Verteporfin Photodynamic Therapy for the Treatment of Chorioretinal Conditions: A Narrative Review.

Photodynamic therapy (PDT) with verteporfin involves intravenous administration of a photosensitizer followed by its laser light activation at the target site to inhibit aberrant choroidal vascularization. This narrative review provides an overview of the role verteporfin PDT plays in the management of chorioretinal conditions. A PubMed literature review of all English-language articles published through October 19, 2023, was conducted to identify relevant references. Verteporfin PDT has been shown to be safe and effective for the treatment of patients with choroidal neovascularization (CNV) due to neovascular age-related macular degeneration and is often used in combination with a vascular endothelial growth factor (VEGF) inhibitor. Additionally, patients with polypoidal choroidal vasculopathy, a subtype of neovascular age-related macular degeneration, also benefit from verteporfin PDT combined with a VEGF inhibitor for improving visual acuity. Verteporfin PDT has also been effective in treating patients with peripapillary CNV, as well as eyes with CNV due to ocular histoplasmosis and pathologic myopia. Reduced dose and/or fluence PDT protocols have been effective in patients with central serous chorioretinopathy while reducing adverse effects. In eyes with choroidal hemangioma, tumor regression and visual outcomes have been improved with verteporfin PDT treatment. Photodynamic therapy with verteporfin continues to play an important role in the management of chorioretinal conditions.

Risk Factors for Worsening Morphology and Visual Acuity in Eyes with Adult-Onset Foveomacular Vitelliform Dystrophy.

PURPOSE: To explore clinical risk factors and OCT features associated with worse visual acuity (VA), progression of disease, choroidal neovascularization (CNV), and atrophy in eyes with adult-onset foveomacular vitelliform dystrophy (AOFVD). DESIGN: Single-center, retrospective, observational cohort study. PARTICIPANTS: Patients seen at Duke Eye Center between January 2012 and May 2023 with a diagnosis of AOFVD confirmed via OCT and fundus autofluorescence. METHODS: Baseline and final-visit images from eyes with AOFVD were examined. Disease stage was assigned, and presence of atrophy or CNV was determined. Clinical and OCT features associated with progression to atrophy and CNV were determined using t tests and chi-square analysis. Correlation with lower VA was determined using linear regression. MAIN OUTCOME MEASURES: Association of clinical characteristics and OCT features with worse VA, progression of disease, CNV, and atrophy as determined by independent t tests, chi-square analysis, and linear regression (P < 0.05). RESULTS: One hundred one eyes (63 patients) met inclusion criteria for this study, with mean follow-up duration of 48 months (standard deviation, 31 months). Fifty-one percent of eyes progressed beyond baseline staging during follow-up; among baseline stage 1 eyes, incidence of atrophy was 0.068/person-year; incidence of CNV was 0.022/person-year. Risk factors for worse final VA were baseline presence of vitreomacular traction ([VMT], P = 0.006), ellipsoid zone attenuation (P = 0.02), and increased lesion height and width (P < 0.001). Predictors of progression include diabetes mellitus (P = 0.01), statin use (P = 0.03), presence of hyperreflective foci (P = 0.01), and increased lesion width and volume (P = 0.03 and P = 0.04, respectively). Predictors of atrophy include the baseline presence of VMT (P = 0.02), decreased choroidal thickness (P = 0.03), and greater maximal height, width, and volume of the lesion (P = 0.03, P = 0.02, and P = 0.009, respectively). Lower baseline VA (P = 0.03) and increased lesion volume (P = 0.04) were associated with CNV. CONCLUSIONS: Clinical and OCT imaging features at baseline may prove useful in stratifying patient risk for progression, atrophy, CNV, and worse VA. Features such as statin use, diabetes, baseline VA, and laterality should be accounted for. OCT features, such as lesion size, VMT, ellipsoid zone attenuation, choroidal thickness, and hyperreflective foci, may impart greater risk of poor outcomes. Future prospective analysis accounting for the time to development of atrophy and CNV is needed. FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

The Use of Optical Coherence Tomography for Early Glaucoma Screening in a Population of Patients with Diabetes.

