Translational Molecular and Fluid Biomarkers for Age-Related Macular Degeneration: Practical Insights from Animal Models and Humans

TL;DR

This paper reviews biomarkers for age-related macular degeneration, comparing human and animal studies to improve diagnosis and treatment.

Contribution

The paper integrates human and animal model data to identify and compare AMD biomarkers for better translational insights.

Findings

AMD biomarkers include oxidative stress, inflammation, and gut microbiota changes in both humans and animal models.

Combining biomarker data from ocular tissues and body fluids could enhance early AMD detection and personalized treatment.

Challenges remain in validating biomarkers and bridging experimental and clinical datasets for AMD management.

Abstract

Age-related macular degeneration (AMD) is a leading cause of irreversible central vision loss. Its pathogenesis is complex and multifactorial, involving genetic predisposition, inflammation, oxidative stress, and environmental influences, which underscores the need to better understand biomarkers associated with the disease. This review provides a comprehensive translational overview of biomarkers linked to both dry and wet forms of AMD by integrating findings from human studies and preclinical mouse models, including chemical, genetic, and laser-induced paradigms. It outlines key tissue, fluid, and systemic biomarkers related to oxidative stress, inflammation, complement activation, extracellular matrix remodeling, angiogenesis, and gut microbiota alterations. The main findings highlight similarities and differences between human AMD and animal models, identify challenges in biomarker validation, and emphasize the potential of combining biomarker profiles from ocular tissues, blood, tear fluid, aqueous and vitreous humor, and gut microbiome samples to improve early diagnosis, therapeutic monitoring, and personalized treatment strategies. These insights suggest that integrating experimental and clinical biomarker data could advance precision medicine in AMD, facilitating better early detection and individualized therapies. Future research should aim to bridge these datasets to optimize biomarker-driven approaches for AMD management.

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