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Cited by 29Dementia and Cognitive Impairment ResearchEEG and Brain-Computer InterfacesAlzheimer's disease research and treatments

Electrophysiological brain signatures for the classification of subjective cognitive decline: towards an individual detection in the preclinical stages of dementia

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López-Sanz, David, Bruña, Ricardo, Delgado-Losada, María Luisa, López-Higes, Ramón, Marcos-Dolado, Alberto, Maestú, Fernando, Walter, Stefan·2019·Alzheimer's Research & Therapy
DOI 10.1186/s13195-019-0502-3PMC PMC6544924
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Abstract

BACKGROUND: Alzheimer's disease (AD) prevalence is rapidly growing as worldwide populations grow older. Available treatments have failed to slow down disease progression, thus increasing research focus towards early or preclinical stages of the disease. Subjective cognitive decline (SCD) is known to increase the risk of developing AD and several other negative outcomes. However, it is still very scarcely characterized and there is no neurophysiological study devoted to its individual classification which could improve targeted sample recruitment for clinical trials. METHODS: Two hundred fifty-two older adults (70 healthy controls, 91 SCD, and 91 MCI) underwent a magnetoencephalography scan. Alpha relative power in the source space was employed to train a LASSO classifier and applied to distinguish between healthy controls and SCD. Moreover, MCI participants were used to further validate the previously trained algorithm. RESULTS: The classifier was significantly associated to SCD with an AUC of 0.81 in the whole sample. After randomly splitting the sample in 2/3 for discovery and 1/3 for validation, the newly trained classifier was also able to correctly classify SCD individuals with an AUC of 0.75 in the validation sample. The regions selected by the algorithm included medial frontal, temporal, and occipital areas. The algorithm trained to select SCD individuals was also significantly associated to MCI diagnostic. CONCLUSIONS: According to our results, magnetoencephalography could be a useful tool for distinguishing individuals with SCD and healthy older adults without cognitive concerns. Furthermore, our classifier showed good external validity, being not only successful for an unseen SCD sample, but also in a different population with MCI cases. This supports its utility in the context of preclinical dementia. These findings highlight the potential applications of electrophysiological techniques to improve sample recruitment at the individual level in the context of clinical trials.

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  1. [1]Christensen Kaare Doblhammer Gabriele Rau Roland Vaupel James W Ageing populations: the challenges ahead The Lancet 2009 374 9696 1196 1208 10.1016/S0140-6736(09)61460-4 PMC2810516 19801098 · DOI
  2. [3]Bloom David E Chatterji Somnath Kowal Paul Lloyd-Sherlock Peter McKee Martin Rechel Bernd Rosenberg Larry Smith James P Macroeconomic implications of population ageing and selected policy responses The Lancet 2015 385 9968 649 657 10.1016/S0140-6736(14)61464-1 PMC4469267 25468167 · DOI · Paper page
