dementia, from non-LBD patients, that is, Alzheimer disease and Parkinson disease. METHODS We performed quantitative EEG analysis for 16 LBD and 14 non-LBD patients. After artifact removal, a fast Fourier transform was performed on 90, 60, and thirty 2-second epochs to derive dominant frequency; dominant frequency variability; and dominant frequency prevalence. RESULTS In LBD patients, there were no significant differences in EEG features derived from 90, 60, and thirty 2-second epochs (all P >0.05). There were no significant differences in EEG features derived from 3 different groups of thirty 2-second epochs (all P >0.05). When analyzing EEG features derived from ninety 2-second epochs, we found that LBD had significantly reduced dominant frequency, reduced dominant frequency variability, and reduced dominant frequency prevalence alpha compared with the non-LBD group (all P <0.05). These same differences were observed between the LBD and non-LBD groups when analyzing thirty 2-second epochs. CONCLUSIONS There were no differences in EEG features derived from 1 minute versus 3 minutes of EEG data, and both durations of EEG data equally differentiated LBD from non-LBD.
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Affiliation(s)
- Lucy Jin
- Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Huma Nawaz
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA
| | - Kenichiro Ono
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA
- U.S. Dept. of Veterans Affairs – Central Virginia Healthcare System, Richmond, VA, USA
| | - Justin Nowell
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA
| | - Erik Haley
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA
| | - Brian D. Berman
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA
| | - Nitai D. Mukhopadhyay
- Department of Biostatistics, Virginia Commonwealth University Health, Richmond, VA, USA
| | - Matthew J. Barrett
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA
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8
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Iannaccone S, Houdayer E, Spina A, Nocera G, Alemanno F. Quantitative EEG for early differential diagnosis of dementia with Lewy bodies. Front Psychol 2023; 14:1150540. [PMID: 37151310 PMCID: PMC10157484 DOI: 10.3389/fpsyg.2023.1150540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 03/31/2023] [Indexed: 05/09/2023] Open
Abstract
Introduction Differentiating between the two most common forms of dementia, Alzheimer's dementia and dementia with Lewy bodies (DLB) remains difficult and requires the use of invasive, expensive, and resource-intensive techniques. We aimed to investigate the sensitivity and specificity of electroencephalography quantified using the statistical pattern recognition method (qEEG-SPR) for identifying dementia and DLB. Methods Thirty-two outpatients and 16 controls underwent clinical assessment (by two blinded neurologists), EEG recording, and a 6-month follow-up clinical assessment. EEG data were processed using a qEEG-SPR protocol to derive a Dementia Index (positive or negative) and DLB index (positive or negative) for each participant which was compared against the diagnosis given at clinical assessment. Confusion matrices were used to calculate sensitivity, specificity, and predictive values for identifying dementia and DLB specifically. Results Clinical assessment identified 30 cases of dementia, 2 of which were diagnosed clinically with possible DLB, 14 with probable DLB and DLB was excluded in 14 patients. qEEG-SPR confirmed the dementia diagnosis in 26 out of the 32 patients and led to 6.3% of false positives (FP) and 9.4% of false negatives (FN). qEEG-SPR was used to provide a DLB diagnosis among patients who received a positive or inconclusive result of Dementia index and led to 13.6% of FP and 13.6% of FN. Confusion matrices indicated a sensitivity of 80%, a specificity of 89%, a positive predictive value of 92%, a negative predictive value of 72%, and an accuracy of 83% to diagnose dementia. The DLB index showed a sensitivity of 60%, a specificity of 90%, a positive predictive value of 75%, a negative predictive value of 81%, and an accuracy of 75%. Neuropsychological scores did not differ significantly between DLB and non- DLB patients. Head trauma or story of stroke were identified as possible causes of FP results for DLB diagnosis. Conclusion qEEG-SPR is a sensitive and specific tool for diagnosing dementia and differentiating DLB from other forms of dementia in the initial state. This non-invasive, low-cost, and environmentally friendly method is a promising diagnostic tool for dementia diagnosis which could be implemented in local care settings.
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Affiliation(s)
- Sandro Iannaccone
- Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elise Houdayer
- Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy
- *Correspondence: Elise Houdayer,
| | - Alfio Spina
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Gianluca Nocera
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Alemanno
- Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy
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9
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Hadiyoso S, Ong PA, Zakaria H, Rajab TLE. EEG-Based Spectral Dynamic in Characterization of Poststroke Patients with Cognitive Impairment for Early Detection of Vascular Dementia. JOURNAL OF HEALTHCARE ENGINEERING 2022; 2022:5666229. [PMID: 36444210 PMCID: PMC9701122 DOI: 10.1155/2022/5666229] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 09/08/2022] [Accepted: 11/03/2022] [Indexed: 10/17/2023]
Abstract
One common type of vascular dementia (VaD) is poststroke dementia (PSD). Vascular dementia can occur in one-third of stroke patients. The worsening of cognitive function can occur quickly if not detected and treated early. One of the potential medical modalities for observing this disorder by considering costs and safety factors is electroencephalogram (EEG). It is thought that there are differences in the spectral dynamics of the EEG signal between the normal group and stroke patients with cognitive impairment so that it can be used in detection. Therefore, this study proposes an EEG signal characterization method using EEG spectral power complexity measurements to obtain features of poststroke patients with cognitive impairment and normal subjects. Working memory EEGs were collected and analyzed from forty-two participants, consisting of sixteen normal subjects, fifteen poststroke patients with mild cognitive impairment, and eleven poststroke patients with dementia. From the analysis results, it was found that there were differences in the dynamics of the power spectral in each group, where the spectral power of the cognitively impaired group was more regular than the normal group. Notably, (1) significant differences in spectral entropy (SpecEn) with a p value <0.05 were found for all electrodes, (2) there was a relationship between SpecEn values and the severity of dementia (SpecEnDem < SpecEnMCI < SpecEnNormal), and (3) a post hoc multiple comparison test showed significant differences between groups at the F7 electrode. This study shows that spectral complexity analysis can discriminate between normal and poststroke patients with cognitive impairment. For further studies, it is necessary to simulate performance validation so that the proposed approach can be used in the early detection of poststroke dementia and monitoring the development of dementia.
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Affiliation(s)
- Sugondo Hadiyoso
- School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia
- School of Applied Science, Telkom University, Bandung, Indonesia
| | - Paulus Anam Ong
- Departement of Neurology, Faculty of Medicine, Padjadjaran University, Dr. Hasan Sadikin General Hospital, Bandung, Indonesia
| | - Hasballah Zakaria
- School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia
| | - Tati Latifah E. Rajab
- School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia
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10
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Zinno L, Negrotti A, Falzoi C, Messa G, Goldoni M, Calzetti S. Generalized Rhythmic Delta Activity Frontally Predominant Differentiates Dementia with Lewy Bodies From Alzheimer's Disease and Parkinson's Disease Dementia: A Conventional Electroencephalography Visual Analysis. Clin EEG Neurosci 2022; 53:426-434. [PMID: 33843293 DOI: 10.1177/1550059421997147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Introduction. An easily accessible and inexpensive neurophysiological technique such as conventional electroencephalography may provide an accurate and generally applicable biomarker capable of differentiating dementia with Lewy bodies (DLB) from Alzheimer's disease (AD) and Parkinson's disease-associated dementia (PDD). Method. We carried out a retrospective visual analysis of resting-state electroencephalography (EEG) recording of 22 patients with a clinical diagnosis of 19 probable and 3 possible DLB, 22 patients with probable AD and 21 with PDD, matched for age, duration, and severity of cognitive impairment. Results. By using the grand total EEG scoring method, the total score and generalized rhythmic delta activity frontally predominant (GRDAfp) alone or, even better, coupled with a slowing of frequency of background activity (FBA) and its reduced reactivity differentiated DLB from AD at an individual level with an high accuracy similar to that obtained with quantitative EEG (qEEG). GRDAfp alone could also differentiate DLB from PDD with a similar level of diagnostic accuracy. AD differed from PDD only for a slowing of FBA. The duration and severity of cognitive impairment did not differ between DLB patients with and without GRDAfp, indicating that this abnormal EEG pattern should not be regarded as a disease progression marker. Conclusions. The findings of this investigation revalorize the role of conventional EEG in the diagnostic workup of degenerative dementias suggesting the potential inclusion of GRDAfp alone or better coupled with the slowing of FBA and its reduced reactivity, in the list of supportive diagnostic biomarkers of DLB.
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Affiliation(s)
- Lucia Zinno
- Neurology Unit, 18630Azienda Ospedaliero-Universitaria of Parma, Parma, Emilia-Romagna, Italy
| | - Anna Negrotti
- Neurology Unit, 18630Azienda Ospedaliero-Universitaria of Parma, Parma, Emilia-Romagna, Italy
| | - Chiara Falzoi
- Center for Cognitive Disorders, AUSL of Parma, Parma, Emilia-Romagna, Italy
| | - Giovanni Messa
- Center for Cognitive Disorders, AUSL of Parma, Parma, Emilia-Romagna, Italy
| | | | - Stefano Calzetti
- Neurology Unit, 18630Azienda Ospedaliero-Universitaria of Parma, Parma, Emilia-Romagna, Italy
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11
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REACTIVITY OF POSTERIOR CORTICAL ELECTROENCEPHALOGRAPHIC ALPHA RHYTHMS DURING EYES OPENING IN COGNITIVELY INTACT OLDER ADULTS AND PATIENTS WITH DEMENTIA DUE TO ALZHEIMER'S AND LEWY BODY DISEASES. Neurobiol Aging 2022; 115:88-108. [DOI: 10.1016/j.neurobiolaging.2022.04.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 03/17/2022] [Accepted: 04/02/2022] [Indexed: 12/19/2022]
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12
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Rea RC, Berlot R, Martin SL, Craig CE, Holmes PS, Wright DJ, Bon J, Pirtošek Z, Ray NJ. Quantitative EEG and cholinergic basal forebrain atrophy in Parkinson's disease and mild cognitive impairment. Neurobiol Aging 2021; 106:37-44. [PMID: 34233212 DOI: 10.1016/j.neurobiolaging.2021.05.023] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 05/22/2021] [Accepted: 05/31/2021] [Indexed: 02/08/2023]
Abstract
Cholinergic degeneration is a key feature of dementia in neurodegenerative conditions including Alzheimer's disease (AD) and Parkinson's disease (PD). Quantitative electro-encephalography (EEG) metrics are altered in both conditions from early stages, and recent research in people with Lewy body and AD dementia suggests these changes may be associated with atrophy in cholinergic basal forebrain nuclei (cBF). To determine if these relationships exist in predementia stages of neurodegenerative conditions, we studied resting-state EEG and in vivo cBF volumes in 31 people with PD (without dementia), 21 people with mild cognitive impairment (MCI), and 21 age-matched controls. People with PD showed increased power in slower frequencies and reduced alpha reactivity compared to controls. Volumes of cholinergic cell clusters corresponding to the medial septum and vertical and horizontal limb of the diagonal band, and the posterior nucleus basalis of Meynert, correlated positively with; alpha reactivity in people with PD (p< 0.01); and pre-alpha power in people with MCI (p< 0.05). These results suggest that alpha reactivity and pre-alpha power are related to changes in cBF volumes in MCI and PD without dementia.
