Dementia and Neurocognitive Disorders (대한치매학회지)

Korean Dementia Association (대한치매학회)
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Electroencephalography for Early Detection of Alzheimer's Disease in Subjective Cognitive Decline

  • YongSoo Shim (Department of Neurology, College of Medicine, The Catholic University of Korea) ;
  • Dong Won Yang (Department of Neurology, College of Medicine, The Catholic University of Korea) ;
  • SeongHee Ho (Department of Neurology, College of Medicine, The Catholic University of Korea) ;
  • Yun Jeong Hong (Department of Neurology, College of Medicine, The Catholic University of Korea) ;
  • Jee Hyang Jeong (Department of Neurology, Ewha Womans University Mokdong Hospital, Ewha Womans University School of Medicine) ;
  • Kee Hyung Park (Department of Neurology, Gachon University Gil Hospital) ;
  • SangYun Kim (Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine) ;
  • Min Jeong Wang (Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine) ;
  • Seong Hye Choi (Department of Neurology, Inha University School of Medicine) ;
  • Seung Wan Kang (Data Center for Korean EEG, College of Nursing, Seoul National University)
  • Received : 2022.07.17
  • Accepted : 2022.09.13
  • Published : 2022.10.31
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Abstract

Background and Purpose: Early detection of subjective cognitive decline (SCD) due to Alzheimer's disease (AD) is important for clinical research and effective prevention and management. This study examined if quantitative electroencephalography (qEEG) could be used for early detection of AD in SCD. Methods: Participants with SCD from 6 dementia clinics in Korea were enrolled. 18F-florbetaben brain amyloid positron emission tomography (PET) was conducted for all the participants. qEEG was performed to measure power spectrum and source cortical activity. Results: The present study included 95 participants aged over 65 years, including 26 amyloid PET (+) and 69 amyloid PET (-). In participants with amyloid PET (+), relative power at delta band was higher in frontal (p=0.025), parietal (p=0.005), and occipital (p=0.022) areas even after adjusting for age, sex, and education. Source activities of alpha 1 band were significantly decreased in the bilateral fusiform and inferior temporal areas, whereas those of delta band were increased in the bilateral cuneus, pericalcarine, lingual, lateral occipital, precuneus, posterior cingulate, and isthmus areas. There were increased connections between bilateral precuneus areas but decreased connections between left rostral middle frontal area and bilateral frontal poles at delta band in participants with amyloid PET (+) showed. At alpha 1 band, there were decreased connections between bilateral entorhinal areas after adjusting for covariates. Conclusions: SCD participants with amyloid PET (+) showed increased delta and decreased alpha 1 activity. qEEG is a potential means for predicting amyloid pathology in SCD. Further longitudinal studies are needed to confirm these findings.

Keywords

Acknowledgement

We would like to thank to research group in the iMediSync, Inc., Korea, which developed source level feature extractions and group statistics functionalities, and applied those to the research data set on iSyncBrain.

