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Purpose: RDH12 is among the most common genes found in individuals with early-onset severe retinal (EOSRD). Adaptive optics scanning light ophthalmoscopy (AOSLO) enables resolution of individual rod and cone photoreceptors in the retina. This study presents the first AOSLO imaging of individuals with RDH12-associated EOSRD., Methods: Case series of patients who attended Moorfields Eye Hospital (London, UK). Spectral-domain optical coherence tomography, near-infrared reflectance (NIR), and blue autofluorescence imaging were analyzed. En face image sequences of photoreceptors were recorded using either of two AOSLO modalities. Cross-sectional analysis was undertaken for seven patients and longitudinal analysis for one patient., Results: Nine eyes from eight patients are presented in this case series. The mean age at the time of the assessment was 11.2 ± 6.5 years of age (range 7-29). A subfoveal continuous ellipsoid zone (EZ) line was present in eight eyes. Posterior pole AOSLO revealed patches of cone mosaics. Average cone densities at regions of interest 0.5° to the fovea ranged from 12,620 to 23,660 cells/mm2, whereas intercell spacing ranged from 7.0 to 9.7 µm., Conclusions: This study demonstrates that AOSLO can provide useful high-quality images in patients with EOSRD, even during childhood, with nystagmus, and early macular atrophy. Cones at the posterior pole can appear as scattered islands or, possibly later in life, as a single subfoveal conglomerate. Detailed image analysis suggests that retinal pigment epithelial stress and dysfunction may be the initial step toward degeneration, with NIR being a useful tool to assess retinal well-being in RDH12-associated EOSRD.

Purpose: To investigate the molecular effect of the variant PHYH:c.678+5G>T. This variant has conflicting interpretations in the ClinVar database and a maximum allele frequency of 0.0045 in the South Asian population in gnomAD., Methods: We recruited patients from Moorfields Eye Hospital (London, UK) and Buenos Aires, Argentina, who were diagnosed with retinitis pigmentosa and found to have biallelic variants in PHYH, with at least one being c.678+5G>T. Total RNA was purified from PaxGene RNA-stabilized whole-blood samples, followed by reverse transcription to cDNA, PCR amplification of the canonical PHYH transcript, Oxford Nanopore Technologies library preparation, and single-molecule amplicon sequencing., Results: Four patients provided a blood sample. One patient had isolated retinitis pigmentosa and three had mild extraocular findings. Blood phytanic acid levels were normal in two patients, mildly elevated in one, and markedly high in the fourth. Retinal evaluation showed an intact ellipsoid zone as well as preserved autofluorescence in the macular region in three of the four patients. In all patients, we observed in-frame skipping of exons 5 and 6 in 31.1% to 88.4% of the amplicons and a smaller proportion (0% to 11.3% of amplicons) skipping exon 6 only., Conclusions: We demonstrate a significant effect of PHYH:c.678+5G>T on splicing of the canonical transcript. The in-frame nature of this may be in keeping with a mild presentation and higher prevalence in the general population. These data support the classification of the variant as pathogenic, and patients harboring a biallelic genotype should undergo phytanic acid testing.

Background: 5' untranslated regions (5'UTRs) are essential modulators of protein translation. Predicting the impact of 5'UTR variants is challenging and rarely performed in routine diagnostics. Here, we present a combined approach of a comprehensive prioritization strategy and functional assays to evaluate 5'UTR variation in two large cohorts of patients with inherited retinal diseases (IRDs)., Methods: We performed an isoform-level re-analysis of retinal RNA-seq data to identify the protein-coding transcripts of 378 IRD genes with highest expression in retina. We evaluated the coverage of their 5'UTRs by different whole exome sequencing (WES) kits. The selected 5'UTRs were analyzed in whole genome sequencing (WGS) and WES data from IRD sub-cohorts from the 100,000 Genomes Project (n = 2397 WGS) and an in-house database (n = 1682 WES), respectively. Identified variants were annotated for 5'UTR-relevant features and classified into seven categories based on their predicted functional consequence. We developed a variant prioritization strategy by integrating population frequency, specific criteria for each category, and family and phenotypic data. A selection of candidate variants underwent functional validation using diverse approaches., Results: Isoform-level re-quantification of retinal gene expression revealed 76 IRD genes with a non-canonical retina-enriched isoform, of which 20 display a fully distinct 5'UTR compared to that of their canonical isoform. Depending on the probe design, 3-20% of IRD genes have 5'UTRs fully captured by WES. After analyzing these regions in both cohorts, we prioritized 11 (likely) pathogenic variants in 10 genes (ARL3, MERTK, NDP, NMNAT1, NPHP4, PAX6, PRPF31, PRPF4, RDH12, RD3), of which 7 were novel. Functional analyses further supported the pathogenicity of three variants. Mis-splicing was demonstrated for the PRPF31:c.-9+1G>T variant. The MERTK:c.-125G>A variant, overlapping a transcriptional start site, was shown to significantly reduce both luciferase mRNA levels and activity. The RDH12:c.-123C>T variant was found in cis with the hypomorphic RDH12:c.701G>A (p.Arg234His) variant in 11 patients. This 5'UTR variant, predicted to introduce an upstream open reading frame, was shown to result in reduced RDH12 protein but unaltered mRNA levels., Conclusions: This study demonstrates the importance of 5'UTR variants implicated in IRDs and provides a systematic approach for 5'UTR annotation and validation that is applicable to other inherited diseases., (© 2024. The Author(s).)

