Search Results (251)

The human eye is a complex organ that is prone to visual impairment from both modifiable and non-modifiable risk factors. While some lifestyle choices, such as smoking, can negatively influence the eye’s visual system, others can have a positive impact. For instance, a healthy diet that includes nutrients such as lutein, zeaxanthin and meso-zeaxanthin can have a beneficial effect on macular health. Similarly, exercise can have a beneficial effect not only on general health and wellbeing but also on ocular health. This article will provide an overview of the link between modifiable risk factors such as diet, exercise, psychological stress and others on ocular diseases including dry eye disease, age-related macular degeneration, myopia, glaucoma and diabetic retinopathy. It will also evaluate whether there is a need to raise awareness amongst the general population on how simple lifestyle changes can improve ocular health. Full article

We previously reported ocular phenotypes of 1-year-old 129S1/SvlmJ lysyl oxidase-like 1 null (Loxl1^−/−) mice. Here we sought to characterize age-dependent changes in C57BL/6J Loxl1^−/− mice in a longitudinal fashion. Retinal ganglion cell (RGC) function was assessed by electroretinography (ERG), and optic nerves were evaluated by histological analysis. Ocular biometric measurements were obtained by optical coherence tomography (OCT). We detected reduced RGC function, revealed by decreased amplitude and increased latency of ERG positive scotopic threshold responses (pSTRs) in Loxl1^−/− mice compared to age-matched wt mice. In addition, there is significant inter-eye asymmetry of RGC function, as well as age-related RGC function loss observed only in Loxl1^−/− mice. Histologically, we observed enlarged optic nerve areas in Loxl1^−/− mice compared to wt mice. Significant ocular biometric differences between two groups were detected, most notably, age-related axial elongation of the globe, accompanied by deepening of anterior chamber depth (ACD). Though eyes elongate with age in both groups, this is more pronounced in Loxl1^−/− mice, and the elongation of the globe correlated with decreased RGC function. The correlation of age-related reduction in RGC function with globe axial elongation may have implications for the association of axial myopia with glaucoma and aging in humans. Full article

Iron is an essential micronutrient integral to ocular physiology, supporting biochemical processes such as mitochondrial respiration, DNA synthesis and phototransduction. Disruptions in systemic or local iron homeostasis, whether due to overload or deficiency, have been increasingly implicated in the pathogenesis of a broad range of anterior and posterior segment ocular disorders. Iron deficiency may compromise retinal bioenergetics, impair cellular repair, and increase susceptibility to oxidative stress, while iron overload facilitates the generation of reactive oxygen species, contributing to lipid peroxidation, mitochondrial dysfunction, and ferroptosis. Dysregulated iron metabolism has been associated with several ocular pathologies, including age-related macular degeneration, diabetic retinopathy, glaucoma, retinal detachment, cataracts, and anemic retinopathy. The eye possesses specialized iron regulatory mechanisms involving proteins such as transferrin, ferritin, ferroportin, and hepcidin that govern iron transport, storage, and export across ocular barriers. Aberrations in these pathways are now recognized as contributing factors in disease progression. This narrative review explores the complex dual role of iron overload and deficiency in ocular diseases. It highlights the molecular mechanisms underlying iron-mediated pathologies in both the posterior and anterior segments of the eye, along with the clinical manifestations of iron imbalance. Current therapeutic approaches are discussed, including oral and parenteral iron supplementation for deficiency and emerging chelation-based or antioxidant strategies to address iron overload, while highlighting their limitations. Key challenges remain in developing targeted ocular delivery systems that optimize bioavailability and minimize systemic toxicity. Hence, maintaining iron homeostasis is critical for visual function, and further research is needed to refine therapeutic interventions and clarify the mechanistic role of iron in ocular health and disease. Full article

