[Plasma proteomics in age-related macular degeneration].

backgroundNeovascular age-related macular degeneration (nAMD) shows a heterogeneous treatment response to anti-vascular endothelial growth factor (VEGF), but the underlying mechanisms remain poorly understood. Classical approaches focus on single biomarkers, whereas the multifactorial and systemic nature of the disease has received less attention.

methodIn the BIOMAC cohort blood proteomes of patients with nAMD were systematically analyzed. Mass spectrometry, dimensionality reduction and pattern-based classifiers were applied to capture systemic proteomic signatures and link them to clinical phenotypes. As a supplement metabolomic analyses were carried out including a focus on xenobiotics.

resultsThe findings demonstrate a distinct yet complex influence of systemic signals: a subset of patients was characterized by oxidative stress and respiratory patterns independent of the ocular morphology. Individual proteins such as aldolase C were associated with disease control but lacked predictive power when considered alone. Only high-dimensional patterns of many proteins enabled a significant, although not yet perfect separation between effectively controlled and chronically active courses of choroidal neovascularization (CNV). Metabolomic profiling further identified unexpected candidates, such as the sweetener saccharin, which consistently showed protective effects in both patients and experimental models.

conclusionSystemic plasma proteome and metabolome signatures reflect the clinical phenotype of nAMD. Modern statistical methods supported by artificial intelligence are the key to unravelling these complex datasets. Although no valid single biomarker has yet emerged, the pattern-based approach provides novel translational insights and can potentially broaden the therapeutic target space for nAMD.