Novel Breast Cancer Susceptibility Locus at 9q31.2: Results of a Genome-Wide Association Study
Bibliographic record
Abstract
BACKGROUND: Genome-wide association studies have identified several common genetic variants associated with breast cancer risk. It is likely, however, that a substantial proportion of such loci have not yet been discovered. METHODS: We compared 296,114 tagging single-nucleotide polymorphisms in 1694 breast cancer case subjects (92% with two primary cancers or at least two affected first-degree relatives) and 2365 control subjects, with validation in three independent series totaling 11,880 case subjects and 12,487 control subjects. Odds ratios (ORs) and associated 95% confidence intervals (CIs) in each stage and all stages combined were calculated using unconditional logistic regression. Heterogeneity was evaluated with Cochran Q and I(2) statistics. All statistical tests were two-sided. RESULTS: We identified a novel risk locus for breast cancer at 9q31.2 (rs865686: OR = 0.89, 95% CI = 0.85 to 0.92, P = 1.75 × 10(-10)). This single-nucleotide polymorphism maps to a gene desert, the nearest genes being Kruppel-like factor 4 (KLF4, 636 kb centromeric), RAD23 homolog B (RAD23B, 794 kb centromeric), and actin-like 7A (ACTL7A, 736 kb telomeric). We also identified two variants (rs3734805 and rs9383938) mapping to 6q25.1 estrogen receptor 1 (ESR1), which were associated with breast cancer in subjects of northern European ancestry (rs3734805: OR = 1.19, 95% CI = 1.11 to 1.27, P = 1.35 × 10(-7); rs9383938: OR = 1.18, 95% CI = 1.11 to 1.26, P = 1.41 × 10(-7)). A variant mapping to 10q26.13, approximately 300 kb telomeric to the established risk locus within the second intron of FGFR2, was also associated with breast cancer risk, although not at genome-wide statistical significance (rs10510102: OR = 1.12, 95% CI = 1.07 to 1.17, P = 1.58 × 10(-6)). CONCLUSIONS: These findings provide further evidence on the role of genetic variation in the etiology of breast cancer. Fine mapping will be needed to identify causal variants and to determine their functional effects.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".