Functional Characterization of <i>ABCA4</i> Missense Variants Aids Variant Interpretation and Phenotype Prediction in Patients With ABCA4-Retinal Dystrophies
Bibliographic record
Abstract
Purpose: Biallelic pathogenic variants in the gene encoding the ATP-binding cassette transporter ABCA4 are the leading cause of irreversible vision loss in inherited retinal dystrophies (IRDs). Interpretation of ABCA4 variants is challenging, due to cis-modifying and hypomorphic variants. We have previously detected 10 missense variants of unknown significance (VUS) in patients with suspected ABCA4-retinal dystrophies (ABCA4-RDs) in Norway. In this study, we functionally characterized the VUS to aid interpretation of the variants and to determine if they are associated with the disease. Methods: The ABCA4 VUS were expressed in HEK293T cells and the ABCA4 expression level and ATPase activity were determined and correlated with the patients' phenotype. The functional data further used for reclassification of the VUS following the American College of Medical Genetics and Genomics (ACMG) guidelines. Results: Of the 10 VUSs, 2 variants, Cys205Phe and Asn415Thr, were categorized as functionally severe. The age at presentation in the 2 patients carrying these variants was divergent and seemed to be driven by the patients' second pathogenic variants Gly1961Glu and c.5461-10T>C, respectively. Three variants, Val643Gly, Pro799Leu, and Val1433Ile were categorized as functionally moderate, and were found in patients with intermediate/late age at presentation. The remaining five variants were categorized as functionally normal/mild. Based on our data, c.614G>T p.(Cys205Phe), c.1244A>C p.(Asn415Thr), and c.2396C>T p.(Pro799Leu) were reclassified to (likely) pathogenic, while 4 of the functionally normal/mild variants could be reclassified to likely benign. Conclusions: Functional analyses of ABCA4 variants are a helpful tool in variant classification and enable us to better predict the disease severity in patients with ABCA4-RDs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".