PURPOSE: The utility of screening for early diagnosis of glaucoma remains a widely debated topic in the care of ophthalmic patients. There are currently no population-based guidelines regarding screening for glaucoma. The purpose of this study is to determine the utility of optical coherence tomography (OCT) for early glaucoma screening in a population of diabetic patients. The results of this study may inform future screening practices. METHODS: The current study is a post hoc analysis of OCT data collected from diabetic patients screened for eye disease over 6 months. Glaucoma suspects (GS) were identified based on abnormal retinal nerve fiber layer (RNFL) thickness on OCT. Fundus photographs of GS were graded by two independent raters for vertical cup-to-disc ratio (CDR) and other signs of glaucomatous changes. RESULTS: Of the 807 subjects screened, 50 patients (6.2%) were identified as GS. The mean RNFL thickness for GS was significantly lower than the mean RNFL in the total screening population (p < .001). Median CDR for GS was 0.44. Twenty-eight eyes of 17 GS were marked as having optic disc notching or rim thinning by at least one grader. Cohen's kappa statistic for inter-rater reliability was 0.85. Racial differences showed that mean CDR was significantly higher in non-whites (p < .001). Older age was associated with thinner RNFL (r = -0.29, p = .004). CONCLUSIONS: Results of this study suggest that in a sample of diabetic patients, a small but clinically significant minority may be flagged as GS based on OCT. Nearly one-third of GS eyes were found to have glaucomatous changes on fundus photography by at least one grader. These results suggest screening with OCT may be useful in detecting early glaucomatous changes in high-risk populations, particularly older, non-white patients with diabetes.

Autoimmune-Related Retinopathy Presenting As Plaquenil Toxicity in Patients With Systemic Lupus Erythematosus.

Purpose: To report 3 cases of autoimmune retinopathy (AIR) in patients with systemic lupus erythematosus (SLE) to explore the association between these conditions and highlight additional clinical consideration of AIR in patients presenting with atypical retinopathy in the context of hydroxychloroquine use. Methods: The medical and clinical follow-up records of 3 clinical cases were reviewed. The eligibility criteria were the absence of other retinopathy or systemic autoimmune diseases. Results: All patients had a long-standing diagnosis of SLE and had been taking hydroxychloroquine at a dose exceeding the American Academy of Ophthalmology recommendations. All 3 patients had extensive retinal degeneration atypical in appearance for drug toxicity alone. Examination, imaging, electroretinograms, and autoantibody assays eventually led to the diagnosis of AIR. Conclusions: Further study of the AIR and SLE may reveal an association between these conditions. In patients with SLE presenting with retinal degeneration, AIR may be underdiagnosed.

A Deep-Learning Algorithm to Predict Short-Term Progression to Geographic Atrophy on Spectral-Domain Optical Coherence Tomography.

Importance: The identification of patients at risk of progressing from intermediate age-related macular degeneration (iAMD) to geographic atrophy (GA) is essential for clinical trials aimed at preventing disease progression. DeepGAze is a fully automated and accurate convolutional neural network-based deep learning algorithm for predicting progression from iAMD to GA within 1 year from spectral-domain optical coherence tomography (SD-OCT) scans. Objective: To develop a deep-learning algorithm based on volumetric SD-OCT scans to predict the progression from iAMD to GA during the year following the scan. Design, Setting, and Participants: This retrospective cohort study included participants with iAMD at baseline and who either progressed or did not progress to GA within the subsequent 13 months. Participants were included from centers in 4 US states. Data set 1 included patients from the Age-Related Eye Disease Study 2 AREDS2 (Ancillary Spectral-Domain Optical Coherence Tomography) A2A study (July 2008 to August 2015). Data sets 2 and 3 included patients with imaging taken in routine clinical care at a tertiary referral center and associated satellites between January 2013 and January 2023. The stored imaging data were retrieved for the purpose of this study from July 1, 2022, to February 1, 2023. Data were analyzed from May 2021 to July 2023. Exposure: A position-aware convolutional neural network with proactive pseudointervention was trained and cross-validated on Bioptigen SD-OCT volumes (data set 1) and validated on 2 external data sets comprising Heidelberg Spectralis SD-OCT scans (data sets 2 and 3). Main Outcomes and Measures: Prediction of progression to GA within 13 months was evaluated with area under the receiver-operator characteristic curves (AUROC) as well as area under the precision-recall curve (AUPRC), sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. Results: The study included a total of 417 patients: 316 in data set 1 (mean [SD] age, 74 [8]; 185 [59%] female), 53 in data set 2, (mean [SD] age, 83 [8]; 32 [60%] female), and 48 in data set 3 (mean [SD] age, 81 [8]; 32 [67%] female). The AUROC for prediction of progression from iAMD to GA within 1 year was 0.94 (95% CI, 0.92-0.95; AUPRC, 0.90 [95% CI, 0.85-0.95]; sensitivity, 0.88 [95% CI, 0.84-0.92]; specificity, 0.90 [95% CI, 0.87-0.92]) for data set 1. The addition of expert-annotated SD-OCT features to the model resulted in no improvement compared to the fully autonomous model (AUROC, 0.95; 95% CI, 0.92-0.95; P = .19). On an independent validation data set (data set 2), the model predicted progression to GA with an AUROC of 0.94 (95% CI, 0.91-0.96; AUPRC, 0.92 [0.89-0.94]; sensitivity, 0.91 [95% CI, 0.74-0.98]; specificity, 0.80 [95% CI, 0.63-0.91]). At a high-specificity operating point, simulated clinical trial recruitment was enriched for patients progressing to GA within 1 year by 8.3- to 20.7-fold (data sets 2 and 3). Conclusions and Relevance: The fully automated, position-aware deep-learning algorithm assessed in this study successfully predicted progression from iAMD to GA over a clinically meaningful time frame. The ability to predict imminent GA progression could facilitate clinical trials aimed at preventing the condition and could guide clinical decision-making regarding screening frequency or treatment initiation.

