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Niu X, Wang Y, Zhang X, Wang Y, Shao W, Chen L, Yang Z, Peng D. Quantitative electroencephalography (qEEG), apolipoprotein A-I (APOA-I), and apolipoprotein epsilon 4 (APOE ɛ4) alleles for the diagnosis of mild cognitive impairment and Alzheimer's disease. Neurol Sci 2024; 45:547-556. [PMID: 37673807 DOI: 10.1007/s10072-023-07028-9] [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: 02/16/2023] [Accepted: 08/19/2023] [Indexed: 09/08/2023]
Abstract
INTRODUCTION Alzheimer's disease (AD) is the most common type of dementia. Amnestic mild cognitive impairment (aMCI), a pre-dementia stage is an important stage for early diagnosis and intervention. This study aimed to investigate the diagnostic value of qEEG, APOA-I, and APOE ɛ4 allele in aMCI and AD patients and found the correlation between qEEG (Delta + Theta)/(Alpha + Beta) ratio (DTABR) and different cognitive domains. METHODS All participants were divided into three groups: normal controls (NCs), aMCI, and AD, and all received quantitative electroencephalography (qEEG), neuropsychological scale assessment, apolipoprotein epsilon 4 (APOE ɛ4) alleles, and various blood lipid indicators. Different statistical methods were used for different data. RESULTS The cognitive domains except executive ability were all negatively correlated with DTABR in different brain regions while executive ability was positively correlated with DTABR in several brain regions, although without statistical significance. The consequences confirmed that the DTABR of each brain area were related to MMSE, MoCA, instantaneous memory, and the language ability (p < 0.05), and the DTABR in the occipital area was relevant to all cognitive domains (p < 0.01) except executive function (p = 0.272). Also, occipital DTABR was most correlated with language domain when tested by VFT with a moderate level (r = 0.596, p < 0.001). There were significant differences in T3, T5, and P3 DTABR between both AD and NC and aMCI and NCs. As for aMCI diagnosis, the maximum AUC was achieved when using T3 combined with APOA-I and APOE ε4 (0.855) and the maximum AUC was achieved when using T5 combined with APOA-I and APOE ε4 (0.889) for AD diagnosis. CONCLUSION These findings highlight that APOA-I, APOE ɛ4, and qEEG play an important role in aMCI and AD diagnosis. During AD continuum, qEEG DTABR should be taken into consideration for the early detection of AD risk.
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Affiliation(s)
- Xiaoqian Niu
- Department of Neurology, China-Japan Friendship Hospital, No. 2 Yinghuayuan East Street, Chaoyang District, Beijing, 100029, China
- Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China
| | - Yuye Wang
- Department of Neurology, China-Japan Friendship Hospital, No. 2 Yinghuayuan East Street, Chaoyang District, Beijing, 100029, China
- China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xiangfei Zhang
- Department of Neurology, China-Japan Friendship Hospital, No. 2 Yinghuayuan East Street, Chaoyang District, Beijing, 100029, China
| | - Yu Wang
- Department of Neurology, China-Japan Friendship Hospital, No. 2 Yinghuayuan East Street, Chaoyang District, Beijing, 100029, China
- Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China
| | - Wen Shao
- Department of Neurology, China-Japan Friendship Hospital, No. 2 Yinghuayuan East Street, Chaoyang District, Beijing, 100029, China
| | - Leian Chen
- Department of Neurology, China-Japan Friendship Hospital, No. 2 Yinghuayuan East Street, Chaoyang District, Beijing, 100029, China
- China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Ziyuan Yang
- Department of Neurology, China-Japan Friendship Hospital, No. 2 Yinghuayuan East Street, Chaoyang District, Beijing, 100029, China
- Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China
| | - Dantao Peng
- Department of Neurology, China-Japan Friendship Hospital, No. 2 Yinghuayuan East Street, Chaoyang District, Beijing, 100029, China.
- Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China.
- China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
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2
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Okumura E, Hoshi H, Morise H, Okumura N, Fukasawa K, Ichikawa S, Asakawa T, Shigihara Y. Reliability of Spectral Features of Resting-State Brain Activity: A Magnetoencephalography Study. Cureus 2024; 16:e52637. [PMID: 38249648 PMCID: PMC10799710 DOI: 10.7759/cureus.52637] [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] [Accepted: 01/20/2024] [Indexed: 01/23/2024] Open
Abstract
Background Cognition is a vital sign and its deterioration is a major concern in clinical medicine. It is usually evaluated using neuropsychological assessments, which have innate limitations such as the practice effect. To compensate for these assessments, the oscillatory power of resting-state brain activity has recently become available. The power is obtained noninvasively using magnetoencephalography and is summarized by spectral parameters such as the median frequency (MF), individual alpha frequency (IAF), spectral edge frequency 95 (SEF95), and Shannon's spectral entropy (SSE). As these parameters are less sensitive to practice effects, they are suitable for longitudinal studies. However, their reliability remains unestablished, hindering their proactive use in clinical practice. Therefore, we aimed to quantify the within-participant reliability of these parameters using repeated measurements of healthy participants to facilitate their clinical use and to evaluate the observed changes/differences in these parameters reported in previous studies. Methodology Resting-state brain activity with eyes closed was recorded using magnetoencephalography for five minutes from 15 healthy individuals (29.3 ± 4.6 years old: ranging from 23 to 28 years old). The following four spectral parameters were calculated: MF, IAF, SEF95, and SSE. To quantify reliability, the minimal detectable change (MDC) and intraclass correlation coefficient (ICC) were computed for each parameter. In addition, we used MDCs to evaluate the changes and differences in the spectral parameters reported in previous longitudinal and cross-sectional studies. Results The MDC at 95% confidence interval (MDC95) of MF, IAF, SEF95, and SSE were 0.61 Hz, 0.44 Hz, 2.91 Hz, and 0.028, respectively. The ICCs of these parameters were 0.96, 0.92, 0.94, and 0.83, respectively. The MDC95 of these parameters was smaller than the mean difference in the parameters between cognitively healthy individuals and patients with dementia, as reported in previous studies. Conclusions The spectral parameter changes/differences observed in prior studies were not attributed to measurement errors but rather reflected genuine effects. Furthermore, all spectral parameters exhibited high ICCs (>0.8), underscoring their robust within-participant reliability. Our results support the clinical use of these parameters, especially in the longitudinal monitoring and evaluation of the outcomes of interventions.
