Abstract
Purpose :
To develop a bioinformatic pipeline to increase the diagnostic rate of inherited retinal degenerations (IRDs) by analysing whole-genome sequencing data (WGS) from patients who have not received a molecular diagnosis via panel testing.
Methods :
We designed a bioinformatic pipeline to interrogate 732 genes with reported retinal expression. The pipeline was applied to WGS data from 44 patients in whom no pathogenic variants had been identified in known retinal disease genes using panel-based testing. In silico proteomics analysis was performed for all novel variants, variants of uncertain significance and variants in new candidate genes, to filter and select variants for further functional assays.
Results :
Potential pathogenic or likely pathogenic variants that could explain the phenotype were identified in 41/44 patients. These included variants in known disease genes not identified by panel testing in 8 patients, novel variants or variants of uncertain significance in previously reported retinal disease genes in 26 patients, and variants in novel genes expressed in the retina in 7 patients. The pipeline did not identify variants for 3 patients.
Conclusions :
This comprehensive bioinformatics pipeline, inclusive of in silico proteomic filtering, enabled the identification of candidate pathogenic variants in a high proportion of patients with inherited retinal degenerations lacking a genetic diagnosis after standard panel testing. It also identified new genes that may be associated with retinal disease. Further work is ongoing to confirm the pathogenicity and function of these variants.
This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.