The Impact of Pregnancy on Diabetic Retinopathy: A Single-Site Study of Clinical Risk Factors.

INTRODUCTION: This study aimed to provide information on modifiable and non-modifiable risk factors for the progression and development of diabetic retinopathy (DR) and diabetic macular edema (DME). This retrospective chart review case-control study was designed to provide perspective on clinical variables. METHODS: Single-center study analysis was completed with chart review, identifying 50 patients (100 eyes) ultimately included in the final analysis. Included patients were women with type 1 or 2 diabetes that entered prenatal care and had a delivery from January 2010 to December 2022. The primary outcome measure was clinical variables between progression and no progression groups. Data were analyzed via χ2 analysis and independent samples t test when appropriate. Significantly different variables were further analyzed by binary logistic regression. RESULTS: The DR progression group had significantly higher prepregnancy HbA1c levels (9.9) when compared to the no progression group (8.5, p value 0.028). DR progression group also had higher rates (51.9%) of full-term births. The DME progression group had significantly higher rates of type 2 diabetics (100%) compared to the no progression group (30.9%, p value 0.029). Hypertension treatment before (81.8%; p value 0.008) pregnancy was also more common in the DME progression group. Intravitreal injections were more common in patients with visual acuity deterioration (26.7%, p value 0.046). The average number of fetal complications was significantly higher in the visual acuity non-worsening group (1.1) compared to the progression group (0.5, p value 0.04). These variables were not statistically significant after entry into multivariate analysis. DISCUSSION: Severity and treatment of retinopathy before pregnancy, type of diabetes, and blood pressure control are all significant factors affecting the progression and development of severe ocular complications in pregnancy.

GLP-1 receptor agonists and diabetic retinopathy: A meta-analysis of randomized clinical trials.

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are used to treat type 2 diabetes mellitus. Recent research suggests that GLP-1 RAs may influence diabetic retinopathy (DR). We searched ClinicalTrials.gov for trials comparing FDA-approved GLP-1 RAs to placebo, insulin, or oral antidiabetic medicine. Rates of DR, ocular adverse events, demographics, and clinical characteristics were compared amongst cohorts on 93 trials. GLP-1 RA use was significantly associated with increased risk of early-stage DR (risk ratio (RR) = 1.31, 95% confidence interval (CI) [1.01, 1.68]) and early-stage retinal adverse events (RR = 1.29, 95% CI [1.01, 1.66]) compared to placebo. Compared to insulin, GLP-1 RA use protected against late-stage DR (RR = 0.38, 95% CI [0.15, 0.98]). Analysis of individual GLP-1 RAs showed that albiglutide is responsible for these trends, as it is significantly associated with a higher risk of early-stage DR (RR = 2.18, 95% CI [1.01, 4.67]) compared to placebo and a lower risk of late-stage DR (RR = 0.25, 95% CI [0.09, 0.70]) compared to insulin. Albiglutide similarly affected retinal and ocular adverse events. Demographic analysis revealed significant differences between GLP-1 RA and comparator groups for age, HbA1c, body weight, BMI, duration of diabetes, sex, race, and ethnicity. The influence of GLP-1 RAs on DR and the eye may depend on the specific GLP-1 RA and patient demographic and clinical characteristics.