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Affiliation(s)
- Eiichi Okumura
- Medical Imaging Business Center, Ricoh Company, Ltd., Kanazawa, JPN
| | - Hideyuki Hoshi
- Medical Imaging Business Center, Ricoh Company, Ltd., Kanazawa, JPN
- Precision Medicine Centre, Hokuto Hospital, Obihiro, JPN
| | - Hirofumi Morise
- Medical Imaging Business Center, Ricoh Company, Ltd., Kanazawa, JPN
| | - Naohiro Okumura
- Medical Imaging Business Center, Ricoh Company, Ltd., Kanazawa, JPN
| | - Keisuke Fukasawa
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, JPN
| | - Sayuri Ichikawa
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, JPN
| | - Takashi Asakawa
- Medical Imaging Business Center, Ricoh Company, Ltd., Kanazawa, JPN
| | - Yoshihito Shigihara
- Precision Medicine Centre, Hokuto Hospital, Obihiro, JPN
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, JPN
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3
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Ponomareva NV, Andreeva TV, Protasova MS, Kunizheva SS, Kuznetsova IL, Kolesnikova EP, Malina DD, Mitrofanov AA, Fokin VF, Illarioshkin SN, Rogaev EI. Neuronal Hyperactivation in EEG Data during Cognitive Tasks Is Related to the Apolipoprotein J/Clusterin Genotype in Nondemented Adults. Int J Mol Sci 2023; 24:6790. [PMID: 37047762 PMCID: PMC10095572 DOI: 10.3390/ijms24076790] [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: 12/26/2022] [Revised: 03/24/2023] [Accepted: 03/30/2023] [Indexed: 04/08/2023] Open
Abstract
The clusterin (CLU) rs11136000 CC genotype is a probable risk factor for Alzheimer's disease (AD). CLU, also known as the apolipoprotein J gene, shares certain properties with the apolipoprotein E (APOE) gene with a well-established relationship with AD. This study aimed to determine whether the electrophysiological patterns of brain activation during the letter fluency task (LFT) depend on CLU genotypes in adults without dementia. Previous studies have shown that LFT performance involves activation of the frontal cortex. We examined EEG alpha1 and alpha2 band desynchronization in the frontal regions during the LFT in 94 nondemented individuals stratified by CLU (rs11136000) genotype. Starting at 30 years of age, CLU CC carriers exhibited more pronounced task-related alpha2 desynchronization than CLU CT&TT carriers in the absence of any differences in LFT performance. In CLU CC carriers, alpha2 desynchronization was significantly correlated with age. Increased task-related activation in individuals at genetic risk for AD may reflect greater "effort" to perform the task and/or neuronal hyperexcitability. The results show that the CLU genotype is associated with neuronal hyperactivation in the frontal cortex during cognitive tasks performances in nondemented individuals, suggesting systematic vulnerability of LFT related cognitive networks in people carrying unfavorable CLU alleles.
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Affiliation(s)
- Natalya V. Ponomareva
- Research Center of Neurology, 125367 Moscow, Russia
- Center for Genetics and Life Science, Sirius University of Science and Technology, 354349 Sochi, Russia
| | - Tatiana V. Andreeva
- Center for Genetics and Life Science, Sirius University of Science and Technology, 354349 Sochi, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
- Centre for Genetics and Genetic Technologies, Faculty of Biology, Lomonosov Moscow State University, 119192 Moscow, Russia
| | - Maria S. Protasova
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Svetlana S. Kunizheva
- Center for Genetics and Life Science, Sirius University of Science and Technology, 354349 Sochi, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Irina L. Kuznetsova
- Center for Genetics and Life Science, Sirius University of Science and Technology, 354349 Sochi, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
| | | | | | | | | | | | - Evgeny I. Rogaev
- Center for Genetics and Life Science, Sirius University of Science and Technology, 354349 Sochi, Russia
- Department of Psychiatry, Umass Chan Medical School, Shrewsbury, MA 01545, USA
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4
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Ponomareva NV, Andreeva TV, Protasova M, Konovalov RN, Krotenkova MV, Kolesnikova EP, Malina DD, Kanavets EV, Mitrofanov AA, Fokin VF, Illarioshkin SN, Rogaev EI. Genetic association of apolipoprotein E genotype with EEG alpha rhythm slowing and functional brain network alterations during normal aging. Front Neurosci 2022; 16:931173. [PMID: 35979332 PMCID: PMC9376365 DOI: 10.3389/fnins.2022.931173] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 06/27/2022] [Indexed: 12/02/2022] Open
Abstract
The ε4 allele of the apolipoprotein E (APOE4+) genotype is a major genetic risk factor for Alzheimer’s disease (AD), but the mechanisms underlying its influence remain incompletely understood. The study aimed to investigate the possible effect of the APOE genotype on spontaneous electroencephalogram (EEG) alpha characteristics, resting-state functional MRI (fMRI) connectivity (rsFC) in large brain networks and the interrelation of alpha rhythm and rsFC characteristics in non-demented adults during aging. We examined the EEG alpha subband’s relative power, individual alpha peak frequency (IAPF), and fMRI rsFC in non-demented volunteers (age range 26–79 years) stratified by the APOE genotype. The presence of the APOE4+ genotype was associated with lower IAPF and lower relative power of the 11–13 Hz alpha subbands. The age related decrease in EEG IAPF was more pronounced in the APOE4+ carriers than in the APOE4+ non-carriers (APOE4-). The APOE4+ carriers had a stronger fMRI positive rsFC of the interhemispheric regions of the frontoparietal, lateral visual and salience networks than the APOE4– individuals. In contrast, the negative rsFC in the network between the left hippocampus and the right posterior parietal cortex was reduced in the APOE4+ carriers compared to the non-carriers. Alpha rhythm slowing was associated with the dysfunction of hippocampal networks. Our results show that in adults without dementia APOE4+ genotype is associated with alpha rhythm slowing and that this slowing is age-dependent. Our data suggest predominant alterations of inhibitory processes in large-scale brain network of non-demented APOE4+ carriers. Moreover, dysfunction of large-scale hippocampal network can influence APOE-related alpha rhythm vulnerability.
