LAUSR

Purpose Retinitis pigmentosa (RP) shows great diversity between genotypes and phenotypes, and it is important to identify the causative genes. This study aimed to analyze the molecular profiles, associated ocular characteristics, and progression of RP in Korean patients. Methods All the genetic variants in patients with RP, identified using targeted next-generation sequencing (NGS) with a panel of 88 RP-related genes between November 2018 and November 2019, were retrospectively reviewed. All the patients underwent comprehensive ophthalmological evaluations, and their clinical and family histories were recorded. The best-corrected visual acuity (BCVA) deterioration and photoreceptor disruption progression rates were determined based on the major causative mutational genes using nonlinear mixed models, and the differences among them were investigated using the interaction effect. Results Among the 144 probands, 82 variants in 24 causative genes were identified in 77 families (53.5%). Most of the RP cases were associated with autosomal recessive variants (N = 64 (44.4%)), followed by autosomal dominant (N = 10 (6.9%)) and X-linked variants (N = 3 (2.1%)). The four most frequently affected genes were EYS (N = 15 (10.4%)), USH2A (N = 12 (8.3%)), PDE6B (N = 9 (6.3%)), and RP1 (N = 8 (5.6%)). Epiretinal membranes and cystoid macular edema were frequently noted in the patients with USH2A (75.0%) and PDE6B (50.0%) variants, respectively. During the follow-up period, the BCVA and photoreceptor disruption changes were significantly different among the patients carrying the four common causative genes (P=0.014 and 0.034, resp.). Patients with PDE6B variants showed faster BCVA changes (0.2 LogMAR/10 years), and those with USH2A variants showed the fastest ellipsoid zone disruptions (−170.4 µm/year). Conclusion In conclusion, our genetic analysis using targeted NGS provides information about the prevalence of RP-associated mutations in Korean patients. Delineating clinical characteristics according to genetic variations may help clinicians identify subtype features and predict the clinical course of RP.