New insight in Metabolomics based study of Age Related Macular Degeneration (AMD): Lipoprotein profile and subclass analysis.

Age-related macular degeneration (AMD) is the leading cause of blindness among the elderly population in developed countries. 90% of all vision loss due to AMD result from the exudative form of this pathology, which is characterized by choroidal neovascularization (CNV). Currently, diagnosis of AMD relies on ophthalmologic exams and treatments of the exudative form are based on the use of anti-angiogenic drug targeting vascular endothelial growth factors (VEGF). Despite these advance, several clinical challenges have to be overcome, among these the choice of adapted therapeutic treatments and the identification of biomarkers as indicator of patient stratification, disease progression and treatment responses are essential. For these reason we decide to study AMD using an innovative translational metabolomics approach.
Here, we decide to apply a 1H NMR metabolomics approach on AMD patients and on a laser-induced murine choroidal neovascularization experimental model1. The human cohort includes (i) bleeder AMD patient that are under treatment, (ii) non-bleeder AMD patient and (iii) Healthy volunteers.
NMR analysis on collected sera allow the differentiation between control and AMD patients and between laser-induced and 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, lipoprotein profile is of particular interest since some studies associated high density lipoprotein cholesterol and oxidized low density lipoprotein with early AMD2;3 and para-inflammatory process inducing pathologic AMD respectively4.
Our primary data shows similar evolution of the whole lipoprotein profile trough the different group on human and mice studies. These data suggest that investigate lipoprotein profile could be a turning point in the comprehension of the pathologic process that occurs during the apparition and/or the development of pathologic CNV process.
In order to get deeper in the analysis of lipoprotein profile on NMR data readily available a deconvolution algorithm that fit with collected spectra has to be created. Here we describe the started point of this adventure with in first the isolation of proper lipoprotein subclass and their NMR analysis.
The work is still in progress and the creation of a deconvolution algorithm that enable quantification of distinct lipoprotein subclass in NMR spectra collected from AMD patient and from the CNV mice model get closer.