Abstract :
[en] Age-related macular degeneration (AMD) is a leading cause of vision loss in the western world in the elderly population. 90% of all vision loss due to AMD result from the exudative form, which is characterized by choroidal neovascularization (CNV). Age-related changes that induce pathologic CNV are incompletely understood. A successful application of anti-VEGF approaches in the clinic is obviously a turning point in AMD treatment. Nevertheless, despite such important advances, critical issues remain to be addressed. To better understand the etiology of this pathology, we decide to apply a NMR-based metabolomics approach on AMD patients and on a laser-induced murine choroidal neovascularization experimental model.
These experiments provide unique challenges to fulfill the goal of improving the current status of physiological information related to metabolome and in general to functional genomics.
For this purpose, sera from control and exudative AMD patients, induced and non-induced mice have been collected and the metabolic profiles of these samples were determined by NMR. After post-processing treatments, the different spectra were analyzed by statistical discriminant methodologies (PCA, ICA, PLS-DA, O-PLS-DA).
This approach allows the differentiation between control and AMD patients and between laser-induced mice and the control mice group. Moreover, the same discriminating spectral zones have been identified in human and mice model, leading to the emergence of different putative biomarkers. Among these markers, Lactate emerges as a key metabolite in both settings. Mechanistically, lactate produced locally and by inflammatory cells, plays a critical role in the onset of the inflammatory and angiogenic phases. In mice model of laser-induced CNV, normalization of circulating lactate by dichloroacetate, decreases CNV development. Our data support the innovative concept of lactate as a parainflammation- and angio-metabolite associated to AMD and CNV progression and metabolomics as a novel option for patients follow-up.
