A Candidate Gene Study of Folate-Associated One Carbon Metabolism Genes and Colorectal Cancer Risk
Bibliographic record
Abstract
BACKGROUND: Folate-associated one-carbon metabolism (FOCM) may play an important role in colorectal carcinogenesis. Variation in FOCM genes may explain some of the underlying risk of colorectal cancer. METHODS: This study utilized data from 1,805 population-based colorectal cancer cases and 2,878 matched sibling controls from the Colon Cancer Family Registry. We used a comprehensive haplotype tagging single nucleotide polymorphism (tagSNP) approach to select 395 tagSNPs in 15 genes involved in folate and vitamin B(12) metabolism. Genotyping was done using the Illumina GoldenGate or Sequenom platforms. Risk factor and dietary data were collected using self-completed questionnaires. Microsatellite instability (MSI) status was determined using standard techniques, and tumor subsite was obtained from pathology reports. The association between SNPs and colorectal cancer was assessed using conditional logistic regression with sibships as the matching factor and assuming a log additive or codominant model. RESULTS: In the log additive model, two linked (r(2) = 0.99) tagSNPs in the DHFR gene (rs1677693 and rs1643659) were associated with a significant decrease in colorectal cancer risk after correction for multiple testing (odds ratio, 0.87; 95% confidence interval, 0.71-0.94; P = 0.029; and odds ratio, 0.87; 95% confidence interval, 0.71-0.95; P = 0.034 for rs1677693 and rs1643659, respectively). These two linked (r(2) = 0.99) tagSNPs and one tagSNP in the MTR gene (rs4659744) were significantly associated with reduced colorectal cancer risk only among individuals not using multivitamin supplements. CONCLUSIONS: Overall, we found only moderate evidence that genetic variation in 15 folate pathway genes may affect colorectal cancer risk except in non-multivitamin users. IMPACT: This study suggests that multivitamin supplement use may modify the association between folate pathway genes and colorectal cancer risk in a post-folic-acid-supplemented population.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".