Peripapillary Oxygenation and Retinal Vascular Responsiveness to Flicker Light in Primary Open Angle Glaucoma

Aging in Ocular Blood Vessels: Molecular Insights and the Role of Oxidative Stress

Acknowledged as a significant pathogenetic driver for numerous diseases, aging has become a focal point in addressing the profound changes associated with increasing human life expectancy, posing a critical concern for global public health. Emerging evidence suggests that factors influencing vascular aging extend their impact to choroidal and retinal blood vessels. The objective of this work is to provide a comprehensive overview of the impact of vascular aging on ocular blood vessels and related diseases. Additionally, this study aims to illuminate molecular insights contributing to vascular cell aging, with a particular emphasis on the choroid and retina. Moreover, innovative molecular targets operating within the domain of ocular vascular aging are presented and discussed.

Aging, Cellular Senescence, and Glaucoma

Aging is one of the most serious risk factors for glaucoma, and according to age-standardized prevalence, glaucoma is the second leading cause of legal blindness worldwide. Cellular senescence is a hallmark of aging that is defined by a stable exit from the cell cycle in response to cellular damage and stress. The potential mechanisms underlying glaucomatous cellular senescence include oxidative stress, DNA damage, mitochondrial dysfunction, defective autophagy/mitophagy, and epigenetic modifications. These phenotypes interact and generate a sufficiently stable network to maintain the cell senescent state. Senescent trabecular meshwork (TM) cells, retinal ganglion cells (RGCs) and vascular endothelial cells reportedly accumulate with age and stress and may contribute to glaucoma pathologies. Therapies targeting the suppression or elimination of senescent cells have been found to ameliorate RGC death and improve vision in glaucoma models, suggesting the pivotal role of cellular senescence in the pathophysiology of glaucoma. In this review, we explore the biological links between aging and glaucoma, specifically delving into cellular senescence. Moreover, we summarize the current data on cellular senescence in key target cells associated with the development and clinical phenotypes of glaucoma. Finally, we discuss the therapeutic potential of targeting cellular senescence for the management of glaucoma.

Automated Retinal Vessel Analysis Based on Fundus Photographs as a Predictor for Non-Ophthalmic Diseases-Evolution and Perspectives

The study of retinal vessels in relation to cardiovascular risk has a long history. The advent of a dedicated tool based on digital imaging, i.e., the retinal vessel analyzer, and also other software such as Integrative Vessel Analysis (IVAN), Singapore I Vessel Assessment (SIVA), and Vascular Assessment and Measurement Platform for Images of the Retina (VAMPIRE), has led to the accumulation of a formidable body of evidence regarding the prognostic value of retinal vessel analysis (RVA) for cardiovascular and cerebrovascular disease (including arterial hypertension in children). There is also the potential to monitor the response of retinal vessels to therapies such as physical activity or bariatric surgery. The dynamic vessel analyzer (DVA) remains a unique way of studying neurovascular coupling, helping to understand the pathogenesis of cerebrovascular and neurodegenerative conditions and also being complementary to techniques that measure macrovascular dysfunction. Beyond cardiovascular disease, retinal vessel analysis has shown associations with and prognostic value for neurological conditions, inflammation, kidney function, and respiratory disease. Artificial intelligence (AI) (represented by algorithms such as QUantitative Analysis of Retinal vessel Topology and siZe (QUARTZ), SIVA-DLS (SIVA-deep learning system), and many others) seems efficient in extracting information from fundus photographs, providing prognoses of various general conditions with unprecedented predictive value. The future challenges will be integrating RVA and other qualitative and quantitative risk factors in a unique, comprehensive prediction tool, certainly powered by AI, while building the much-needed acceptance for such an approach inside the medical community and reducing the "black box" effect, possibly by means of saliency maps.