Abstract:
Introduction. Age-related macular degeneration is a multifactorial, polyetiological condition, affecting individuals over
the age of 50, primarily characterized by progressive and irreversible loss of central vision. In the pursuit of a deeper understanding
of its etiopathogenesis, risk factors, associated biomarkers, and diagnostic metabolites, the omics approach
plays an essential role. The primary objective of this study was to evaluate selected omics biomarkers along with hematological
and clinical data and to establish their correlations with macular degeneration.
Material and methods A pilot retrospective study was conducted, analyzing medical records of 80 patients admitted to
the Ophthalmology Department of the Timofei Moșneaga Republican Clinical Hospital. Laboratory parameters were assessed
and statistically analyzed using the Statistical Package for the Social Sciences. Statistical methods included binomial
tests, Wilcoxon Signed-Rank tests, and One-sample tests. The data obtained were compared with the results of a comprehensive
analysis of the latest scientific literature on age-related macular degeneration.
Results. Omics approach analysis, particularly proteomic and metabolomic analyses, has contributed significantly to the
identification of metabolic pathways involved in age-related macular degeneration pathogenesis, facilitating the investigation
of novel biomarkers for early diagnosis and potential therapeutic targets. In our pilot study, we evaluated clinical
and biochemical data, including age, sex, laboratory values, and comorbidities, and compared them with currently published
research data. Statistically significant biomarkers identified included glucose, triglycerides, prothrombin, fibrinogen,
platelet count, and leukocyte count. Partially significant (dual) biomarkers included total cholesterol, erythrocyte
sedimentation rate, and lymphocyte count. No statistical significance was observed for HDL-cholesterol, LDL-cholesterol,
and international normalized ratio.
Conclusions. Omics approach represents a promising avenue for monitoring, diagnosing, and potentially treating age-related
macular degeneration. By identifying key biomarkers, this approach supports early detection and opens the path for
advanced therapeutic strategies such as gene therapy, cell-based treatments, complement pathway inhibitors, and nanotechnology-
based interventions.
