High Frequency of BRCA1 Founder Mutations in the Bahamas.
Bibliographic record
Abstract
Abstract The frequency of mutations in the BRCA1 and BRCA2 genes differs among ethnic groups, due to regional founder effects. The Bahamas is an island nation of 305,000 people, with a complex history of immigration from the 1600s-1800s including English, Americans and African slaves. An initial survey by our group demonstrated that 48% of breast cancers in the Bahamas are diagnosed in women under 50 suggesting an inherited cause for many. In a follow up study, we identified four distinct BRCA1 mutations in 9 of 19 high risk Bahamian breast and ovarian cancer families (47.36%). A fifth mutation has been previously published in a Bahamian family and is a confirmed African founder mutation. In the current study, we sought to estimate the prevalence of these mutations among unselected breast and ovarian cancer patients from the Bahamas. We have enrolled 135 unrelated women with breast (n = 133) or ovarian cancer (n=2) attending public and private clinics in the Bahamas and Miami. A detailed family history was obtained from each patient and a saliva sample was obtained for DNA analysis. DNA samples were tested by mutation specific assay for the presence of five BRCA1 mutations (IVS13+1G>A, M1775R, IVS16+6A>C, 4730insG and 943ins10). Twenty-three mutations were detected, representing 17% mutation prevalence in this population, including IVS13+1G>A (14 times), IVS16+6A>C (two times), M1775R (three times), 4730insG (three times) and 943ins10 (once). This reflects a very high rate of genetic breast cancer in this population with a strong founder effect. This important finding raises the possibility of developing an inexpensive genetic screen for inherited susceptibility to breast cancer in the Bahamas and the need to mount an effective cancer prevention strategy for this population at high risk. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 4078.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".