Genome-wide interaction analysis of folate for colorectal cancer risk
Bibliographic record
Abstract
Epidemiological and experimental evidence suggests that higher folate intake is associated with a decreased colorectal cancer (CRC) risk; however, the mechanisms underlying this relationship are not fully understood. Genetic variation that may have a direct or indirect impact on folate metabolism can provide insights into folate’s role in CRC. Our aim was to perform a genome-wide interaction analysis to identify genetic variants that may modify the association of folate on CRC risk. We applied traditional case-control logistic regression, joint 3-degree of freedom (3DF), and a two-step weighted hypothesis approach to test the interactions of common variants (allele frequency >1%) across the genome and dietary folate, folic acid supplement use, and total folate in relation to risk of CRC, in 30,550 cases and 42,336 controls from 51 studies from 3 genetic consortia (CCFR, CORECT, GECCO). Inverse associations of dietary, total folate, and folic acid supplement with CRC were found [odds ratio: 0.93 (95% confidence intervals [CI]: 0.90-0.96), and 0.91 (0.89-0.94) per quartile higher intake, and 0.82 (0.78-0.88) for users vs. non-users, respectively]. Interactions (P-interaction <5×10-8) of folic acid supplement and variants in the 3p25.2 locus [in the region of Synapsin II (SYN2)/tissue inhibitor of metalloproteinase 4 (TIMP4)] were found using the traditional interaction analysis, with variant rs150924902 (located upstream to SYN2) showing the strongest interaction. In stratified analyses by rs150924902 genotypes, folate supplement was associated with decreased CRC risk among those carrying the TT genotype (OR = 0.82; 95%CI: 0.79-0.86) but increased CRC risk among those carrying the TA genotype (OR = 1.63; 95%CI: 1.29-2.05), suggesting a qualitative interaction (P-interaction = 1.4×10-8). No interactions were observed for dietary and total folate. Variation in 3p25.2 locus may modify the association of folate supplement with CRC risk. Experimental studies and studies incorporating other relevant -omics data are warranted to validate this finding.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.008 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".