Gene Variant Spectrum in Probands With Familial Exudative Vitreoretinopathy Using an Expanded Panel
Bibliographic record
Abstract
Purpose: To investigate the gene variant spectrum in patients with familial exudative vitreoretinopathy (FEVR). Methods: Probands clinically diagnosed with FEVR and their relatives were enrolled and clinical information and DNA collected. An expanded FEVR panel was used, including six recognized FEVR genes (FZD4, NDP, LRP5, TSPAN12, ZNF408, and CTNNB1) and 19 genes previously associated with ocular features overlapping FEVR (FEVR-associated genes). Variants identified using targeted next-generation sequencing and/or Sanger sequencing were analyzed and classified using the American College of Medical Genetics and Clinical Genome Resource Sequence Variant Interpretation (ClinGen SVI) working group recommendations to detect disease-causing variants (DCVs). Results: Analyses of data from a cohort of 94 probands provided a molecular diagnosis for 39 (41.5%) probands: 34 (87.2%) had a single DCV, whereas 5 (12.8%) harbored more than 1 DCV. Of 41 total DCVs in solved probands, 33 (80.5%) were in 4 of the 6 recognized genes, LRP5, FZD4, TSPAN12, and NDP, whereas 8 were found in FEVR-associated genes, 6 in KIF11, and 2 (LAMA1 and DOCK6) each in association with a KIF11 DCV. Reanalyzing variants using the latest criteria impacted the variant classification in five probands (5.3%), changing variants that were once deemed likely pathogenic to variants of uncertain significance. Conclusions: The expanded FEVR gene panel detected DCVs in nearly one-half of our cohort. Including the criteria used in classification will improve transparency of variant calls as more data become available. Four FEVR genes account for most cases, and the role of rare FEVR genes and candidate genes requires further study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".