Background/aims Reticular pseudodrusen (RPD) are increasingly recognised as a distinct phenotype in the age-related macular degeneration (AMD) disease spectrum. This study investigates the association between RPD and cardiovascular outcomes, specifically myocardial infarction (MI) and stroke in the UK Biobank (UKBB).Methods Retrospective analysis of UKBB participants (n=2010). A validated deep learning framework identified and quantified subjects with RPD, drusen and controls on optical coherence tomography. Five retina specialists validated the artificial intelligence findings. Multivariable logistic regression models assessed the association between RPD/drusen and stroke, MI and combined MI/stroke, adjusting for age, sex, high-density lipoprotein cholesterol/low-density lipoprotein cholesterol ratio and smoking history.Results The study cohort included 71 subjects with pure RPD, 401 with pure drusen, 368 with both and 1170 controls. Univariable analysis showed that for every 20 RPD lesions, the OR for stroke increased by 1.02 (95% CI 1.00 to 1.04, p=0.028). The mean number of RPD per patient in this cohort was 199, indicating an increased stroke risk of 20%. Multivariable analysis showed a significant association between RPD load and stroke risk (OR 1.02, 95% CI 1.00 to 1.04, p=0.042) after adjustment for confounders. No significant association was found between drusen and stroke or between RPD/drusen and MI.Conclusion Increased RPD load is associated with a higher risk of stroke, independent of traditional cardiovascular risk factors. Drusen did not have similar associations, suggesting that RPD may represent a distinct disease entity. Evaluating cardiovascular risk in patients with numerous RPD might be advisable. Further prospective studies are needed to validate these findings and explore the underlying mechanisms.

PURPOSE:To identify retinal diseases that mimic macular telangiectasia type 2 (MacTel), categorize these masquerading entities based on multimodal imaging characteristics, and evaluate the diagnostic performance of individual imaging modalities for differentiation from true MacTel. DESIGN:Retrospective, cross-sectional observational study analyzing data from the MacTel Natural History Observation Registry. SUBJECTS:Eyes of patients submitted to the registry with a potential diagnosis of MacTel, which was not confirmed by the central reading center, were included if spectral-domain OCT and fundus autofluorescence (FAF) were available. METHODS:Two independent retina specialists assigned the most likely diagnosis for each eye based on full multimodal imaging, with adjudication by senior graders when required. Diagnoses were grouped into clusters of similar etiology or imaging phenotypes. Discrimination between MacTel and masquerading diseases was tested by calculating the sensitivity of detecting masquerading diseases for each imaging modality. MAIN OUTCOME MEASURES:Frequency of different clusters of masquerading diseases and sensitivity for their detection based on different imaging modalities. RESULTS:Of 172 eyes reviewed, 108 eyes with confirmed pathologic findings were included in the final analysis; 6 eyes were reclassified as true MacTel, and 58 eyes showed no pathologic changes and were therefore excluded. The most frequent MacTel mimickers were vitreomacular interface disorders (29%), large retinal capillary aneurysms (LCAs; 22%), and central serous chorioretinopathy (19%). Optical coherence tomography showed the highest sensitivity in detecting mimicking disease (sensitivity 90%), followed by FAF (81%), fluorescein angiography (77%), and blue-light reflectance (75%), and was poor for color fundus photographs (59%). Intergrader agreement was substantial across all imaging modalities (κ = 0.69-0.78). CONCLUSIONS:Several retinal disorders can closely mimic MacTel, most commonly vitreomacular interface abnormalities and LCAs. Multimodal imaging-particularly OCT and FAF-enables reliable differentiation in most cases. These findings underscore the importance of comprehensive imaging assessment and provide a practical framework for avoiding MacTel misdiagnosis in clinical practice and clinical trials. FINANCIAL DISCLOSURE(S):Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