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Affiliation(s)
- Natalya V. Ponomareva
- Research Center of Neurology, Moscow, Russia
- Center for Genetics and Life Science, Sirius University of Science and Technology, Sochi, Russia
- *Correspondence: Natalya V. Ponomareva,
| | - Tatiana V. Andreeva
- Center for Genetics and Life Science, Sirius University of Science and Technology, Sochi, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences (RAS), Moscow, Russia
| | - Maria Protasova
- Center for Genetics and Life Science, Sirius University of Science and Technology, Sochi, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences (RAS), Moscow, Russia
| | | | | | | | | | | | | | | | | | - Evgeny I. Rogaev
- Center for Genetics and Life Science, Sirius University of Science and Technology, Sochi, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences (RAS), Moscow, Russia
- Brudnick Neuropsychiatric Research Institute (BNRI), University of Massachusetts Medical School, Worcester, MA, United States
- Evgeny I. Rogaev,
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5
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Chino-Vilca B, Concepción Rodríguez-Rojo I, Torres-Simón L, Cuesta P, Carnes Vendrell A, Piñol-Ripoll G, Huerto R, Tahan N, Maestú F. Sex specific EEG signatures associated with cerebrospinal fluid biomarkers in mild cognitive impairment. Clin Neurophysiol 2022; 142:190-198. [DOI: 10.1016/j.clinph.2022.08.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 06/07/2022] [Accepted: 08/06/2022] [Indexed: 11/25/2022]
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6
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Smailovic U, Johansson C, Koenig T, Kåreholt I, Graff C, Jelic V. Decreased Global EEG Synchronization in Amyloid Positive Mild Cognitive Impairment and Alzheimer's Disease Patients-Relationship to APOE ε4. Brain Sci 2021; 11:brainsci11101359. [PMID: 34679423 PMCID: PMC8533770 DOI: 10.3390/brainsci11101359] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 10/07/2021] [Accepted: 10/08/2021] [Indexed: 11/16/2022] Open
Abstract
The apolipoprotein E (APOE) ε4 allele is a risk factor for Alzheimer's disease (AD) that has been linked to changes in brain structure and function as well as to different biological subtypes of the disease. The present study aimed to investigate the association of APOE ε4 genotypes with brain functional impairment, as assessed by quantitative EEG (qEEG) in patients on the AD continuum. The study population included 101 amyloid positive patients diagnosed with mild cognitive impairment (MCI) (n = 50) and AD (n = 51) that underwent resting-state EEG recording and CSF Aβ42 analysis. In total, 31 patients were APOE ε4 non-carriers, 42 were carriers of one, and 28 were carriers of two APOE ε4 alleles. Quantitative EEG analysis included computation of the global field power (GFP) and global field synchronization (GFS) in conventional frequency bands. Amyloid positive patients who were carriers of APOE ε4 allele(s) had significantly higher GFP beta and significantly lower GFS in theta and beta bands compared to APOE ε4 non-carriers. Increased global EEG power in beta band in APOE ε4 carriers may represent a brain functional compensatory mechanism that offsets global EEG slowing in AD patients. Our findings suggest that decreased EEG measures of global synchronization in theta and beta bands reflect brain functional deficits related to the APOE ε4 genotype in patients that are on a biomarker-verified AD continuum.
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Affiliation(s)
- Una Smailovic
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 14152 Huddinge, Sweden;
- Department of Clinical Neurophysiology, Karolinska University Hospital, 14186 Huddinge, Sweden
- Correspondence:
| | - Charlotte Johansson
- Division of Neurogeriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 14152 Huddinge, Sweden; (C.J.); (C.G.)
- Clinic for Cognitive Disorders, Karolinska University Hospital, 14186 Huddinge, Sweden
| | - Thomas Koenig
- Translational Research Center, University Hospital of Psychiatry, University of Bern, 3012 Bern, Switzerland;
| | - Ingemar Kåreholt
- Aging Research Centre, Karolinska Institutet and Stockholm University, 17165 Solna, Sweden;
- School of Health and Welfare, Aging Research Network—Jönköping (ARN-J), Institute for Gerontology, Jönköping University, 55111 Jönköping, Sweden
| | - Caroline Graff
- Division of Neurogeriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 14152 Huddinge, Sweden; (C.J.); (C.G.)
- Unit for Hereditary Dementia, Karolinska University Hospital-Solna, 17176 Solna, Sweden
| | - Vesna Jelic
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 14152 Huddinge, Sweden;
- Clinic for Cognitive Disorders, Karolinska University Hospital, 14186 Huddinge, Sweden
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7
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Babiloni C, Arakaki X, Azami H, Bennys K, Blinowska K, Bonanni L, Bujan A, Carrillo MC, Cichocki A, de Frutos-Lucas J, Del Percio C, Dubois B, Edelmayer R, Egan G, Epelbaum S, Escudero J, Evans A, Farina F, Fargo K, Fernández A, Ferri R, Frisoni G, Hampel H, Harrington MG, Jelic V, Jeong J, Jiang Y, Kaminski M, Kavcic V, Kilborn K, Kumar S, Lam A, Lim L, Lizio R, Lopez D, Lopez S, Lucey B, Maestú F, McGeown WJ, McKeith I, Moretti DV, Nobili F, Noce G, Olichney J, Onofrj M, Osorio R, Parra-Rodriguez M, Rajji T, Ritter P, Soricelli A, Stocchi F, Tarnanas I, Taylor JP, Teipel S, Tucci F, Valdes-Sosa M, Valdes-Sosa P, Weiergräber M, Yener G, Guntekin B. Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: Recommendations of an expert panel. Alzheimers Dement 2021; 17:1528-1553. [PMID: 33860614 DOI: 10.1002/alz.12311] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 12/28/2020] [Accepted: 01/01/2021] [Indexed: 12/25/2022]
Abstract
The Electrophysiology Professional Interest Area (EPIA) and Global Brain Consortium endorsed recommendations on candidate electroencephalography (EEG) measures for Alzheimer's disease (AD) clinical trials. The Panel reviewed the field literature. As most consistent findings, AD patients with mild cognitive impairment and dementia showed abnormalities in peak frequency, power, and "interrelatedness" at posterior alpha (8-12 Hz) and widespread delta (< 4 Hz) and theta (4-8 Hz) rhythms in relation to disease progression and interventions. The following consensus statements were subscribed: (1) Standardization of instructions to patients, resting state EEG (rsEEG) recording methods, and selection of artifact-free rsEEG periods are needed; (2) power density and "interrelatedness" rsEEG measures (e.g., directed transfer function, phase lag index, linear lagged connectivity, etc.) at delta, theta, and alpha frequency bands may be use for stratification of AD patients and monitoring of disease progression and intervention; and (3) international multisectoral initiatives are mandatory for regulatory purposes.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,San Raffaele of Cassino, Cassino (FR), Italy
| | | | - Hamed Azami
- Department of Neurology and Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Karim Bennys
- Centre Mémoire de Ressources et de Recherche (CMRR), Centre Hospitalier, Universitaire de Montpellier, Montpellier, France