Background: Autonomic nervous system (ANS) and vascular factors are associated with glaucoma. However, the association between systemic comorbidity burden and ANS and hemodynamic function in patients with glaucoma remains unclear. This study aimed to examine the association between heart rate variability (HRV) and acceleration plethysmography (APG) parameters and the age-adjusted Charlson Comorbidity Index (ACCI) in patients with glaucoma. Methods: A total of 260 subjects (260 eyes), including 186 with primary open-angle glaucoma (PG) and 74 with exfoliation glaucoma (EG), were enrolled at Shimane University Hospital from June 2023 to July 2024. HRV and APG were assessed using a sphygmograph (TAS9 Pulse Analyzer Plus View). HRV parameters included time-domain measures (SDNN, RMSSD, CVRR) and frequency-domain measures (TP, VLF, LF, HF, LF/HF). APG parameters included the a, b, c, d, and e components of the accelerated pulse wave, and the following vascular types: Type A, Type B, and Type C. The association between ACCI and HRV and APG parameters was evaluated using Spearman’s rank correlation and multivariate regression adjusted for sex, body mass index, pulse rate, systolic and diastolic blood pressure, intraocular pressure, medication score, mean deviation, and glaucoma type. Results: By univariate analysis, against ACCI, significant inverse correlations were observed for several parameters: LnLF (R = −0.17, p = 0.0062); LnLF/LnHF (R = −0.24, p = 0.00012); b peak (R = −0.14, p = 0.031); d peak (R = −0.17, p = 0.0072); and e peak (R = −0.15, p = 0.015). Regarding HRV parameters, multivariate linear regression models showed that ACCI was significantly positively associated with RMSSD (coefficient: 2.861; 95% CI: 0.447 to 5.274) and significantly negatively associated with the frequency-domain parameters LnLF (coefficient: −0.127; 95% CI: −0.245 to −0.009) and LnLF/LnHF (coefficient: −0.038; 95% CI: −0.062 to −0.014). In APG parameters, the c peak was significant associated with ACCI (coefficient: −12.6; 95% CI: −22.5 to −2.69). ACCI was significantly associated with Type B (coefficient: 0.305; 95% CI: 0.057 to 0.552). Conclusions: Greater systemic comorbidity burden may be related to impaired ANS regulation and increased vascular stiffness in glaucoma patients. Full article

Although conventional medicine has seen substantial progress in recent years, there is a growing interest in nutraceuticals, bioactive compounds derived from natural sources such as plants, fruits, and cereals, due to their potential therapeutic applications. These substances have garnered increasing attention for their capacity to support ocular health and to aid in the prevention and management of age-related eye disorders, including age-related macular degeneration (AMD), cataracts, and glaucoma. This review provides a comprehensive and detailed analysis of selected nutraceuticals related to ocular health and diseases. It aims to define their pharmacodynamic properties, to elucidate the molecular and cellular mechanisms underlying their effects and to critically evaluate the current evidence regarding their potential clinical applications. By integrating findings from both preclinical and clinical studies, this review seeks to offer insights into the role of these nutraceuticals in the prevention, management, and adjunctive treatment of various ocular disorders, thereby suggesting future research directions and clinical practice. Notable attention is given to their antioxidant, anti-inflammatory, and neuroprotective properties, which are believed to contribute to the preservation of visual function and the deceleration of disease progression. Elucidating the medicinal benefits of these compounds may open new pathways for complementary or alternative strategies in the prevention and treatment of ocular diseases. Full article

Molecular imaging and precision therapies are transforming ophthalmology, enabling earlier and more accurate diagnosis and targeted treatment of sight-threatening diseases. This review focuses on age-related macular degeneration, diabetic retinopathy, glaucoma, and uveitis, examining high-resolution imaging techniques such as optical coherence tomography (OCT), OCT angiography, MALDI-MSI, and spatial transcriptomics. Artificial intelligence supports these methods by improving image interpretation and enabling personalized analysis. The review also discusses therapeutic advances, including gene therapies (e.g., AAV-mediated RPE65 delivery), stem cell-based regenerative approaches, and biologics targeting inflammatory and neovascular processes. Targeted molecular therapies targeting specific signaling pathways, such as MAPK, are also explored. The combination of single-cell transcriptomics, proteomics, and machine learning facilitates the development of personalized treatment strategies. Although these technologies hold enormous potential, their implementation in routine clinical care requires further validation, regulatory approval, and long-term safety assessment. This review highlights the potential and challenges of integrating molecular imaging and advanced therapies in the future of precision ophthalmic medicine. Full article

