Authors :
Presenting Author: Navnika Gupta, MD – Emory University School of Medicine
Denise Chen, MD – University of Washington School of Medicine; Adam Dickey, MD – Emory University School of Medicine; Brianna Burlock, MD – Emory University School of Medicine; Andres Rodriguez, MD – Emory University School of Medicine; Allan Levey, MD – Emory University School of Medicine; James Lah, MD – Emory University School of Medicine; Ioannis Karakis, MD – Emory University School of Medicine
Rationale:
Quantitative EEG (QEEG) has emerged as a potential biomarker aiding in Alzheimer disease (AD) diagnosis and prognosis. This study aims to evaluate the value ot QEEG in evaluating AD severity compared to other established biomarkers (cerebrospinal fluid-CSF-analysis).
Methods:
Retrospective evaluation of QEEG indices (absolute and relative delta, theta, alpha and beta power, as well as delta-alpha ratio-DAR) in the assessment of AD severity (mild cognitive impairment-MCI-vs established AD and absolute Montreal Cognitive Assessement-MOCA-scores) compared to CSF biomarkers (p-tau, t-tau and a-beta amyloid levels as well a-beta/tau ratio). Wilcoxon Rank Sum test was used for comparison of continuous with categorical variables and Pearson correlation coefficient was used for comparison of continuous with continuous variables.
Results:
Thirty five patients with AD (8 with MCI and 27 with established AD) were evaluated in our institution from 2012 to 2019 for cognitive impairment with neuropsychological evaluation, CSF collection and routine EEG recordings. Their median MOCA score was 17 (normal ≥26), their median abeta/tau index was 0.4 (normal ≤0.1) and their median DAR was 4.5. Compared to patients with MCI, patients with established AD had significantly higher relative delta power (p=0.04) (Figure 1). There was a trend for lower relative alpha power (p=0.06) (Figure 2) and higher DAR (p=0.06) in patients with established AD. There was a statistically significant, moderate, inverse correlation between the patients’ MOCA scores and their DAR (r=-0.43, p=0.0038). Conversely, no statistically significant association was identified between the investigated CSF biomarkers and AD severity (p >0.05).
Conclusions:
Current AD biomarkers, including CSF, can detect the presence of AD pathology but do not reflect stage of disease. Quantitative EEG emerges as a promising biomarker in evaluation of AD severity. Larger longitudinal studies are need to assess its utility in AD differential diagnosis and prognosis compared to additional established (e.g., radiological) biomarkers.
Funding: NA