The Role of Sleep Disturbances in Alzheimer's Disease Progression: A Systematic Review
Bibliographic record
Abstract
Sleep disturbances are increasingly recognized as potential contributors to Alzheimer's disease (AD) progression, but their exact role remains debated. This systematic review aims to synthesize existing evidence on the association between sleep disturbances, particularly disruptions in sleep architecture and obstructive sleep apnea (OSA), and cognitive decline or AD biomarkers, while exploring underlying mechanisms. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 14 studies were selected from a comprehensive search of PubMed, Excerpta Medica Database (Embase), Psychological Information Database (PsycINFO), and Web of Science. Eligible studies included observational and longitudinal designs assessing sleep disturbances and their links to cognitive outcomes or AD pathology. Risk of bias was evaluated using the Newcastle-Ottawa Scale (NOS). Disruptions in rapid eye movement (REM) and non-rapid eye movement (NREM) sleep, such as reduced REM duration and fragmented sleep, were consistently associated with cognitive decline and new-onset dementia. Severe OSA increased AD risk, with hypoxia and sleep fragmentation implicated in neurodegeneration. Both objective (e.g., actigraphy) and subjective sleep measures predicted cognitive impairment, while cerebrospinal fluid (CSF) biomarkers and apolipoprotein E epsilon 4 (APOE ε4) genotype moderated these associations. Mechanistically, sleep disturbances may impair glymphatic clearance and exacerbate amyloid-β accumulation. Sleep disturbances, particularly REM/NREM disruptions and OSA, are robustly linked to AD progression, suggesting their potential as early biomarkers or therapeutic targets. However, causal inferences are limited by observational designs. Future research should prioritize interventional studies to determine whether improving sleep can mitigate AD risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".