Raw resting-state electroencephalogram biomarker emerges as an indicator of Alzheimer’s disease over a two-year period

Aim: Alzheimer’s disease (AD) is associated with several electrophysiological biomarkers. These biomarkers are associated with global decline in cognition and a diagnosis of AD. However, a specific electrophysiological biomarker is not characterized as normal-functioning older adults convert to AD. The longitudinal retrospective study was conducted to describe an electrophysiological biomarker indicator for AD as normal-functioning older adults convert to a diagnosis in the AD continuum over a 2-year period. Methods: The study was conducted with 54 community-residing older adults, ranging from normal functioning to a diagnosis of AD. All initial and follow-up electrophysiological evaluations were completed in the New York University Brain Research Laboratories, and overall decline assessments with the Global Deterioration Scale (GDS) were completed in the New York University Aging and Dementia Research Center. Data included measurements from the GDS and raw resting-state electroencephalogram (rsEEG), which was transformed into quantitative EEG (qEEG) data. Data analysis consisted of descriptive statistics and a Kruskal-Wallis test. The level of significance was 0.05 with a moderate effect size. Topographic brain images displayed electrophysiological biomarkers. Results: A consistently increasing rsEEG theta frequency (P ≤ 0.01) occurred as normal-functioning older adults converted to AD across all GDS stages from the frontal to posterior regions with the progressive global decline. No discernible consistent electrophysiological changes were observed for rsEEG delta, alpha, or beta frequencies over all GDS stages. The GDS stages differed at baseline and follow-up (P ≤ 0.01). The rsEEG theta frequency increased with the progressive global decline across the GDS stages. Conclusions: The consistently increasing rsEEG theta frequency may be an electrophysiological biomarker indicator for AD from normal functioning to a diagnosis within the AD continuum. This biomarker will enhance the assessment of the risk, onset, and progression of AD and potentially inform the treatment of AD.