ABSTRACT We propose a new framework for the analysis of large clinical phenotypic datasets through the repurposing of single‐cell RNA‐sequencing analysis techniques. By utilizing similarities between cellular development and clinical heterogeneity, we show that techniques such as clustering, pseudo‐time, and trajectory analysis can reveal different disease progression trajectories. Our approach permits the extraction of long‐term progression trajectories from large cross‐sectional datasets while overcoming the hurdle of a lack of longitudinal data plaguing many large clinical phenotypic studies. We present this framework on the retinal degenerative disease macular telangiectasia type 2 (MacTel) and derived previously unknown differential disease progression trajectories from 87 clinically graded phenotypic variables measured in 7888 eyes (3971 patients). One progression trajectory was characterized by vascular alterations, the other by severe neurodegeneration and vision loss. Older and diabetic patients were significantly more likely to progress toward the neurodegenerative route. We demonstrate how pseudo‐time calculations reveal a holistic fine‐scale data‐driven progression score useful for analytical investigations, which complements previously established clinical severity scores. Lastly, integration of genetic data on 71% of patients revealed that genetic background affects phenotype heterogeneity, differential progression trajectory, but not progression rate.

Objective Comparative evaluations of commercially available artificial intelligence (AI) systems for use in diabetic retinopathy (DR) screening – particularly studies that identify systems by name – are limited, constraining procurement and implementation. The study aimed to identify commercially available AI systems potentially suitable for DR screening in a low-resource Tanzanian setting and to compare their accuracy for detecting referable DR. Research Design and Methods Through a scoping review and expert consultation, we identified AI systems potentially suitable for implementation. Systems confirmed as suitable, and whose developers agreed to participate, were evaluated. Performance was assessed on a dataset of retinal images collected from a Tanzanian DR screening programme. The primary outcome was sensitivity and specificity for detecting referable DR. Additional implementation data, including regulatory approvals, referral thresholds and additional product features, were also collected. Results Four commercially available AI systems (Medios AI / Remidio, MONA, Ophtai and SELENA+) were evaluated. Among 689 people included in the test dataset, 379 (55·0%) had referable DR and 93 (13·5%) had proliferative DR. Sensitivity for detecting referable DR ranged from 83·9%-93·7%, with lower specificities ranging from 70·3%-79·0%. Sensitivity for proliferative DR exceeded 98% for all four AI systems. All the evaluated AI systems were CE-marked medical devices; one system (Medios AI / Remidio) functions offline as standard. Conclusions Several commercially available AI systems demonstrated high sensitivity for detecting referable and proliferative DR, supporting their potential implementation. Consensus of minimum performance thresholds and consideration of implementation factors such as regulatory approval and offline functionality are needed.

Screening for diabetic retinopathy has been shown to reduce the risk of sight loss in people with diabetes, because of early detection and treatment of sight-threatening disease. There is long-standing interest in the possibility of automating parts of this process through artificial intelligence, commonly known as automated retinal imaging analysis software (ARIAS). A number of such products are now on the market. In the UK, Scotland has used a rules-based autograder since 2011, but the diabetic eye screening programmes in the rest of the UK rely solely on human graders. With more sophisticated machine learning-based ARIAS now available and greater challenges in terms of human grader capacity, in 2019 the UK's National Screening Committee (NSC) was asked to consider the modification of diabetic eye screening in England with ARIAS. Following up on a review of ARIAS research highlighting the strengths and limitations of existing evidence, the NSC here sets out their considerations for evaluating evidence to support the introduction of ARIAS into the diabetic eye screening programme.

