Associations of the<i>A66G</i>Methionine Synthase Reductase Polymorphism in Colorectal Cancer: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Inconsistency in the reported associations between the A66G polymorphism in the methionine synthase reductase (MTRR) gene and colorectal cancer (CRC) prompted a meta-analysis, so that we could obtain a more precise estimate. Databases searches of the published literature yielded 20 case-control studies from 17 articles (8,371 cases and 12,574 controls). We calculated pooled odds ratios (ORs) and 95% confidence intervals in three genetic comparisons (A allele, G allele, and A/G genotype). We found no evidence of overall associations between MTRR A66G and CRC risk (OR 0.96-1.05, P = 0.12-0.44). This was materially unchanged when reanalyzed without the Hardy-Weinberg equilibrium (HWE)-deviating studies (OR 0.97-1.06, P = 0.11-0.65). In the A allele comparison, however, outlier treatment generated significant protection (OR 0.91, P = 0.01). Combined removal of the outliers and HWE-deviating studies reflected this summary effect (OR 0.90, P = 0.01) as did the pooled OR from high-quality studies (OR 0.90, P = 0.01). Only the Asian subgroup showed significant (both at P = 0.05) A allele (OR 1.13) and A/G genotype (OR 0.88) associations. In conclusion, post-outlier A allele effects were protective. Our study also suggests ethnic-specific associations with Asian susceptibility and protection in the A allele and A/G genotype comparisons, respectively. Folate status showed no association of this polymorphism with CRC.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.001 | 0.005 |
| 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".