Francesca Marino1, Wolfgang Ganglberger2, Haoqi Sun2, Yulin Liu1, Huitong Ding1, Robert Thomas2, Rhoda Au3, Brandon Westover2
1Boston University, 2Beth Israel Deaconess Medical Center, 3Boston University School of Medicine
Objective:
To evaluate whether an integrated score derived from sleep state electrocortical activity predicts future performance on neuropsychological (NP) tests.
Background:
Sleep state electrocortical activity, as measured using electroencephalograms (EEG), is linked with cognitive function and dementia risk. The rich information in overnight EEG can be condensed into integrated scores using machine learning. The Brain Health Score (BHS) was derived in prior work using an end-to-end deep learning model trained to jointly optimize higher cognitive function and lower disease risk from raw EEG, and correlates with NP test scores.
Design/Methods:
This study included 426 Framingham Heart Study (FHS) Generation 2 or Omni 1 participants with BHS values from in-home polysomnography in mid-to-late life, and subsequent digital clock drawing (dCDT) and NP testing an average of 12.6 years later. Linear regression models estimated associations between BHS and dCDT, memory, executive function, or language scores, adjusting for age, sex, race, education, smoking, body mass index, and FHS cohort. To enable comparison across outcomes, the independent variables were centered and rescaled, and then the model was refitted to generate standardized estimates. These standardized estimates were interpreted as the standard deviation (SD) change in each cognitive outcome associated with each 1-SD higher BHS. Higher BHS indicates better brain health (higher cognition and lower disease risk).
Results:
Participants were on average 56 years at sleep assessment, 55% female, and 86% non-Hispanic White. Each 1-SD higher BHS was associated with higher dCDT, memory, language, and executive function scores (dCDT: β: 0.16, 95% CI: 0.06-0.26; memory: β: 0.13, 95% CI: 0.03-0.23; language: β: 0.13, 95% CI: 0.03-0.23; executive: β: 0.10, 95% CI: 0.01-0.19).
Conclusions:
Higher BHS in mid-to-late life was associated with better digital and traditional NP performance more than a decade later. These findings support the potential of EEG-derived, data-driven scores as a biomarker of future cognitive health.
Disclaimer: Abstracts were not reviewed by Neurology® and do not reflect the views of Neurology® editors or staff.