A Variant in the Cytochrome P450 Oxidoreductase Gene Is Associated with Breast Cancer Risk in African Americans
Bibliographic record
Abstract
Variation in the cytochrome P450 oxidoreductase (POR) gene, a key regulator of type II cytochrome P450 enzymes, may affect exposure to endogenous steroid hormones and breast cancer risk. We sequenced the POR locus and tested candidate polymorphisms G5G and A503V for association with breast cancer risk among women in the Multiethnic Cohort Study (1,615 cases and 1,962 controls). The single nucleotide polymorphism (SNP) A503V was common in all racial/ethnic populations (minor allele frequency, > or =0.05) but was not associated with risk. SNP G5G (A --> G nucleotide change), which lies in a suggestive exonic splicing enhancer motif in exon 1, was common only in African Americans (minor allele frequency, 0.21) and the homozygous state was modestly associated with increased breast risk among all cases [345 cases and 426 controls; odds ratio (OR), 1.64; 95% confidence interval (CI), 0.89-3.04; P = 0.12] and among cases with advanced disease (95 cases: OR, 3.08; 95% CI, 1.42-6.70; P = 0.005). In an attempt to replicate this association, we genotyped SNP G5G in additional African American case-control studies (747 cases and 468 controls). Nonsignificant positive associations were noted with the GG genotype class in all studies. In the pooled analysis (1,038 cases and 877 controls with genotype data), the association was statistically significant among all cases (OR, 1.58; 95% CI, 1.04-2.41; P = 0.03) and stronger in those with advanced disease (411 cases and 877 controls; OR, 2.60; 95% CI, 1.56-4.34; P = 0.0002). These data suggest that African Americans harbor an allele at the POR locus that may increase breast cancer risk.
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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 | 0.001 | 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) | 0.001 | 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".