Plasma Ghrelin and Risks of Sex-Specific, Site-Specific, and Early-Onset Colorectal Cancer: A Mendelian Randomization Analysis
Bibliographic record
Abstract
BACKGROUND: Epidemiological and laboratory-based studies have provided conflicting evidence for a role of ghrelin in colorectal cancer development. We conducted two-sample Mendelian randomization (MR) analyses to evaluate evidence for an association of circulating ghrelin and colorectal cancer risk overall and by sex, cancer subsite, and age at diagnosis. METHODS: Genetic instruments proxying plasma total ghrelin levels were obtained from a recent genome-wide association study of 54,219 participants. Summary data for colorectal cancer risk were obtained from a recent meta-analysis of several genetic consortia (up to 73,673 cases and 86,854 controls). A two-sample MR approach and several sensitivity analyses were applied. RESULTS: We found no evidence for an association of genetically predicted plasma total ghrelin levels and colorectal cancer risk (0.95, 95% confidence interval, 0.81-1.12; R2 of ghrelin genetic instruments: 4.6%), with similarly null results observed when stratified by sex, anatomical subsite, and for early-onset colorectal cancer. CONCLUSIONS: Our study suggests that plasma ghrelin levels are unlikely to have a causal relationship with overall, early-onset, and sex- and cancer subsite-stratified colorectal cancer risk. IMPACT: This large-scale analysis adds to the growing body of evidence that plasma total ghrelin levels are not associated with colorectal cancer 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 | 0.045 | 0.074 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".