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Affiliation(s)
- River C Rea
- Department of Psychology, Health, Psychology, and Communities Research Centre, Manchester Metropolitan University, Manchester, UK.
| | - Rok Berlot
- Department of Neurology, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Sarah L Martin
- Department of Psychology, Health, Psychology, and Communities Research Centre, Manchester Metropolitan University, Manchester, UK
| | - Chesney E Craig
- Department of Psychology, Health, Psychology, and Communities Research Centre, Manchester Metropolitan University, Manchester, UK
| | - Paul S Holmes
- Department of Psychology, Health, Psychology, and Communities Research Centre, Manchester Metropolitan University, Manchester, UK
| | - David J Wright
- Department of Psychology, Health, Psychology, and Communities Research Centre, Manchester Metropolitan University, Manchester, UK
| | - Jurij Bon
- Department of Neurology, University Medical Centre Ljubljana, Ljubljana, Slovenia; University Psychiatric Clinic Ljubljana, Ljubljana, Slovenia
| | - Zvezdan Pirtošek
- Department of Neurology, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Nicola J Ray
- Department of Psychology, Health, Psychology, and Communities Research Centre, Manchester Metropolitan University, Manchester, UK
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Chatzikonstantinou S, McKenna J, Karantali E, Petridis F, Kazis D, Mavroudis I. Electroencephalogram in dementia with Lewy bodies: a systematic review. Aging Clin Exp Res 2021; 33:1197-1208. [PMID: 32383032 DOI: 10.1007/s40520-020-01576-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 04/21/2020] [Indexed: 01/26/2023]
Abstract
Dementia with Lewy bodies (DLB) belongs to the spectrum of Lewy body dementia (LBD) that also encompasses Parkinson's disease dementia (PDD). It is a common neurodegenerative disorder characterized by memory decline, cognitive fluctuations, visual hallucinations, autonomic nervous system disturbance, REM sleep behavior disorder, and parkinsonism. Definite diagnosis can be established only through neuropathological confirmation of Lewy bodies' presence in brain tissue. Probable or possible diagnosis relies upon clinical features, imaging, polysomnography, and electroencephalogram (EEG) findings. Potential neurophysiological biomarkers for the diagnosis, management, and evaluation of treatment-response in DLB should be affordable and widely available outside academic centers. Increasing evidence supports the use of quantitative EEG (qEEG) as a potential DLB biomarker, with promising results in discriminating DLB from other dementias and in identifying subjects who are on the trajectory to develop DLB. Several studies evaluated the diagnostic value of EEG in DLB. Visual analysis and qEEG techniques have been implemented, showing a superiority of the last in terms of sensitivity and objectivity. In this systematic review, we attempt to provide a general synthesis of the current knowledge on EEG application in DLB. We review the findings from original studies and address the issues remaining to be further clarified.
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Affiliation(s)
- Simela Chatzikonstantinou
- Third Department of Neurology, Aristotle University of Thessaloniki, 3 Arsaki Street, Pefka, 57010, Thessaloníki, Greece.
| | | | - Eleni Karantali
- Third Department of Neurology, Aristotle University of Thessaloniki, 3 Arsaki Street, Pefka, 57010, Thessaloníki, Greece
| | - Fivos Petridis
- Third Department of Neurology, Aristotle University of Thessaloniki, 3 Arsaki Street, Pefka, 57010, Thessaloníki, Greece
| | - Dimitrios Kazis
- Third Department of Neurology, Aristotle University of Thessaloniki, 3 Arsaki Street, Pefka, 57010, Thessaloníki, Greece
| | - Ioannis Mavroudis
- Leeds Teaching Hospitals, Leeds, UK
- Medical School, Cyprus University, Nicosia, Cyprus
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14
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Resting-state EEG alpha/theta ratio related to neuropsychological test performance in Parkinson's Disease. Clin Neurophysiol 2021; 132:756-764. [PMID: 33571883 DOI: 10.1016/j.clinph.2021.01.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 12/23/2020] [Accepted: 01/06/2021] [Indexed: 12/15/2022]
Abstract
OBJECTIVE To determine possible associations of hemispheric-regional alpha/theta ratio (α/θ) with neuropsychological test performance in Parkinson's Disease (PD) non-demented patients. METHODS 36 PD were matched to 36 Healthy Controls (HC). The α/θ in eight hemispheric regions was computed from the relative power spectral density of the resting-state quantitative electroencephalogram (qEEG). Correlations between α/θ and performance in several neuropsychological tests were conducted, significant findings were included in a moderation analysis. RESULTS The α/θ in all regions was lower in PD than in HC, with larger effect sizes in the posterior regions. Right parietal, and right and left occipital α/θ had significant positive correlations with performance in Judgement of Line Orientation Test (JLOT) in PD. Adjusted moderation analysis indicated that right, but not left, occipital α/θ influenced the JLOT performance related to PD. CONCLUSIONS Reduction of the occipital α/θ, in particular on the right side, was associated with visuospatial performance impairment in PD. SIGNIFICANCE Visuospatial impairment in PD, which is highly correlated with the subsequent development of dementia, is reflected in α/θ in the right posterior regions. The right occipital α/θ may represent a useful qEEG marker for evaluating the presence of early signs of cognitive decline in PD and the subsequent risk of dementia.
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15
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Armstrong MJ, Irwin DJ, Leverenz JB, Gamez N, Taylor A, Galvin JE. Biomarker Use for Dementia With Lewy Body Diagnosis: Survey of US Experts. Alzheimer Dis Assoc Disord 2021; 35:55-61. [PMID: 33009039 PMCID: PMC7904569 DOI: 10.1097/wad.0000000000000414] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 08/08/2020] [Indexed: 11/26/2022]
Abstract
BACKGROUND Dementia with Lewy body (DLB) diagnostic criteria define "indicative" and "supportive" biomarkers, but clinical practice patterns are unknown. METHODS An anonymous survey querying clinical use of diagnostic tests/biomarkers was sent to 38 center of excellence investigators. The survey included "indicative" biomarkers (dopamine transporter scan, myocardial scintigraphy, polysomnography), "supportive" biomarkers [magnetic resonance imaging (MRI)], positron emission tomography, or single-photon emission computed tomography perfusion/metabolism scans, quantitative electroencephalography), and other diagnostic tests (neuropsychological testing, cerebrospinal fluid analysis, genetics). Responses were analyzed descriptively. RESULTS Of the 22 respondents (58%), all reported the capability to perform neuropsychological testing, MRI, polysomnography, dopamine transporter scans, positron emission tomography/single-photon emission computed tomography scans, and cerebrospinal fluid analysis; 96% could order genetic testing. Neuropsychological testing and MRI were the most commonly ordered tests. Diagnostic testing beyond MRI and neuropsychological testing was most helpful in the context of "possible" DLB and mild cognitive impairment and to assist with differential diagnosis. Myocardial scintigraphy and electroencephalograpy use were rare. CONCLUSIONS AND RELEVANCE Neuropsychological testing and MRI remain the most widely used diagnostic tests by DLB specialists. Other tests-particularly indicative biomarkers-are used only selectively. Research is needed to validate existing potential DLB biomarkers, develop new biomarkers, and investigate mechanisms to improve DLB diagnosis.
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Affiliation(s)
- Melissa J. Armstrong
- Department of Neurology, University of Florida College of Medicine, McKnight Brain Institute
| | | | - James B. Leverenz
- Cleveland Lou Ruvo Center for Brain Health – Neurological Institute, Cleveland Clinic
| | - Noheli Gamez
- Department of Neurology, University of Florida College of Medicine, McKnight Brain Institute
| | | | - James E. Galvin
- Comprehensive Center for Brain Health, Department of Neurology, University of Miami Miller School of Medicine
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16
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Belkhiria C, Peysakhovich V. Electro-Encephalography and Electro-Oculography in Aeronautics: A Review Over the Last Decade (2010-2020). FRONTIERS IN NEUROERGONOMICS 2020; 1:606719. [PMID: 38234309 PMCID: PMC10790927 DOI: 10.3389/fnrgo.2020.606719] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 11/17/2020] [Indexed: 01/19/2024]
Abstract
Electro-encephalography (EEG) and electro-oculography (EOG) are methods of electrophysiological monitoring that have potentially fruitful applications in neuroscience, clinical exploration, the aeronautical industry, and other sectors. These methods are often the most straightforward way of evaluating brain oscillations and eye movements, as they use standard laboratory or mobile techniques. This review describes the potential of EEG and EOG systems and the application of these methods in aeronautics. For example, EEG and EOG signals can be used to design brain-computer interfaces (BCI) and to interpret brain activity, such as monitoring the mental state of a pilot in determining their workload. The main objectives of this review are to, (i) offer an in-depth review of literature on the basics of EEG and EOG and their application in aeronautics; (ii) to explore the methodology and trends of research in combined EEG-EOG studies over the last decade; and (iii) to provide methodological guidelines for beginners and experts when applying these methods in environments outside the laboratory, with a particular focus on human factors and aeronautics. The study used databases from scientific, clinical, and neural engineering fields. The review first introduces the characteristics and the application of both EEG and EOG in aeronautics, undertaking a large review of relevant literature, from early to more recent studies. We then built a novel taxonomy model that includes 150 combined EEG-EOG papers published in peer-reviewed scientific journals and conferences from January 2010 to March 2020. Several data elements were reviewed for each study (e.g., pre-processing, extracted features and performance metrics), which were then examined to uncover trends in aeronautics and summarize interesting methods from this important body of literature. Finally, the review considers the advantages and limitations of these methods as well as future challenges.
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17
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Stylianou M, Zaaimi B, Thomas A, Taylor JP, LeBeau FEN. Early Disruption of Cortical Sleep-Related Oscillations in a Mouse Model of Dementia With Lewy Bodies (DLB) Expressing Human Mutant (A30P) Alpha-Synuclein. Front Neurosci 2020; 14:579867. [PMID: 33041770 PMCID: PMC7527476 DOI: 10.3389/fnins.2020.579867] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 08/25/2020] [Indexed: 01/03/2023] Open
Abstract
Changes in sleep behavior and sleep-related cortical activity have been reported in conditions associated with abnormal alpha-synuclein (α-syn) expression, in particular Parkinson’s disease (PD) and dementia with Lewy bodies (DLB). Notably, changes can occur in patients years before the onset of cognitive decline. Sleep-related network oscillations play a key role in memory function, but how abnormal α-syn impacts the generation of such activity is currently unclear. To determine whether early changes in sleep-related network activity could also be observed, prior to any previously reported cognitive dysfunction, we used mice that over-express human mutant α-syn (A30P). Recordings in vivo were performed under urethane anesthesia in the medial prefrontal cortex (mPFC) and CA1 region of the hippocampus in young male (2.5 – 4 months old) A30P and age-matched wild type (WT) mice. We found that the slow oscillation (SO) < 1 Hz frequency was significantly faster in both the mPFC and hippocampus in A30P mice, and Up-state-associated fast oscillations at beta (20 – 30 Hz) and gamma (30 – 80 Hz) frequencies were delayed relative to the onset of the Up-state. Spindle (8 – 15 Hz) activity in the mPFC was also altered in A30P mice, as spindles were shorter in duration and had reduced density compared to WT. These changes demonstrate that dysregulation of sleep-related oscillations occurs in young A30P mice long before the onset of cognitive dysfunction. Our data suggest that, as seen in patients, changes in sleep-related oscillations are an early consequence of abnormal α-syn aggregation in A30P mice.
