Genotype-Phenotype Correlations in Axenfeld-Rieger Malformation and Glaucoma Patients with<i>FOXC1</i>and<i>PITX2</i>Mutations
Bibliographic record
Abstract
PURPOSE: To improve the understanding of Axenfeld-Rieger Malformation (ARM)-associated glaucoma and to determine the best glaucoma treatment for patients with ARM who have known genetic defects in FOXC1 or PITX2. METHODS: Clinical data were collected from patients with diagnosed ARM, in whom we had previously identified disease-causing mutations in either the FOXC1 or PITX2 genes, by examination of patient records and use of clinical questionnaires. One hundred twenty-six patients with ARM, representing 20 different probands, with FOXC1 and PITX2 alterations were included in the study. RESULTS: ARM-associated glaucoma is a bilateral anterior segment dysgenesis disease that affects males and females equally. Seventy-five percent of the patients with ARM who participated in this study had glaucoma that had developed in adolescence or early adulthood. Of note, the patients with nonocular findings were more likely to have PITX2 defects than FOXC1 defects. Glaucoma in only 18% of patients with either PITX2 or FOXC1 genetic defects responded to medical or surgical treatment (used solely or in combination). CONCLUSIONS: Patients with FOXC1 mutations have the mildest prognosis for glaucoma development, whereas patients with PITX2 defects and patients with FOXC1 duplication have a more severe prognosis for glaucoma development than do patients with FOXC1 mutations. In the present study, current medical therapies do not successfully lower intraocular pressure or prevent progression of glaucoma in patients with ARM who have FOXC1 or PITX2 alterations. This clinical study also provides useful diagnostic criteria to identify the gene responsible for ARM.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".