Obesity and Risk of Esophageal Adenocarcinoma and Barrett’s Esophagus: A Mendelian Randomization Study
Bibliographic record
Abstract
BACKGROUND: Data from observational studies suggest that body mass index (BMI) is causally related to esophageal adenocarcinoma (EAC) and its precursor, Barrett's esophagus (BE). However, the relationships may be affected by bias and confounding. METHODS: We used data from the Barrett's and Esophageal Adenocarcinoma Genetic Susceptibility Study: 999 patients with EAC, 2061 patients with BE, and 2169 population controls. We applied the two-stage control function instrumental variable method of the Mendelian randomization approach to estimate the unbiased, unconfounded effect of BMI on risk of EAC and BE. This was performed using a genetic risk score, derived from 29 genetic variants shown to be associated with BMI, as an instrument for lifetime BMI. A higher score indicates propensity to obesity. All tests were two-sided. RESULTS: The genetic risk score was not associated with potential confounders, including gastroesophageal reflux symptoms and smoking. In the instrumental variable analyses (IV), EAC risk increased by 16% (IV-odds ratio [OR] = 1.16, 95% confidence interval [CI] = 1.01 to 1.33) and BE risk increased by 12% (IV-OR = 1.12, 95% CI = 1.00 to 1.25) per 1kg/m(2) increase in BMI. BMI was statistically significantly associated with EAC and BE in conventional epidemiologic analyses. CONCLUSIONS: People with a high genetic propensity to obesity have higher risks of esophageal metaplasia and neoplasia than people with low genetic propensity. These analyses provide the strongest evidence to date that obesity is independently associated with BE and EAC, and is not due to confounding or bias inherent in conventional epidemiologic analyses.
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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 | 0.010 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".