GENETIC BASIS OF RETINAL DEGENERATIVE DISORDERS: A MOLECULAR OPHTHALMOLOGY STUDY

Abstract

One of the most genetically heterogeneous groups of human diseases is the inherited retinal degenerative disorders (IRDs), of which over 270 genes are linked with the malfunction of the photoreceptors and the subsequent degradation of the retinal pigment epithelia.  This study employed the technique of quantitative, observational molecular ophthalmology to clarify the genetic basis and genotype phenotype ties of inherited retinal illnesses (IRDs) in a clinically defined sample group of 224 patients.  Tiered genomic testing using gene panel targeted screens, whole-exome sequencing (WES), and reflex whole-genome sequencing (WGS) was combined with standardized retinal phenotyping, which consisted of visual acuity, optical coherence tomography (OCT), fundus autofluorescence (FAF) and electroretinography (ERG).  The overall MD yield was at 59.8% (95% CI: 53.3-66.0), and higher yields were among consanguinity families (63.2%), and those that underwent reflex WGS (80.6%).  Pathogenic mutations were located in most cases in USH2A, RPGR and ABCA4. The most popular was an autosomal recessive (59.0%), then it was in autosomal dominant (25.4%) and X-linked (15.7) inheritance.  The variant distribution revealed that the most frequent types of alterations were missense mutation (42%), and frameshift /nonsense mutation (28%).  Structural-functional studies found that there was a strong correlation between best-corrected visual acuity and ellipsoid zone extent (r = -0.71, p = 0.001).  Age of onset and consanguinity at a young age were also strong predictors of successful molecular diagnosis (adjusted OR 1.72, 95% CI 1.102.70), but more preservation of the ellipsoid zone supplied protection against severe visual impairment (adjusted OR 0.58, 95% CI 0.460.72).  These findings support the purpose of diagnostic and prognostic importance of extensive genomic testing in inherited retinal diseases (IRDs) and underline the need to combine molecular data with clinical imaging to provide specific treatment.