Deciphering the impact of ABCA4 genetic variants of unknown significance in inherited retinal disease through computational and functional approaches.

Abstract

Variants in the ABCA4 gene are a fundamental cause of several inherited retinal degenerations (IRDs), including Stargardt macular dystrophy, retinitis pigmentosa, and cone-rod dystrophy. These three ABCA4-driven diseases are estimated to cause blindness in 1.4 million people worldwide. As a result, genetic testing of ABCA4 is increasingly common in clinical settings. Of the 4111 identified variants in ABCA4, 1668 are missense, of which 47 % are of unknown pathogenicity (variants of unknown significance, VUS). This genetic uncertainty leads to three fundamental problems: (i) for IRD patients with multiple unclassified ABCA4 mutations, it is impossible to predict which variant will cause disease in relatives who have not yet developed it; (ii) development of variant-specific therapies remains limited; and (iii) these variants cannot be used to predict disease prospectively, which is essential for life-planning decisions and for directing patients to new clinical trials. This chapter describes approaches to deciphering the impact of ABCA4 genetic variants of unknown significance (VUS) using a combination of in silico and in vitro analyses. By leveraging complementary fields-protein biochemistry and computational biology-to create a "sequence-structure-function" workflow, where in silico 3D protein structural analysis of ABCA4 sequence variants serves as a tool to predict disease severity and clinical pathogenicity in conjunction with first-line bioinformatic tools and functional analysis. This approach represents a helpful step forward in understanding how ABCA4 variants affect structure and function and in evaluating their potential to cause inherited retinal diseases.