Risk factors for the development or progression of diabetic retinopathy in pregnancy: Meta-analysis and systematic review.

BACKGROUND: Diabetic retinopathy (DR) is the leading cause of blindness in the working-age population, and it increases in severity during pregnancy. METHODS: Systematic review of literature from PubMed, Cochrane Library and Web of Science using keywords 'diabetic retinopathy' and 'pregnancy' and 'progression' from inception to 2021 was completed. Included studies were (1) peer-reviewed observational studies addressing progression/development of DR in pregnancy, (2) provided the number of diabetic patients that developed/progressed in DR during pregnancy, and (3) included differential data on variables between progression and non-progression groups. This was applied by two independent researchers and referred to a third researcher as necessary. Twenty-seven of the original 138 studies met this criterion. Data were pooled and analysed using fixed-effects in meta-analysis. RESULTS: From 27 studies, 2537 patients were included. Pre-eclampsia [Risk Ratio (RR) 2.62 (95% CI = 1.72, 4.00)] and hypertension treatment during pregnancy [RR 2.74 (95% CI = 1.72, 4.00)] were significantly associated with the development/progression of DR. HbA1c at baseline [MD 0.82 (95% CI = 0.59, 1.06)], duration of diabetes [mean difference (MD) 5.97 (95% CI = 5.38, 6.57)], and diastolic blood pressure at baseline [MD 3.29 (95% CI = 0.46, 6.12)] were all significantly higher in the progression group while only mean birth weight [MD -0.17 (95% CI = -0.31, -0.03)] was significantly higher in the non-progression group. CONCLUSIONS: This study fills a gap in the literature and provide physicians with more information on the risk factors associated with the progression of DR in pregnancy and how to counsel this vulnerable patient population appropriately.

Adult-onset foveomacular vitelliform dystrophy: epidemiology, pathophysiology, imaging, and prognosis.

Adult-onset foveomacular dystrophy (AOFVD) is a retinal pattern dystrophy that may affect up to 1 in 7,400 individuals. There is much that is unknown regarding this disease's epidemiology, risk factors for development, and rate of progression through its four stages. Advancements in retinal imaging over the past 15 years have enabled improved characterization of the different stages of AOFVD. These imaging advancements also offer new ways of differentiating AOFVD from phenotypically similar retinal diseases like age-related macular degeneration and Best disease. This review synthesizes the most recent discoveries regarding imaging correlates within AOFVD as well as risk factors for the development of AOFVD, complications of AOFVD, and treatment options. Our aim is to provide ophthalmologists a succinct resource so that they may offer clarity, guidance, and appropriate monitoring and treatments for their patients with suspected AOFVD.

Incidence of Referable Retinal Disease in Diabetic Patients at a Primary Care Practice.

Purpose: This work tests the feasibility of remote ophthalmic imaging to identify referable retinal abnormalities and assesses the effectiveness of color fundus photography (CFP) vs optical coherence tomography (OCT) for this purpose. Methods: This prospective, nonrandomized study included 633 patients with diabetes at Duke Primary Care. Undilated patients underwent screening with CFP and OCT camera (MaestroCare, Topcon). Images were graded independently for interpretability and the presence of predetermined retinal disease. Retinal disease was classified as diabetic retinopathy (DR) referable to a retina specialist or incidental findings referable to either a retina specialist or a general ophthalmologist, depending on severity. Results: Mean (SD) age of screened patients was 66 (13) years, and 49% were women. The average glycated hemoglobin A1c level was 7.6 % (SD, 1.7%), and 30% of the patients were on insulin. The average duration of diabetes was 5.9 (SD, 7.3) years. Remote images from OCT were significantly more interpretable than CFP (98% vs 83%, respectively; P < .001). Referral rates were 9% for DR and 28% for incidental findings. Among patients with DR, OCT and CFP were helpful in 58% and 87% of cases, respectively (P < .001). Conclusions: Remote diagnosis of ophthalmic imaging at the point of service may allow for early identification of retinal disease and timely referral and treatment. Our approach showed that OCT had significantly better interpretability, while CFP was more helpful in identifying DR. These findings may be important when choosing the screening device in a specific context.