  3. [4]Association A 2017 Alzheimer’s disease facts and figures Alzheimers Dement 2017 13 325 373 10.1016/j.jalz.2017.02.001 · DOI
  4. [5]Winblad Bengt Amouyel Philippe Andrieu Sandrine Ballard Clive Brayne Carol Brodaty Henry Cedazo-Minguez Angel Dubois Bruno Edvardsson David Feldman Howard Fratiglioni Laura Frisoni Giovanni B Gauthier Serge Georges Jean Graff Caroline Iqbal Khalid Jessen Frank Johansson Gunilla Jönsson Linus Kivipelto Miia Knapp Martin Mangialasche Francesca Melis René Nordberg Agneta Rikkert Marcel Olde Qiu Chengxuan Sakmar Thomas P Scheltens Philip Schneider Lon S Sperling Reisa Tjernberg Lars O Waldemar Gunhild Wimo Anders Zetterberg Henrik Defeating Alzheimer's disease and other dementias: a priority for European science and society The Lancet Neurology 2016 15 5 455 532 10.1016/S1474-4422(16)00062-4 26987701 · DOI · Paper page
  5. [6]Jessen F, Amariglio RE, van Boxtel M, Breteler M, Ceccaldi M, Chételat G, et al. A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease. Alzheimer’s Dement [Internet] 2014;10(6):844–852. Available from: http://linkinghub.elsevier.com/retrieve/pii/S1552526014000028. PMC4317324 24798886
  6. [8]Buckley Rachel F. Maruff Paul Ames David Bourgeat Pierrick Martins Ralph N. Masters Colin L. Rainey-Smith Stephanie Lautenschlager Nicola Rowe Christopher C. Savage Greg Villemagne Victor L. Ellis Kathryn A. Subjective memory decline predicts greater rates of clinical progression in preclinical Alzheimer's disease Alzheimer's & Dementia 2016 12 7 796 804 10.1016/j.jalz.2015.12.013 26852195 · DOI
  7. [9]Mitchell A. J. Beaumont H. Ferguson D. Yadegarfar M. Stubbs B. Risk of dementia and mild cognitive impairment in older people with subjective memory complaints: meta-analysis Acta Psychiatrica Scandinavica 2014 130 6 439 451 10.1111/acps.12336 25219393 · DOI
  8. [10]Singh-Manoux Archana Dugravot Aline Ankri Joel Nabi Hermann Berr Claudine Goldberg Marcel Zins Marie Kivimaki Mika Elbaz Alexis Subjective cognitive complaints and mortality: Does the type of complaint matter? Journal of Psychiatric Research 2014 48 1 73 78 10.1016/j.jpsychires.2013.10.005 24161314 · DOI
  9. [11]Ogata Soshiro Hayashi Chisato Sugiura Keiko Hayakawa Kazuo Association between subjective memory complaints and impaired higher-level functional capacity in people aged 60 years or older Archives of Gerontology and Geriatrics 2015 60 1 201 205 10.1016/j.archger.2014.10.015 25465503 · DOI
  10. [12]Waldorff FB, Siersma V, Waldemar G. Association between subjective memory complaints and nursing home placement: a four-year follow-up. Int J Geriatr Psychiatry [Internet]. Wiley-Blackwell; 2009 Jun 1 [cited 2018 May 8];24(6):602–9. Available from: http://doi.wiley.com/10.1002/gps.2163. 19058296 · DOI
  11. [13]Roehr Susanne Luck Tobias Heser Kathrin Fuchs Angela Ernst Annette Wiese Birgitt Werle Jochen Bickel Horst Brettschneider Christian Koppara Alexander Pentzek Michael Lange Carolin Prokein Jana Weyerer Siegfried Mösch Edelgard König Hans-Helmut Maier Wolfgang Scherer Martin Jessen Frank Riedel-Heller Steffi G. Incident Subjective Cognitive Decline Does Not Predict Mortality in the Elderly – Results from the Longitudinal German Study on Ageing, Cognition, and Dementia (AgeCoDe) PLOS ONE 2016 11 1 e0147050 10.1371/journal.pone.0147050 26766555 PMC4713115 · DOI