Background: Exfoliation syndrome (XFS) is a form of deleterious ocular aging mediated by genetic and environmental factors that frequently produces glaucoma (XFG). We aimed to develop a genetic risk score (GRS), assess its clinical utility, and identify metabolites/metabolite classes associated with a high GRS. Methods: For 39,472 Nurses’ Health Studies (NHS, 1980–2018; NHS2, 1989–2019) and Health Professionals Follow-up Study (1986–2018) participants aged ≥ 40 years reporting eye exams and no baseline glaucoma, we formed an eight-single nucleotide polymorphism Genetic Risk Score (GRS8) using loci with genome-wide associations with XFS. We estimated relative risks (RR) for incident XFG suspect (XFGS)/XFG (n = 118 cases) and Harrell’s C statistics. Among 7547 participants with plasma metabolites measured via liquid chromatography-mass spectrometry, we evaluated the relation between GRS8 and 427 individual metabolites and 20 metabolite classes, adjusting for multiple comparisons. Results: Higher GRS8 was associated with XFGS/XFG (GRS8 RR_{Quintile(Q)5vs.Q1} = 3.82, 95% CI: 1.76, 8.29). GRS8 significantly (p = 0.04) improved model prediction from C-index of 88% (95% CI: 0.84, 0.92) to 93% (95% CI: 0.91, 0.95) when added to a basic risk model including age, sex, period at risk, intraocular pressure, and glaucoma family history. Metabolite class analyses revealed positive associations of bile acids and inverse associations of fatty acyls with GRS8 (adjusted p < 0.001). Conclusions: XFS GRS8 improved XFGS/XFG prediction, and a higher XFS GRS8 was associated with altered levels of fatty acyl and bile acid metabolite classes. Full article

Objective: The objective was to provide evidence on the effectiveness (intraocular pressure, IOP) and safety of Deep Sclerectomy with the Esnoper Clip implant with and without the use of mitomycin C (MMC) in uncontrolled primary open-angle glaucoma. Methods: This was a multicentric, retrospective, consecutive case series study undertaken as a collaboration between University Hospital Trias i Pujol, Spain, and University Hospital Kralovske Vinohrady, Czech Republic. The IOP reduction was compared between patients who underwent Deep Sclerectomy with the Esnoper Clip implant, where the antifibrotic agent mitomycin C was used perioperatively (MMC group), and patients who underwent Deep Sclerectomy with Esnoper Clip implants where mitomycin C was not used either peri- or postoperatively (non-MMC group). At the end of the study (12 months after surgery), complete success probability (defined as an IOP <21 mmHg without medication) and qualified success probability (defined as an IOP <21 mmHg with or without medication) were assessed. Safety was based on postoperative complications. A descriptive and exploratory analysis was performed. Results: Between January 2017 and June 2019, a total of 72 consecutive patients (40 women and 32 men; age [median (range)] 70 (39–90)) with uncontrolled primary open-angle glaucoma who underwent Deep Sclerectomy with an Esnoper Clip implant were included. Of these, 78 eyes were included: 44 eyes (38 patients) in the MMC group and 34 eyes (34 patients) in the non-MMC group. At the end of the study (38 and 32 eyes, respectively), the complete success probabilities (95% confidence interval) were 62.2% (51.5–75.2%) and 80.5% (69.5–93.2%), p-value: 0.001; qualified success probability (95% confidence interval): 84.7% (76.6–93.7%) and 85.7% (75.8–97%), p-value: 0.188; and complications (total): 36 and 24, p-value: 0.286. Conclusions: In this case series study, the use of mitomycin C in Deep Sclerectomy with the Esnoper Clip implant for patients with uncontrolled primary open-angle glaucoma does not appear to improve IOP one year after surgery. No safety issues related to mitomycin C were observed. Further study is needed to confirm the effectiveness and to assess long-term safety. Full article

Transcriptomic profiling is a powerful tool for dissecting the cellular and molecular complexity of ocular tissues, providing insights into retinal development, corneal disease, macular degeneration, and glaucoma. With the expansion of microarray, bulk RNA sequencing (RNA-seq), and single-cell RNA-seq technologies, artificial intelligence (AI) has emerged as a key strategy for analyzing high-dimensional gene expression data. This review synthesizes AI-enabled transcriptomic studies in ophthalmology from 2019 to 2025, highlighting how supervised and unsupervised machine learning (ML) methods have advanced biomarker discovery, cell type classification, and eye development and ocular disease modeling. Here, we discuss unsupervised techniques, such as principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), uniform manifold approximation and projection (UMAP), and weighted gene co-expression network analysis (WGCNA), now the standard in single-cell workflows. Supervised approaches are also discussed, including the least absolute shrinkage and selection operator (LASSO), support vector machines (SVMs), and random forests (RFs), and their utility in identifying diagnostic and prognostic markers in age-related macular degeneration (AMD), diabetic retinopathy (DR), glaucoma, keratoconus, thyroid eye disease, and posterior capsule opacification (PCO), as well as deep learning frameworks, such as variational autoencoders and neural networks that support multi-omics integration. Despite challenges in interpretability and standardization, explainable AI and multimodal approaches offer promising avenues for advancing precision ophthalmology. Full article