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Affiliation(s)
- Myrto Stylianou
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Boubker Zaaimi
- School of Life & Health Sciences, Aston University, Birmingham, United Kingdom
| | - Alan Thomas
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - John-Paul Taylor
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Fiona E N LeBeau
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
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18
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Oppedal K, Borda MG, Ferreira D, Westman E, Aarsland D. European DLB consortium: diagnostic and prognostic biomarkers in dementia with Lewy bodies, a multicenter international initiative. Neurodegener Dis Manag 2020; 9:247-250. [PMID: 31580225 DOI: 10.2217/nmt-2019-0016] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Affiliation(s)
- Ketil Oppedal
- Centre for Age-Related Medicine (SESAM), Stavanger University Hospital, Stavanger, Norway.,Department of Radiology, Stavanger University Hospital, Stavanger, Norway.,Department of Electrical Engineering & Computer Science, University of Stavanger, Stavanger, Norway
| | - Miguel G Borda
- Centre for Age-Related Medicine (SESAM), Stavanger University Hospital, Stavanger, Norway.,Faculty of Health Sciences, University of Stavanger, Stavanger, Norway.,Semillero de Neurociencias y Envejecimiento, Ageing Institute, Medical School, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Sweden.,Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Dag Aarsland
- Centre for Age-Related Medicine (SESAM), Stavanger University Hospital, Stavanger, Norway.,Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
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19
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The Role of EEG in the Diagnosis, Prognosis and Clinical Correlations of Dementia with Lewy Bodies-A Systematic Review. Diagnostics (Basel) 2020; 10:diagnostics10090616. [PMID: 32825520 PMCID: PMC7555753 DOI: 10.3390/diagnostics10090616] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 08/14/2020] [Accepted: 08/18/2020] [Indexed: 12/31/2022] Open
Abstract
Despite improvements in diagnostic criteria for dementia with Lewy bodies (DLB), the ability to discriminate DLB from Alzheimer’s disease (AD) and other dementias remains suboptimal. Electroencephalography (EEG) is currently a supportive biomarker in the diagnosis of DLB. We performed a systematic review to better clarify the diagnostic and prognostic role of EEG in DLB and define the clinical correlates of various EEG features described in DLB. MEDLINE, EMBASE, and PsycINFO were searched using search strategies for relevant articles up to 6 August 2020. We included 43 studies comparing EEG in DLB with other diagnoses, 42 of them included a comparison of DLB with AD, 10 studies compared DLB with Parkinson’s disease dementia, and 6 studies compared DLB with other dementias. The studies were visual EEG assessment (6), quantitative EEG (35) and event-related potential studies (2). The most consistent observation was the slowing of the dominant EEG rhythm (<8 Hz) assessed visually or through quantitative EEG, which was observed in ~90% of patients with DLB and only ~10% of patients with AD. Other findings based on qualitative rating, spectral power analyses, connectivity, microstate and machine learning algorithms were largely heterogenous due to differences in study design, EEG acquisition, preprocessing and analysis. EEG protocols should be standardized to allow replication and validation of promising EEG features as potential biomarkers in DLB.
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Schumacher J, Taylor JP, Hamilton CA, Firbank M, Cromarty RA, Donaghy PC, Roberts G, Allan L, Lloyd J, Durcan R, Barnett N, O'Brien JT, Thomas AJ. Quantitative EEG as a biomarker in mild cognitive impairment with Lewy bodies. ALZHEIMERS RESEARCH & THERAPY 2020; 12:82. [PMID: 32641111 PMCID: PMC7346501 DOI: 10.1186/s13195-020-00650-1] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 07/02/2020] [Indexed: 02/06/2023]
Abstract
Objectives To investigate using quantitative EEG the (1) differences between patients with mild cognitive impairment with Lewy bodies (MCI-LB) and MCI with Alzheimer’s disease (MCI-AD) and (2) its utility as a potential biomarker for early differential diagnosis. Methods We analyzed eyes-closed, resting-state, high-density EEG data from highly phenotyped participants (39 MCI-LB, 36 MCI-AD, and 31 healthy controls). EEG measures included spectral power in different frequency bands (delta, theta, pre-alpha, alpha, and beta), theta/alpha ratio, dominant frequency, and dominant frequency variability. Receiver operating characteristic (ROC) analyses were performed to assess diagnostic accuracy. Results There was a shift in power from beta and alpha frequency bands towards slower frequencies in the pre-alpha and theta range in MCI-LB compared to healthy controls. Additionally, the dominant frequency was slower in MCI-LB compared to controls. We found significantly increased pre-alpha power, decreased beta power, and slower dominant frequency in MCI-LB compared to MCI-AD. EEG abnormalities were more apparent in MCI-LB cases with more diagnostic features. There were no significant differences between MCI-AD and controls. In the ROC analysis to distinguish MCI-LB from MCI-AD, beta power and dominant frequency showed the highest area under the curve values of 0.71 and 0.70, respectively. While specificity was high for some measures (up to 0.97 for alpha power and 0.94 for theta/alpha ratio), sensitivity was generally much lower. Conclusions Early EEG slowing is a specific feature of MCI-LB compared to MCI-AD. However, there is an overlap between the two MCI groups which makes it difficult to distinguish between them based on EEG alone.
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Affiliation(s)
- Julia Schumacher
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Biomedical Research Building 3rd floor, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, UK.
| | - John-Paul Taylor
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Biomedical Research Building 3rd floor, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, UK
| | - Calum A Hamilton
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Biomedical Research Building 3rd floor, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, UK
| | - Michael Firbank
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Biomedical Research Building 3rd floor, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, UK
| | - Ruth A Cromarty
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Biomedical Research Building 3rd floor, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, UK
| | - Paul C Donaghy
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Biomedical Research Building 3rd floor, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, UK
| | - Gemma Roberts
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Biomedical Research Building 3rd floor, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, UK
| | - Louise Allan
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Biomedical Research Building 3rd floor, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, UK.,Institute of Health Research, University of Exeter, Exeter, UK
| | - Jim Lloyd
- Nuclear Medicine Department, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Rory Durcan
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Biomedical Research Building 3rd floor, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, UK
| | - Nicola Barnett
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Biomedical Research Building 3rd floor, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, UK
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge School of Medicine, Cambridge, CB2 0SP, UK
| | - Alan J Thomas
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Biomedical Research Building 3rd floor, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, UK
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21
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van der Zande JJ, Gouw AA, van Steenoven I, van de Beek M, Scheltens P, Stam CJ, Lemstra AW. Diagnostic and prognostic value of EEG in prodromal dementia with Lewy bodies. Neurology 2020; 95:e662-e670. [PMID: 32636325 DOI: 10.1212/wnl.0000000000009977] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 01/27/2020] [Indexed: 01/03/2023] Open
Abstract
OBJECTIVE Early biomarkers for dementia with Lewy bodies (DLB) are lacking. To determine whether EEG differentiates the prodromal phase of DLB from other causes of mild cognitive impairment (MCI) and whether EEG is predictive for time to conversion from MCI to DLB, we compared EEGs and clinical follow-up of patients with MCI due to DLB with those of patients with MCI due to Alzheimer disease (MCI-AD). METHODS We compared 37 patients with MCI who developed DLB during follow-up or had an abnormal 123I-PF-CIT SPECT scan (MCI-DLB) with 67 age-matched patients with MCI-AD. EEGs were assessed visually with a score of increasing abnormality (range 1-5). We performed fast Fourier transform to analyze the power spectrum. With survival analyses, EEG characteristics were related to time to progression to dementia. RESULTS The visual EEG score was higher in MCI-DLB (score >2 in 60%) compared to MCI-AD (score >2 in 8%, p < 0.001). We found frontal intermittent delta activity in 22% of MCI-DLB, not in MCI-AD. Patients with MCI-DLB had a lower peak frequency (7.5 [6.0-9.9] Hz vs 8.8 [6.8-10.2] in MCI-AD, p < 0.001) and more slow-wave activity. Several individual EEG measures showed good performance to discriminate MCI-DLB from MCI-AD (areas under the curve up to 0.94). In MCI-DLB, high visual EEG score, diffuse abnormalities, and low α2 power were related to time to progression to dementia (hazard ratios 4.1, 9.9, 5.1, respectively). CONCLUSIONS Profound EEG abnormalities are already present in the prodromal stage of DLB and have diagnostic and prognostic value. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that EEG abnormalities are more common in MCI-DLB than MCI-AD.
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Affiliation(s)
- Jessica Joanne van der Zande
- From the Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience (J.J.v.d.Z., A.A.G., I.v.S., M.v.d.B., P.S., A.W.L.), and Department of Clinical Neurophysiology (A.A.G., C.J.S.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands.
| | - Alida A Gouw
- From the Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience (J.J.v.d.Z., A.A.G., I.v.S., M.v.d.B., P.S., A.W.L.), and Department of Clinical Neurophysiology (A.A.G., C.J.S.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
| | - Inger van Steenoven
- From the Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience (J.J.v.d.Z., A.A.G., I.v.S., M.v.d.B., P.S., A.W.L.), and Department of Clinical Neurophysiology (A.A.G., C.J.S.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
| | - Marleen van de Beek
- From the Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience (J.J.v.d.Z., A.A.G., I.v.S., M.v.d.B., P.S., A.W.L.), and Department of Clinical Neurophysiology (A.A.G., C.J.S.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
| | - Philip Scheltens
- From the Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience (J.J.v.d.Z., A.A.G., I.v.S., M.v.d.B., P.S., A.W.L.), and Department of Clinical Neurophysiology (A.A.G., C.J.S.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
| | - Cornelis Jan Stam
- From the Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience (J.J.v.d.Z., A.A.G., I.v.S., M.v.d.B., P.S., A.W.L.), and Department of Clinical Neurophysiology (A.A.G., C.J.S.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
| | - Afina Willemina Lemstra
- From the Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience (J.J.v.d.Z., A.A.G., I.v.S., M.v.d.B., P.S., A.W.L.), and Department of Clinical Neurophysiology (A.A.G., C.J.S.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
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O'Dowd S, Schumacher J, Burn DJ, Bonanni L, Onofrj M, Thomas A, Taylor JP. Fluctuating cognition in the Lewy body dementias. Brain 2020; 142:3338-3350. [PMID: 31411317 DOI: 10.1093/brain/awz235] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 05/28/2019] [Accepted: 06/09/2019] [Indexed: 01/17/2023] Open
Abstract
Fluctuating cognition is a core diagnostic feature of dementia with Lewy bodies and is also a key clinical feature of Parkinson's disease dementia. These dementias share common pathological features and are referred to as Lewy body dementias. Whilst highly prevalent in Lewy body dementia, with up to 90% of patients experiencing the symptom at some point in the disease trajectory, clinical identification of fluctuating cognition is often challenging. Furthermore, its underlying pathophysiological processes remain unclear. However, neuroimaging and neurophysiological techniques have recently provided insight into potential drivers of the phenomenon. In this update, we review data pertaining to clinical features and underlying mechanisms of fluctuating cognition in Lewy body dementia. We collate evidence for different proposed aetiologies: fluctuating cognition as an attentional disorder, as a consequence of loss of cholinergic drive, as a manifestation of failure in neuronal efficiency and synchrony, and as a disorder of sleep/arousal. We also review data relating to putative mechanisms that have received less attention to date. Increased understanding of fluctuating cognition may help to illuminate pathophysiological mechanisms in cognitive processing in Lewy body dementia, guide future research, and facilitate the design of targeted therapeutic approaches.
