Physical activity and molecular subtypes of colorectal cancer: a pooled observational analysis and Mendelian randomization study
Bibliographic record
Abstract
BACKGROUND: Physical activity is associated with lower colorectal cancer (CRC) risk, but its association with molecular subtypes defined by genetic and epigenetic alterations of the disease is unclear. Such information may enhance the understanding of the mechanisms related to the benefits of physical activity. METHODS: Pooled observational (cases: n = 5386; controls: n = 6798; studies n = 5) and genome-wide association data (cases: n = 8178; controls: n = 10 472; studies n = 5) were used. We used multivariable logistic regression models and Mendelian randomization to assess the association between physical activity and the risk of CRC subtypes defined by individual tumor markers (and marker combinations), namely microsatellite instability status, CpG island methylator phenotype status, and BRAF and KRAS mutations. We used case-only analysis to test for differences between molecular subtypes. We applied Bonferroni correction to account for multiple tests. RESULTS: In the pooled observational analysis, higher levels of physical activity were associated with lower CRC risk (Obs-per 1SD, odds ratio [OR] = 0.94, 95% confidence interval [CI] = 0.90 to 0.97), with an association that was stronger in males (Obs-per 1SD, OR = 0.91, 95% CI = 0.87 to 0.96) than in females (Obs-per 1SD, OR = 0.97, 95% CI = 0.91 to 1.03; Pinteraction = .04). Higher physical activity was associated with a lower risk of CRC across all molecular subtypes, especially in males. There was no difference in the associations by subtypes by pooled observational or Mendelian randomization analyses. The findings did not differ by study design, anatomical site, and early or late age onset of CRC. CONCLUSIONS: Our findings suggest that physical activity is not differentially associated with the 4 major molecular subtypes involved in colorectal carcinogenesis, indicating that its benefits extend broadly across colorectal cancer pathogenesis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".