Optical coherence tomography (OCT) is a leading imaging technique for diagnosing retinal disorders such as age-related macular degeneration and diabetic retinopathy. Its ability to detect structural changes, especially in the optic nerve head, has made it vital for early diagnosis and monitoring. This paper surveys techniques for ocular disease prediction using OCT, focusing on both hand-crafted and deep learning-based feature extractors. While the field has seen rapid growth, a detailed comparative analysis of these methods has been lacking. We address this by reviewing research from the past 20 years, evaluating methods based on accuracy, sensitivity, specificity, and computational cost. Key diseases examined include glaucoma, diabetic retinopathy, cataracts, amblyopia, and macular degeneration. We also assess public OCT datasets widely used in model development. A unique contribution of this paper is the exploration of adversarial attacks targeting OCT-based diagnostic systems and the vulnerabilities of different feature extraction techniques. We propose a practical, robust defense strategy that integrates with existing models and outperforms current solutions. Our findings emphasize the value of combining classical and deep learning methods with strong defenses to enhance the security and reliability of OCT-based diagnostics, and we offer guidance for future research and clinical integration. Full article

Ocular disease (OD) represents a complex medical condition affecting humans. OD diagnosis is a challenging process in the current medical system, and blindness may occur if the disease is not detected at its initial phase. Recent studies showed significant outcomes in the identification of OD using deep learning (DL) models. Thus, this work aims to develop a multi-classification DL-based model for the classification of seven ODs, including normal (NOR), age-related macular degeneration (AMD), diabetic retinopathy (DR), glaucoma (GLU), maculopathy (MAC), non-proliferative diabetic retinopathy (NPDR), and proliferative diabetic retinopathy (PDR), using color fundus images (CFIs). This work proposes a custom model named the ocular disease detection model (ODDM) based on a CNN. The proposed ODDM is trained and tested on a publicly available ocular disease dataset (ODD). Additionally, the SMOTE Tomek (SM-TOM) approach is also used to handle the imbalanced distribution of the OD images in the ODD. The performance of the ODDM is compared with seven baseline models, including DenseNet-201 (R₁), EfficientNet-B0 (R₂), Inception-V3 (R₃), MobileNet (R₄), Vgg-16 (R₅), Vgg-19 (R₆), and ResNet-50 (R₇). The proposed ODDM obtained a 98.94% AUC, along with 97.19% accuracy, a recall of 88.74%, a precision of 95.23%, and an F1-score of 88.31% in classifying the seven different types of OD. Furthermore, ANOVA and Tukey HSD (Honestly Significant Difference) post hoc tests are also applied to represent the statistical significance of the proposed ODDM. Thus, this study concludes that the results of the proposed ODDM are superior to those of baseline models and state-of-the-art models. Full article

Background/Objectives: The relationship between systemic health and ocular diseases is well-documented, with various body metrics potentially playing significant roles in the pathogenesis of cataracts, glaucoma, and age-related macular degeneration (AMD). However, comprehensive studies linking these metrics with ocular health are sparse. This study aims to explore the associations between height, weight, waist circumference, and BMI with the prevalence and current status of cataracts, glaucoma, and AMD in a large cohort. Methods: We used data from Korean National Health and Nutrition Survey (KNHANES 2015–2021), a national, cross-sectional health examination and survey, for which representative data on the health, nutritional status, and physical activities of the Korean general population are collected by the Korea Centers for Disease Control and Prevention (KCDC). We compared height, weight, waist circumference, and BMI among patients with diagnosed and current cataracts, glaucoma, and AMD versus those without these conditions. Statistical analyses included t-tests and Pearson correlation analyses to examine the relationships between body metrics and ocular diseases. Results: Our findings indicate that shorter height and lower weight are associated with diagnosed cataracts and glaucoma but not with their current status. A greater waist circumference was observed in patients with diagnosed cataracts, glaucoma, and AMD compared to controls, suggesting central obesity as a potential associated factor. No significant differences in BMI were found in patients with current ocular diseases. Additionally, certain body metrics were correlated with refractive errors and visual acuity, suggesting broader implications for ocular health. Conclusions: The study highlights significant associations between body metrics and the risk of developing cataracts, glaucoma, and AMD. AMD was found to be more closely related to systemic diseases, such as diabetes and hypertension, than to body metrics. These findings suggest that interventions targeting obesity and metabolic health could potentially reduce the risk or severity of these common ocular conditions. Further research is needed to confirm these relationships and explore underlying mechanisms. Full article

