Single nucleotide polymorphisms in the matrix metalloproteinase gene family and the frequency and duration of gastroesophageal reflux disease influence the risk of esophageal adenocarcinoma
Bibliographic record
Abstract
The matrix metalloproteinase (MMP) family of proteins mediates various cellular pathways, including apoptosis and angiogenesis. Polymorphisms of MMP genes are associated with increased esophageal adenocarcinoma (EAC) risk. Gastroesophageal reflux disease (GERD) is an established EAC risk factor. We examined whether MMP polymorphism-EAC risk is modified by GERD. In total, 309 EAC patients and 279 frequency-matched healthy controls underwent MMP1 1G/2G, MMP3 6A/5A, MMP12 -82A/G and MMP12 1082A/G genotyping. Questionnaires collected GERD history. EAC risk was analyzed using logistic regression, adjusted for key covariates and stratified by GERD. Joint effects models explored GERD severity and duration, whereas additional models explored genotype-GERD interactions in EAC risk. We determined that each MMP1 and MMP3 minor (variant) allele was independently associated with increased EAC risk (adjusted odds ratio (AOR) 3.2, 95% confidence interval (CI) 2.0-5.1, p < 0.001 and AOR 1.8, 95% CI 1.1-2.7, p = 0.01, respectively) only among those with GERD but not in GERD-free individuals (all p = nonsignificant). There were significant interactions between the MMP1 variants and the presence of GERD (p = 0.002) and between MMP3 variants and GERD (p = 0.04). There was an equally strong interaction between cumulative GERD severity and MMP1 (p = 0.002). The AOR of each variant allele was 14.9 (95% CI 1.6-136) for individuals with severe GERD, 1.7 (95% CI 1.0-2.7) for mild-moderate GERD and 0.98 (95% CI 0.7-1.4) for those without GERD. This was further reflected in separate analyses of frequency and duration of GERD. In conclusion, MMP1 1G/2G (and possibly MMP3 6A/5A) polymorphisms alter EAC risk differentially for GERD and GERD-free individuals.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".