Resting-state EEG alpha/theta power ratio discriminates early-onset Alzheimer's disease from healthy controls.

Objectives: The present study aims to compare early-onset Alzheimer's disease (EOAD) patients with healthy controls (HC), and late-onset Alzheimer's disease (LOAD) patients using resting-state delta, theta, alpha, and beta oscillations and provide a cut-off score of alpha/theta ratio to discriminate individuals with EOAD and young HC.
Methods: Forty-seven individuals with EOAD, 51 individuals with LOAD, and demographically-matched 49 young and 51 older controls were included in the study. Spectral-power analysis using Fast-Fourier Transformation (FFT) is performed on resting-state electroencephalography (EEG) data. Delta, theta, alpha, and beta oscillations compared between groups and Receiver Operating Characteristic (ROC) curve analysis was conducted.
Results: Compared to healthy controls individuals with EOAD showed an increase in slow frequency bands and a decrease in fast frequency bands. Frontal alpha/theta power ratio is the best discriminating value between EOAD and young HC with the sensitivity and specificity greater than 80% with area under the curve (AUC) 0.881.
Conclusions: EOAD display more widespread and severe electrophysiological abnormalities than LOAD and HC which may reflect more pronounced pathological burden and cholinergic deficits in EOAD. Additionally, the alpha/theta ratio can discriminate EOAD and young HC successfully.
Significance: This study is the first to report that resting-state EEG power can be a promising marker for diagnostic accuracy between EOAD and healthy controls.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)