Purpose:To clinically and biochemically characterize a rare autosomal recessive rod-cone dysfunction, with electroretinographic similarities to some forms of stationary night blindness (SNB), associated with biallelic variants in GUCY2D. Methods:Six patients from five families with a history of longstanding night blindness, no fundus features suggestive of retinitis pigmentosa, and an unusual electroretinographic phenotype were ascertained. Clinical examination and genotyping were performed. Selected GUCY2D variants were tested for binding to and activation by guanylate cyclase-activating proteins (GCAPs) in HEK293 cells. Results:The visual acuity was normal or moderately reduced (20/20-20/60) with three patients having a tritan defect on color vision testing. Retinal imaging showed central macular hypopigmentation with temporal vascular attenuation. Rod photoreceptor-mediated electroretinogram (ERG) components were undetectable or severely reduced in all but one case, and cone-mediated responses were variable. A high degree of ERG stability was demonstrated in three cases. Molecular analyses revealed biallelic variants of GUCY2D in all patients, four of which are clinically and biochemically characterized for the first time, to our knowledge. These allelic variants encoded retinal guanylyl/guanylate cyclase 1 (RetGC1) mutants whose enzymatic activities were significantly diminished due to drastically reduced affinity of RetGC1 for GCAPs. Conclusions:The apparent lack of retinal degeneration, clinical features, predominant and severe rod photoreceptor involvement, and relatively high degree of ERG stability are similar to rare forms of SNB. Biallelic disease-causing variants in GUCY2D are usually associated with Leber's congenital amaurosis (LCA); however, this study illustrates the phenotypic variability of GUCY2D retinopathies in association with variants not biochemically dissimilar to those causing LCA and highlights the complexity of RetGC1 regulation in rod and cone photoreceptor function.

Objective:To primarily assess long-term safety and retinal imaging outcomes of NT-501 (revakinagene taroretcel-lwey), which releases ciliary neurotrophic factor into the vitreous over an extended time, for treating macular telangiectasia type 2 (MacTel). Design:Phase I, nonrandomized, multicenter, open-label extension study. Participants:Six participants with bilateral MacTel who completed the parent 60-month phase I study. Methods:In the parent study, participants had NT-501 surgically implanted in the study eye. The eye with more advanced disease was determined to be the study eye. For the purposes of this extension study, the fellow eye provided untreated natural history data. The extension study included visits 72, 84, 96, and 108 months postimplantation. Main Outcome Measures:Safety outcomes included adverse events (AEs), change from baseline in best-corrected visual acuity (BCVA), and the proportions of eyes with ≥10- or ≥15-letter loss in BCVA from baseline. Retinal imaging variables included change from baseline in ellipsoid zone (EZ) (inner segment/outer segment) area loss and proportion of study eyes with ≥35% increase from baseline in EZ area loss. Results:All implants were retained through the final study visit. All ocular treatment-emergent AEs were mild to moderate; none resulted in study discontinuation. No study eyes had ≥15-letter loss in BCVA from baseline at any study visit. Similarly, no study eyes had ≥10-letter loss at months 72, 84, and 96; 1 study eye (17%) experienced it at month 108. The portion of study eyes with a ≥35% increase in EZ area loss from baseline was lower (range, 50%-60%) relative to fellow eyes (range, 75%-100%). Conclusions:Over the 9-year follow-up period, NT-501 was well tolerated and safe. Further studies are ongoing to investigate the long-term efficacy of NT-501 for treating MacTel. Financial Disclosures:Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Objective To primarily assess long-term safety and retinal imaging outcomes of NT-501 (revakinagene taroretcel-lwey), which releases ciliary neurotrophic factor into the vitreous over an extended time, for treating macular telangiectasia type 2 (MacTel). Design Phase 1, nonrandomized, multicenter, open-label extension study. Participants Six participants with bilateral MacTel who completed the parent 60-month phase 1 study. Methods In the parent study, participants had NT-501 surgically implanted in the study eye. The eye with more advanced disease was determined to be the study eye. For the purposes of this extension study, the fellow eye provided untreated natural history data. The extension study included visits 72, 84, 96, and 108 months post implantation. Main Outcome Measures Safety outcomes included adverse events (AEs), change from baseline in best-corrected visual acuity (BCVA), and the proportions of eyes with ≥10- or ≥15-letter loss in BCVA from baseline. Retinal imaging variables included change from baseline in ellipsoid zone (EZ) (inner segment/outer segment) area loss and proportion of study eyes with ≥35% increase from baseline in EZ area loss. Results All implants were retained through the final study visit. All ocular treatment-emergent AEs were mild to moderate; none resulted in study discontinuation. No study eyes had ≥15-letter loss in BCVA from baseline at any study visit. Similarly, no study eyes had ≥10-letter loss at months 72, 84, and 96; 1 study eye (16.7%) experienced it at month 108. The portion of study eyes with a ≥35% increase in EZ area loss from baseline was lower (range, 50%–60%) relative to fellow eyes (range, 75%–100%). Conclusions NT-501 was well tolerated and safe over the 9-year follow-up period. Further studies are ongoing to investigate the long-term efficacy of NT-501 for treating MacTel.

