Candidate Gene Association Study of Esophageal Squamous Cell Carcinoma in a High-Risk Region in Iran
Bibliographic record
Abstract
There is a region with a high risk for esophageal squamous cell carcinoma (ESCC) in the northeast of Iran. Previous studies suggest that hereditary factors play a role in the high incidence of cancer in the region. We selected 22 functional variants (and 130 related tagSNPs) from 15 genes that have been associated previously with the risk of ESCC. We genotyped a primary set of samples from 451 Turkmens (197 cases and 254 controls). Seven of 152 variants were associated with ESCC at the P = 0.05 level; these single nucleotide polymorphisms were then studied in a validation set of 549 cases and 1,119 controls, which included both Turkmens and non-Turkmens. The association observed for a functional variant in ADH1B was confirmed in the validation set, and that of a tagSNP in MGMT, the association was borderline significant in the validation set, after correcting for multiple testing. The other 5 variants that were associated in the primary set were not significantly associated in the validation set. The histidine allele at codon 48 of ADH1B gene was associated with a significantly decreased risk of ESCC in the joint data set (primary and validation set) under a recessive model (odds ratio, 0.41; 95% confidence interval, 0.29-0.76; P = 4 x 10(-4)). The A allele of the rs7087131 variant of MGMT gene was associated with a decreased risk of ESCC under a dominant model (odds ratio, 0.79; 95% confidence interval, 0.64-0.96; P = 0.02). These results support the hypothesis that genetic predisposition plays a role in the high incidence of ESSC in Iran.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".