Target 5000: Genetic characterisation of a cohort of inherited retinal degeneration (IRD) patients

Abstract

Purpose : While clinical trials are in progress for patients with inherited retinal degenerations (IRDs), many such trials require patients to have a known causative mutation to participate in these trials. The Target 5000 research project aims to genetically characterise the estimated 5,000 people in Ireland with IRDs.

Methods : The IRD patient cohort used in the study has been obtained via a collaborative network of ophthalmologists whereby if an IRD is suspected given consent, a DNA sample is taken and provided to a central laboratory for genetic analysis. The study seeks to detect previously identified, together with as yet undiscovered, pathological mutations in a panel of known retinal degeneration genes utilizing target capture next generation sequencing (NGS). The study to date includes over 700 IRD patients from more than 400 pedigrees.

Results : To date, as part of Target 5000, over 10% of the Irish IRD population has been sequenced providing real insights into the genetic architecture of IRDs in Ireland. Target 5000 offers not only a chance to discover new relevant and pathogenic mutations, but is vital to providing patients with information regarding the underlying genetic pathogenesis of their disease. Over 50 novel IRD mutations have been discovered to date, as well as some previously ambiguous disease phenotypes resolved.

Conclusions : The aim of the study is to genetically characterise patients with IRDs in Ireland and in principle potentially enable clinical trials to be more accessible for some patients analysed where appropriate. Thus far, during the course of the study, genetic analysis of IRD patients has helped to resolve ambiguous phenotypes and to identify causative mutations in approximately 60% of cases. The growing body of data from NGS studies of IRDs globally should facilitate better correlations between genotype and phenotype and refine methods for diagnoses and prognoses.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.