Automated Identification of Referable Retinal Pathology in Teleophthalmology Setting.

Purpose: This study aims to meet a growing need for a fully automated, learning-based interpretation tool for retinal images obtained remotely (e.g. teleophthalmology) through different imaging modalities that may include imperfect (uninterpretable) images. Methods: A retrospective study of 1148 optical coherence tomography (OCT) and color fundus photography (CFP) retinal images obtained using Topcon's Maestro care unit on 647 patients with diabetes. To identify retinal pathology, a Convolutional Neural Network (CNN) with dual-modal inputs (i.e. CFP and OCT images) was developed. We developed a novel alternate gradient descent algorithm to train the CNN, which allows for the use of uninterpretable CFP/OCT images (i.e. ungradable images that do not contain sufficient image biomarkers for the reviewer to conclude absence or presence of retinal pathology). Specifically, a 9:1 ratio to split the training and testing dataset was used for training and validating the CNN. Paired CFP/OCT inputs (obtained from a single eye of a patient) were grouped as retinal pathology negative (RPN; 924 images) in the absence of retinal pathology in both imaging modalities, or if one of the imaging modalities was uninterpretable and the other without retinal pathology. If any imaging modality exhibited referable retinal pathology, the corresponding CFP/OCT inputs were deemed retinal pathology positive (RPP; 224 images) if any imaging modality exhibited referable retinal pathology. Results: Our approach achieved 88.60% (95% confidence interval [CI] = 82.76% to 94.43%) accuracy in identifying pathology, along with the false negative rate (FNR) of 12.28% (95% CI = 6.26% to 18.31%), recall (sensitivity) of 87.72% (95% CI = 81.69% to 93.74%), specificity of 89.47% (95% CI = 83.84% to 95.11%), and area under the curve of receiver operating characteristic (AUC-ROC) was 92.74% (95% CI = 87.71% to 97.76%). Conclusions: Our model can be successfully deployed in clinical practice to facilitate automated remote retinal pathology identification. Translational Relevance: A fully automated tool for early diagnosis of retinal pathology might allow for earlier treatment and improved visual outcomes.

Automated Recognition of Retinal Pigment Epithelium Cells on Limited Training Samples Using Neural Networks.

Purpose: To develop a neural network (NN)-based approach, with limited training resources, that identifies and counts the number of retinal pigment epithelium (RPE) cells in confocal microscopy images obtained from cell culture or mice RPE/choroid flat-mounts. Methods: Training and testing dataset contained two image types: wild-type mice RPE/choroid flat-mounts and ARPE 19 cells, stained for Rhodamine-phalloidin, and imaged with confocal microscopy. After image preprocessing for denoising and contrast adjustment, scale-invariant feature transform descriptors were used for feature extraction. Training labels were derived from cells in the original training images, annotated and converted to Gaussian density maps. NNs were trained using the set of training input features, such that the obtained NN models accurately predicted corresponding Gaussian density maps and thus accurately identifies/counts the cells in any such image. Results: Training and testing datasets contained 229 images from ARPE19 and 85 images from RPE/choroid flat-mounts. Within two data sets, 30% and 10% of the images, were selected for validation. We achieved 96.48% ± 6.56% and 96.88% ± 3.68% accuracy (95% CI), on ARPE19 and RPE/choroid flat-mounts. Conclusions: We developed an NN-based approach that can accurately estimate the number of RPE cells contained in confocal images. Our method achieved high accuracy with limited training images, proved that it can be effectively used on images with unclear and curvy boundaries, and outperformed existing relevant methods by decreasing prediction error and variance. Translational Relevance: This approach allows efficient and effective characterization of RPE pathology and furthermore allows the assessment of novel therapeutics.

Age-Related Macular Degeneration Revisited: From Pathology and Cellular Stress to Potential Therapies.

