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Saoud Al-khuzaei, Charlotte Foster, Suzanne Broadgate, Mital shah, Morag Shanks, Robert E MacLaren, Peter Charbel Issa, Penny Clouston, Stephanie Halford, Susan M Downes; Genotype-phenotype correlation of novel variants in ABCA4. Invest. Ophthalmol. Vis. Sci. 2021;62(8):1545.
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Stargardt disease (STGD1) associated with mutations in ABCA4 is genetically and phenotypically heterogeneous. Phenotypes range from yellow-white flecks in the macula with varying degrees of atrophy, some with more extensive distribution; bull’s eye maculopathy, to a more severe chorioretinal atrophy. In this study, we report novel variants in the ABCA4 gene and describe their genotype-phenotype correlation.
Patients with novel sequence variants were identified from a large cohort of clinically diagnosed STGD1 patients with at least two variants in ABCA4, by the Oxford Medical Genetics Laboratories. Phenotyping included: visual acuity, Goldmann visual field and electrophysiology testing, optical coherence tomography (OCT), false-color ultra-widefield and fundus autofluorescence (AF) imaging. This study was carried out in accordance with the tenets of the declaration of Helsinki, with ethics approval.
In this cohort of 20 patients, we identified 19 novel variants in ABCA4 of which 7 were missense mutations, 7 frameshift mutations, 1 whole exon deletion, 1 nonsense mutation, and 3 splice site mutations. The phenotypes in this cohort included the typical flecks seen in STGD1, macular atrophy and peripapillary sparing disease. Other features identified in these patients included; foveal sparing disease, a region of reduced foveal AF surrounded by a ring of raised AF, and widespread chorioretinal atrophy.
We describe 19 novel variants in ABCA4 and their associated phenotypes in a cohort of STGD1 patients. The identification of novel variants is important, as defining ABCA4 variants as pathogenic underpins genetic counselling, helps to confirm the diagnosis and in the future identify potential candidates for recruitment to therapeutic trials.
This is a 2021 ARVO Annual Meeting abstract.
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