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Affiliation(s)
- Seán O'Dowd
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK.,Department of Neurology, Tallaght University Hospital, Dublin 24, Ireland; Academic Unit of Neurology, Trinity College Dublin, Ireland
| | - Julia Schumacher
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
| | - David J Burn
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
| | - Laura Bonanni
- Department of Neuroscience, Imaging and Clinical Science and Aging Research Centre, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
| | - Marco Onofrj
- Department of Neuroscience, Imaging and Clinical Science and Aging Research Centre, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
| | - Alan Thomas
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
| | - John-Paul Taylor
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
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23
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Franciotti R, Pilotto A, Moretti DV, Falasca NW, Arnaldi D, Taylor JP, Nobili F, Kramberger M, Ptacek SG, Padovani A, Aarlsand D, Onofrj M, Bonanni L. Anterior EEG slowing in dementia with Lewy bodies: a multicenter European cohort study. Neurobiol Aging 2020; 93:55-60. [PMID: 32450445 DOI: 10.1016/j.neurobiolaging.2020.04.023] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 04/19/2020] [Accepted: 04/21/2020] [Indexed: 02/08/2023]
Abstract
Electroencephalography (EEG) slowing with prealpha dominant frequency (DF) in posterior derivations is a biomarker for dementia with Lewy bodies (DLB) diagnosis, in contrast with Alzheimer's disease (AD). However, an intrasubject re-evaluation of the original data, which contributed to the identification of EEG DLB biomarker, showed that DF was slower in anterior than posterior derivations. We suppose this anterior-posterior gradient of DF slowing could arise in DLB from a thalamocortical dysrhythmia, differently involving the anterior and posterior cortical areas, and correlating with cognitive impairment (Mini-Mental State Examination). EEG was recorded in 144 DLB, 116 AD, and 65 controls from 7 Centers of the European DLB Consortium. Spectra were divided into delta, theta, prealpha, alpha frequency bands. In DLB, mean DF was prealpha both anteriorly and posteriorly, but lower anteriorly (p < 0.001). In 14% of DLB, DF was prealpha anteriorly, whereas alpha posteriorly. In AD and controls, DF was constantly alpha. EEG slowing in DLB correlated with cognitive impairment. Thalamocortical dysrhythmia gives rise to prealpha rhythm with an anterior-posterior gradient and correlates with impaired cognition.
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Affiliation(s)
- Raffaella Franciotti
- Department of Neuroscience, Imaging and Clinical Science, and Aging Research Centre, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
| | - Andrea Pilotto
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Davide V Moretti
- Alzheimer's Epidemiology and Rehabilitation in Alzheimer's Disease Operative Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Nicola Walter Falasca
- Department of Neuroscience, Imaging and Clinical Science, and Aging Research Centre, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
| | - Dario Arnaldi
- Clinical Neurology, Department of Neuroscience (DINOGMI), University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy; IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - John-Paul Taylor
- Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, UK
| | - Flavio Nobili
- Clinical Neurology, Department of Neuroscience (DINOGMI), University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy; IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Milica Kramberger
- Department of Neurology, University Medical Centre, Ljubljana, Slovenia
| | - Sara Garcia Ptacek
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, and Memory Clinic Department of Geriatric Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Alessandro Padovani
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | | | - Marco Onofrj
- Department of Neuroscience, Imaging and Clinical Science, and Aging Research Centre, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
| | - Laura Bonanni
- Department of Neuroscience, Imaging and Clinical Science, and Aging Research Centre, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy.
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Schumacher J, Thomas AJ, Peraza LR, Firbank M, Cromarty R, Hamilton CA, Donaghy PC, O'Brien JT, Taylor JP. EEG alpha reactivity and cholinergic system integrity in Lewy body dementia and Alzheimer's disease. Alzheimers Res Ther 2020; 12:46. [PMID: 32321573 PMCID: PMC7178985 DOI: 10.1186/s13195-020-00613-6] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 04/02/2020] [Indexed: 11/14/2023]
Abstract
BACKGROUND Lewy body dementia (LBD), which includes dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD), is characterised by marked deficits within the cholinergic system which are more severe than in Alzheimer's disease (AD) and are mainly caused by degeneration of the nucleus basalis of Meynert (NBM) whose widespread cholinergic projections provide the main source of cortical cholinergic innervation. EEG alpha reactivity, which refers to the reduction in alpha power over occipital electrodes upon opening the eyes, has been suggested as a potential marker of cholinergic system integrity. METHODS Eyes-open and eyes-closed resting state EEG data were recorded from 41 LBD patients (including 24 patients with DLB and 17 with PDD), 21 patients with AD, and 40 age-matched healthy controls. Alpha reactivity was calculated as the relative reduction in alpha power over occipital electrodes when opening the eyes. Structural MRI data were used to assess volumetric changes within the NBM using a probabilistic anatomical map. RESULTS Alpha reactivity was reduced in AD and LBD patients compared to controls with a significantly greater reduction in LBD compared to AD. Reduced alpha reactivity was associated with smaller volumes of the NBM across all groups (ρ = 0.42, pFDR = 0.0001) and in the PDD group specifically (ρ = 0.66, pFDR = 0.01). CONCLUSIONS We demonstrate that LBD patients show an impairment in alpha reactivity upon opening the eyes which distinguishes this form of dementia from AD. Furthermore, our results suggest that reduced alpha reactivity might be related to a loss of cholinergic drive from the NBM, specifically in PDD.
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Affiliation(s)
- Julia Schumacher
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Campus for Ageing and Vitality, Biomedical Research Building 3rd floor, Newcastle upon Tyne, NE4 5PL, UK.
| | - Alan J Thomas
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Campus for Ageing and Vitality, Biomedical Research Building 3rd floor, Newcastle upon Tyne, NE4 5PL, UK
| | | | - Michael Firbank
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Campus for Ageing and Vitality, Biomedical Research Building 3rd floor, Newcastle upon Tyne, NE4 5PL, UK
| | - Ruth Cromarty
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Campus for Ageing and Vitality, Biomedical Research Building 3rd floor, Newcastle upon Tyne, NE4 5PL, UK
| | - Calum A Hamilton
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Campus for Ageing and Vitality, Biomedical Research Building 3rd floor, Newcastle upon Tyne, NE4 5PL, UK
| | - Paul C Donaghy
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Campus for Ageing and Vitality, Biomedical Research Building 3rd floor, Newcastle upon Tyne, NE4 5PL, UK
| | - John T O'Brien
- Department of Psychiatry, School of Medicine, University of Cambridge, Cambridge, CB2 0SP, UK
| | - John-Paul Taylor
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Campus for Ageing and Vitality, Biomedical Research Building 3rd floor, Newcastle upon Tyne, NE4 5PL, UK
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Schumacher J, Peraza LR, Firbank M, Thomas AJ, Kaiser M, Gallagher P, O’Brien JT, Blamire AM, Taylor JP. Dysfunctional brain dynamics and their origin in Lewy body dementia. Brain 2019; 142:1767-1782. [PMID: 30938426 PMCID: PMC6536851 DOI: 10.1093/brain/awz069] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Revised: 01/06/2019] [Accepted: 01/27/2019] [Indexed: 01/08/2023] Open
Abstract
Lewy body dementia includes dementia with Lewy bodies and Parkinson's disease dementia and is characterized by transient clinical symptoms such as fluctuating cognition, which might be driven by dysfunction of the intrinsic dynamic properties of the brain. In this context we investigated whole-brain dynamics on a subsecond timescale in 42 Lewy body dementia compared to 27 Alzheimer's disease patients and 18 healthy controls using an EEG microstate analysis in a cross-sectional design. Microstates are transiently stable brain topographies whose temporal characteristics provide insight into the brain's dynamic repertoire. Our additional aim was to explore what processes in the brain drive microstate dynamics. We therefore studied associations between microstate dynamics and temporal aspects of large-scale cortical-basal ganglia-thalamic interactions using dynamic functional MRI measures given the putative role of these subcortical areas in modulating widespread cortical function and their known vulnerability to Lewy body pathology. Microstate duration was increased in Lewy body dementia for all microstate classes compared to Alzheimer's disease (P < 0.001) and healthy controls (P < 0.001), while microstate dynamics in Alzheimer's disease were largely comparable to healthy control levels, albeit with altered microstate topographies. Correspondingly, the number of distinct microstates per second was reduced in Lewy body dementia compared to healthy controls (P < 0.001) and Alzheimer's disease (P < 0.001). In the dementia with Lewy bodies group, mean microstate duration was related to the severity of cognitive fluctuations (ρ = 0.56, PFDR = 0.038). Additionally, mean microstate duration was negatively correlated with dynamic functional connectivity between the basal ganglia (r = - 0.53, P = 0.003) and thalamic networks (r = - 0.38, P = 0.04) and large-scale cortical networks such as visual and motor networks in Lewy body dementia. The results indicate a slowing of microstate dynamics and disturbances to the precise timing of microstate sequences in Lewy body dementia, which might lead to a breakdown of the intricate dynamic properties of the brain, thereby causing loss of flexibility and adaptability that is crucial for healthy brain functioning. When contrasted with the largely intact microstate dynamics in Alzheimer's disease, the alterations in dynamic properties in Lewy body dementia indicate a brain state that is less responsive to environmental demands and might give rise to the apparent slowing in thinking and intermittent confusion which typify Lewy body dementia. By using Lewy body dementia as a probe pathology we demonstrate a potential link between dynamic functional MRI fluctuations and microstate dynamics, suggesting that dynamic interactions within the cortical-basal ganglia-thalamic loop might play a role in the modulation of EEG dynamics.
