Sleep/wake cycle alterations as a cause of neurodegenerative diseases: A Mendelian randomization study
Bibliographic record
Abstract
Sleep and/or wake cycle alterations are common in neurodegenerative diseases (ND). Our aim was to determine whether there is a causal relationship between sleep and/or wake cycle patterns and ND (Parkinson's disease (PD) age at onset (AAO), Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS)) using two-sample Mendelian Randomization (MR). We selected 12 sleep traits with available Genome-Wide Association Study (GWAS) to evaluate their causal relationship with the ND risk through Inverse-Variance Weighted regression as main analysis. We used as outcome the latest ND GWAS with available summary-statistics: PD-AAO (N = 17,996), AD (N = 21,235) and ALS (N = 40,136). MR results pointed to a causal effect of subjective and objective-measured morning chronotype on later PD-AAO (95%CI:0.33-1.81, p = 8.47×10−09 and 95%CI:-7.28 to -4.44, p = 5.87×10−16, respectively). Sleep efficiency was causally associated with a decreased AD risk (95%CI:-20.408 to -0.66, p = 0.04) and daytime sleepiness with an increased ALS risk (95%CI:0.15 to 1.61, p = 0.01). Our study suggests that sleep and/or wake patterns have causal relationship with ND. Given that sleep and/or wake patterns are modifiable risk factors, sleep interventions should be investigated as a potential treatment in PD-AAO, AD and ALS.
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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 | 0.017 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".