Retinal thickness is a marker of retinal health and more broadly, is seen as a promising biomarker for many systemic diseases. Retinal thickness measurements are procured from optical coherence tomography (OCT) as part of routine clinical eyecare. We processed the UK Biobank OCT images using a convolutional neural network to produce fine-scale retinal thickness measurements across > 29,000 points in the macula, the part of the retina responsible for human central vision. The macula is disproportionately affected by high disease burden retinal disorders such as age-related macular degeneration and diabetic retinopathy, which both involve metabolic dysregulation. Analysis of common genomic variants, metabolomic, blood and immune biomarkers, disease PheCodes and genetic scores across a fine-scale macular thickness grid, reveals multiple novel genetic loci including four on the X chromosome; retinal thinning associated with many systemic disorders including multiple sclerosis; and multiple associations to correlated metabolites that cluster spatially in the retina. We highlight parafoveal thickness to be particularly susceptible to systemic insults. These results demonstrate the gains in discovery power and resolution achievable with AI-leveraged analysis. Results are accessible using a bespoke web interface that gives full control to pursue findings. Retinal morphology is emerging as a key biomarker for disease. Here, using AI to create a high-resolution map of retinal thickness from optical coherence tomography images, the authors demonstrate spatial associations with genetic variation, metabolites and disease, with the parafovea showing the highest enrichment

OBJECTIVES:To investigate whether quantitative retinal markers, derived from multimodal retinal imaging, are associated with increased risk of mortality among individuals with proliferative diabetic retinopathy (PDR), the most severe form of diabetic retinopathy. DESIGN:Longitudinal retrospective cohort analysis. SETTING:This study was nested within the AlzEye cohort, which links longitudinal multimodal retinal imaging data routinely collected from a large tertiary ophthalmic institution in London, UK, with nationally held hospital admissions data across England. PARTICIPANTS:A total of 675 individuals (1129 eyes) with PDR were included from the AlzEye cohort. Participants were aged ≥40 years (mean age 57.3 years, SD 10.3), and 410 (60.7%) were male. OUTCOME MEASURES:The primary outcome was all-cause mortality. Quantitative retinal markers were derived from fundus photographs and optical coherence tomography using AutoMorph and Topcon Advanced Boundary Segmentation, respectively. We used unadjusted and adjusted Cox-proportional hazards models to estimate hazard ratios (HR) for the association between retinal features and time to death. RESULTS:After adjusting for sociodemographic factors, each 1-SD decrease in arterial fractal dimension (HR: 1.54, 95% CI: 1.18 to 2.04), arterial vessel density (HR: 1.59, 95% CI: 1.15 to 2.17), arterial average width (HR: 1.35, 95% CI: 1.02 to 1.79), central retinal arteriolar equivalent (HR: 1.39, 95% CI: 1.05 to 1.82) and ganglion cell-inner plexiform layer (GC-IPL) thickness (HR: 1.61, 95% CI: 1.03 to 2.50) was associated with increased mortality risk. When also adjusting for hypertension, arterial fractal dimension (HR: 1.45, 95% CI: 1.08 to 1.92), arterial vessel density (HR: 1.47, 95% CI: 1.05 to 2.08) and GC-IPL thickness (HR: 1.56, 95% CI: 1.03 to 2.38) remained significantly associated with mortality. CONCLUSIONS:Several quantitative retinal markers, relating to both microvascular morphology and retinal neural thickness, are associated with increased mortality among individuals with PDR. The role of retinal imaging in identifying those individuals with PDR most at risk of imminent life-threatening sequelae warrants further investigation.

