Sleep and electroencephalography biomarkers in preclinical Alzheimer’s Disease
Bibliographic record
Abstract
Abstract Background Accumulating evidence supports a bi‐directional relationship between sleep and Alzheimer’s Disease, including sleep disruptions in preclinical Alzheimer’s Disease (pAD), prior to onset of overt cognitive symptoms. Subsequently, sleep phenotypic variables and electroencephalography (EEG) features are attractive noninvasive biomarkers for pAD. The Biomarkers of Alzheimer’s Disease in Sleep and EEG (BASE) study seeks to develop such sleep‐EEG biomarkers for pAD. Method Community‐dwelling participants (n = 52, mean age: 70.8 ± 4.5 years) underwent cognitive testing including Montreal Cognitive Assessment (MOCA, general cognition), Craft Story 21 (CS21, memory), and Trails A and B (visuospatial, executive); performance was z‐scored by age, sex, and education. Objective measures of sleep quality were obtained using actigraphy over 4‐14 (mean 9.1) days at home: wake time after sleep onset (WASO), number of awakenings (NoA), and sleep efficiency. In‐lab overnight polysomnography was performed, and EEG features were extracted during NREM sleep from F3, F4, C3, and C4 channels: relative slow and fast delta power (RSDP, RFDP), spindle density, and slow wave density. The following morning (9‐10AM), CSF was obtained by fasted lumbar puncture, and assessed for amyloid‐b‐42 and tau; pAD was determined by tau/amyloid‐b‐42 ratio. Correlations between cognitive performance and EEG /sleep variables were performed using linear models, adjusted for age, sex, education, and sleep apnea status. Interaction between pAD status and correlations were assessed. Result There were 36 biomarker‐negative healthy controls (HC) and 16 with pAD; groups did not significantly differ demographically. RSDP and WASO were negatively associated with CS21 (RSDP: p = 0.040; WASO: p = 0.034). RFDP and NoA interacted with pAD status for MOCA (RFDP: p = 0.010; NoA: p = 0.026), and RFDP interacted with pAD status for CS21 (p = 0.017). Conclusion We assessed objective sleep quality and sleep‐EEG features against cognitive performance, and any interaction with pAD status. Worse sleep quality was associated with worse memory performance. Among the EEG features assessed, RFDP was strongly negatively correlated with memory performance in those with pAD, suggesting neurophysiological aberrations of NREM sleep in this cohort.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".