Mendelian randomization study of sleep traits and risk of colorectal cancer
Bibliographic record
Abstract
Abstract A potential association of endogenous circadian rhythm disruption with risk of cancer development has been suggested, however, epidemiological evidence for the association of sleep traits with colorectal cancer (CRC) is limited and often contradictory. Here we investigated whether genetically predicted chronotype, insomnia and sleep duration are associated with CRC risk in males, females and overall and according to CRC anatomical subsites using Mendelian randomization (MR). The two-sample inverse variance weighted (IVW) method was applied using summary-level data in up to 58,221 CRC cases and 67,694 controls and genome-wide association data of genetic variants for self-reported sleep traits. Secondary analyses using alternative instruments and sensitivity analyses assessing potential violations of MR assumptions were conducted. Genetically predicted morning preference was associated with 13% lower risk of CRC in men (OR IVW = 0.87, 95% CI = 0.78, 0.97, P = 0.01), but not in women or in both sexes combined. Τhis association remained consistent in some, but not all, sensitivity analyses and was very similar for colon and rectal cancer. There was no evidence of an association for any other sleep trait. Overall, this study provides little to no evidence of an association between genetically predicted sleep traits and CRC risk.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".