Age-related macular degeneration (AMD) is a neurodegenerative disease of the aging retina, in which patients experience severe vision loss. Therapies available to patients are limited and are only effective in a sub-population of patients. Future comprehensive clinical care depends on identifying new therapeutic targets and adopting a multi-therapeutic approach. With this goal in mind, this review examines the fundamental concepts underlying the development and progression of AMD and re-evaluates the pathogenic pathways associated with the disease, focusing on the impact of injury at the cellular level, with the understanding that critical assessment of the literature may help pave the way to identifying disease-relevant targets. During this process, we elaborate on responses of AMD vulnerable cells, including photoreceptors, retinal pigment epithelial cells, microglia, and choroidal endothelial cells, based on in vitro and in vivo studies, to select stressful agents, and discuss current therapeutic developments in the field, targeting different aspects of AMD pathobiology.

Evaluation of a Remote Diagnosis Imaging Model vs Dilated Eye Examination in Referable Macular Degeneration.

Importance: In improving clinical outcomes, developing a sustainable, transformative care delivery model is important for accessible, efficient, low-cost, high-quality community-based imaging and diagnosis of retinal diseases. Objective: To test the feasibility and accuracy of the remote diagnosis imaging model as a clinical screening tool to facilitate the identification of referable macular degeneration. Design, Setting, and Participants: A nonrandomized study of 159 patients was conducted in sites with a relatively high disease prevalence (Duke University Health System endocrinology clinic and 2 Duke University Health System assisted living centers in North Carolina). All patients underwent remote diagnosis imaging, defined as color fundus photography (CFP) and optical coherence tomography (OCT) of nondilated pupils, acquired by nonexpert imagers using a retinal imaging device located at the point of service. The criterion standard examination was defined as a traditional dilated eye examination performed by retinal specialists. Deidentified remote diagnosis images were graded for interpretability and presence of referable macular degeneration, defined as any condition requiring a retinal specialist attention. Data analysis was performed from November 20, 2015, to February 10, 2019. Main Outcomes and Measures: Primary outcome was feasibility of the remote retinal imaging. Secondary outcomes were operational characteristics and diagnostic and referral accuracy. Results: Of the 159 patients included in the study, the mean (SD) age of enrolled participants was 65 (17) years, with a female to male ratio of 1.3 to 1. Most patients were white (111 [69.8%]), 44 were black patients (27.7%), approximately 1% were Asian patients and Hispanic patients, and 2 patients declined to disclose their race/ethnicity. Thirty-five eyes (22.0%) were determined to require referral to the retinal specialist by criterion standard examination. Remote diagnosis image interpretability was better when OCT was used compared with CFP (241 [96.4%] vs 164 [65.6%]). Remote diagnosis had high diagnostic accuracy in identifying referable macular degeneration: OCT and CFP both had 94% sensitivity (95% CI, 84%-98%), and OCT had specificity higher than for CFP (93% [95% CI, 87%-96% ] vs 63% [95% CI, 53%-71%]). Substantial agreement was found between the criterion standard and OCT (κ = 0.83; 95% CI, 0.76-0.91; P < .001) and between the criterion standard and CFP (κ = 0.76; 95% CI, 0.64-0.87; P < .001). The nonvalidated patient satisfaction survey revealed that 122 participants (76.7%; mean score, 4.16; 95% CI, 3.98-4.35) preferred remote imaging over the standard care examination. Conclusions and Relevance: Remote diagnosis imaging and a standard examination by a retinal specialist appeared equivalent in identifying referable macular degeneration in patients with high disease prevalence; these results may assist in delivering timely treatment and seem to warrant future research into additional metrics.

Region-specific ischemia, neovascularization and macular oedema in treatment-naïve proliferative diabetic retinopathy.