References

  1. Jessen F, Amariglio RE, van Boxtel M, Breteler M, Ceccaldi M, Chetelat G, et al. A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer's disease. Alzheimers Dement 2014;10:844-852.
  2. Amariglio RE, Becker JA, Carmasin J, Wadsworth LP, Lorius N, Sullivan C, et al. Subjective cognitive complaints and amyloid burden in cognitively normal older individuals. Neuropsychologia 2012;50:2880-2886.
  3. Perrotin A, Mormino EC, Madison CM, Hayenga AO, Jagust WJ. Subjective cognition and amyloid deposition imaging: a Pittsburgh compound B positron emission tomography study in normal elderly individuals. Arch Neurol 2012;69:223-229.
  4. Prichep LS, John ER, Ferris SH, Rausch L, Fang Z, Cancro R, et al. Prediction of longitudinal cognitive decline in normal elderly with subjective complaints using electrophysiological imaging. Neurobiol Aging 2006;27:471-481.
  5. Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, et al. Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement 2011;7:280-292.
  6. Jessen F, Wiese B, Bachmann C, Eifflaender-Gorfer S, Haller F, Kolsch H, et al. Prediction of dementia by subjective memory impairment: effects of severity and temporal association with cognitive impairment. Arch Gen Psychiatry 2010;67:414-422.
  7. Blennow K. CSF biomarkers for mild cognitive impairment. J Intern Med 2004;256:224-234.
  8. Heinonen O, Soininen H, Sorvari H, Kosunen O, Paljarvi L, Koivisto E, et al. Loss of synaptophysin-like immunoreactivity in the hippocampal formation is an early phenomenon in Alzheimer's disease. Neuroscience 1995;64:375-384.
  9. Selkoe DJ. Alzheimer's disease is a synaptic failure. Science 2002;298:789-791.
  10. Jelic V, Kowalski J. Evidence-based evaluation of diagnostic accuracy of resting EEG in dementia and mild cognitive impairment. Clin EEG Neurosci 2009;40:129-142.
  11. Michel CM, Koenig T, Brandeis D, Wackermann J, Gianotti LR. Electrical Neuroimaging. New York: Cambridge University Press, 2009.
  12. Tait L, Stothart G, Coulthard E, Brown JT, Kazanina N, Goodfellow M. Network substrates of cognitive impairment in Alzheimer's disease. Clin Neurophysiol 2019;130:1581-1595.
  13. Briels CT, Schoonhoven DN, Stam CJ, de Waal H, Scheltens P, Gouw AA. Reproducibility of EEG functional connectivity in Alzheimer's disease. Alzheimers Res Ther 2020;12:68.
  14. Tait L, Tamagnini F, Stothart G, Barvas E, Monaldini C, Frusciante R, et al. EEG microstate complexity for aiding early diagnosis of Alzheimer's disease. Sci Rep 2020;10:17627.
  15. Kumar S. Relevance of cortical excitability in Alzheimer's disease. Clin Neurophysiol 2021;132:1961-1963.
  16. Dierks T, Perisic I, Frolich L, Ihl R, Maurer K. Topography of the quantitative electroencephalogram in dementia of the Alzheimer type: relation to severity of dementia. Psychiatry Res 1991;40:181-194.
  17. Soininen H, Partanen J, Paakkonen A, Koivisto E, Riekkinen PJ. Changes in absolute power values of EEG spectra in the follow-up of Alzheimer's disease. Acta Neurol Scand 1991;83:133-136.
  18. Jelic V, Blomberg M, Dierks T, Basun H, Shigeta M, Julin P, et al. EEG slowing and cerebrospinal fluid tau levels in patients with cognitive decline. Neuroreport 1998;9:157-160.
  19. Babiloni C, Binetti G, Cassarino A, Dal Forno G, Del Percio C, Ferreri F, et al. Sources of cortical rhythms in adults during physiological aging: a multicentric EEG study. Hum Brain Mapp 2006;27:162-172.
  20. Kang Y, Jahng S, Na DL. Seoul Neuropsychological Screening Battery, 2nd Edition (SNSB-II). Seoul: Human Brain Research & Consulting Co., 2012.
  21. Becker GA, Ichise M, Barthel H, Luthardt J, Patt M, Seese A, et al. PET quantification of 18F-florbetaben binding to β-amyloid deposits in human brains. J Nucl Med 2013;54:723-731.
  22. Barthel H, Gertz HJ, Dresel S, Peters O, Bartenstein P, Buerger K, et al. Cerebral amyloid-β PET with florbetaben (18F) in patients with Alzheimer's disease and healthy controls: a multicentre phase 2 diagnostic study. Lancet Neurol 2011;10:424-435.
  23. Shim YS, Youn YC, Na DL, Kim SY, Cheong HK, Moon SY, et al. Effects of medial temporal atrophy and white matter hyperintensities on the cognitive functions in patients with Alzheimer's disease. Eur Neurol 2011;66:75-82.
  24. Scheltens P, Leys D, Barkhof F, Huglo D, Weinstein HC, Vermersch P, et al. Atrophy of medial temporal lobes on MRI in "probable" Alzheimer's disease and normal ageing: diagnostic value and neuropsychological correlates. J Neurol Neurosurg Psychiatry 1992;55:967-972.
  25. Delorme A, Palmer J, Onton J, Oostenveld R, Makeig S. Independent EEG sources are dipolar. PLoS One 2012;7:e30135.
  26. Shim YS, Shin HE. Analysis of neuropsychiatric symptoms in patients with Alzheimer's disease using quantitative EEG and sLORETA. Neurodegener Dis 2020;20:12-19.
  27. iMediSync, Inc. iSyncBrain [Internet]. Seoul: iMediSync, Inc.; 2019 [cited 2019 Apr 24]. Available from: https://isyncbrain.com/research/.