This study corresponds to the first large-scale genetic analysis of inherited eye diseases (IED) in Argentina and describes the comprehensive genetic profile of a large cohort of patients. Medical records of 22 ophthalmology and genetics services throughout 13 Argentinian provinces were analyzed retrospectively. Patients with a clinical diagnosis of an ophthalmic genetic disease and a history of genetic testing were included. Medical, ophthalmological and family history was collected. A total of 773 patients from 637 families were included, with 98% having inherited retinal disease. The most common phenotype was retinitis pigmentosa (RP, 62%). Causative variants were detected in 379 (59%) patients. USH2A, RPGR, and ABCA4 were the most common disease-associated genes. USH2A was the most frequent gene associated with RP, RDH12 early-onset severe retinal dystrophy, ABCA4 Stargardt disease, PROM1 cone-rod dystrophy, and BEST1 macular dystrophy. The most frequent variants were RPGR c.1345 C > T, p.(Arg449*) and USH2A c.15089 C > A, p.(Ser5030*). The study revealed 156/448 (35%) previously unreported pathogenic/likely pathogenic variants and 8 possible founder mutations. We present the genetic landscape of IED in Argentina and the largest cohort in South America. This data will serve as a reference for future genetic studies, aid diagnosis, inform counseling, and assist in addressing the largely unmet need for clinical trials to be conducted in the region., (© 2023. The Author(s).)

Introduction: Inherited retinal diseases (IRD) are a leading cause of visual impairment and blindness in the working age population. Mutations in over 300 genes have been found to be associated with IRDs and identifying the affected gene in patients by molecular genetic testing is the first step towards effective care and patient management. However, genetic diagnosis is currently slow, expensive and not widely accessible. The aim of the current project is to address the evidence gap in IRD diagnosis with an AI algorithm, Eye2Gene, to accelerate and democratise the IRD diagnosis service., Methods and Analysis: The data-only retrospective cohort study involves a target sample size of 10 000 participants, which has been derived based on the number of participants with IRD at three leading UK eye hospitals: Moorfields Eye Hospital (MEH), Oxford University Hospital (OUH) and Liverpool University Hospital (LUH), as well as a Japanese hospital, the Tokyo Medical Centre (TMC). Eye2Gene aims to predict causative genes from retinal images of patients with a diagnosis of IRD. For this purpose, 36 most common causative IRD genes have been selected to develop a training dataset for the software to have enough examples for training and validation for detection of each gene. The Eye2Gene algorithm is composed of multiple deep convolutional neural networks, which will be trained on MEH IRD datasets, and externally validated on OUH, LUH and TMC., Ethics and Dissemination: This research was approved by the IRB and the UK Health Research Authority (Research Ethics Committee reference 22/WA/0049) 'Eye2Gene: accelerating the diagnosis of IRDs' Integrated Research Application System (IRAS) project ID: 242050. All research adhered to the tenets of the Declaration of Helsinki. Findings will be reported in an open-access format., Competing Interests: Competing interests: Neither the chief investigator (NP) nor any of the coinvestigators have any direct personal involvement (financial, shareholder or personal) with the NIHR that may give rise to a conflict of interest. As has been disclosed to the study sponsor (UCL) and the funder (NIHR), NP and IM are shareholders at Phenopolis, which is one of the two subcontractors mentioned above (WP6). Phenopolis will provide professional software development services for Eye2Gene., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

The purpose of this paper is to identify likely pathogenic non-coding variants in inherited retinal dystrophy (IRD) genes, using genome sequencing (GS). Patients with IRD were recruited to the study and underwent comprehensive ophthalmological evaluation and GS. The results of GS were investigated through virtual gene panel analysis, and plausible pathogenic variants and clinical phenotype evaluated by the multidisciplinary team (MDT) discussion. For unsolved patients in whom a specific gene was suspected to harbor a missed pathogenic variant, targeted re-analysis of non-coding regions was performed on GS data. Candidate variants were functionally tested by messenger RNA analysis, minigene or luciferase reporter assays. Previously unreported, likely pathogenic, non-coding variants in 7 genes (PRPF31, NDP, IFT140, CRB1, USH2A, BBS10 and GUCY2D), were identified in 11 patients. These were shown to lead to mis-splicing (PRPF31, IFT140, CRB1 and USH2A) or altered transcription levels (BBS10 and GUCY2D). MDT-led, phenotype-driven, non-coding variant re-analysis of GS is effective in identifying the missing causative alleles., (© The Author(s) 2022. Published by Oxford University Press.)