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Affiliation(s)
- Julia Schumacher
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
| | - Luis R Peraza
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle University, Newcastle upon Tyne, UK
| | - Michael Firbank
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
| | - Alan J Thomas
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
| | - Marcus Kaiser
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle University, Newcastle upon Tyne, UK
- Institute of Neuroscience, Newcastle University, The Henry Wellcome Building, Newcastle upon Tyne, UK
| | - Peter Gallagher
- Institute of Neuroscience, Newcastle University, The Henry Wellcome Building, Newcastle upon Tyne, UK
| | - John T O’Brien
- Department of Psychiatry, University of Cambridge School of Medicine, Cambridge, UK
| | - Andrew M Blamire
- Institute of Cellular Medicine and Newcastle Magnetic Resonance Centre, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
| | - John-Paul Taylor
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
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Babiloni C, Del Percio C, Lizio R, Noce G, Lopez S, Soricelli A, Ferri R, Pascarelli MT, Catania V, Nobili F, Arnaldi D, Famà F, Aarsland D, Orzi F, Buttinelli C, Giubilei F, Onofrj M, Stocchi F, Vacca L, Stirpe P, Fuhr P, Gschwandtner U, Ransmayr G, Garn H, Fraioli L, Pievani M, Frisoni GB, D'Antonio F, De Lena C, Güntekin B, Hanoğlu L, Başar E, Yener G, Emek-Savaş DD, Triggiani AI, Franciotti R, Taylor JP, De Pandis MF, Bonanni L. Abnormalities of Resting State Cortical EEG Rhythms in Subjects with Mild Cognitive Impairment Due to Alzheimer's and Lewy Body Diseases. J Alzheimers Dis 2019; 62:247-268. [PMID: 29439335 DOI: 10.3233/jad-170703] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The present study tested the hypothesis that cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms reveal different abnormalities in cortical neural synchronization in groups of patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) and dementia with Lewy bodies (DLBMCI) as compared to cognitively normal elderly (Nold) subjects. Clinical and rsEEG data in 30 ADMCI, 23 DLBMCI, and 30 Nold subjects were available in an international archive. Age, gender, and education were carefully matched in the three groups. The Mini-Mental State Evaluation (MMSE) score was matched between the ADMCI and DLBMCI groups. Individual alpha frequency peak (IAF) was used to determine the delta, theta, alpha1, alpha2, and alpha3 frequency band ranges. Fixed beta1, beta2, and gamma bands were also considered. eLORETA estimated the rsEEG cortical sources. Receiver operating characteristic curve (ROCC) classified these sources across individuals. Compared to Nold, IAF showed marked slowing in DLBMCI and moderate in ADMCI. Furthermore, the posterior alpha 2 and alpha 3 source activities were more abnormal in the ADMCI than the DLBMCI group, while widespread delta source activities were more abnormal in the DLBMCI than the ADMCI group. The posterior delta and alpha sources correlated with the MMSE score and correctly classified the Nold and MCI individuals (area under the ROCC >0.85). In conclusion, the ADMCI and DLBMCI patients showed different features of cortical neural synchronization at delta and alpha frequencies underpinning brain arousal and vigilance in the quiet wakefulness. Future prospective cross-validation studies will have to test the clinical validity of these rsEEG markers.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy.,Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | | | - Roberta Lizio
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy.,Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Giuseppe Noce
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy
| | - Andrea Soricelli
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Raffaele Ferri
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging, Troina, Enna, Italy
| | - Maria Teresa Pascarelli
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging, Troina, Enna, Italy
| | - Valentina Catania
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging, Troina, Enna, Italy
| | - Flavio Nobili
- Department of Neuroscience (DiNOGMI), Clinical Neurology, University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dario Arnaldi
- Department of Neuroscience (DiNOGMI), Clinical Neurology, University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Francesco Famà
- Department of Neuroscience (DiNOGMI), Clinical Neurology, University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dag Aarsland
- Department of Old Age Psychiatry, King's College University, London, UK
| | - Francesco Orzi
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Marco Onofrj
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Laura Vacca
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Paola Stirpe
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Peter Fuhr
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Ute Gschwandtner
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Gerhard Ransmayr
- Department of Neurology 2, Med Campus III, Kepler University Hospital, Medical Faculty of the Johannes Kepler University, Linz, Austria
| | - Heinrich Garn
- AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | | | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and 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
| | - Fabrizia D'Antonio
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Italy
| | - Carlo De Lena
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Italy
| | - Bahar Güntekin
- Department of Biophysics, Istanbul Medipol University, Istanbul, Turkey
| | - Lutfu Hanoğlu
- Department of Neurology, University of Istanbul-Medipol, Istanbul, Turkey
| | - Erol Başar
- IBG, Departments of Neurology and Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - Görsev Yener
- IBG, Departments of Neurology and Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - Derya Durusu Emek-Savaş
- Department of Psychology and Department of Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | | | - Raffaella Franciotti
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | | | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
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27
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Morbelli S, Chincarini A, Brendel M, Rominger A, Bruffaerts R, Vandenberghe R, Kramberger MG, Trost M, Garibotto V, Nicastro N, Frisoni GB, Lemstra AW, van der Zande J, Pilotto A, Padovani A, Garcia-Ptacek S, Savitcheva I, Ochoa-Figueroa MA, Davidsson A, Camacho V, Peira E, Arnaldi D, Bauckneht M, Pardini M, Sambuceti G, Aarsland D, Nobili F. Metabolic patterns across core features in dementia with lewy bodies. Ann Neurol 2019; 85:715-725. [PMID: 30805951 DOI: 10.1002/ana.25453] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 02/22/2019] [Accepted: 02/22/2019] [Indexed: 12/14/2022]
Abstract
OBJECTIVE To identify brain regions whose metabolic impairment contributes to dementia with Lewy bodies (DLB) clinical core features expression and to assess the influence of severity of global cognitive impairment on the DLB hypometabolic pattern. METHODS Brain fluorodeoxyglucose positron emission tomography and information on core features were available in 171 patients belonging to the imaging repository of the European DLB Consortium. Principal component analysis was applied to identify brain regions relevant to the local data variance. A linear regression model was applied to generate core-feature-specific patterns controlling for the main confounding variables (Mini-Mental State Examination [MMSE], age, education, gender, and center). Regression analysis to the locally normalized intensities was performed to generate an MMSE-sensitive map. RESULTS Parkinsonism negatively covaried with bilateral parietal, precuneus, and anterior cingulate metabolism; visual hallucinations (VH) with bilateral dorsolateral-frontal cortex, posterior cingulate, and parietal metabolism; and rapid eye movement sleep behavior disorder (RBD) with bilateral parieto-occipital cortex, precuneus, and ventrolateral-frontal metabolism. VH and RBD shared a positive covariance with metabolism in the medial temporal lobe, cerebellum, brainstem, basal ganglia, thalami, and orbitofrontal and sensorimotor cortex. Cognitive fluctuations negatively covaried with occipital metabolism and positively with parietal lobe metabolism. MMSE positively covaried with metabolism in the left superior frontal gyrus, bilateral-parietal cortex, and left precuneus, and negatively with metabolism in the insula, medial frontal gyrus, hippocampus in the left hemisphere, and right cerebellum. INTERPRETATION Regions of more preserved metabolism are relatively consistent across the variegate DLB spectrum. By contrast, core features were associated with more prominent hypometabolism in specific regions, thus suggesting a close clinical-imaging correlation, reflecting the interplay between topography of neurodegeneration and clinical presentation in DLB patients. Ann Neurol 2019;85:715-725.
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Affiliation(s)
- Silvia Morbelli
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Nuclear Medicine Unit, Department of Health Sciences, University of Genoa
| | - Andrea Chincarini
- National Institute of Nuclear Physics (INFN), Genoa section, Genoa, Italy
| | - Matthias Brendel
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Axel Rominger
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany.,Department of Nuclear Medicine, Inselspital, University Hospital Bern, Bern, Switzerland
| | - Rose Bruffaerts
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Belgium.,Neurology Department, University Hospitals Leuven, Leuven, Belgium
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Belgium.,Neurology Department, University Hospitals Leuven, Leuven, Belgium
| | | | - Maja Trost
- Department of Neurology, University Medical Centre, Ljubljana, Slovenia.,Faculty of Medicine, University of Ljubljana, Slovenia
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals and NIMTLab, Geneva University
| | - Nicolas Nicastro
- Department of Clinical Neurosciences, Geneva University Hospitals, Switzerland.,Department of Psychiatry, University of Cambridge, United Kingdom
| | - Giovanni B Frisoni
- LANVIE (Laboratoire de Neuroimagerie du Vieillissement), Department of Psychiatry, Geneva University Hospitals, Geneva, Switzerland
| | - Afina W Lemstra
- VU Medical Center Alzheimer Center, Amsterdam, The Netherlands
| | | | - Andrea Pilotto
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.,Parkinson's Disease Rehabilitation Centre, FERB ONLUS - S. Isidoro Hospital, Trescore Balneario (BG), Italy
| | - Alessandro Padovani
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Sara Garcia-Ptacek
- Department of Clinical Geriatrics, division of Neurobiology, Care Sciences and Society, Karolinska Institutet.,Internal Medicine, section for Neurology, Sädersjukhuset, Stockholm, Sweden
| | - Irina Savitcheva
- Department of Radiology, Karolinska Institutet, Stockholm, Sweden
| | - Miguel A Ochoa-Figueroa
- Department of Clinical Physiology, Institution of Medicine and Health Sciences, Linköping, Sweden.,Department of Diagnostic Radiology, Linköping University Hospital, Linköping, Sweden.,Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Annette Davidsson
- Department of Clinical Physiology, Institution of Medicine and Health Sciences, Linköping, Sweden
| | - Valle Camacho
- Servicio de Medicina Nuclear, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, España
| | - Enrico Peira
- National Institute of Nuclear Physics (INFN), Genoa section, Genoa, Italy.,Clinical Neurology, Department of Neuroscience (DINOGMI), University of Genoa, Italy
| | - Dario Arnaldi
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Clinical Neurology, Department of Neuroscience (DINOGMI), University of Genoa, Italy
| | - Matteo Bauckneht
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Nuclear Medicine Unit, Department of Health Sciences, University of Genoa
| | - Matteo Pardini
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Clinical Neurology, Department of Neuroscience (DINOGMI), University of Genoa, Italy
| | - Gianmario Sambuceti
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Nuclear Medicine Unit, Department of Health Sciences, University of Genoa
| | - Dag Aarsland
- Centre for Age-Related Medicine (SESAM), Stavanger University Hospital, Stavanger, Norway.,Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London
| | - Flavio Nobili
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Clinical Neurology, Department of Neuroscience (DINOGMI), University of Genoa, Italy
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28
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Lin YW, Truong D. Diffuse Lewy body disease. J Neurol Sci 2019; 399:144-150. [PMID: 30807982 DOI: 10.1016/j.jns.2019.02.021] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Revised: 02/09/2019] [Accepted: 02/11/2019] [Indexed: 12/15/2022]
Abstract
Diffuse Lewy body disease, also called dementia with Lewy bodies (DLB), is defined as progressive dementia and pathological Lewy bodies distributed in the central and autonomic nervous systems. The clinical features are dementia, cognitive fluctuations, visual hallucinations, parkinsonism, and REM sleep behavior disorder (RBD). Confirmatory techniques include dopamine transporter imaging, meta-iodobenzylguanidine (MIBG) myocardial scintigraphy, and polysomnography. The pathology finding in DLB is misfolded alpha-synuclein, the main component of Lewy bodies, propagating in the central nervous system. This may interrupt the acetylcholine pathway and activate an inflammatory response. Mutations of several genes have been found in patients with DLB, including SNCA, GBA, and APOE. The differential diagnosis of DLB and Parkinson's disease with dementia (PDD) is a debated issue. Clinical features distinguishing DLB from PDD include the timing of dementia and visual hallucinations, responses to dopaminergic agents and anti-psychotics, and imaging findings. As to the management of DLB, cholinesterase inhibitors are the Level-A recommendation for treating dementia in DLB patients and also are beneficial for treating visual hallucinations and psychotic symptoms. Dopamine agonists have the risk of inducing psychotic symptoms, while levodopa should be used carefully for motor symptoms. Melatonin and clonazepam are effective in controlling RBD. Several other treatment methods are undergoing trials, including pimavanserine, nilotinib, psychological interventions, and behavior therapy.
