Microarray-based mutation detection and phenotypic characterization in Korean patients with retinitis pigmentosa

PURPOSE: To evaluate microarray-based genotyping technology for the detection of mutations responsible for retinitis pigmentosa (RP) and to perform phenotypic characterization of patients with pathogenic mutations. METHODS: DNA from 336 patients with RP and 360 controls was analyzed using the GoldenGate assay with microbeads containing 95 previously reported disease-associated mutations from 28 RP genes. Mutations identified by microarray-based genotyping were confirmed by direct sequencing. Segregation analysis and phenotypic characterization were performed in patients with mutations. The disease severity was assessed by visual acuity, electroretinography, optical coherence tomography, and kinetic perimetry. RESULTS: Ten RP-related mutations of five RP genes (PRP3 pre-mRNA processing factor 3 homolog [PRPF3], rhodopsin [RHO], phosphodiesterase 6B [PDE6B], peripherin 2 [PRPH2], and retinitis pigmentosa 1 [RP1]) were identified in 26 of the 336 patients (7.7%) and in six of the 360 controls (1.7%). The p.H557Y mutation in PDE6B, which was homozygous in four patients and heterozygous in nine patients, was the most frequent mutation (2.5%). Mutation segregation was assessed in four families. Among the patients with missense mutations, the most severe phenotype occurred in patients with p.D984G in RP1; less severe phenotypes occurred in patients with p.R135W in RHO; a relatively moderate phenotype occurred in patients with p.T494M in PRPF3, p.H557Y in PDE6B, or p.W316G in PRPH2; and a mild phenotype was seen in a patient with p.D190N in RHO. CONCLUSIONS: The results reveal that the GoldenGate assay may not be an efficient method for molecular diagnosis in RP patients with rare mutations, although it has proven to be reliable and efficient for high-throughput genotyping of single-nucleotide polymorphisms. The clinical features varied according to the mutations. Continuous effort to identify novel RP genes and mutations in a population is needed to improve the efficiency and accuracy of the genetic diagnosis of RP.