| | - Katarzyna Blinowska
- Institute of Biocybernetics, Warsaw, Poland.,Faculty of Physics University of Warsaw and Nalecz, Warsaw, Poland
| | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Ana Bujan
- Psychological Neuroscience Lab, School of Psychology, University of Minho, Minho, Portugal
| | - Maria C Carrillo
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Andrzej Cichocki
- Skolkowo Institute of Science and Technology (SKOLTECH), Moscow, Russia.,Systems Research Institute PAS, Warsaw, Poland.,Nicolaus Copernicus University (UMK), Torun, Poland
| | - Jaisalmer de Frutos-Lucas
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Bruno Dubois
- Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Institute of Memory and Alzheimer's Disease (IM2A), Paris, France.,ICM, INSERM U1127, CNRS UMR 7225, Sorbonne Université, Institut du Cerveau et de la Moelle épinière, Paris, France
| | - Rebecca Edelmayer
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Gary Egan
- Foundation Director of the Monash Biomedical Imaging (MBI) Research Facilities, Monash University, Clayton, Australia
| | - Stephane Epelbaum
- Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Institute of Memory and Alzheimer's Disease (IM2A), Paris, France.,ICM, INSERM U1127, CNRS UMR 7225, Sorbonne Université, Institut du Cerveau et de la Moelle épinière, Paris, France
| | - Javier Escudero
- School of Engineering, Institute for Digital Communications, The University of Edinburgh, Edinburgh, UK
| | - Alan Evans
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
| | - Francesca Farina
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Keith Fargo
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Alberto Fernández
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | | | - Giovanni Frisoni
- IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Harald Hampel
- GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Sorbonne University, Paris, France
| | | | - Vesna Jelic
- Division of Clinical Geriatrics, NVS Department, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Jaeseung Jeong
- Department of Bio and Brain Engineering/Program of Brain and Cognitive Engineering Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
| | - Yang Jiang
- Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, Kentucky, USA
| | - Maciej Kaminski
- Faculty of Physics University of Warsaw and Nalecz, Warsaw, Poland
| | - Voyko Kavcic
- Institute of Gerontology, Wayne State University, Detroit, Michigan, USA
| | - Kerry Kilborn
- School of Psychology, University of Glasgow, Glasgow, UK
| | - Sanjeev Kumar
- Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Alice Lam
- MGH Epilepsy Service, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Lew Lim
- Vielight Inc., Toronto, Ontario, Canada
| | | | - David Lopez
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Brendan Lucey
- Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - William J McGeown
- School of Psychological Sciences and Health, University of Strathclyde, Glasgow, UK
| | - Ian McKeith
- Newcastle upon Tyne, Translational and Clinical Research Institute, Newcastle University, UK
| | | | - Flavio Nobili
- Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy.,Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | | | - John Olichney
- UC Davis Department of Neurology and Center for Mind and Brain, Davis, California, USA
| | - Marco Onofrj
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Ricardo Osorio
- Center for Brain Health, Department of Psychiatry, NYU Langone Medical Center, New York, New York, USA
| | | | - Tarek Rajji
- Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Petra Ritter
- Brain Simulation Section, Department of Neurology, Charité Universitätsmedizin and Berlin Institute of Health, Berlin, Germany.,Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Andrea Soricelli
- IRCCS SDN, Napoli, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | | | - Ioannis Tarnanas
- Global Brain Health Institute, University of California San Francisco, San Francisco, USA.,Global Brain Health Institute, Trinity College Dublin, Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - John Paul Taylor
- Newcastle upon Tyne, Translational and Clinical Research Institute, Newcastle University, UK
| | - Stefan Teipel
- Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany.,German Center for Neurodegenerative Diseases (DZNE) - Rostock/Greifswald, Rostock, Germany
| | - Federico Tucci
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | | | - Pedro Valdes-Sosa
- Cuban Neuroscience Center, Havana, Cuba.,Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Marco Weiergräber
- Experimental Neuropsychopharmacology, BfArM), Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, Bonn, Germany
| | - Gorsev Yener
- Departments of Neurosciences and Department of Neurology, Dokuz Eylül University Medical School, Izmir, Turkey
| | - Bahar Guntekin
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey.,REMER, Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab, Istanbul Medipol University, Istanbul, Turkey
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8
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Macedo A, Gómez C, Rebelo MÂ, Poza J, Gomes I, Martins S, Maturana-Candelas A, Pablo VGD, Durães L, Sousa P, Figueruelo M, Rodríguez M, Pita C, Arenas M, Álvarez L, Hornero R, Lopes AM, Pinto N. Risk Variants in Three Alzheimer's Disease Genes Show Association with EEG Endophenotypes. J Alzheimers Dis 2021; 80:209-223. [PMID: 33522999 PMCID: PMC8075394 DOI: 10.3233/jad-200963] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Background: Dementia due to Alzheimer’s disease (AD) is a complex neurodegenerative disorder, which much of heritability remains unexplained. At the clinical level, one of the most common physiological alterations is the slowing of oscillatory brain activity, measurable by electroencephalography (EEG). Relative power (RP) at the conventional frequency bands (i.e., delta, theta, alpha, beta-1, and beta-2) can be considered as AD endophenotypes. Objective: The aim of this work is to analyze the association between sixteen genes previously related with AD: APOE, PICALM, CLU, BCHE, CETP, CR1, SLC6A3, GRIN2
β, SORL1, TOMM40, GSK3
β, UNC5C, OPRD1, NAV2, HOMER2, and IL1RAP, and the slowing of the brain activity, assessed by means of RP at the aforementioned frequency bands. Methods: An Iberian cohort of 45 elderly controls, 45 individuals with mild cognitive impairment, and 109 AD patients in the three stages of the disease was considered. Genomic information and brain activity of each subject were analyzed. Results: The slowing of brain activity was observed in carriers of risk alleles in IL1RAP (rs10212109, rs9823517, rs4687150), UNC5C (rs17024131), and NAV2 (rs1425227, rs862785) genes, regardless of the disease status and situation towards the strongest risk factors: age, sex, and APOE ɛ4 presence. Conclusion: Endophenotypes reduce the complexity of the general phenotype and genetic variants with a major effect on those specific traits may be then identified. The found associations in this work are novel and may contribute to the comprehension of AD pathogenesis, each with a different biological role, and influencing multiple factors involved in brain physiology.
