Genetic Polymorphisms of Ataxia Telangiectasia Mutated and Breast Cancer Risk
Bibliographic record
Abstract
To evaluate the role of genetic polymorphisms of ataxia telangiectasia mutated (ATM) in the etiology of breast cancer, a hospital-based case-control study was conducted in Korea. Nine-hundred ninety-six histologically confirmed incident breast cancer cases and 1,181 cancer-free controls were recruited in Seoul between 1995 and 2003. Genotypes of the ATM polymorphisms-5144A > T, IVS21 + 1049T > C, IVS33 - 55T > C, IVS34 + 60G > A, and 3393T > G were determined by the 5'-nuclease assay. Individual haplotypes were estimated from genotype data by a Bayesian method. Five ATM alleles were found to be in strong linkage disequilibrium (D' > 0.82; P < 0.001). Haplotype frequencies were significantly different between cases and controls (chi2 test, P < 0.001). The ATM IVS21 + 1049 TC or CC, IVS34 + 60 GA or AA, and 3393 TG or GG genotypes were associated with increased breast cancer risk, particularly in premenopausal women [odds ratios (OR), 1.51; 95% confidence interval (CI), 1.11-2.05; OR, 1.42; 95% CI, 1.08-1.88; and OR, 1.37; 95% CI, 1.04-1.80, respectively]. Compared with diploid of TCCAG:TCCAG, the most common haplotype, the ATTGT:ATTGT was associated with decreased risk of breast cancer with borderline significance (OR, 0.77; 95% CI, 0.58-1.04) and TCCAG:ATCGT and ATTGT:ACCAG were associated with increased breast cancer risk (OR, 2.30; 95% CI, 1.18-4.48 and OR, 2.43; 95% CI, 1.1.07-5.52, respectively) after adjusting for age, education, age at first full-term pregnancy, parity, family history of breast cancer, alcohol consumption, and smoking. As the number of ATTGT haplotype decreased, the risk of breast cancer increased (P for trend < 0.01). Our results thus suggest that genetic polymorphisms of ATM play an important role in the development of breast cancer in Korean women.
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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 | 0.000 |
| 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".