Day‐to‐day sleep and circadian variability in association with Alzheimer’s Disease biomarkers
Bibliographic record
Abstract
Abstract Background Increasing evidence shows that Alzheimer’s Disease (AD) pathology, i.e., the Aß peptide, tau tangles and the APOEε4 allele, have all been associated with disrupted sleep and change in circadian rhythms. However, objective sleep measurements are often assessed over a single night. Measures of day‐to‐day variability might reveal unstable sleep and circadian rhythms that may reflect neurodegenerative processes. We sought to evaluate the association between AD biomarkers and sleep and circadian variability measured over a week of actigraphy. Method 203 dementia‐free participants (age: 68.5±5.4 years, 151 women) from the PREVENT‐AD cohort with known APOEε4 carrier status were tested with a week of actigraphy. Overlapping subsamples were tested for determination of cerebrospinal fluid (CSF) Aß1‐42, total t‐tau and p(181)‐tau (n = 100); CSF apoE protein (n = 69); and plasma Aß1‐42 (n = 144). Day‐to‐day variability in actigraphy circadian and sleep measures were assessed using the standard deviation of individual results. Day‐to‐day variability was compared between APOEε4 carriers were compared to non‐carriers using t‐tests. Linear regressions were performed between day‐to‐day variability with CSF and plasma, adjusted for age, sex, and time interval between measurements. An interaction term for APOEε4 carrier status was additionally tested in regression models. Result APOEε4 carriers did not differ meaningfully from non‐carriers regarding sleep and circadian variability. Lower CSF Aß1‐42 was associated with higher day‐to‐day variability of time of morning awakening and nighttime sleep duration (ß = ‐0.263, p = 0.009; b = ‐0.206, p = 0.041). Higher plasma Aß1‐42 was also associated with higher day‐to‐day variability for time in bed, activity counts, sleep onset latency, sleep efficiency, and nighttime sleep duration (ß = 0.160 to 0.242; p = 0.010 to 0.002). Lower CSF apoE protein was associated with increased day‐to‐day variability for time of morning awakening, time in bed, activity counts, and nighttime sleep duration (ß = ‐0.243 to ‐0.420; p = 0.042 to <0.001). Higher CSF t‐tau, and a trend for p(181)‐tau were associated with time of morning awakening day‐to‐day variability inε4 carriers only (interaction p<0.001;ß = 0.330, p = 0.047; b = 0.281, p = 0.094). Conclusion Sleep and circadian variability are associated with biomarkers of AD pathology and apoE metabolism. These results may suggest that unstable sleep promotes neurodegeneration or, conversely, that AD neuropathology disrupts sleep and circadian function.
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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".