  12. [14]Luck T Roehr S Jessen F Villringer A Angermeyer MC Riedel-Heller SG Mortality in individuals with subjective cognitive decline: results of the Leipzig longitudinal study of the aged (LEILA75+) J Alzheimers Dis 2015 48 Suppl 1 S33 S42 10.3233/JAD-150090 26402077 · DOI
  13. [15]Scheef L. Spottke A. Daerr M. Joe A. Striepens N. Kolsch H. Popp J. Daamen M. Gorris D. Heneka M. T. Boecker H. Biersack H. J. Maier W. Schild H. H. Wagner M. Jessen F. Glucose metabolism, gray matter structure, and memory decline in subjective memory impairment Neurology 2012 79 13 1332 1339 10.1212/WNL.0b013e31826c1a8d 22914828 · DOI · Paper page
  14. [17]Engels M.M.A. van der Flier W.M. Stam C.J. Hillebrand A. Scheltens Ph. van Straaten E.C.W. Alzheimer’s disease: The state of the art in resting-state magnetoencephalography Clinical Neurophysiology 2017 128 8 1426 1437 10.1016/j.clinph.2017.05.012 28622527 · DOI
  15. [18]Nakamura Akinori Cuesta Pablo Fernández Alberto Arahata Yutaka Iwata Kaori Kuratsubo Izumi Bundo Masahiko Hattori Hideyuki Sakurai Takashi Fukuda Koji Washimi Yukihiko Endo Hidetoshi Takeda Akinori Diers Kersten Bajo Ricardo Maestú Fernando Ito Kengo Kato Takashi Electromagnetic signatures of the preclinical and prodromal stages of Alzheimer’s disease Brain 2018 141 5 1470 1485 10.1093/brain/awy044 29522156 PMC5920328 · DOI · Paper page
  16. [19]López-Sanz D, Brunã R, Garcés P, Camara C, Serrano N, Rodríguez-Rojo IC, et al. Alpha band disruption in the AD-continuum starts in the subjective cognitive decline stage: a MEG study. Sci Rep. 2016;6(37685). 10.1038/srep37685. PMC5121589 27883082 · DOI
  17. [21]López-Sanz D, Serrano N, Maestú F. The role of magnetoencephalography in the early stages of Alzheimer’s disease. Front Neurosci [Internet]. Frontiers; 2018 Aug 15 [cited 2019 Jan 17];12:572. Available from: 10.3389/fnins.2018.00572. PMC6104188 30158852 · DOI
  18. [22]ALEXANDER DAVID M. ARNS MARTIJN W. PAUL ROBERT H. ROWE DONALD L. COOPER NICHOLAS ESSER ARISTIDE H. FALLAHPOUR KAMRAN STEPHAN BLOSSOM C. M. HEESEN ERICA BRETELER RIEN WILLIAMS LEANNE M. GORDON EVIAN EEG MARKERS FOR COGNITIVE DECLINE IN ELDERLY SUBJECTS WITH SUBJECTIVE MEMORY COMPLAINTS Journal of Integrative Neuroscience 2006 05 01 49 74 10.1142/S0219635206001021 16544366 · DOI · Paper page
  19. [23]Rami Lorena Mollica Maria A. García-Sanchez Carmen Saldaña Judith Sanchez Belen Sala Isabel Valls-Pedret Cinta Castellví Magda Olives Jaume Molinuevo Jose L. The Subjective Cognitive Decline Questionnaire (SCD-Q): A Validation Study Journal of Alzheimer's Disease 2014 41 2 453 466 10.3233/JAD-132027 24625794 · DOI
  20. [24]Petersen R. C. Mild cognitive impairment as a diagnostic entity Journal of Internal Medicine 2004 256 3 183 194 10.1111/j.1365-2796.2004.01388.x 15324362 · DOI · Paper page
  21. [25]Garcés Pilar López-Sanz David Maestú Fernando Pereda Ernesto Choice of Magnetometers and Gradiometers after Signal Space Separation Sensors 2017 17 12 2926 10.3390/s17122926 PMC5751446 29258189 · DOI
  22. [26]Tibshirani R. Regression selection and shrinkage via the Lasso [Internet]. Vol. 58, Journal of the Royal Statistical Society B. WileyRoyal Statistical Society; 1996 [cited 2018 Jul 26]. p. 267–88. Available from: https://www.jstor.org/stable/2346178.
