Genetic Predictors of Circulating 25-Hydroxyvitamin D and Risk of Colorectal Cancer
Bibliographic record
Abstract
BACKGROUND: Experimental evidence has demonstrated an antineoplastic role for vitamin D in the colon, and higher circulating 25-hydroxyvitamin D [25(OH)D] levels are consistently associated with a lower risk of colorectal cancer. Genome-wide association studies have identified loci associated with levels of circulating 25(OH)D. The identified single-nucleotide polymorphisms (SNPs) from four gene regions collectively explain approximately 5% of the variance in circulating 25(OH)D. METHODS: We investigated whether five polymorphisms in GC, CYP2R1, CYP24A1, and DHCR7/NADSYN1, genes previously shown to be associated with circulating 25(OH)D levels, were associated with colorectal cancer risk in 10,061 cases and 12,768 controls drawn from 13 studies included in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and Colon Cancer Family Registry (CCFR). We conducted a meta-analysis of crude and multivariate-adjusted logistic regression models to calculate odds ratios and associated confidence intervals for SNPs individually, SNPs simultaneously, and for a vitamin D additive genetic risk score (GRS). RESULTS: We did not observe a statistically significant association between the 25(OH)D-associated SNPs and colorectal cancer marginally, conditionally, or as a GRS, or for colon or rectal cancer separately. CONCLUSIONS: Our findings do not support an association between SNPs associated with circulating 25(OH)D and risk of colorectal cancer. Additional work is warranted to investigate the complex relationship between 25(OH)D and colorectal cancer risk. IMPACT: There was no association observed between genetic markers of circulating 25(OH)D and colorectal cancer. These genetic markers account for a small proportion of the variance in 25(OH)D.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".