AIMS/HYPOTHESIS:Biennial, as opposed to annual, screening for diabetic retinopathy was recently introduced within England for those considered to be at 'low risk'. This study aims to examine the impact that annual vs biennial screening has on equitable risk of diagnosis of sight-threatening diabetic retinopathy (STDR) among people at 'low risk' and to develop an amelioration protocol. METHODS:In the North East London Diabetic Eye Screening Programme (NELDESP), 105,083 people without diabetic retinopathy were identified on two consecutive screening visits between January 2012 and September 2023. Data for these individuals were linked to electronic health records (EHR). Characteristics associated with subsequent STDR diagnosis were identified (including age, gender, ethnicity and diabetes duration), and logistic regression was performed to identify people who require annual screening, using variables available to the NELDESP and data from EHR. Simulations of the biennial screening protocol, and of protocols incorporating the outcomes of the logistic models and a simplified points model, were implemented, and the relative risk of STDR calculated at each screening appointment was compared amongst various population subgroups. The results were validated using data from the South East London DESP. RESULTS:Among the low-risk participants, there were 3694 incident STDR cases over a mean duration of 5.0 years (SD 3.4 years). Under the biennial screening protocol, almost all groups had a significantly higher risk of STDR diagnosis compared with people aged 41 years or older who were of white ethnicity and had been living with diabetes for <10 years. Compared with biennial screening, a simplified screening protocol based on age, diabetes duration and ethnicity reduced the number of delayed STDR diagnoses from 39% to 25%, with a more equitable performance across population groups, and a modest impact on screening appointment numbers (46% vs 57% reduction in annual screening appointments, respectively). CONCLUSIONS/INTERPRETATION:A simple, clinically deliverable, personalised protocol for identifying who should be screened annually or biennially for diabetic eye disease would improve equity in risk of delayed STDR diagnosis per appointment.

Few metrics exist to describe phenotypic diversity within ophthalmic imaging datasets, with researchers often using ethnicity as a surrogate marker for biological variability. We derived a continuous, measured metric, the retinal pigment score (RPS), that quantifies the degree of pigmentation from a colour fundus photograph of the eye. RPS was validated using two large epidemiological studies with demographic and genetic data (UK Biobank and EPIC-Norfolk Study) and reproduced in a Tanzanian, an Australian, and a Chinese dataset. A genome-wide association study (GWAS) of RPS from UK Biobank identified 20 loci with known associations with skin, iris and hair pigmentation, of which eight were replicated in the EPIC-Norfolk cohort. There was a strong association between RPS and ethnicity, however, there was substantial overlap between each ethnicity and the respective distributions of RPS scores. RPS decouples traditional demographic variables from clinical imaging characteristics. RPS may serve as a useful metric to quantify the diversity of the training, validation, and testing datasets used in the development of AI algorithms to ensure adequate inclusion and explainability of the model performance, critical in evaluating all currently deployed AI models. The code to derive RPS is publicly available at: https://github.com/uw-biomedical-ml/retinal-pigmentation-score.

