Spectral power ratio as a measure of EEG changes in mild cognitive impairment due to Alzheimer’s disease: a case-control study

Adopting preventive strategies in individuals with subclinical Alzheimer’s disease (AD) has the potential to delay dementia onset and reduce healthcare costs. Thus, it is extremely important to identify inexpensive, scalable, sensitive, and specific markers to track disease progression. The electroe...

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Published inNeurobiology of aging Vol. 130; pp. 50 - 60
Main Authors Flores-Sandoval, Aimee A., Davila-Pérez, Paula, Buss, Stephanie S., Donohoe, Kevin, O’Connor, Margaret, Shafi, Mouhsin M., Pascual-Leone, Alvaro, Benwell, Christopher S.Y., Fried, Peter J.
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.10.2023
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Summary:Adopting preventive strategies in individuals with subclinical Alzheimer’s disease (AD) has the potential to delay dementia onset and reduce healthcare costs. Thus, it is extremely important to identify inexpensive, scalable, sensitive, and specific markers to track disease progression. The electroencephalography spectral power ratio (SPR: the fast to slow spectral power ratio), a measure of the shift in power distribution from higher to lower frequencies, holds potential for aiding clinical practice. The SPR is altered in patients with AD, correlates with cognitive functions, and can be easily implemented in clinical settings. However, whether the SPR is sensitive to pathophysiological changes in the prodromal stage of AD is unclear. We explored the SPR of individuals diagnosed with amyloid-positive amnestic mild cognitive impairment (Aβ+aMCI) and its association with both cognitive function and amyloid load. The SPR was lower in Aβ+aMCI than in the cognitively unimpaired individuals and correlated with executive function scores but not with amyloid load. Hypothesis-generating analyses suggested that aMCI participants with a lower SPR had an increased probability of a positive amyloid positron emission tomography. Future research may explore the potential of this measure to classify aMCI individuals according to their AD biomarker status.
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Equal contributions.
Authors’ contributions
Aimee A. Flores-Sandoval. and Peter J. Fried: writing- original draft preparation, formal analysis and conceptualization. Kevin Donohoe: data curation, writing-review and editing. Paula. Davila P., Mouhsin M. Shafi, Christopher S.Y. Benwell: writing-review and editing, formal analysis and conceptualization. Alvaro. Pascual-Leone: writing-review and editing, conceptualization and supervision. Stephanie S. Buss. and Margaret. O’Connor: writing-review and editing. All authors read and approved the final manuscript.
ISSN:0197-4580
1558-1497
1558-1497
DOI:10.1016/j.neurobiolaging.2023.05.010