Purpose: Rare disease diagnosis is challenging in medical image-based artificial intelligence due to a natural class imbalance in datasets, leading to biased prediction models. Inherited retinal diseases (IRDs) are a research domain that particularly faces this issue. This study investigates the applicability of synthetic data in improving artificial intelligence-enabled diagnosis of IRDs using generative adversarial networks (GANs)., Design: Diagnostic study of gene-labeled fundus autofluorescence (FAF) IRD images using deep learning., Participants: Moorfields Eye Hospital (MEH) dataset of 15 692 FAF images obtained from 1800 patients with confirmed genetic diagnosis of 1 of 36 IRD genes., Methods: A StyleGAN2 model is trained on the IRD dataset to generate 512 × 512 resolution images. Convolutional neural networks are trained for classification using different synthetically augmented datasets, including real IRD images plus 1800 and 3600 synthetic images, and a fully rebalanced dataset. We also perform an experiment with only synthetic data. All models are compared against a baseline convolutional neural network trained only on real data., Main Outcome Measures: We evaluated synthetic data quality using a Visual Turing Test conducted with 4 ophthalmologists from MEH. Synthetic and real images were compared using feature space visualization, similarity analysis to detect memorized images, and Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) score for no-reference-based quality evaluation. Convolutional neural network diagnostic performance was determined on a held-out test set using the area under the receiver operating characteristic curve (AUROC) and Cohen's Kappa (κ)., Results: An average true recognition rate of 63% and fake recognition rate of 47% was obtained from the Visual Turing Test. Thus, a considerable proportion of the synthetic images were classified as real by clinical experts. Similarity analysis showed that the synthetic images were not copies of the real images, indicating that copied real images, meaning the GAN was able to generalize. However, BRISQUE score analysis indicated that synthetic images were of significantly lower quality overall than real images ( P < 0.05). Comparing the rebalanced model (RB) with the baseline (R), no significant change in the average AUROC and κ was found (R-AUROC = 0.86[0.85-88], RB-AUROC = 0.88[0.86-0.89], R-k = 0.51[0.49-0.53], and RB-k = 0.52[0.50-0.54]). The synthetic data trained model (S) achieved similar performance as the baseline (S-AUROC = 0.86[0.85-87], S-k = 0.48[0.46-0.50])., Conclusions: Synthetic generation of realistic IRD FAF images is feasible. Synthetic data augmentation does not deliver improvements in classification performance. However, synthetic data alone deliver a similar performance as real data, and hence may be useful as a proxy to real data. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references., (© 2022 by the American Academy of Ophthalmology. Published by Elsevier Inc.)

Purpose: Genetic variation in PDE6C is associated with achromatopsia and cone dystrophy, with only a few reports of cone-rod dystrophy in the literature. We describe two pediatric and two adult patients with PDE6C related cone and cone-rod dystrophy and the first longitudinal data of a pediatric patient with PDE6C-related cone dystrophy., Methods: This cohort of four patients underwent comprehensive ophthalmologic evaluation at the National Eye Institute's Ophthalmic Genetics clinic, including visual field testing, retinal imaging and electroretinogram (ERG). Next-generation sequencing-based genetic testing was performed and subsequent analysis of the variants was done through three-dimensional protein models generated by Phyre2 and Chimera., Results: All cases shared decreased best-corrected visual acuity and poor color discrimination. Three of the four patients had a cone-rod dystrophy, presenting with an ERG showing decreased amplitude on both photopic and scotopic waveforms and a mild to moderately constricted visual field. One of the children was diagnosed with cone dystrophy, having a preserved peripheral field. The children had none to minor structural retinal changes, whereas the adults had clear macular dystrophy., Conclusions: PDE6C-related cone-rod dystrophy consists of a severe phenotype characterized by early-onset nystagmus, decreased best-corrected visual acuity, poor color discrimination, progressive constriction of the visual field, and night blindness. Our work contributes with valuable information toward understanding the visual prognosis and allelic heterogeneity of PDE6C-related cone and cone-rod dystrophy.