  23. [28]Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J Stat Softw [Internet]. NIH Public Access; 2010 [cited 2018 Jul 26];33(1):1–22. Available from: http://www.ncbi.nlm.nih.gov/pubmed/20808728. PMC2929880 20808728
  24. [29]Stomrud Erik Hansson Oskar Blennow Kaj Minthon Lennart Londos Elisabet Cerebrospinal Fluid Biomarkers Predict Decline in Subjective Cognitive Function over 3 Years in Healthy Elderly Dementia and Geriatric Cognitive Disorders 2007 24 2 118 124 10.1159/000105017 17622715 · DOI
  25. [31]López-Sanz D, Bruña R, Garcés P, Martín-Buro MC, Walter S, Delgado ML, et al. Functional connectivity disruption in subjective cognitive decline and mild cognitive impairment: a common pattern of alterations. Front Aging Neurosci. 2017;9:109. 10.3389/fnagi.2017.00109. PMC5399035 28484387 · DOI
  26. [32]Chen Chih-Chung Hsu Chien-Yeh Chiu Hung-Wen Hu Chaur-Jong Lee Tsung-Chieh Frequency power and coherence of electroencephalography are correlated with the severity of Alzheimer's disease: A multicenter analysis in Taiwan Journal of the Formosan Medical Association 2015 114 8 729 735 10.1016/j.jfma.2013.07.008 23969043 · DOI
  27. [33]Herholz K. Salmon E. Perani D. Baron J-C. Holthoff V. Frölich L. Schönknecht P. Ito K. Mielke R. Kalbe E. Discrimination between Alzheimer Dementia and Controls by Automated Analysis of Multicenter FDG PET NeuroImage 2002 17 1 302 316 10.1006/nimg.2002.1208 12482085 · DOI · Paper page
  28. [34]Sepulcre Jorge Sabuncu Mert R. Becker Alex Sperling Reisa Johnson Keith A. In vivo characterization of the early states of the amyloid-beta network Brain 2013 136 7 2239 2252 10.1093/brain/awt146 23801740 PMC3692037 · DOI · Paper page
  29. [35]Babiloni Claudio Del Percio Claudio Caroli Anna Salvatore Elena Nicolai Emanuele Marzano Nicola Lizio Roberta Cavedo Enrica Landau Susan Chen Kewei Jagust William Reiman Eric Tedeschi Gioacchino Montella Patrizia De Stefano Manuela Gesualdo Loreto Frisoni Giovanni B. Soricelli Andrea Cortical sources of resting state EEG rhythms are related to brain hypometabolism in subjects with Alzheimer's disease: an EEG-PET study Neurobiology of Aging 2016 48 122 134 10.1016/j.neurobiolaging.2016.08.021 27668356 · DOI
  30. [36]Babiloni Claudio Lizio Roberta Marzano Nicola Capotosto Paolo Soricelli Andrea Triggiani Antonio Ivano Cordone Susanna Gesualdo Loreto Del Percio Claudio Brain neural synchronization and functional coupling in Alzheimer's disease as revealed by resting state EEG rhythms International Journal of Psychophysiology 2016 103 88 102 10.1016/j.ijpsycho.2015.02.008 25660305 · DOI
  31. [37]Smailovic Una Koenig Thomas Kåreholt Ingemar Andersson Thomas Kramberger Milica Gregoric Winblad Bengt Jelic Vesna Quantitative EEG power and synchronization correlate with Alzheimer's disease CSF biomarkers Neurobiology of Aging 2018 63 88 95 10.1016/j.neurobiolaging.2017.11.005 29245058 · DOI · Paper page
  32. [38]Gouw Alida A. Alsema Astrid M. Tijms Betty M. Borta Andreas Scheltens Philip Stam Cornelis J. van der Flier Wiesje M. EEG spectral analysis as a putative early prognostic biomarker in nondemented, amyloid positive subjects Neurobiology of Aging 2017 57 133 142 10.1016/j.neurobiolaging.2017.05.017 28646686 · DOI
  33. [39]Buckley Rachel F. Hanseeuw Bernard Schultz Aaron P. Vannini Patrizia Aghjayan Sarah L. Properzi Michael J. Jackson Jonathan D. Mormino Elizabeth C. Rentz Dorene M. Sperling Reisa A. Johnson Keith A. Amariglio Rebecca E. Region-Specific Association of Subjective Cognitive Decline With Tauopathy Independent of Global β-Amyloid Burden JAMA Neurology 2017 74 12 1455 10.1001/jamaneurol.2017.2216 28973551 PMC5774633 · DOI · Paper page
