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Genetic basis of inherited retinal disease in a UK cohort of over 2900 families

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Posterboard#: A0392

Abstract Number: 401 - A0392

AuthorBlock: Omar Abdul Rahman Mahroo1,2, NIKOLAS PONTIKOS1,2, Gavin Arno1,2, Rola Ba-Abbad2,1, Samantha Malka1,2, Genevieve Wright1,2, Monica Armengol1,2, Menachem Katz2, Anthony Moore3,1, Michel Michaelides1,2, Andrew Webster1,2
1Ophthalmology, UCL Institute of Ophthalmology, London, ENGLAND, United Kingdom; 2Moorfields Eye Hospital, , United Kingdom; 3University of California San Fransisco, California, United States;

DisclosureBlock: Omar Abdul Rahman Mahroo, None; NIKOLAS PONTIKOS, None; Gavin Arno, None; Rola Ba-Abbad, None; Samantha Malka, None; Genevieve Wright, None; Monica Armengol, None; Menachem Katz, None; Anthony Moore, None; Michel Michaelides, None; Andrew Webster, None;


Sequence variants in >250 genes have been identified as causing inherited retinal disease. In our molecularly characterised cohort of nearly 3000 families, we sought to quantify proportions of families with causative variants in each gene.


We retrospectively searched the database of the retinal genetics service of Moorfields Eye Hospital, London, UK. Molecular diagnoses were sought using a combination of single gene testing, panel testing, whole exome sequencing, and, increasingly, whole genome sequencing. For this study we included those genes listed on the Retinal Information Network online resource (www.retnet.org accessed 14 Nov 2018). We also extracted transcript length for the wild type version of each gene (Ensembl, release 94).

Our search yielded 2928 families in whom a likely causative gene had been found for their phenotype, with 135 disease-causing genes in total. The 20 most prevalent genes accounted for 71.2% of the cohort. These were ABCA4 (20.0%), USH2A (8.9%), RPGR (5.7%), PRPH2 (4.6%), BEST1 (3.9%), RP1 (3.5%), RHO (3.4%), RS1 (3.3%), CHM (2.8%), CRB1 (2.2%), MYO7A (1.8%), PRPF31 (1.7%), OPA1 (1.5%), CNGB3 (1.4%), GUCY2D (1.4%), RPE65 (1.4%), RDH12 (1.3%), CNGA3 (1.1%), and PROM1 (1.1%). 14.5% of families had variants in X-linked genes; 0.9% had variants in mitochondrial genes; 84.6% had variants in autosomal genes (51.4% with exclusively autosomal recessive inheritance; 25.1% in genes in which different variants can show either dominant or recessive inheritance; 8.1% in genes associated only with dominant inheritance). The Spearman coefficient for correlation between number of affected families and normal transcript length was 0.21 (p=0.015).


Our findings help quantify the burden of inherited retinal disease attributable to each gene in terms of numbers of affected families. Over 70% of families had disease-causing variants in one of only 20 genes. Transcript length, of relevance in developing strategies for gene delivery, correlated significantly with numbers of affected families: larger transcripts tended to have greater numbers of families with disease attributable to variants in those genes, but the correlation was weak.

Layman Abstract (optional): Provide a 50-200 word description of your work that non-scientists can understand. Describe the big picture and the implications of your findings, not the study itself and the associated details.

Our genes, which we inherit from our parents (one copy of each gene from each parent), contain instructions for our bodies to develop correctly. There can be a number of variations in genes that are harmless and some, more rare variations, that cause disease. Inherited retinal diseases are a major cause of blindness in young people. These are diseases due to particular variations in one or both copies of a single gene. There are over 200 genes identified in which different variations can cause retinal disease, and more are being discovered. Ability to determine which gene is responsible in which patient has improved dramatically in recent years, and we can now look in detail at all of a person’s genes. We have discovered the relevant gene in nearly 3000 families, and we are examining which genes are the most common, and whether this is linked to how long the gene is. This is helpful in advising affected patients and selecting patients in a timely way for new therapies that are emerging to try to correct the variations in some of the genes. It also helps us determine which genes to prioritise in research to achieve maximum benefit.