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Affiliation(s)
- Ana Macedo
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,JTA: The Data Scientists, Porto, Portugal
| | - Carlos Gómez
- Grupo de Ingeniería Biomédica, Universidad de Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain
| | - Miguel Ângelo Rebelo
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Jesús Poza
- Grupo de Ingeniería Biomédica, Universidad de Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain.,Instituto de Investigación en Matemáticas (IMUVA), Universidad de Valladolid, Valladolid, Spain
| | - Iva Gomes
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Sandra Martins
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | | | | | - Luis Durães
- Associação Portuguesa de Familiares e Amigos de Doentes de Alzheimer, Lavra, Portugal
| | - Patrícia Sousa
- Associação Portuguesa de Familiares e Amigos de Doentes de Alzheimer, Lavra, Portugal
| | - Manuel Figueruelo
- Asociación de Familiares y Amigos de Enfermos de Alzheimer y otras demencias de Zamora, Zamora, Spain
| | - María Rodríguez
- Asociación de Familiares y Amigos de Enfermos de Alzheimer y otras demencias de Zamora, Zamora, Spain
| | - Carmen Pita
- Asociación de Familiares y Amigos de Enfermos de Alzheimer y otras demencias de Zamora, Zamora, Spain
| | - Miguel Arenas
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,CINBIO (Biomedical Research Center), University of Vigo, Vigo, Spain.,Department of Biochemistry, Genetics and Immunology, University of Vigo, Vigo, Spain
| | - Luis Álvarez
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,Adeneas, Valencia, Spain
| | - Roberto Hornero
- Grupo de Ingeniería Biomédica, Universidad de Valladolid, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain.,Instituto de Investigación en Matemáticas (IMUVA), Universidad de Valladolid, Valladolid, Spain
| | - Alexandra M Lopes
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Nádia Pinto
- IPATIMUP - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, Portugal.,i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,Centro de Matemática da Universidade do Porto, Porto, Portugal
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9
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Abstract
Currently established and employed biomarkers of Alzheimer's disease (AD) predominantly mirror AD-associated molecular and structural brain changes. While they are necessary for identifying disease-specific neuropathology, they lack a clear and robust relationship with the clinical presentation of dementia; they can be altered in healthy individuals, while they often inadequately mirror the degree of cognitive and functional deficits in affected subjects. There is growing evidence that synaptic loss and dysfunction are early events during the trajectory of AD pathogenesis that best correlate with the clinical symptoms, suggesting measures of brain functional deficits as candidate early markers of AD. Resting-state electroencephalography (EEG) is a widely available and noninvasive diagnostic method that provides direct insight into brain synaptic activity in real time. Quantitative EEG (qEEG) analysis additionally provides information on physiologically meaningful frequency components, dynamic alterations and topography of EEG signal generators, i.e. neuronal signaling. Numerous studies have shown that qEEG measures can detect disruptions in activity, topographical distribution and synchronization of neuronal (synaptic) activity such as generalized EEG slowing, reduced global synchronization and anteriorization of neuronal generators of fast-frequency resting-state EEG activity in patients along the AD continuum. Moreover, qEEG measures appear to correlate well with surrogate markers of AD neuropathology and discriminate between different types of dementia, making them promising low-cost and noninvasive markers of AD. Future large-scale longitudinal clinical studies are needed to elucidate the diagnostic and prognostic potential of qEEG measures as early functional markers of AD on an individual subject level.
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Affiliation(s)
- Una Smailovic
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden.
| | - Vesna Jelic
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Clinic for Cognitive Disorders, Theme Aging, Karolinska University Hospital, Huddinge, Sweden
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10
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Nakamura A, Cuesta P, Fernández A, Arahata Y, Iwata K, Kuratsubo I, Bundo M, Hattori H, Sakurai T, Fukuda K, Washimi Y, Endo H, Takeda A, Diers K, Bajo R, Maestú F, Ito K, Kato T. Electromagnetic signatures of the preclinical and prodromal stages of Alzheimer's disease. Brain 2019. [PMID: 29522156 PMCID: PMC5920328 DOI: 10.1093/brain/awy044] [Citation(s) in RCA: 97] [Impact Index Per Article: 19.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Biomarkers useful for the predementia stages of Alzheimer’s disease are needed. Electroencephalography and magnetoencephalography (MEG) are expected to provide potential biomarker candidates for evaluating the predementia stages of Alzheimer’s disease. However, the physiological relevance of EEG/MEG signal changes and their role in pathophysiological processes such as amyloid-β deposition and neurodegeneration need to be elucidated. We evaluated 28 individuals with mild cognitive impairment and 38 cognitively normal individuals, all of whom were further classified into amyloid-β-positive mild cognitive impairment (n = 17, mean age 74.7 ± 5.4 years, nine males), amyloid-β-negative mild cognitive impairment (n = 11, mean age 73.8 ± 8.8 years, eight males), amyloid-β-positive cognitively normal (n = 13, mean age 71.8 ± 4.4 years, seven males), and amyloid-β-negative cognitively normal (n = 25, mean age 72.5 ± 3.4 years, 11 males) individuals using Pittsburgh compound B-PET. We measured resting state MEG for 5 min with the eyes closed, and investigated regional spectral patterns of MEG signals using atlas-based region of interest analysis. Then, the relevance of the regional spectral patterns and their associations with pathophysiological backgrounds were analysed by integrating information from Pittsburgh compound B-PET, fluorodeoxyglucose-PET, structural MRI, and cognitive tests. The results demonstrated that regional spectral patterns of resting state activity could be separated into several types of MEG signatures as follows: (i) the effects of amyloid-β deposition were expressed as the alpha band power augmentation in medial frontal areas; (ii) the delta band power increase in the same region was associated with disease progression within the Alzheimer’s disease continuum and was correlated with entorhinal atrophy and an Alzheimer’s disease-like regional decrease in glucose metabolism; and (iii) the global theta power augmentation, which was previously considered to be an Alzheimer’s disease-related EEG/MEG signature, was associated with general cognitive decline and hippocampal atrophy, but was not specific to Alzheimer’s disease because these changes could be observed in the absence of amyloid-β deposition. The results suggest that these MEG signatures may be useful as unique biomarkers for the predementia stages of Alzheimer’s disease.
