Age-related macular degeneration (AMD) is a leading cause of blindness in developed countries and a growing global health concern. The multifactorial nature of AMD calls for integrative multi-omics approaches. We summarize studies employing multi-omics in AMD. A comprehensive search in PubMed and Scopus databases identified 561 records with multi-omics criteria, of which duplicates, unrelated and unavailable articles were excluded, resulting in 33 reports. Quality was assessed following the Office of Health Assessment and Translation (OHAT) method, and data was synthesized through standardized evidence tables. Across the reviewed reports, multi-omics approaches were applied to non-clinical and clinical samples, including ocular and systemic fluids. Methodological trends included the widespread use of causal inference approaches (e.g., Mendelian randomization and Bayesian colocalization) and increasing adoption of spatial and single-cell resolution techniques. Converging molecular patterns consistently suggested inflammation, complement activation, angiogenesis, lipid dysregulation, and mitochondrial dysfunction as key processes underlying AMD. Integration of genetic risk with proteomic and metabolomic alterations, enabled the identification of candidate diagnostic and prognostic biomarkers such as carboxyethylpyrrole and PRMT3. Additionally, this review revealed opportunities for personalized medicine in AMD patient stratification, improvement of prediction models, and therapeutic personalization; however, heterogeneity was noted across studies, particularly regarding sample source (systemic vs. ocular), analytical platforms, integration strategies, and ancestry representation. Despite this variability, this review illustrates how integrating multiple omics layers provides a comprehensive and multidimensional understanding of AMD pathology, advancing research towards better diagnosis, prognosis, and therapeutics for these patients.
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