Founder TIGR/myocilin mutations for glaucoma in the Quebec population Mathieu Faucher1, Jean-Louis Anctil2,3, Marc-Andre Rodrigue1, Annie Duchesne1,
Bibliographic record
Abstract
Primary open-angle glaucoma (POAG) is a complex disorder characterized by a progressive and treatable degeneration of the optic nerve. TIGR/myocilin (MYOC) gene mutations are found in 4 % of all POAG patients. Populations with frequent founder effects, such as the French-Canadians, offer unique advantages to implement genetic testing for the disorder. To assess molecular diagnosis for POAG in this population, we determined the prevalence of TIGR/MYOC mutations in 384 unrelated glaucoma patients, 38 ocular hypertensive subjects and 18 affected families (180 patients). We further analyzed the clinical features associated with these variations. Nine coding sequence variants were defined as mutations causing mostly, but not exclusively, POAG. Four families segregated distinct mutations (Gly367Arg, Gln368Stop, Lys423Glu and Pro481Leu), while 14 unrelated glaucoma patients harbored six known mutations (Thr293Lys, Glu352Lys, Gly367Arg, Gln368Stop, Lys423Glu and Ala445Val) and two novel (Ala427Thr and Arg126Trp). The frequencies of these mutations were respectively 3.8 % and 22.2 % in the unrelated and family studies. The Gly367Arg and Lys423Glu variants caused the earliest ages at onset. When achievable, assement of relatives of unrelated mutation carriers showed the Arg126Trp and Gly367Arg to be familial. Characteristic allele signatures, indicative of specific founder effects, were observed for five of the six mutations conveyed by at least two patients. Recombination probability estimates suggested that the French-Canadian population had
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".