Bioinformatics in Age-Related Macular Degeneration: A Narrative Review

Abstract

Purpose: Age-related macular degeneration (AMD) is the leading cause of irreversible blindness worldwide. Understanding AMD's complex pathophysiology of AMD and its associated genetic and molecular mechanisms is critical for the development of effective diagnostics and therapeutics. This review explores the evolving role of bioinformatics in AMD with a focus on current applications and future opportunities in clinical research and patient care. Methods: A comprehensive literature search was conducted using major databases to identify articles related to bioinformatic applications in AMD. Selected studies were evaluated to extract data on bioinformatics tools and techniques, including genomic analysis, artificial intelligence (AI), and systems biology, utilized in AMD research. Results: Bioinformatics has advanced AMD research through genome-wide association studies (GWAS) that identify susceptibility genes, and transcriptomics and proteomics analyses that reveal biomarkers and pathways. AI and machine learning models enhance disease prediction and classification, whereas integrative omics approaches facilitate personalized treatment strategies. Conclusion: Bioinformatics is revolutionizing AMD research by providing insights into its molecular basis, enabling early diagnosis, and aiding in the development of personalized therapies. Continued advancements in computational tools and data integration will further our understanding of AMD and improve preventive and therapeutic outcomes.