Diagnostic yield of targeted next-generation sequencing in infantile nystagmus syndrome

Background: Infantile nystagmus syndrome (INS) is a genetically heterogeneous disorder. Identifying genetic causes of INS would help clinicians to facilitate clinical diagnosis and provide appropriate treatment. The aim of this study was to determine the diagnostic utility of targeted next-generation sequencing (NGS) for INS. Materials and methods: We recruited 37 patients who were referred to the Neuro-ophthalmology clinics for evaluations of INS. NGS was performed using a targeted panel that included 98 candidate genes associated with INS. We identified pathogenic variants according to guidelines of the American College of Medical Genetics and Genomics. We also calculated the sensitivity and specificity of each clinical sign to assess the diagnostic yield of our gene panel. Results: After variant filtering, annotation, and interpretation, the potential pathogenic variants were detected in 13 of the 37 patients, achieving a molecular diagnostic rate of 35%. The identified genes were PAX6 (n = 4), FRMD7 (n = 4), GPR143 (n = 2), CACNA1F (n = 1), CNGA3 (n = 1) and GUCY2D (n = 1). In approximately 30% (n = 4) of the patients, the initial clinical diagnosis was revised after a molecular diagnosis was performed. The presence of a family history had the highest predictive power for a molecular diagnosis (sensitivity = 61.5%, specificity = 91.7%), and the sensitivity increased when the family history was considered together with one of two clinical signs such as pendular nystagmus waveforms or anterior segment dysgenesis. Conclusions: Our study shows that targeted NGS can be useful to determine a molecular diagnosis for patients with INS. Targeted NGS also helps to confirm a clinical diagnosis in atypical phenotypes or unresolved cases.

Automated summary

This study utilized targeted next-generation sequencing for diagnostic analysis of infantile nystagmus syndrome, identifying 13 potential pathogenic variants with a 35% molecular diagnostic rate. Family history showed the highest predictive power for molecular diagnosis.