The spectrum of <i>BRCA1</i> and <i>BRCA2</i> pathogenic sequence variants in Middle Eastern, North African, and South European countries
Bibliographic record
Abstract
BRCA1 BRCA2 mutational spectrum in the Middle East, North Africa, and Southern Europe is not well characterized. The unique history and cultural practices characterizing these regions, often involving consanguinity and inbreeding, plausibly led to the accumulation of population-specific founder pathogenic sequence variants (PSVs). To determine recurring BRCA PSVs in these locales, a search in PUBMED, EMBASE, BIC, and CIMBA was carried out combined with outreach to researchers from the relevant countries for unpublished data. We identified 232 PSVs in BRCA1 and 239 in BRCA2 in 25 of 33 countries surveyed. Common PSVs that were detected in four or more countries were c.5266dup (p.Gln1756Profs), c.181T>G (p.Cys61Gly), c.68_69del (p.Glu23Valfs), c.5030_5033del (p.Thr1677Ilefs), c.4327C>T (p.Arg1443Ter), c.5251C>T (p.Arg1751Ter), c.1016dup (p.Val340Glyfs), c.3700_3704del (p.Val1234Glnfs), c.4065_4068del (p.Asn1355Lysfs), c.1504_1508del (p.Leu502Alafs), c.843_846del (p.Ser282Tyrfs), c.798_799del (p.Ser267Lysfs), and c.3607C>T (p.Arg1203Ter) in BRCA1 and c.2808_2811del (p.Ala938Profs), c.5722_5723del (p.Leu1908Argfs), c.9097dup (p.Thr3033Asnfs), c.1310_1313del (p. p.Lys437Ilefs), and c.5946del (p.Ser1982Argfs) for BRCA2. Notably, some mutations (e.g., p.Asn257Lysfs (c.771_775del)) were observed in unrelated populations. Thus, seemingly genotyping recurring BRCA PSVs in specific populations may provide first pass BRCA genotyping platform.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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".