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Affiliation(s)
- Yu Wei Lin
- Taiwan Adventist Hospital, Taipei, Taiwan
| | - Daniel Truong
- The Truong Neuroscience Institute, Orange Coast Memorial Medical Center, Fountain Valley, CA, USA; Departments of Psychiatry and Neuroscience, UC Riverside, Riverside, CA, USA.
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29
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Outeiro TF, Koss DJ, Erskine D, Walker L, Kurzawa-Akanbi M, Burn D, Donaghy P, Morris C, Taylor JP, Thomas A, Attems J, McKeith I. Dementia with Lewy bodies: an update and outlook. Mol Neurodegener 2019; 14:5. [PMID: 30665447 PMCID: PMC6341685 DOI: 10.1186/s13024-019-0306-8] [Citation(s) in RCA: 197] [Impact Index Per Article: 39.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Accepted: 01/08/2019] [Indexed: 01/17/2023] Open
Abstract
Dementia with Lewy bodies (DLB) is an age-associated neurodegenerative disorder producing progressive cognitive decline that interferes with normal life and daily activities. Neuropathologically, DLB is characterised by the accumulation of aggregated α-synuclein protein in Lewy bodies and Lewy neurites, similar to Parkinson’s disease (PD). Extrapyramidal motor features characteristic of PD, are common in DLB patients, but are not essential for the clinical diagnosis of DLB. Since many PD patients develop dementia as disease progresses, there has been controversy about the separation of DLB from PD dementia (PDD) and consensus reports have put forward guidelines to assist clinicians in the identification and management of both syndromes. Here, we present basic concepts and definitions, based on our current understanding, that should guide the community to address open questions that will, hopefully, lead us towards improved diagnosis and novel therapeutic strategies for DLB and other synucleinopathies.
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Affiliation(s)
- Tiago Fleming Outeiro
- Institute of Neuroscience, The Medical School, Newcastle University, Framlington Place, Newcastle Upon Tyne, NE2 4HH, UK. .,Department of Experimental Neurodegeneration, Center for Nanoscale Microscopy and Molecular Physiology of the Brain, Center for Biostructural Imaging of Neurodegeneration, University Medical Center Göttingen, Göttingen, Germany. .,Max Planck Institute for Experimental Medicine, Göttingen, Germany.
| | - David J Koss
- Institute of Neuroscience, The Medical School, Newcastle University, Framlington Place, Newcastle Upon Tyne, NE2 4HH, UK
| | - Daniel Erskine
- Institute of Neuroscience, The Medical School, Newcastle University, Framlington Place, Newcastle Upon Tyne, NE2 4HH, UK
| | - Lauren Walker
- Institute of Neuroscience, The Medical School, Newcastle University, Framlington Place, Newcastle Upon Tyne, NE2 4HH, UK
| | - Marzena Kurzawa-Akanbi
- Institute of Neuroscience, The Medical School, Newcastle University, Framlington Place, Newcastle Upon Tyne, NE2 4HH, UK
| | - David Burn
- Institute of Neuroscience, The Medical School, Newcastle University, Framlington Place, Newcastle Upon Tyne, NE2 4HH, UK
| | - Paul Donaghy
- Institute of Neuroscience, The Medical School, Newcastle University, Framlington Place, Newcastle Upon Tyne, NE2 4HH, UK
| | - Christopher Morris
- Institute of Neuroscience, The Medical School, Newcastle University, Framlington Place, Newcastle Upon Tyne, NE2 4HH, UK
| | - John-Paul Taylor
- Institute of Neuroscience, The Medical School, Newcastle University, Framlington Place, Newcastle Upon Tyne, NE2 4HH, UK
| | - Alan Thomas
- Institute of Neuroscience, The Medical School, Newcastle University, Framlington Place, Newcastle Upon Tyne, NE2 4HH, UK
| | - Johannes Attems
- Institute of Neuroscience, The Medical School, Newcastle University, Framlington Place, Newcastle Upon Tyne, NE2 4HH, UK
| | - Ian McKeith
- Institute of Neuroscience, The Medical School, Newcastle University, Framlington Place, Newcastle Upon Tyne, NE2 4HH, UK.
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30
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Bonanni L. The democratic aspect of machine learning: Limitations and opportunities for Parkinson's disease. Mov Disord 2018; 34:164-166. [DOI: 10.1002/mds.27600] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 12/03/2018] [Accepted: 12/06/2018] [Indexed: 12/13/2022] Open
Affiliation(s)
- Laura Bonanni
- Department of Neuroscience, Imaging and Clinical SciencesUniversity G. d'Annunzio of Chieti‐Pescara Chieti Italy
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31
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van der Zande JJ, Gouw AA, van Steenoven I, Scheltens P, Stam CJ, Lemstra AW. EEG Characteristics of Dementia With Lewy Bodies, Alzheimer's Disease and Mixed Pathology. Front Aging Neurosci 2018; 10:190. [PMID: 30018548 PMCID: PMC6037893 DOI: 10.3389/fnagi.2018.00190] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 06/05/2018] [Indexed: 11/13/2022] Open
Abstract
Introduction: Previous studies on electroencephalography (EEG) to discriminate between dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) have been promising. These studies did not consider the pathological overlap of the two diseases. DLB-patients with concomitant AD pathology (DLB/AD+) have a more severe disease manifestation. The EEG may also be influenced by a synergistic effect of the two pathologies. We aimed to compare EEG characteristics between DLB/AD+, "pure" DLB (DLB/AD-) and AD. Methods: We selected probable DLB patients who had an EEG and cerebrospinal fluid (CSF) available, from the Amsterdam Dementia Cohort (ADC). Concomitant AD-pathology was defined as a CSF tau/Aβ-42 ratio > 0.52. Forty-one DLB/AD+ cases were matched for age (mean 70 (range 53-85)) and sex (85% male) 1:1 to DLB/AD- and AD-patients. EEGs were assessed visually, with Fast Fourier Transform (FFT), network- and connectivity measures. Results: EEG visual severity score (range 1-5) did not differ between DLB/AD- and DLB/AD+ (2.7 in both groups) and was higher compared to AD (1.9, p < 0.01). Both DLB groups had a lower peak frequency (7.0 Hz and 6.9 Hz in DLB vs. 8.2 in AD, p < 0.05), more slow-wave activity and more prominent disruptions of connectivity and networks, compared to AD. No significant differences were found between DLB/AD+ and DLB/AD-. Discussion: EEG abnormalities are more pronounced in DLB, regardless of AD co-pathology. This emphasizes the valuable role of EEG in discriminating between DLB and AD. It suggests that EEG slowing in DLB is influenced more by the α-synucleinopathy, or the associated cholinergic deficit, than by amyloid and tau pathology.
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Affiliation(s)
| | - Alida A Gouw
- VU Medical Center Alzheimer Center, Amsterdam, Netherlands.,Department of Clinical Neurophysiology, VU Medical Center, Amsterdam, Netherlands
| | | | | | - Cornelis Jan Stam
- Department of Clinical Neurophysiology, VU Medical Center, Amsterdam, Netherlands
| | - Afina W Lemstra
- VU Medical Center Alzheimer Center, Amsterdam, Netherlands.,Department of Clinical Neurophysiology, VU Medical Center, Amsterdam, Netherlands
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32
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Abstract
Despite decades of publications attesting to the role of the clinical EEG in diagnosing and managing psychiatric disorders, the procedure remains highly underutilized in the practice of psychiatry. The visually inspected EEG (vEEG) can detect various forms of abnormalities, each with its own clinical significance. Abnormalities can be paroxysmal (i.e., suggestive of an epileptic-like process) or stationary. The most important unanswered question remains the value of detecting epileptiform activity in a nonepileptic psychiatric patient in predicting favorable responses to anticonvulsant treatment. Despite the many shortcomings of vEEG, the available evidence suggests that in the presence of paroxysmal activity in a nonepileptic psychiatric patient a trial of a psychotropic anticonvulsant may be warranted if standard treatment has failed. More research on the contribution of paroxysmal EEG abnormalities to the problem of episodic psychiatric symptoms (e.g., panic attacks, dissociative episodes, repeated violence) is sorely needed. It is postulated that at least some of these conditions may represent an epilepsy spectrum disorder. Similarly, the significance of the presence of a slow-wave activity (whether focal or generalized) also deserves further well-designed research to ascertain the exact clinical significance. Nonetheless, the available data suggest that further medical workup is necessary to ascertain the nature and degree of the pathology when present.
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33
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Quantitative electroencephalography as a marker of cognitive fluctuations in dementia with Lewy bodies and an aid to differential diagnosis. Clin Neurophysiol 2018; 129:1209-1220. [PMID: 29656189 PMCID: PMC5954167 DOI: 10.1016/j.clinph.2018.03.013] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Revised: 02/07/2018] [Accepted: 03/10/2018] [Indexed: 12/16/2022]
Abstract
EEG slowing was evident in dementia with Lewy bodies (DLB) and Parkinson’s disease dementia (PDD) and less in Alzheimer’s disease (AD) patients compared to controls. Dominant rhythm variability was larger in AD but only correlated with cognitive fluctuations in DLB. QEEG variables classified DLB and AD patients with high sensitivity and specificity.
