ArticleOphthalmology science2026
Benchmarking AlphaMissense against ClinVar for Diagnostic Interpretation of Missense Variants in Inherited Retinal Diseases.
Article in Ophthalmology science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Review
- Functional screening of ZIP8 naturally occurring variants identifies pathogenic mutations and trafficking defects.bioRxiv : the preprint server for biology · 2026Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: AlphaMissense is a newer deep learning-based variant predictor that evaluates the structural consequences of missense variants, the most common pathogenic variant type in inherited retinal diseases (IRDs). This study evaluates the diagnostic utility of AlphaMissense in IRDs by assessing its concordance with ClinVar annotations and exploring how other variant-level metrics may refine its predictions. Design: A cross-sectional benchmarking study using public variant resources, with a single illustrative clinical case. Participants: Missense variants from 107 IRD genes; 1 patient case undergoing long-read sequencing. Methods: Pathogenicity scores from AlphaMissense were extracted from 128 248 variants present in both IRD genes and the Genome Aggregation Database. Among these, 4204 had definitive ClinVar classifications and were used to calculate AlphaMissense specificity, sensitivity, and false discovery rate (FDR). Population-based metrics, including allele frequency, homozygote count, and Combined Annotation Dependent Depletion score, were analyzed to identify salient features that would be associated with discordance. Long-read sequencing was carried out in a monoallelic Main Outcome Measures: Concordance between AlphaMissense predictions and ClinVar annotations was used to calculate sensitivity, specificity, and FDR. Variant-level metrics between discordant variants. Case-based reclassification of hypomorphic variants with long-read sequencing. Results: AlphaMissense achieved a specificity of 94.1% and sensitivity of 79.4% in IRD genes, with specificity reaching 100% in A Conclusions: AlphaMissense demonstrates high specificity for pathogenicity prediction in IRD-associated genes; however, its reduced sensitivity, as seen in hypomorphic variants, suggests a need to incorporate population and functional metrics scores, which may improve classification accuracy, especially as long-read sequencing enables phased variant analysis. Financial Disclosures: The authors have no proprietary or commercial interest in any materials discussed in this article.
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