IMPORTANCE: Region-specific pathology in proliferative diabetic retinopathy enhances our understanding and management of this disease. BACKGROUND: To investigate non-perfusion, neovascularization and macular oedema. DESIGN: A cross-sectional, observational, non-randomized study. PARTICIPANTS: Consecutive 43 eyes of 27 treatment-naïve patients. METHODS: Ultra-widefield fluorescein angiography for studying specific zones, that is, far-peripheral zone, mid-peripheral zone and central retina (cr), and spectral-domain optical coherence tomography for analysing thickness of macular layers. MAIN OUTCOME MEASURES: Non-perfusion index (NPI) and neovascularization index (NVI) in different zones, thickness of cr, retinal nerve fibre layer, ganglion cell layer (GCL), inner nuclear layer (INL) and outer plexiform layer in parafoveal regions. RESULTS: The NPI of far-periphery and NVI of mid-periphery were the highest by one-way analysis of variance testing. Ischemic retina defined as high NPI in far-periphery was significantly related to macular oedema via a binary classification approach (P < 0.05). The ischemic retina was correlated with a decreased thickness of both retinal nerve fibre and GCL (P < 0.05); macular oedema was correlated with increased INL thickness (P < 0.0001). CONCLUSIONS AND RELEVANCE: The region-specific correlation of NPI of far-periphery and NVI of mid-periphery, but not with central retinal thickness, suggests different pathogeneses of neovascularization and macular oedema. Retinal nerve fibre layer and GCL, both biomarkers of diabetic retinal neuronopathy, are associated with retinal ischemia, but not with macular oedema, suggesting that diabetic microangiopathy and neuronopathy possess distinct pathogenic pathways. The strong correlation between macular oedema and INL indicates that intracellular oedema is a determining factor of diabetic macular oedema.

Iron importers Zip8 and Zip14 are expressed in retina and regulated by retinal iron levels.

Intracellular retinal iron accumulation has been implicated in the pathogenesis of age-related macular degeneration (AMD), the leading cause of irreversible blindness among individuals over the age of 50. Ceruloplasmin/hephaestin double knockout mice (Cp/Heph DKO) and hepcidin knockout mice (Hepc KO) accumulate retinal iron and model some features of AMD. Two canonical pathways govern cellular iron import - transferrin-bound iron import and non-transferrin bound iron import. In Cp/Heph DKO and Hepc KO iron-loaded retinas, transferrin-bound iron import is downregulated. Despite this effort to reduce cellular iron burden, iron continues to accumulate in these retinas in an age-dependent manner. Quantitative RT-PCR and Western analysis were used to quantify the expression of three ferrous iron importers, Dmt1, Zip8, and Zip14, in wild-type (Wt), Cp/Heph DKO, and Hepc KO retinas. Zip8 and Zip14 protein levels were analyzed using Western analysis in mice injected intravitreally with either apo- or holo-transferrin to elucidate one possible mechanism of Zip14 regulation in the retina. Both zip8 and zip14 were expressed in the mouse retina. Paradoxically, protein levels of non-transferrin bound iron importers were upregulated in both Cp/Heph DKO and Hepc KO retinas. Intravitreal holo-transferrin injection decreased Zip 14 protein levels. These data indicate that Zip8 and Zip14 may take up increasing amounts of non-transferrin bound iron in these two mouse models of retinal iron accumulation. Their upregulation in these already iron-loaded retinas suggests a vicious cycle leading to toxicity.

Cp/Heph mutant mice have iron-induced neurodegeneration diminished by deferiprone.

Brain iron accumulates in several neurodegenerative diseases and can cause oxidative damage, but mechanisms of brain iron homeostasis are incompletely understood. Patients with mutations in the cellular iron-exporting ferroxidase ceruloplasmin (Cp) have brain iron accumulation causing neurodegeneration. Here, we assessed the brains of mice with combined mutation of Cp and its homolog hephaestin. Compared to single mutants, brain iron accumulation was accelerated in double mutants in the cerebellum, substantia nigra, and hippocampus. Iron accumulated within glia, while neurons were iron deficient. There was loss of both neurons and glia. Mice developed ataxia and tremor, and most died by 9 months. Treatment with the oral iron chelator deferiprone diminished brain iron levels, protected against neuron loss, and extended lifespan. Ferroxidases play important, partially overlapping roles in brain iron homeostasis by facilitating iron export from glia, making iron available to neurons. Above: Iron (Fe) normally moves from capillaries to glia to neurons. It is exported from the glia by ferroportin (Fpn) with ferroxidases ceruloplasmin (Cp) and/or Hephaestin (Heph). Below: In mice with mutation of Cp and Heph, iron accumulates in glia, while neurons have low iron levels. Both neurons and glia degenerate and mice become ataxic unless given an iron chelator.