Metabolomics in serum of patients with non-advanced age-related macular degeneration reveals aberrations in the glutamine pathway

Abstract

Age-related macular degeneration (AMD) is a common, progressive multifactorial vision-threatening disease and many genetic and environmental risk factors have been identified. The risk of AMD is influenced by lifestyle and diet, which may be reflected by an altered metabolic profile. Therefore, measurements of metabolites could identify biomarkers for AMD, and could aid in identifying high-risk individuals. Hypothesis-free technologies such as metabolomics have a great potential to uncover biomarkers or pathways that contribute to disease pathophysiology. To date, only a limited number of metabolomic studies have been performed in AMD. Here, we aim to contribute to the discovery of novel biomarkers and metabolic pathways for AMD using a targeted metabolomics approach of 188 metabolites. This study focuses on non-advanced AMD, since there is a need for biomarkers for the early stages of disease before severe visual loss has occurred. Targeted metabolomics was performed in 72 patients with early or intermediate AMD and 72 control individuals, and metabolites predictive for AMD were identified by a sparse partial least squares discriminant analysis. In our cohort, we identified four metabolite variables that were most predictive for early and intermediate stages of AMD. Increased glutamine and phosphatidylcholine diacyl C28:1 levels were detected in non-advanced AMD cases compared to controls, while the rate of glutaminolysis and the glutamine to glutamate ratio were reduced in non-advanced AMD. The association of glutamine with non-advanced AMD corroborates a recent report demonstrating an elevated glutamine level in early AMD using a different metabolomics technique. In conclusion, this study indicates that metabolomics is a suitable method for the discovery of biomarker candidates for AMD. In the future, larger metabolomics studies could add to the discovery of novel biomarkers in yet unknown AMD pathways and expand our insights in AMD pathophysiology.

Fig 1. Boxplots of the four metabolite predictors for non-advanced AMD from sPLSda.

All metabolites were measured in μM. Glutaminolysis is measured as (c_Ala+c_Asp+c_Glu)/c_Gln.

Fig 2. Metabolic conversion of glutamine.

Glutaminolysis, the metabolic conversion of glutamine to glutamate, aspartate and alanine, represents an alternative pathway to supply the mitochondrial citric acid cycle with a surplus of α-ketoglutarate. As this pathway is preferentially used by proliferating tissue, glutaminolysis measured as (c_Ala+c_Asp+c_Glu)/c_Gln is increased in tumor tissue.[22] Metabolites determined in this study are marked in grey.

Fig 3. Receiver operating characteristic curves of the logistic regression models obtained from the entire dataset including derivative variables (black curve) and from crude dataset (blue curve).