Evidence of association between sleep quality and <i>APOE</i> ε4 in healthy older adults
Bibliographic record
Abstract
BACKGROUND: It has been estimated that the prevalence of Alzheimer disease (AD) and related dementias will triple by 2035, unless effective interventions or treatments are found for the neurodegenerative disease. Understanding sleep changes as a marker for both AD risk and progression is a burgeoning area of investigation. Specifically, there is emerging evidence that both sleep disturbances and the APOE ε4 allele are associated with increased dementia risk. Previous research has suggested that in AD, individuals carrying the APOE ε4 allele have decreased sleep quality compared to individuals without the APOE ε4 allele. This observational trial aimed to determine if healthy older adults with the risk allele (APOE ε4+) have more sleep complaints or evidence of objective sleep disruption compared to healthy older adults without the risk allele (APOE ε4-). METHODS: Within the larger Brain in Motion study, a subset of participants completed at-home polysomnography (PSG) and actigraphy sleep assessment. Subjective sleep complaints were determined using the Pittsburgh Sleep Quality Index. RESULTS: This investigation found a significant relationship between presence of APOE ε4 allele and objective sleep disturbances measured by both actigraphy and PSG, but not subjective sleep complaints in a healthy population screened for dementia. CONCLUSIONS: These data suggest that the influence of APOE ε4 allele on objective sleep quality may precede subjective sleep complaints in individuals at increased risk for dementia.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".