Inherited retinal dystrophies (IRDs) are a genetically diverse group of vision loss disorders with over 360 implicated genes. However, 30-50% of cases remain unresolved after panel-based clinical testing and may benefit from exome or genome sequencing for a genetic diagnosis. To manage the extensive and analytically demanding datasets generated by genome sequencing, we developed ReDGAP (Retinal Degeneration Genome Analysis Pipeline), a phenotype-guided, semi-automated genome analysis pipeline that integrates clinical phenotyping with flexible variant scoring to prioritize variants of interest (https://github.com/vincentlab-la/ReDGAP). The pipeline supports the joint analysis of multiple variant classes, using an evidence-weighted scoring system informed by in silico predictors. Validation in eleven previously solved IRD cases achieved a 100% re-identification rate. Application to five unsolved cases yielded diagnoses in four (80%), including intronic variants in CRB1 and HGSNAT, a tandem duplication in OAT, and a 5'UTR deletion affecting a retina-specific promoter of RPGRIP1. Functional validation confirmed transcript-level disruptions in three variants, while computational analysis demonstrated regulatory impact in the fourth. Integrating phenotypic data with broad variant analysis offers a tailored model for improving IRD diagnostics, enabling timely molecular diagnoses and informing eligibility for emerging gene-targeted therapies. This positions ReDGAP as a tailored, clinically relevant model for investigating rare diseases within the evolving landscape of precision health.
Ahmed et al. (Sat,) studied this question.