Novel Variants in ABCA4-Related Retinopathies with Structural Re-Assessment of Variants of Uncertain Significance
Bibliographic record
Abstract
INTRODUCTION: Conclusive molecular genetic diagnoses in inherited retinal diseases remains a major challenge due to the large number of variants of uncertain significance (VUS) identified in genetic testing. Here, we determined the genotypic and phenotypic spectrum of ABCA4 gene variants in a cohort of Canadian inherited retinal dystrophy subjects. METHODS: This retrospective study evaluated 64 subjects with an inherited retinal dystrophy diagnosis with variants in the ABCA4 gene. Pathogenicity of variants was assessed by comparison to genetic databases and in silico modelling. ABCA4 variants classified as VUS were further evaluated using a cryo-electron structural model of the ABCA4 protein to predict impact on protein function and were also assessed for evolutionary conservation. RESULTS: Conclusive disease-causing biallelic ABCA4 variants were detected in 52 subjects with either Stargardt's disease, cone-rod dystrophy, macular dystrophy, or pattern dystrophy. A further 14 variants were novel comprising 1 nonsense, 1 frameshift, 3 splicing, and 9 missense variants. Based on in silico modelling, protein modelling and evolutionary conservation from human to zebrafish, we re-classified 5 of these as pathogenic and a further 3 as likely pathogenic. We also added to the ABCA4 phenotypic spectrum seen with four known pathogenic variants (c.2161-2A>G; Leu296Cysfs*4; Arg1640Gln; and Pro1380Leu). CONCLUSIONS: This study expands the genotypic and phenotypic spectrum of ABCA4 disease-associated variants. By panel-based genetic testing, we identified 14 novel ABCA4 variants of which 8 were determined to be disease-causing or likely disease-causing. These methodologies could circumvent somewhat the need for labour intensive in vitro and in vivo assessments of novel ABCA4 variants.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".