BACKGROUND:The global prevalence of diabetes is rising, alongside costs and workload associated with screening for diabetic eye disease (diabetic retinopathy). Automated retinal image analysis systems (ARIAS) could replace primary human grading of images for diabetic retinopathy. We evaluated multiple ARIAS in a real-life screening programme. METHODS:Eight of 25 invited and potentially eligible CE-marked systems for diabetic retinopathy detection from retinal images agreed to participate. From 202 886 screening encounters at the North East London Diabetic Eye Screening Programme (between Jan 1, 2021, and Dec 31, 2022) we curated a database of 1·2 million images and sociodemographic and grading data. Images were manually graded by up to three graders according to a standard national protocol. ARIAS performance overall and by subgroups of age, sex, ethnicity, and index of multiple deprivation (IMD) were assessed against the reference standard, defined as the final human grade in the worst eye for referable diabetic retinopathy (primary outcome). Vendor algorithms did not have access to human grading data. FINDINGS:Sensitivity across vendors ranged from 83·7% to 98·7% for referable diabetic retinopathy, from 96·7% to 99·8% for moderate-to-severe non-proliferative diabetic retinopathy, and from 95·8% to 99·5% for proliferative diabetic retinopathy. Sensitivity was largely consistent for moderate-to-severe non-proliferative and proliferative diabetic retinopathy by subgroups of age, sex, ethnicity, and IMD for all ARIAS. For mild-to-moderate non-proliferative diabetic retinopathy with referable maculopathy, sensitivity across vendors ranged from 79·5% to 98·3%, with greater variability across population subgroups. False positive rates for no observable diabetic retinopathy ranged from 4·3% to 61·4% and within vendors varied by 0·5 to 44 percentage points across population subgroups. INTERPRETATION:ARIAS showed high sensitivity for medium-risk and high-risk diabetic retinopathy in a real-world screening service, with equitable performance across population subgroups. ARIAS could provide a cost-effective solution to deal with the rising burden of screening for diabetic retinopathy by safely triaging for human grading, substantially increasing grading capacity and rapid diabetic retinopathy detection. FUNDING:NHS Transformation Directorate, The Health Foundation, and The Wellcome Trust.

OBJECTIVE:To identify genetic determinants specific to reticular pseudodrusen (RPD) compared with drusen. DESIGN:Genome-wide association study (GWAS) SUBJECTS: Participants with RPD, drusen, and controls from the UK Biobank (UKBB), a large, multisite, community-based cohort. METHODS:Participants with RPD, drusen, and controls from the UK Biobank (UKBB), a large, multisite, community-based cohort, were included. A deep learning framework analyzed 169,370 optical coherence tomography (OCT) volumes to identify cases and controls within the UKBB. Five retina specialists validated the cohorts using OCT and color fundus photographs. Several GWAS were undertaken utilizing the quantity and presence of RPD and drusen. Genome-wide significance was defined as P < 5e-8. MAIN OUTCOMES MEASURES:Genetic associations were examined with the number of RPD and drusen within 'pure' cases, where only RPD or drusen were present in either eye. A candidate approach assessed 46 previously known AMD loci. Secondary GWAS were conducted for number of RPD and drusen in mixed cases, and binary case-control analyses for pure RPD and pure drusen. RESULTS:The study included 1787 participants: 1037 controls, 361 pure drusen, 66 pure RPD, and 323 mixed cases. The primary pure RPD GWAS identified four genome-wide significant loci: rs11200630 near ARMS2-HTRA1 (P = 1.9e-09), rs79641866 at PARD3B (P = 1.3e-08), rs143184903 near ITPR1 (P = 8.1e-09), and rs76377757 near SLN (P = 4.3e-08). The latter three are uncommon variants (minor allele frequency <5%). A significant association at the CFH locus was also observed using a candidate approach (P = 1.8e-04). For pure drusen, two loci reached genome-wide significance: rs10801555 at CFH (P = 6.0e-33) and rs61871744 at ARMS2-HTRA1 (P = 4.2e-20). CONCLUSIONS:The study highlights a clear association between the ARMS2-HTRA1 locus and higher RPD load. Although the CFH locus association did not achieve genome-wide significance, a suggestive link was observed. Three novel associations unique to RPD were identified, albeit for uncommon genetic variants. Further studies with larger sample sizes are needed to explore these findings.