  28. Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 2004;134:9-21.
  29. Pascual-Marqui RD. Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods Find Exp Clin Pharmacol 2002;24 Suppl D:5-12.
  30. Holmes CJ, Hoge R, Collins L, Woods R, Toga AW, Evans AC. Enhancement of MR images using registration for signal averaging. J Comput Assist Tomogr 1998;22:324-333.
  31. Desikan RS, Segonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 2006;31:968-980.
  32. Kwak YT. Quantitative EEG findings in different stages of Alzheimer's disease. J Clin Neurophysiol 2006;23:456-461.
  33. Luckhaus C, Grass-Kapanke B, Blaeser I, Ihl R, Supprian T, Winterer G, et al. Quantitative EEG in progressing vs stable mild cognitive impairment (MCI): results of a 1-year follow-up study. Int J Geriatr Psychiatry 2008;23:1148-1155.
  34. Babiloni C, Binetti G, Cassetta E, Cerboneschi D, Dal Forno G, Del Percio C, et al. Mapping distributed sources of cortical rhythms in mild Alzheimer's disease. A multicentric EEG study. Neuroimage 2004;22:57-67.
  35. Leirer VM, Wienbruch C, Kolassa S, Schlee W, Elbert T, Kolassa IT. Changes in cortical slow wave activity in healthy aging. Brain Imaging Behav 2011;5:222-228.
  36. Marshall AC, Cooper NR. The association between high levels of cumulative life stress and aberrant resting state EEG dynamics in old age. Biol Psychol 2017;127:64-73.
  37. Hier DB, Mangone CA, Ganellen R, Warach JD, Van Egeren R, Perlik SJ, et al. Quantitative measurement of delta activity in Alzheimer's disease. Clin Electroencephalogr 1991;22:178-182.
  38. Brunovsky M, Matousek M, Edman A, Cervena K, Krajca V. Objective assessment of the degree of dementia by means of EEG. Neuropsychobiology 2003;48:19-26.
  39. Lopes da Silva F. Neural mechanisms underlying brain waves: from neural membranes to networks. Electroencephalogr Clin Neurophysiol 1991;79:81-93.
  40. Babiloni C, Carducci F, Lizio R, Vecchio F, Baglieri A, Bernardini S, et al. Resting state cortical electroencephalographic rhythms are related to gray matter volume in subjects with mild cognitive impairment and Alzheimer's disease. Hum Brain Mapp 2013;34:1427-1446.
  41. Babiloni C, Del Percio C, Boccardi M, Lizio R, Lopez S, Carducci F, et al. Occipital sources of resting-state alpha rhythms are related to local gray matter density in subjects with amnesic mild cognitive impairment and Alzheimer's disease. Neurobiol Aging 2015;36:556-570.
  42. Rodriguez G, Nobili F, Copello F, Vitali P, Gianelli MV, Taddei G, et al. 99mTc-HMPAO regional cerebral blood flow and quantitative electroencephalography in Alzheimer's disease: a correlative study. J Nucl Med 1999;40:522-529.
  43. Mattia D, Babiloni F, Romigi A, Cincotti F, Bianchi L, Sperli F, et al. Quantitative EEG and dynamic susceptibility contrast MRI in Alzheimer's disease: a correlative study. Clin Neurophysiol 2003;114:1210-1216.
  44. Kai T, Asai Y, Sakuma K, Koeda T, Nakashima K. Quantitative electroencephalogram analysis in dementia with Lewy bodies and Alzheimer's disease. J Neurol Sci 2005;237:89-95.
  45. Kelly JF, Furukawa K, Barger SW, Rengen MR, Mark RJ, Blanc EM, et al. Amyloid beta-peptide disrupts carbachol-induced muscarinic cholinergic signal transduction in cortical neurons. Proc Natl Acad Sci U S A 1996;93:6753-6758.
  46. Vaucher E, Aumont N, Pearson D, Rowe W, Poirier J, Kar S. Amyloid beta peptide levels and its effects on hippocampal acetylcholine release in aged, cognitively-impaired and -unimpaired rats. J Chem Neuroanat 2001;21:323-329.
  47. Riekkinen P Jr, Sirvio J, Riekkinen P. Relationship between the cortical choline acetyltransferase content and EEG delta-power. Neurosci Res 1990;8:12-20.
  48. Prichep LS. Quantitative EEG and electromagnetic brain imaging in aging and in the evolution of dementia. Ann N Y Acad Sci 2007;1097:156-167.
  49. Prichep LS, John ER, Ferris SH, Reisberg B, Almas M, Alper K, et al. Quantitative EEG correlates of cognitive deterioration in the elderly. Neurobiol Aging 1994;15:85-90.
  50. Reisberg B, Prichep L, Mosconi L, John ER, Glodzik-Sobanska L, Boksay I, et al. The pre-mild cognitive impairment, subjective cognitive impairment stage of Alzheimer's disease. Alzheimers Dement 2008;4:S98-S108.
  51. Parnetti L, Chipi E, Salvadori N, D'Andrea K, Eusebi P. Prevalence and risk of progression of preclinical Alzheimer's disease stages: a systematic review and meta-analysis. Alzheimers Res Ther 2019;11:7.
  52. Gauthier S, Albert M, Fox N, Goedert M, Kivipelto M, Mestre-Ferrandiz J, et al. Why has therapy development for dementia failed in the last two decades? Alzheimers Dement 2016;12:60-64.
  53. Sabbagh MN, Hendrix S, Harrison JE. FDA position statement "Early Alzheimer's disease: developing drugs for treatment, guidance for industry". Alzheimers Dement (N Y) 2019;5:13-19.