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Affiliation(s)
- Akinori Nakamura
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Pablo Cuesta
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, 28223, Spain.,Electrical Engineering and Bioengineering Lab, Department of Industrial Engineering, University of La Laguna, Tenerife, 38200, Spain
| | - Alberto Fernández
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, 28223, Spain.,Department of Psychiatry, Faculty of Medicine, Complutense University of Madrid, Madrid, 28040, Spain
| | - Yutaka Arahata
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,Innovation Center for Clinical Research, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Kaori Iwata
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Izumi Kuratsubo
- Innovation Center for Clinical Research, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Masahiko Bundo
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Hideyuki Hattori
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Takashi Sakurai
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Koji Fukuda
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Yukihiko Washimi
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Hidetoshi Endo
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Akinori Takeda
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Kersten Diers
- Department of Psychology, Technische Universität Dresden, Dresden, 01069, Germany
| | - Ricardo Bajo
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, 28223, Spain
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, 28223, Spain.,Department of Basic Psychology II, Complutense University of Madrid, Madrid, 28223, Spain
| | - Kengo Ito
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,Innovation Center for Clinical Research, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Takashi Kato
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
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11
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Koelewijn L, Lancaster TM, Linden D, Dima DC, Routley BC, Magazzini L, Barawi K, Brindley L, Adams R, Tansey KE, Bompas A, Tales A, Bayer A, Singh K. Oscillatory hyperactivity and hyperconnectivity in young APOE-ɛ4 carriers and hypoconnectivity in Alzheimer's disease. eLife 2019; 8:e36011. [PMID: 31038453 PMCID: PMC6491037 DOI: 10.7554/elife.36011] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Accepted: 04/17/2019] [Indexed: 11/14/2022] Open
Abstract
We studied resting-state oscillatory connectivity using magnetoencephalography in healthy young humans (N = 183) genotyped for APOE-ɛ4, the greatest genetic risk for Alzheimer's disease (AD). Connectivity across frequencies, but most prevalent in alpha/beta, was increased in APOE-ɛ4 in a set of mostly right-hemisphere connections, including lateral parietal and precuneus regions of the Default Mode Network. Similar regions also demonstrated hyperactivity, but only in gamma (40-160 Hz). In a separate study of AD patients, hypoconnectivity was seen in an extended bilateral network that partially overlapped with the hyperconnected regions seen in young APOE-ɛ4 carriers. Using machine-learning, AD patients could be distinguished from elderly controls with reasonable sensitivity and specificity, while young APOE-e4 carriers could also be distinguished from their controls with above chance performance. These results support theories of initial hyperconnectivity driving eventual profound disconnection in AD and suggest that this is present decades before the onset of AD symptomology.
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Affiliation(s)
- Loes Koelewijn
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUnited Kingdom
| | - Thomas M Lancaster
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUnited Kingdom
- Neuroscience and Mental Health Research Institute, Cardiff UniversityCardiffUnited Kingdom
- MRC Centre for Neuropsychiatric Genetics and GenomicsCardiff UniversityCardiffUnited Kingdom
| | - David Linden
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUnited Kingdom
- Neuroscience and Mental Health Research Institute, Cardiff UniversityCardiffUnited Kingdom
- MRC Centre for Neuropsychiatric Genetics and GenomicsCardiff UniversityCardiffUnited Kingdom
| | - Diana C Dima
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUnited Kingdom
| | - Bethany C Routley
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUnited Kingdom
| | - Lorenzo Magazzini
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUnited Kingdom
| | - Kali Barawi
- MRC Centre for Neuropsychiatric Genetics and GenomicsCardiff UniversityCardiffUnited Kingdom
| | - Lisa Brindley
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUnited Kingdom
| | - Rachael Adams
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUnited Kingdom
| | - Katherine E Tansey
- Core Bioinformatics and Statistics Team, College of Biomedical and Life Sciences, Cardiff UniversityCardiffUnited Kingdom
| | - Aline Bompas
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUnited Kingdom
| | - Andrea Tales
- Department of PsychologyCollege of Human and Health Sciences, Swansea UniversitySwanseaUnited Kingdom
| | - Antony Bayer
- School of Medicine, Cardiff UniversityCardiffUnited Kingdom
| | - Krish Singh
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUnited Kingdom
- Neuroscience and Mental Health Research Institute, Cardiff UniversityCardiffUnited Kingdom
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12
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van der Flier WM, Scheltens P. Amsterdam Dementia Cohort: Performing Research to Optimize Care. J Alzheimers Dis 2018; 62:1091-1111. [PMID: 29562540 PMCID: PMC5870023 DOI: 10.3233/jad-170850] [Citation(s) in RCA: 196] [Impact Index Per Article: 32.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/04/2017] [Indexed: 01/01/2023]
Abstract
The Alzheimer center of the VU University Medical Center opened in 2000 and was initiated to combine both patient care and research. Together, to date, all patients forming the Amsterdam Dementia Cohort number almost 6,000 individuals. In this cohort profile, we provide an overview of the results produced based on the Amsterdam Dementia Cohort. We describe the main results over the years in each of these research lines: 1) early diagnosis, 2) heterogeneity, and 3) vascular factors. Among the most important research efforts that have also impacted patients' lives and/or the research field, we count the development of novel, easy to use diagnostic measures such as visual rating scales for MRI and the Amsterdam IADL Questionnaire, insight in different subgroups of AD, and findings on incidence and clinical sequelae of microbleeds. Finally, we describe in the outlook how our research endeavors have improved the lives of our patients.
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Affiliation(s)
- Wiesje M. van der Flier
- Department of Neurology, Alzheimer Center, VU University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | - Philip Scheltens
- Department of Neurology, Alzheimer Center, VU University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
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13
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Ochoa JF, Alonso JF, Duque JE, Tobón CA, Baena A, Lopera F, Mañanas MA, Hernández AM. Precuneus Failures in Subjects of the PSEN1 E280A Family at Risk of Developing Alzheimer's Disease Detected Using Quantitative Electroencephalography. J Alzheimers Dis 2017; 58:1229-1244. [PMID: 28550254 DOI: 10.3233/jad-161291] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Presenilin-1 (PSEN1) mutations are the most common cause of familial early onset Alzheimer's disease (AD). The PSEN1 E280A (E280A) mutation has an autosomal dominant inheritance and is involved in the production of amyloid-β. The largest family group of carriers with E280A mutation is found in Antioquia, Colombia. The study of mutation carriers provides a unique opportunity to identify brain changes in stages previous to AD. Electroencephalography (EEG) is a low cost and minimally invasiveness technique that enables the following of brain changes in AD. OBJECTIVE To examine how previous reported differences in EEG for Theta and Alpha-2 rhythms in E280A subjects are related to specific regions in cortex and could be tracked across different ages. METHODS EEG signals were acquired during resting state from non-carriers and carriers, asymptomatic and symptomatic subjects from E280A kindred from Antioquia, Colombia. Independent component analysis (ICA) and inverse solution methods were used to locate brain regions related to differences in Theta and Alpha-2 bands. RESULTS ICA identified two components, mainly related to the Precuneus, where the differences in Theta and Alpha-2 exist simultaneously at asymptomatic and symptomatic stages. When the ratio between Theta and Alpha-2 is used, significant correlations exist with age and a composite cognitive scale. CONCLUSION Theta and Alpha-2 rhythms are altered in E280A subjects. The alterations are possible to track at Precuneus regions using EEG, ICA, and inverse solution methods.