Background/Objectives: We analyzed recent changes in the incidence of glaucoma and associated visual impairment (VI) in Korea over a 16-year period. Methods: We utilized nationwide, longitudinal cohort data from the Korea National Health Insurance System (KNHIS) National Health Screening Cohort from 2004 to 2019 to evaluate the age-standardized incidence rate (SIR) of glaucoma and glaucoma-related VI. VI was determined based on KNHIS health examinations and the National Registry for Visual Disability. The incidence rates were estimated per 100,000 person-years. Joinpoint regression analysis was applied to assess significant changes in incidence trends, and subgroup analyses were conducted by age and sex. Results: The age-SIR of glaucoma increased from 864.1 per 100,000 in 2004 to a peak of 1101.1 in 2016, followed by a decline to 978.9 in 2019. Joinpoint regression identified a significant rise from 2007 to 2015 (annual percent change [APC]: +3.92%), with a subsequent decline (APC: –3.30%). The incidence of glaucoma-related severe VI decreased from 26.23 per 100,000 in 2004 to 8.76 in 2012, remaining stable thereafter at 12.49 in 2019. The VI-to-incidence ratio also declined from 0.030 in 2004 to 0.009 in 2012, which remained stable thereafter at 0.013 in 2019. Females consistently exhibited higher glaucoma incidence but lower VI rates than males. Conclusions: These recent trends highlight the evolving landscape of glaucoma epidemiology in Korea and underscore the need for sustained early detection efforts and optimized patient management. Full article

Background/Objectives: Heart rate variability (HRV) is a marker of autonomic nervous system function, based on fluctuations in heartbeat intervals. Although several studies have investigated the association between frequency-domain HRV parameters and glaucoma, evidence based on large sample sizes remains limited. Therefore, the present study aimed to examine the relationship between frequency-domain HRV parameters and glaucoma subtypes, including primary open-angle glaucoma (PG) and exfoliation glaucoma (EG), using a larger sample size. Methods: Participants with primary open-angle glaucoma (PG), exfoliation glaucoma (EG), or no ocular disease other than cataract (controls) were recruited at Shimane University between June 2023 and July 2024. Frequency-domain HRV parameters (total power [TP], very-low-frequency [VLF], low-frequency [LF], high-frequency [HF], and LF/HF) were measured using a sphygmograph (TAS9 Pulse Analyzer Plus View). Group comparisons were conducted using unpaired t-tests, Fisher’s exact tests, and Tukey’s HSD test. Multivariate analyses were performed to identify factors associated with each HRV parameter. Results: A total of 809 participants were analyzed, including 522 with PG, 191 with EG, and 96 controls. The EG group showed significantly lower values across all frequency-domain HRV parameters compared to the PG group, and significantly lower LnLF values than the control group (p = 0.012). Multivariate analyses revealed that no significant associations were found between HRV measures and the presence of glaucoma or pseudoexfoliation material (PEM) deposition. Older age was significantly associated with lower values across all HRV parameters. Conclusions: In elderly glaucoma patients, age-related alterations in frequency-domain HRV parameters have been observed. Full article

Age-related ocular conditions like macular degeneration (AMD), diabetic retinopathy (DR), and glaucoma are leading causes of irreversible vision loss globally. Optical coherence tomography (OCT) provides essential non-invasive visualization of retinal structures for early diagnosis, but manual analysis of these images is labor-intensive and prone to variability. Deep learning (DL) techniques have emerged as powerful tools for automating the segmentation of the retinal layer in OCT scans, potentially improving diagnostic efficiency and consistency. This review systematically evaluates the state of the art in DL-based retinal layer segmentation using the PRISMA methodology. We analyze various architectures (including CNNs, U-Net variants, GANs, and transformers), examine the characteristics and availability of datasets, discuss common preprocessing and data augmentation strategies, identify frequently targeted retinal layers, and compare performance evaluation metrics across studies. Our synthesis highlights significant progress, particularly with U-Net-based models, which often achieve Dice scores exceeding 0.90 for well-defined layers, such as the retinal pigment epithelium (RPE). However, it also identifies ongoing challenges, including dataset heterogeneity, inconsistent evaluation protocols, difficulties in segmenting specific layers (e.g., OPL, RNFL), and the need for improved clinical integration. This review provides a comprehensive overview of current strengths, limitations, and future directions to guide research towards more robust and clinically applicable automated segmentation tools for enhanced ocular disease diagnosis. Full article