Purpose: To explore genetic determinants specific to reticular pseudodrusen (RPD), and to compare these with genetic associations for drusen. Setting: Participants with RPD, drusen, or controls from the UK Biobank (UKBB), a large, multisite, community-based cohort study. Methods: A previously validated deep learning framework was deployed on 169,370 optical coherence tomography (OCT) volumes from the UKBB to identify cases with RPD and/or drusen and controls without these phenotypes. Cases were included if they were 60 years or older, with at least 5 lesions. Five retina specialists manually validated the cohorts using OCT and color fundus photographs. Quantifications of RPD and drusen derived by the framework were used as variables. Two primary genome-wide association study (GWAS) analyses were performed to explore potential genetic associations with number of RPD and drusen within "pure" cases, where only RPD or drusen were present in either eye. A candidate approach was furthermore adopted to assess 46 previously known AMD loci. Secondary GWAS were undertaken for number of RPD and drusen in mixed cases, as well as binary case-control analyses for pure RPD and pure drusen. Genome-wide significance was defined as p<5e-8. Results: A total of 1,787 participants were identified and analysed, including 1,037 controls, 361 pure drusen, 66 pure RPD and 323 mixed cases. The primary pure RPD GWAS yielded four genome-wide significant loci: rs11200630/ARMS2-HTRA1 (p=1.9e-09), rs79641866/PARD3B on chromosome 2 (p=1.3e-08), rs143184903/ITPR1 on chromosome 3 (p=8.1e-09), and rs76377757/SLN on chromosome 11 (p=4.3e-08). The latter three are all uncommon variants (minor allele frequency <5%). A significant association at CFH was also observed adopting a candidate approach (p=1.8e-04). Two loci reached genome-wide significance for the primary pure drusen GWAS: rs10801555/CFH on chromosome 1 (p=6.0e-33) and rs61871744/ARMS2-HTRA1 on chromosome 10 (p=4.2e-20). For the mixed RPD and drusen secondary analyses, lead variants at both the CFH and ARMS2-HTRA1 loci reached genome-wide significance, with C2-CFB-SKIV2L additionally associated for mixed drusen alone. Findings from the binary case-control GWAS for drusen mirrored those of the primary drusen analysis, however no variants reached genome-wide significance in the case-control RPD GWAS. Conclusions: Our findings indicate a clear association between the ARMS2-HTRA1 locus with higher RPD load. Although the association at the CFH locus did not reach genome-wide significance, we observed a suggestive link. We furthermore identified three novel associations that are unique to RPD, albeit for uncommon genetic variants. These findings were only observable when quantifying RPD load as a continuous trait, which increased the statistical power of the study. Further studies with larger sample sizes are now required to explore the relative contributions of AMRS2- HTRA1 and CFH to RPD development, and to explore the validity of these newly presented RPD-specific genetic associations. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement Sponsored by the EURETINA Retinal Medicine Clinical Research Grant. R.S., C.E., and A.T. received a proportion of their financial support from the UK Department of Health through an award made by the National Institute for Health Research to Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology for a Biomedical Research Centre for Ophthalmology. A.P.K is supported by a UK Research and Innovation Future Leaders Fellowship, an Alcon Research Institute Young Investigator Award and a Lister Institute for Preventive Medicine Award. This research was supported by the NIHR Biomedical Research Centre at Moorfields Eye Hospital and the UCL Institute of Ophthalmology. This work was supported in part by the Said Foundation ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was approved by the North West Multi-centre Research Ethics Committee (REC reference number: 06/MRE08/65, UKBB project ID 60078), adhering to the principles of the Declaration of Helsinki (www.ukbiobank.ac.uk). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data produced in the present study are available upon reasonable request to the authors

