Polymorphisms of the FOXF1 and MHC locus genes in individuals undergoing esophageal acid reflux assessments
Bibliographic record
Abstract
Gastroesophageal reflux disease (GERD) may lead to Barrett's esophagus (BE). Previously, a large genome-wide association study found two germline markers to be associated with BE, FOXF1 rs9936833 (C allele) and MHC rs9257809 (A allele). This study evaluated whether these two polymorphisms are associated with gastroesphageal acid reflux as measured by 24-hour pH testing. Patients with acid reflux symptoms referred for esophageal manometry and 24-hour pH monitoring at University Health Network (Toronto, ON) were enrolled. DNA extracted from blood was genotyped using a Taqman Polymerase Chain Reaction (PCR) assay. DeMeester scores of ≥14.7 or prior evidence of reflux esophagitis on endoscopy defined individuals with esophageal acid reflux. Logistic regression analysis, adjusted for clinical risk factors, was used to calculate odds ratios with 95% confidence intervals for each polymorphism in relation to the presence of acid reflux. Of 182 patients, the median age was 50 years and 62% were female; 95 (52%) met the definition of GERD. In the multivariable analysis, both FOXF1 rs9936833 (OR = 1.82; 95%CI: 1.12-2.96; P = 0.02) and MHC rs9257809 (OR = 9.36; 95%CI: 2.92-29.99; P < 0.001) remained significantly associated with presence of acid reflux. When both polymorphisms were placed in the same model, the adjusted ORs were 2.10 (95%CI: 1.24-3.53; P = 0.005) and 10.95 (95%CI: 3.32-36.09; P < 0.001), respectively. The association for risk allele C in FOXF1 rs9936833 and risk allele A in MHC rs9257809 with the presence of acid reflux suggests a potential pathophysiologic mechanism for the role of genetic influences in BE development.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".