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Enhancing Molecular Diagnostic Accuracy in Genetic Eye Disorders Through a Personalized Re-Evaluation Strategy

Year: 2026
Type: article
Study design: Observational Study
Abstract: Purpose: Although genetic testing is crucial to provide prognostic information in genetic eye disorders (GEDs), up to 35% of cases remain unsolved after testing. We aim to describe how a tailored re-evaluation strategy, using up-to-date molecular testing, case-by-case review, and integration of in silico tools may increase the diagnostic yield. Methods: A total of 988 individuals from 800 families evaluated at the largest Portuguese GED referral center (Hospitais da Universidade de Coimbra) were included. All had a clinical diagnosis based on clinical findings and deep phenotyping and underwent genetic testing. Targeted re-evaluation included updated Next Generation Sequencing (NGS) panels, Exome Sequencing (ES) reanalysis, and assays for intronic variants, copy number variants, and ORF15-RPGR region. Variants of uncertain significance (VUS) were reassessed using segregation studies, literature/database review, and bioinformatic tools. Results: Initial testing yielded a molecular diagnosis in 475 families (59.4%). Variant reclassification enabled 39 additional diagnoses. A personalized re-testing strategy resolved 43 more, either through updated NGS panels (11), ES-reanalysis (14) and identification of deletions, GC-rich, and intronic variants (22). Overall, the solved rate increased from 59.4% to 70.1%. An additional 45 families (5.6%) carry phenotype-consistent VUS that could not be reclassified at the present date (partially-solved cases). Conclusions: This personalized re-evaluation strategy, incorporating state-of-the-art genetic testing, evidence-based variant reclassification, and case review by a multidisciplinary team increased the solved rate by over 10%. Consequently, 86 additional families received a definitive diagnosis and accurate genetic counseling, underscoring the impact of periodic re-evaluation and continuous improvement in genetic testing methodologies.
Language: English
Subfield: Genetics
Open Access status: gold
Estimated APC paid: $1,850
OpenAlex ID: W7126149985
FWCI: 3.72
Cites: 59
Cited by: 1
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