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Affiliation(s)
- John Fredy Ochoa
- Bioinstrumentation and Clinical Engineering Research Group, Bioengineering Program, Universidad de Antioquia, Medellín, Colombia
| | - Joan Francesc Alonso
- Department of Automatic Control (ESAII), Biomedical Engineering Research Center (CREB), Universitat Politènica de Catalunya (UPC), Barcelona, Spain.,Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain
| | - Jon Edinson Duque
- Bioinstrumentation and Clinical Engineering Research Group, Bioengineering Program, Universidad de Antioquia, Medellín, Colombia
| | - Carlos Andrés Tobón
- Neuroscience Group of Antioquia, Medical School, Universidad de Antioquia, Medellín, Colombia.,Neuropsychology and Behavior Group, Medical School, Universidad de Antioquia, Medellín, Colombia
| | - Ana Baena
- Neuroscience Group of Antioquia, Medical School, Universidad de Antioquia, Medellín, Colombia
| | - Francisco Lopera
- Neuroscience Group of Antioquia, Medical School, Universidad de Antioquia, Medellín, Colombia
| | - Miguel Angel Mañanas
- Department of Automatic Control (ESAII), Biomedical Engineering Research Center (CREB), Universitat Politènica de Catalunya (UPC), Barcelona, Spain.,Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain
| | - Alher Mauricio Hernández
- Bioinstrumentation and Clinical Engineering Research Group, Bioengineering Program, Universidad de Antioquia, Medellín, Colombia
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14
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Volf NV, Belousova LV, Knyazev GG, Kulikov AV. Interactive effect of 5-HTTLPR genotype and age on sources of cortical rhythms in healthy women. Int J Psychophysiol 2016; 109:107-115. [PMID: 27616474 DOI: 10.1016/j.ijpsycho.2016.09.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2016] [Revised: 08/29/2016] [Accepted: 09/07/2016] [Indexed: 11/26/2022]
Abstract
This study was aimed to localize the effects of 5-HTTLPR (serotonin-transporter-linked polymorphic region) on the age differences of spontaneous EEG activity in women using neuroimaging analysis sLORETA (Standardized Low Resolution brain Electromagnetic Tomography). DNA samples extracted from cheek swabs and resting-state EEG recorded at 60 standard leads were collected from young (YW, N=86, 18-35years) and older (OW, N=45; 55-80years) healthy women. We have shown that advanced age was associated with increased posterior EEG desynchronization in S'/S'. S' (LG allele was grouped with S alleles owing to its functional equivalence and this group was labeled as S') genotype carriers denoted by decrease of delta - beta1 current source density, and to a lesser extent in L/L homozygotes denoted by decrease in delta activity. In heterozygotes OW, as compared with heterozygotes YW, higher source density estimates of beta1 in frontal and temporal cortex were observed. Age differences were more pronounced in the right hemisphere in S'/S' and L/L carriers and in the left hemisphere in heterozygotes. We also found that in OW, current source density estimates of theta, alpha1, alpha2, alpha3 and beta1 sources in the right occipital lobe were higher in S'/L than in S'/S' carriers. These results may have implications for understanding 5-HTT-dependent variation in the effect of aging on brain activity.
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Affiliation(s)
- Nina V Volf
- State Scientific-Research Institute of Physiology and Basic Medicine, Timakova Street 4, Novosibirsk 630117, Russia; Novosibirsk State University, Pirogova Street 2, Novosibirsk 630090, Russia
| | - Ludmila V Belousova
- State Scientific-Research Institute of Physiology and Basic Medicine, Timakova Street 4, Novosibirsk 630117, Russia.
| | - Gennady G Knyazev
- State Scientific-Research Institute of Physiology and Basic Medicine, Timakova Street 4, Novosibirsk 630117, Russia
| | - Alexander V Kulikov
- Novosibirsk State University, Pirogova Street 2, Novosibirsk 630090, Russia; Institute of Cytology and Genetics of Siberian Branch of Russian Academy of Sciences, Prospekt Lavrentyeva, 10, Novosibirsk 630090, Russia
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15
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Benedictus MR, Leeuwis AE, Binnewijzend MAA, Kuijer JPA, Scheltens P, Barkhof F, van der Flier WM, Prins ND. Lower cerebral blood flow is associated with faster cognitive decline in Alzheimer's disease. Eur Radiol 2016; 27:1169-1175. [PMID: 27334014 PMCID: PMC5306323 DOI: 10.1007/s00330-016-4450-z] [Citation(s) in RCA: 87] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2016] [Revised: 05/19/2016] [Accepted: 05/25/2016] [Indexed: 01/23/2023]
Abstract
Objective To determine whether lower cerebral blood flow (CBF) is associated with faster cognitive decline in patients with Alzheimer’s disease (AD). Methods We included 88 patients with dementia due to AD from the Amsterdam Dementia Cohort. Mean follow-up was 2 ± 1 years. Linear mixed models were used to determine associations of lower whole brain and regional pseudo-continuous arterial spin labelling measured CBF with rate of cognitive decline as measured with repeated mini-mental state examination (MMSE). Model 1 was adjusted for age, sex, and education. Model 2 was additionally adjusted for normalized gray matter volume, medial temporal lobe atrophy, white matter hyperintensities, microbleeds, and lacunes. Analyses were repeated after partial volume correction (PVC) of CBF. Statistical significance was set at p ≤ 0.05. Results Patients were 65 ± 7 years old, 44 (50 %) were women, and mean baseline MMSE was 22 ± 4. Annual decline (β[SE]) on the MMSE was estimated at -2.11 (0.25) points per year. Lower whole brain (β[SE]-0.50[0.25]; p ≤ 0.05) and parietal (β[SE]-0.59[0.25]; p < 0.05) CBF were associated with faster cognitive decline. PVC cortical CBF was not associated with cognitive decline. Conclusions Lower CBF, in particular in the posterior brain regions, may have value as a prognostic marker for rate of cognitive decline in AD. Key points • In AD, lower CBF is associated with more rapid cognitive decline. • Decreasing CBF does not reach a plateau early in AD. • PcASL-CFB has additive value to conventional structural MRI measures in AD.