Objective We investigated for quantitative EEG (QEEG) differences between Alzheimer’s disease (AD), dementia with Lewy bodies (DLB) and Parkinson’s disease dementia (PDD) patients and healthy controls, and for QEEG signatures of cognitive fluctuations (CFs) in DLB. Methods We analysed eyes-closed, resting state EEGs from 18 AD, 17 DLB and 17 PDD patients with mild dementia, and 21 age-matched controls. Measures included spectral power, dominant frequency (DF), frequency prevalence (FP), and temporal DF variability (DFV), within defined EEG frequency bands and cortical regions. Results DLB and PDD patients showed a leftward shift in the power spectrum and DF. AD patients showed greater DFV compared to the other groups. In DLB patients only, greater DFV and EEG slowing were correlated with CFs, measured by the clinician assessment of fluctuations (CAF) scale. The diagnostic accuracy of the QEEG measures was 94% (90.4–97.9%), with 92.26% (80.4–100%) sensitivity and 83.3% (73.6–93%) specificity. Conclusion Although greater DFV was only shown in the AD group, within the DLB group a positive DFV – CF correlation was found. QEEG measures could classify DLB and AD patients with high sensitivity and specificity. Significance The findings add to an expanding literature suggesting that EEG is a viable diagnostic and symptom biomarker in dementia, particularly DLB.
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34
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Electroencephalographic derived network differences in Lewy body dementia compared to Alzheimer's disease patients. Sci Rep 2018; 8:4637. [PMID: 29545639 PMCID: PMC5854590 DOI: 10.1038/s41598-018-22984-5] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2017] [Accepted: 03/05/2018] [Indexed: 01/10/2023] Open
Abstract
Dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD) require differential management despite presenting with symptomatic overlap. Currently, there is a need of inexpensive DLB biomarkers which can be fulfilled by electroencephalography (EEG). In this regard, an established electrophysiological difference in DLB is a decrease of dominant frequency (DF)—the frequency with the highest signal power between 4 and 15 Hz. Here, we investigated network connectivity in EEG signals acquired from DLB patients, and whether these networks were able to differentiate DLB from healthy controls (HCs) and associated dementias. We analysed EEG recordings from old adults: HCs, AD, DLB and Parkinson’s disease dementia (PDD) patients. Brain networks were assessed with the minimum spanning tree (MST) within six EEG bands: delta, theta, high-theta, alpha, beta and DF. Patients showed lower alpha band connectivity and lower DF than HCs. DLB and PDD showed a randomised MST compared with HCs and AD in high-theta and alpha but not in DF. The MST randomisation in DLB and PDD reflects decreased brain efficiency as well as impaired neural synchronisation. However, the lack of network topology differences at the DF between all dementia groups and HCs may indicate a compensatory response of the brain to the neuropathology.
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35
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Robson E, Tweedy C, Manzanza N, Taylor JP, Atkinson P, Randall F, Reeve A, Clowry GJ, LeBeau FEN. Impaired Fast Network Oscillations and Mitochondrial Dysfunction in a Mouse Model of Alpha-synucleinopathy (A30P). Neuroscience 2018. [PMID: 29524634 DOI: 10.1016/j.neuroscience.2018.02.032] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Intracellular accumulation of alpha-synuclein (α-syn) is a key pathological process evident in Lewy body dementias (LBDs), including Parkinson's disease dementia (PDD) and dementia with Lewy bodies (DLB). LBD results in marked cognitive impairments and changes in cortical networks. To assess the impact of abnormal α-syn expression on cortical network oscillations relevant to cognitive function, we studied changes in fast beta/gamma network oscillations in the hippocampus in a mouse line that over-expresses human mutant α-syn (A30P). We found an age-dependent reduction in the power of the gamma (20-80 Hz) frequency oscillations in slices taken from mice aged 9-16 months (9+A30P), that was not present in either young 2-6 months old (2+A30P) mice, or in control mice at either age. The mitochondrial blockers potassium cyanide and rotenone both reduced network oscillations in a concentration-dependent manner in aged A30P mice and aged control mice but slices from A30P mice showed a greater reduction in the oscillations. Histochemical analysis showed an age-dependent reduction in cytochrome c oxidase (COX) activity, suggesting a mitochondrial dysfunction in the 9+A30P group. A deficit in COX IV expression was confirmed by immunohistochemistry. Overall, our data demonstrate an age-dependent impairment in mitochondrial function and gamma frequency activity associated with the abnormal expression of α-syn. These findings provide mechanistic insights into the consequences of over-expression of α-syn which might contribute to cognitive decline.
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Affiliation(s)
- Emma Robson
- Institute of Neuroscience, Newcastle University, Medical School, Framlington Place, Newcastle-upon-Tyne, NE2 4HH, UK
| | - Clare Tweedy
- Institute of Neuroscience, Newcastle University, Medical School, Framlington Place, Newcastle-upon-Tyne, NE2 4HH, UK
| | - Nelson Manzanza
- Institute of Neuroscience, Newcastle University, Medical School, Framlington Place, Newcastle-upon-Tyne, NE2 4HH, UK
| | - John-Paul Taylor
- Institute of Neuroscience, Newcastle University, Medical School, Framlington Place, Newcastle-upon-Tyne, NE2 4HH, UK
| | - Peter Atkinson
- Eisai Hatfield Research Laboratories, Eisai Ltd., European Knowledge Centre, Mosquito Way, Hatfield, Herts AL10 9SN, UK
| | - Fiona Randall
- Eisai AiM Institute, Eisai Inc., 4 Corporate Drive, Andover, MA 01810, USA
| | - Amy Reeve
- Institute of Neuroscience, Newcastle University, Medical School, Framlington Place, Newcastle-upon-Tyne, NE2 4HH, UK
| | - Gavin J Clowry
- Institute of Neuroscience, Newcastle University, Medical School, Framlington Place, Newcastle-upon-Tyne, NE2 4HH, UK
| | - Fiona E N LeBeau
- Institute of Neuroscience, Newcastle University, Medical School, Framlington Place, Newcastle-upon-Tyne, NE2 4HH, UK.
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36
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Jellinger KA, Korczyn AD. Are dementia with Lewy bodies and Parkinson's disease dementia the same disease? BMC Med 2018; 16:34. [PMID: 29510692 PMCID: PMC5840831 DOI: 10.1186/s12916-018-1016-8] [Citation(s) in RCA: 191] [Impact Index Per Article: 31.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2017] [Accepted: 01/30/2018] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD), which share many clinical, neurochemical, and morphological features, have been incorporated into DSM-5 as two separate entities of major neurocognitive disorders with Lewy bodies. Despite clinical overlap, their diagnosis is based on an arbitrary distinction concerning the time of onset of motor and cognitive symptoms, namely as early cognitive impairment in DLB and later onset following that of motor symptoms in PDD. Their morphological hallmarks - cortical and subcortical α-synuclein/Lewy body plus β-amyloid and tau pathologies - are similar, but clinical differences at onset suggest some dissimilar profiles. Based on recent publications, including the fourth consensus report of the DLB Consortium, a critical overview is provided herein. DISCUSSION The clinical constellations of DLB and PDD include cognitive impairment, parkinsonism, visual hallucinations, and fluctuating attention. Intravitam PET and postmortem studies have revealed a more pronounced cortical atrophy, elevated cortical and limbic Lewy body pathologies, higher Aβ and tau loads in cortex and striatum in DLB compared to PDD, and earlier cognitive defects in DLB. Conversely, multitracer PET studies have shown no differences in cortical and striatal cholinergic and dopaminergic deficits. Clinical management of both DLB and PDD includes cholinesterase inhibitors and other pharmacologic and non-drug strategies, yet with only mild symptomatic effects. Currently, no disease-modifying therapies are available. CONCLUSION DLB and PDD are important dementia syndromes that overlap in many clinical features, genetics, neuropathology, and management. They are currently considered as subtypes of an α-synuclein-associated disease spectrum (Lewy body diseases), from incidental Lewy body disease and non-demented Parkinson's disease to PDD, DLB, and DLB with Alzheimer's disease at the most severe end. Cognitive impairment in these disorders is induced not only by α-synuclein-related neurodegeneration but by multiple regional pathological scores. Both DLB and PDD show heterogeneous pathology and neurochemistry, suggesting that they share important common underlying molecular pathogenesis with Alzheimer's disease and other proteinopathies. While we prefer to view DLB and PDD as extremes on a continuum, there remains a pressing need to more clearly differentiate these syndromes and to understand the synucleinopathy processes leading to either one.
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Affiliation(s)
- Kurt A Jellinger
- Institute of Clinical Neurobiology, Alberichgasse 5/13, A-1150, Vienna, Austria.
| | - Amos D Korczyn
- Tel-Aviv University, Sackler Faculty of Medicine, Ramat Aviv, Israel
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Babiloni C, Del Percio C, Lizio R, Noce G, Lopez S, Soricelli A, Ferri R, Nobili F, Arnaldi D, Famà F, Aarsland D, Orzi F, Buttinelli C, Giubilei F, Onofrj M, Stocchi F, Stirpe P, Fuhr P, Gschwandtner U, Ransmayr G, Garn H, Fraioli L, Pievani M, Frisoni GB, D'Antonio F, De Lena C, Güntekin B, Hanoğlu L, Başar E, Yener G, Emek-Savaş DD, Triggiani AI, Franciotti R, Taylor JP, Vacca L, De Pandis MF, Bonanni L. Abnormalities of resting-state functional cortical connectivity in patients with dementia due to Alzheimer's and Lewy body diseases: an EEG study. Neurobiol Aging 2017; 65:18-40. [PMID: 29407464 DOI: 10.1016/j.neurobiolaging.2017.12.023] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Revised: 12/21/2017] [Accepted: 12/21/2017] [Indexed: 11/30/2022]
Abstract
Previous evidence showed abnormal posterior sources of resting-state delta (<4 Hz) and alpha (8-12 Hz) rhythms in patients with Alzheimer's disease with dementia (ADD), Parkinson's disease with dementia (PDD), and Lewy body dementia (DLB), as cortical neural synchronization markers in quiet wakefulness. Here, we tested the hypothesis of additional abnormalities in functional cortical connectivity computed in those sources, in ADD, considered as a "disconnection cortical syndrome", in comparison with PDD and DLB. Resting-state eyes-closed electroencephalographic (rsEEG) rhythms had been collected in 42 ADD, 42 PDD, 34 DLB, and 40 normal healthy older (Nold) participants. Exact low-resolution brain electromagnetic tomography (eLORETA) freeware estimated the functional lagged linear connectivity (LLC) from rsEEG cortical sources in delta, theta, alpha, beta, and gamma bands. The area under receiver operating characteristic (AUROC) curve indexed the classification accuracy between Nold and diseased individuals (only values >0.7 were considered). Interhemispheric and intrahemispheric LLCs in widespread delta sources were abnormally higher in the ADD group and, unexpectedly, normal in DLB and PDD groups. Intrahemispheric LLC was reduced in widespread alpha sources dramatically in ADD, markedly in DLB, and moderately in PDD group. Furthermore, the interhemispheric LLC in widespread alpha sources showed lower values in ADD and DLB than PDD groups. At the individual level, AUROC curves of LLC in alpha sources exhibited better classification accuracies for the discrimination of ADD versus Nold individuals (0.84) than for DLB versus Nold participants (0.78) and PDD versus Nold participants (0.75). Functional cortical connectivity markers in delta and alpha sources suggest a more compromised neurophysiological reserve in ADD than DLB, at both group and individual levels.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy; Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy.
