Characterization of two Ashkenazi Jewish founder mutations in MSH6 gene causing Lynch syndrome
Bibliographic record
Abstract
Founder mutations are an important cause of Lynch syndrome and facilitate genetic testing in specific ethnic populations. Two putative founder mutations in MSH6 were analyzed in 2685 colorectal cancer (CRC) cases, 337 endometrial cancer (EnCa) cases and 3310 healthy controls of Ashkenazi Jewish (AJ) descent from population-based and hospital-based case–control studies in Israel, Canada and the United States. The carriers were haplotyped and the age of the mutations was estimated. MSH6*c.3984_3987dupGTCA was found in 8/2685 CRC cases, 2/337 EnCa cases, and 1/3310 controls, consistent with a high risk of CRC (odds ratio (OR) = 9.9, 95% confidence interval (CI) = 1.2–78.9, p = 0.0079) and a very high risk of EnCa (OR = 19.6, 95% CI = 1.8–217.2, p = 0.0006). MSH6*c.3959_3962delCAAG was identified in 3/2685 CRC cases, 2/337 EnCa cases and no controls. Each mutation was observed on separate conserved haplotypes. MSH6*c.3984_3987dupGTCA and MSH6*c.3959_3962delCAAG probably arose around 585 CE and 685 CE, respectively. No carriers were identified in Sephardi Jews (450 cases and 490 controls). Truncating mutations MSH6*c.3984_3987dupGTCA and MSH6*c.3959_3962delCAAG cause Lynch syndrome and are founder mutations in Ashkenazi Jews. Together with other AJ founder mutations, they contribute substantially to the incidence of CRC and EnCa and are important tools for the early diagnosis and appropriate management of AJ Lynch syndrome patients.
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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 | 0.000 |
| 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) | 0.001 | 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".