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Affiliation(s)
- Marije R Benedictus
- Alzheimer Centre & Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, PO Box 7057, 1007 MB, Amsterdam, The Netherlands.
| | - Annebet E Leeuwis
- Alzheimer Centre & Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Maja A A Binnewijzend
- Alzheimer Centre & Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Joost P A Kuijer
- Department of Physics and Medical Technology, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Centre & Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Centre & Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, PO Box 7057, 1007 MB, Amsterdam, The Netherlands.,Department of Epidemiology & Biostatistics, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
| | - Niels D Prins
- Alzheimer Centre & Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
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Engels MMA, Stam CJ, van der Flier WM, Scheltens P, de Waal H, van Straaten ECW. Declining functional connectivity and changing hub locations in Alzheimer's disease: an EEG study. BMC Neurol 2015; 15:145. [PMID: 26289045 PMCID: PMC4545875 DOI: 10.1186/s12883-015-0400-7] [Citation(s) in RCA: 106] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2015] [Accepted: 08/07/2015] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND EEG studies have shown that patients with Alzheimer's disease (AD) have weaker functional connectivity than controls, especially in higher frequency bands. Furthermore, active regions seem more prone to AD pathology. How functional connectivity is affected in AD subgroups of disease severity and how network hubs (highly connected brain areas) change is not known. We compared AD patients with different disease severity and controls in terms of functional connections, hub strength and hub location. METHODS We studied routine 21-channel resting-state electroencephalography (EEG) of 318 AD patients (divided into tertiles based on disease severity: mild, moderate and severe AD) and 133 age-matched controls. Functional connectivity between EEG channels was estimated with the Phase Lag Index (PLI). From the PLI-based connectivity matrix, the minimum spanning tree (MST) was derived. For each node (EEG channel) in the MST, the betweenness centrality (BC) was computed, a measure to quantify the relative importance of a node within the network. Then we derived color-coded head plots based on BC values and calculated the center of mass (the exact middle had x and y values of 0). A shifting of the hub locations was defined as a shift of the center of mass on the y-axis across groups. Multivariate general linear models with PLI or BC values as dependent variables and the groups as continuous variables were used in the five conventional frequency bands. RESULTS We found that functional connectivity decreases with increasing disease severity in the alpha band. All, except for posterior, regions showed increasing BC values with increasing disease severity. The center of mass shifted from posterior to more anterior regions with increasing disease severity in the higher frequency bands, indicating a loss of relative functional importance of the posterior brain regions. CONCLUSIONS In conclusion, we observed decreasing functional connectivity in the posterior regions, together with a shifted hub location from posterior to central regions with increasing AD severity. Relative hub strength decreases in posterior regions while other regions show a relative rise with increasing AD severity, which is in accordance with the activity-dependent degeneration theory. Our results indicate that hubs are disproportionally affected in AD.
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Affiliation(s)
- Marjolein M A Engels
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
| | - Wiesje M van der Flier
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
- Department of Epidemiology and Biostatistics, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
| | - Philip Scheltens
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
| | - Hanneke de Waal
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
| | - Elisabeth C W van Straaten
- Department of Clinical Neurophysiology and MEG center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
- Nutricia Advanced Medical Nutrition, Nutricia Research, Utrecht, The Netherlands.
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van Straaten EC, Scheltens P, Gouw AA, Stam CJ. Eyes-closed task-free electroencephalography in clinical trials for Alzheimer's disease: an emerging method based upon brain dynamics. ALZHEIMERS RESEARCH & THERAPY 2014; 6:86. [PMID: 25621017 PMCID: PMC4304266 DOI: 10.1186/s13195-014-0086-x] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Electroencephalography (EEG) is a longstanding technique to measure electrical brain activity and thereby an indirect measure of synaptic activity. Synaptic dysfunction accompanies Alzheimer’s disease (AD) and EEG can be regarded as a potentially useful biomarker in this disease. Lately, emerging analysis techniques of time series have become available for EEG, such as functional connectivity and network analysis, which have increased the possibilities for use in AD clinical trials. In this review, we report the EEG changes in the course of AD, including slowing of the EEG oscillations, decreased functional connectivity in the higher-frequency bands, and decline in optimal functional network organization. We discuss the use of EEG in clinical trials and provide directions for future research.
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Affiliation(s)
- Elisabeth Cw van Straaten
- Department of Clinical Neurophysiology, VU University Medical Center, de Bolelaan 1118, P.O. box 7057, 1007 MB Amsterdam, The Netherlands ; Nutricia Research, Nutricia Advanced Medical Nutrition, Utrecht Science Park, Uppsalalaan 12, 3584 CT Utrecht, The Netherlands
| | - Philip Scheltens
- Alzheimer Center & Department of Neurology, VU University Medical Center, de Boelelaan 1118, P.O. box 7057, 1007 MB Amsterdam, the Netherlands
| | - Alida A Gouw
- Department of Clinical Neurophysiology, VU University Medical Center, de Bolelaan 1118, P.O. box 7057, 1007 MB Amsterdam, The Netherlands ; Alzheimer Center & Department of Neurology, VU University Medical Center, de Boelelaan 1118, P.O. box 7057, 1007 MB Amsterdam, the Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology, VU University Medical Center, de Bolelaan 1118, P.O. box 7057, 1007 MB Amsterdam, The Netherlands
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Impaired cortical oscillatory coupling in mild cognitive impairment: anatomical substrate and ApoE4 effects. Brain Struct Funct 2014; 220:1721-37. [PMID: 24682246 DOI: 10.1007/s00429-014-0757-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2013] [Accepted: 03/16/2014] [Indexed: 01/04/2023]
Abstract
Our current knowledge about the anatomical substrate of impaired resting-state cortical oscillatory coupling in mild cognitive impairment is still rudimentary. Here, we show that both resting-state oscillatory coupling and its anatomical correlates clearly distinguish healthy older (HO) adults from individuals with amnestic mild cognitive impairment (aMCI). aMCI showed failures in neural-phase coupling of resting-state electroencephalographic alpha activity mostly evident between fronto-temporal and parietal regions. As oligomers of amyloid-beta (Aβ) are linked to synaptic dysfunction in Alzheimer's disease (AD), we further investigated whether plasma concentrations of these oligomers (Aβ40 and Aβ42) accounted for impaired patterns of oscillatory coupling in aMCI. Results revealed that decreased plasma Aβ42 was associated with augmented coupling of parieto-temporal regions in HO subjects, but no relationship was found in aMCI. Oscillatory coupling of frontal regions was also significantly reduced in aMCI carriers of the ε4 allele of the Apolipoprotein E (ApoE) compared to ε4 noncarriers, although neither neuroanatomical nor plasma Aβ changes accounted for this difference. However, the abnormal pattern of oscillatory coupling in aMCI was negatively related to volume of the angular gyrus, and positively related to volume of the precuneus and the splenium of the corpus callosum. Previous evidence suggests that all these regions are neuropathological targets of AD. The current study takes that scenario one step further, suggesting that this anatomical damage could be responsible for disrupted cortical oscillatory coupling in aMCI. Together, these data shed light on how the MCI status modifies anatomo-functional relationships underlying coordination of large-scale cortical systems in the resting-state.
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