| | | | - Roberta Lizio
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy; Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Giuseppe Noce
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy
| | - Andrea Soricelli
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy; Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Raffaele Ferri
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging, Troina, Enna, Italy
| | - Flavio Nobili
- Clinical Neurology, Department of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dario Arnaldi
- Clinical Neurology, Department of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Francesco Famà
- Clinical Neurology, Department of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dag Aarsland
- Department of Old Age Psychiatry, King's College University, London, UK
| | - Francesco Orzi
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Marco Onofrj
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Paola Stirpe
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Peter Fuhr
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Ute Gschwandtner
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Gerhard Ransmayr
- Department of Neurology and Psychiatry and Faculty of Medicine, Johannes Kepler University Linz, General Hospital of the City of Linz, Linz, Austria
| | - Heinrich Garn
- AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | | | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and 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
| | - Fabrizia D'Antonio
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Rome, Italy
| | - Carlo De Lena
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Rome, Italy
| | - Bahar Güntekin
- Department of Biophysics, Istanbul Medipol University, Istanbul, Turkey
| | - Lutfu Hanoğlu
- Department of Neurology, University of Istanbul-Medipol, Istanbul, Turkey
| | - Erol Başar
- IBG, Departments of Neurology and Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - Görsev Yener
- IBG, Departments of Neurology and Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - Derya Durusu Emek-Savaş
- Department of Psychology and Department of Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | | | - Raffaella Franciotti
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | - Laura Vacca
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy; Casa di Cura Privata del Policlinico (CCPP) Milano SpA, Milan, Italy
| | | | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
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Jellinger KA. Dementia with Lewy bodies and Parkinson's disease-dementia: current concepts and controversies. J Neural Transm (Vienna) 2017; 125:615-650. [PMID: 29222591 DOI: 10.1007/s00702-017-1821-9] [Citation(s) in RCA: 172] [Impact Index Per Article: 24.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 11/28/2017] [Indexed: 12/15/2022]
Abstract
Dementia with Lewy bodies (DLB) and Parkinson's disease-dementia (PDD), although sharing many clinical, neurochemical and morphological features, according to DSM-5, are two entities of major neurocognitive disorders with Lewy bodies of unknown etiology. Despite considerable clinical overlap, their diagnosis is based on an arbitrary distinction between the time of onset of motor and cognitive symptoms: dementia often preceding parkinsonism in DLB and onset of cognitive impairment after onset of motor symptoms in PDD. Both are characterized morphologically by widespread cortical and subcortical α-synuclein/Lewy body plus β-amyloid and tau pathologies. Based on recent publications, including the fourth consensus report of the DLB Consortium, a critical overview is given. The clinical features of DLB and PDD include cognitive impairment, parkinsonism, visual hallucinations, and fluctuating attention. Intravitam PET and post-mortem studies revealed more pronounced cortical atrophy, elevated cortical and limbic Lewy pathologies (with APOE ε4), apart from higher prevalence of Alzheimer pathology in DLB than PDD. These changes may account for earlier onset and greater severity of cognitive defects in DLB, while multitracer PET studies showed no differences in cholinergic and dopaminergic deficits. DLB and PDD sharing genetic, neurochemical, and morphologic factors are likely to represent two subtypes of an α-synuclein-associated disease spectrum (Lewy body diseases), beginning with incidental Lewy body disease-PD-nondemented-PDD-DLB (no parkinsonism)-DLB with Alzheimer's disease (DLB-AD) at the most severe end, although DLB does not begin with PD/PDD and does not always progress to DLB-AD, while others consider them as the same disease. Both DLB and PDD show heterogeneous pathology and neurochemistry, suggesting that they share important common underlying molecular pathogenesis with AD and other proteinopathies. Cognitive impairment is not only induced by α-synuclein-caused neurodegeneration but by multiple regional pathological scores. Recent animal models and human post-mortem studies have provided important insights into the pathophysiology of DLB/PDD showing some differences, e.g., different spreading patterns of α-synuclein pathology, but the basic pathogenic mechanisms leading to the heterogeneity between both disorders deserve further elucidation. In view of the controversies about the nosology and pathogenesis of both syndromes, there remains a pressing need to differentiate them more clearly and to understand the processes leading these synucleinopathies to cause one disorder or the other. Clinical management of both disorders includes cholinesterase inhibitors, other pharmacologic and nonpharmacologic strategies, but these have only a mild symptomatic effect. Currently, no disease-modifying therapies are available.
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Affiliation(s)
- Kurt A Jellinger
- Institute of Clinical Neurobiology, Alberichgasse 5/13, 1150, Vienna, Austria.
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Skogseth R, Hortobágyi T, Soennesyn H, Chwiszczuk L, Ffytche D, Rongve A, Ballard C, Aarsland D. Accuracy of Clinical Diagnosis of Dementia with Lewy Bodies versus Neuropathology. J Alzheimers Dis 2017; 59:1139-1152. [DOI: 10.3233/jad-170274] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Affiliation(s)
- Ragnhild Skogseth
- Haraldsplass Deaconess Hospital, Kavli Research Centre for Geriatrics and Dementia, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Tibor Hortobágyi
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- MTA-DE Cerebrovascular and Neurodegenerative Research Group, Departments of Neurology & Neuropathology, University of Debrecen, Debrecen, Hungary
| | - Hogne Soennesyn
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Luiza Chwiszczuk
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Department of Research and Innovation, Helse Fonna, Haugesund Hospital, Haugesund, Norway
| | - Dominic Ffytche
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Arvid Rongve
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Department of Research and Innovation, Helse Fonna, Haugesund Hospital, Haugesund, Norway
| | - Clive Ballard
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Dag Aarsland
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
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Babiloni C, Del Percio C, Lizio R, Noce G, Cordone S, Lopez S, Soricelli A, Ferri R, Pascarelli MT, Nobili F, Arnaldi D, Aarsland D, Orzi F, Buttinelli C, Giubilei F, Onofrj M, Stocchi F, Stirpe P, Fuhr P, Gschwandtner U, Ransmayr G, Caravias G, Garn H, Sorpresi F, Pievani M, Frisoni GB, D'Antonio F, De Lena C, Güntekin B, Hanoğlu L, Başar E, Yener G, Emek-Savaş DD, Triggiani AI, Franciotti R, De Pandis MF, Bonanni L. Abnormalities of cortical neural synchronization mechanisms in patients with dementia due to Alzheimer's and Lewy body diseases: an EEG study. Neurobiol Aging 2017; 55:143-158. [PMID: 28454845 DOI: 10.1016/j.neurobiolaging.2017.03.030] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Revised: 03/24/2017] [Accepted: 03/26/2017] [Indexed: 12/15/2022]
Abstract
The aim of this retrospective exploratory study was that resting state eyes-closed electroencephalographic (rsEEG) rhythms might reflect brain arousal in patients with dementia due to Alzheimer's disease dementia (ADD), Parkinson's disease dementia (PDD), and dementia with Lewy body (DLB). Clinical and rsEEG data of 42 ADD, 42 PDD, 34 DLB, and 40 healthy elderly (Nold) subjects were available in an international archive. Demography, education, and Mini-Mental State Evaluation score were not different between the patient groups. Individual alpha frequency peak (IAF) determined the delta, theta, alpha 1, alpha 2, and alpha 3 frequency bands. Fixed beta 1, beta 2, and gamma bands were also considered. rsEEG cortical sources were estimated by means of the exact low-resolution brain electromagnetic source tomography and were then classified across individuals, on the basis of the receiver operating characteristic curves. Compared to Nold, IAF showed marked slowing in PDD and DLB and moderate slowing in ADD. Furthermore, all patient groups showed lower posterior alpha 2 source activities. This effect was dramatic in ADD, marked in DLB, and moderate in PDD. These groups also showed higher occipital delta source activities, but this effect was dramatic in PDD, marked in DLB, and moderate in ADD. The posterior delta and alpha sources allowed good classification accuracy (approximately 0.85-0.90) between the Nold subjects and patients, and between ADD and PDD patients. In quiet wakefulness, delta and alpha sources unveiled different spatial and frequency features of the cortical neural synchronization underpinning brain arousal in ADD, PDD, and DLB patients. Future prospective cross-validation studies should test these rsEEG markers for clinical applications and drug discovery.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy; Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy.
| | | | - Roberta Lizio
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy; Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Giuseppe Noce
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy
| | - Susanna Cordone
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy
| | - Andrea Soricelli
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy; Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Raffaele Ferri
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging, Troina, Italy
| | - Maria Teresa Pascarelli
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging, Troina, Italy
| | - Flavio Nobili
- Department of Neuroscience (DiNOGMI), Clinical Neurology, University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dario Arnaldi
- Department of Neuroscience (DiNOGMI), Clinical Neurology, University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dag Aarsland
- Department of Old Age Psychiatry, King's College University, London, UK
| | - Francesco Orzi
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Marco Onofrj
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Paola Stirpe
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Peter Fuhr
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Ute Gschwandtner
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Gerhard Ransmayr
- Department of Neurology and Psychiatry and Faculty of Medicine, Johannes Kepler University Linz, General Hospital of the City of Linz, Linz, Austria
| | - Georg Caravias
- Department of Neurology and Psychiatry and Faculty of Medicine, Johannes Kepler University Linz, General Hospital of the City of Linz, Linz, Austria
| | - Heinrich Garn
- AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | | | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and 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
| | - Fabrizia D'Antonio
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Rome, Italy
| | - Carlo De Lena
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Rome, Italy
| | - Bahar Güntekin
- Department of Biophysics, Istanbul Medipol University, Istanbul, Turkey
| | - Lutfu Hanoğlu
- Department of Neurology, University of Istanbul-Medipol, Istanbul, Turkey
| | - Erol Başar
- Department of Neurosciences, Dokuz Eylül University Medical School, Izmir, Turkey; Department of Neurology, Dokuz Eylül University Medical School, Izmir, Turkey
| | - Görsev Yener
- Department of Psychology, Dokuz Eylül University, Izmir, Turkey; Department of Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - Derya Durusu Emek-Savaş
- Department of Psychology, Dokuz Eylül University, Izmir, Turkey; Department of Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | | | - Raffaella Franciotti
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
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Physiological Informatics: Collection and Analyses of Data from Wearable Sensors and Smartphone for Healthcare. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2017; 1028:17-37. [PMID: 29058214 DOI: 10.1007/978-981-10-6041-0_2] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Physiological data from wearable sensors and smartphone are accumulating rapidly, and this provides us the chance to collect dynamic and personalized information as phenotype to be integrated to genotype for the holistic understanding of complex diseases. This integration can be applied to early prediction and prevention of disease, therefore promoting the shifting of disease care tradition to the healthcare paradigm. In this chapter, we summarize the physiological signals which can be detected by wearable sensors, the sharing of the physiological big data, and the mining methods for the discovery of disease-associated patterns for personalized diagnosis and treatment. We discuss the challenges of physiological informatics about the storage, the standardization, the analyses, and the applications of the physiological data from the wearable sensors and smartphone. At last, we present our perspectives on the models for disentangling the complex relationship between early disease prediction and the mining of physiological phenotype data.
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