Aims Automated retinal image analysis using Artificial Intelligence (AI) can detect diabetic retinopathy as accurately as human graders, but it is not yet licensed in the NHS Diabetic Eye Screening Programme (DESP) in England. This study aims to assess perceptions of People Living with Diabetes (PLD) and Healthcare Practitioners (HCP) towards AI’s introduction in DESP. Methods Two online surveys were co-developed with PLD and HCP from a diverse DESP in North East London. Surveys were validated through interviews across three centres and distributed via DESP centres, charities, and the British Association of Retinal Screeners. A coding framework was used to analyse free-text responses. Results 387 (24%) PLD and 98 (37%) HCP provided comments. Themes included trust, workforce impact, the patient-practitioner relationship, AI implementation challenges, and inequalities. Both groups agreed AI in DESP was inevitable, would improve efficiency, and save costs. Concerns included job losses, data security, and AI decision safety. A common misconception was that AI would directly affect patient interactions, though it only processes retinal images. Conclusions Limited understanding of AI was a barrier to acceptance. Educating diverse PLD groups and HCP about AI’s accuracy and reliability is crucial to building trust and facilitating its integration into screening practices.

PURPOSE:To describe the occurrence of bilateral outer retinal columnar abnormalities, nonvasogenic cystoid macular edema, and drusen in the context of dense deposit disease. METHODS:Case report. PATIENT:An 18-year-old girl with dense deposit disease was referred to our specialist center for diagnosis and management with findings consistent with bilateral nonvasogenic cystoid macular edema and drusen. She was followed-up in our clinic for 40 months and treated with acetazolamide and ketorolac drops. RESULTS:Baseline examination revealed bilateral visual acuity reduction and macular elevation with peripapillary drusen on fundus biomicroscopy. Optical coherence tomography revealed bilateral hyporeflective cystoid central macula changes, microcystoid changes with increased central subfield thickness (>450 μm), and outer retinal columnar abnormalities. Fluorescein angiography showed no evidence of macular leakage. Electrodiagnostic testing was within normal limits. Over the course of follow-up, she received treatment with acetazolamide 250 mg twice a day by mouth and ketorolac 0.5% eye drops, with a partial reduction in her edema and improvement in visual acuity. CONCLUSION:Dense deposit disease is a rare disease secondary to complement cascade dysregulation, associated with drusen. To the best of our knowledge, this is the first report of bilateral nonvasogenic cystoid macular edema and outer retinal columnar abnormalities in a young female patient with dense deposit disease, confirmed with multimodal imaging.

Objective To report insights on proliferative diabetic retinopathy (PDR) risk modification with repeated antivascular endothelial growth factor (VEGF) injections for the treatment of diabetic macular oedema (DMO) in routine care.Methods and analysis Multicentre study (27 UK-National Health Service centres) of patients with non-PDR (NPDR) and DMO. Primary outcome was PDR development. Repeated anti-VEGF injections were modelled as time-dependent covariates using Cox regression and weighted cumulative exposure (WCE) adjusting for baseline diabetic retinopathy (DR) grade, age, sex, ethnicity, type of diabetes and deprivation. PDR incidence rates (IRs) were calculated.Results We included 2858 DMO anti-VEGF-treated eyes. Anti-VEGF injections showed a protective effect on PDR risk during the most recent 4 weeks from exposure, which rapidly decreased. Mild-NPDR had a lower PDR risk compared with moderate-NPDR (HR 1.99, 95% CI 1.13 to 3.51, p=0.015) and severe-NPDR (HR 4.63, 95% CI 2.55 to 8.41, p<0.001). Patients with type 1 diabetes showed an increased PDR risk when compared with patients with type 2 diabetes (HR 2.08, 95% CI 1.35 to 3.21, p<0.001). And every 5-year increase in age showed a 9% reduction in PDR hazards (p=0.002). The PDR cumulative IR was 4.45 (95% CI 3.89 to 5.09) per 100 person-years.Conclusions The WCE method is a valuable modelling strategy for repeated exposures in ophthalmology. Injections are protective against PDR predominantly within the most recent 4 weeks. Based on observed data, we show that age and baseline DR severity are relevant predictors of poor outcomes in patients with DMO treated with anti-VEGF.