  34. [41]Ferreira D, Falahati F, Linden C, Buckley RF, Ellis KA, Savage G, et al. A “Disease Severity Index” to identify individuals with subjective memory decline who will progress to mild cognitive impairment or dementia. Sci Rep [Internet] Nature Publishing Group; 2017 Mar 13 [cited 2018 May 4];7:44368. Available from: http://www.nature.com/articles/srep44368. PMC5347012 28287184
  35. [42]Gordon Brian A Blazey Tyler M Su Yi Hari-Raj Amrita Dincer Aylin Flores Shaney Christensen Jon McDade Eric Wang Guoqiao Xiong Chengjie Cairns Nigel J Hassenstab Jason Marcus Daniel S Fagan Anne M Jack Clifford R Hornbeck Russ C Paumier Katrina L Ances Beau M Berman Sarah B Brickman Adam M Cash David M Chhatwal Jasmeer P Correia Stephen Förster Stefan Fox Nick C Graff-Radford Neill R la Fougère Christian Levin Johannes Masters Colin L Rossor Martin N Salloway Stephen Saykin Andrew J Schofield Peter R Thompson Paul M Weiner Michael M Holtzman David M Raichle Marcus E Morris John C Bateman Randall J Benzinger Tammie L S Spatial patterns of neuroimaging biomarker change in individuals from families with autosomal dominant Alzheimer's disease: a longitudinal study The Lancet Neurology 2018 17 3 241 250 10.1016/S1474-4422(18)30028-0 29397305 PMC5816717 · DOI · Paper page
  36. [43]Babiloni Claudio Carducci Filippo Lizio Roberta Vecchio Fabrizio Baglieri Annalisa Bernardini Silvia Cavedo Enrica Bozzao Alessandro Buttinelli Carla Esposito Fabrizio Giubilei Franco Guizzaro Antonio Marino Silvia Montella Patrizia Quattrocchi Carlo C. Redolfi Alberto Soricelli Andrea Tedeschi Gioacchino Ferri Raffaele Rossi-Fedele Giancarlo Ursini Francesca Scrascia Federica Vernieri Fabrizio Pedersen Torleif Jan Hardemark Hans-Goran Rossini Paolo M. Frisoni Giovanni B. Resting state cortical electroencephalographic rhythms are related to gray matter volume in subjects with mild cognitive impairment and Alzheimer's disease Human Brain Mapping 2012 34 6 1427 1446 10.1002/hbm.22005 22331654 PMC6869852 · DOI

Cited by

Sorted by citations

Authors
López-Sanz, D., Bruña, R., Delgado-Losada, M. L., López-Higes, R., Marcos-Dolado, A., Maestú, F., & Walter, S.
Affiliations
  • Universidad Complutense de Madrid (ES)
  • University of California, San Francisco (US)
Corresponding author
Walter, Stefan
ORCID
Venue
Alzheimer's Research & Therapy
Publisher
Springer Science and Business Media LLC
Published
2019-06-01
Volume
11
Issue
1
Pages
49-49
ISSN
1758-9193 (ISSN-L)
DOI
10.1186/s13195-019-0502-3
PMC
PMC6544924
OpenAlex
W2947708084
Cited by
29
References
6
Citations by year
2025: 3 · 2024: 3 · 2023: 6 · 2022: 7 · 2021: 5 · 2020: 3 · 2019: 2
FWCI
3.39
Type
journal article
Language
en
Open access
Licence
Locations
  • Alzheimer s Research & Therapy (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Ministerio de Economía, Industria y Competitividad, Gobierno de España (PSI2009-14415-C03-01, PSI2012-38375-C03-01)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
Keywords
subjective cognitive decline, preclinical dementia, Alzheimer's disease, magnetoencephalography, medial frontal cortex, temporal cortex, occipital cortex, mild cognitive impairment, individual classification, clinical trial recruitment, older adults
MeSH terms
Aged, Brain, Dementia, Female, Humans, Male, Neuropsychological Tests, Sensitivity and Specificity, Magnetoencephalography, Diagnostic Self Evaluation, Cognitive Dysfunction

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