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

Eveline Kersten, Sascha Dammeier, EYE-RISK Consortium, Soufiane Ajana, Joannes M.M. Groenewoud, Marius Codrea, Franziska Klose, Yara T. Lechanteur, Sascha Fauser, Marius Ueffing, Cécile Delcourt, Carel B. Hoyng, Eiko de Jong, Anneke I. Den Hollander*, Blanca Arango-Gonzalez, Verena Arndt, Vaibhav Bhatia, Shomi S. Bhatta-Charya, Marc Biarnés, Anna BorrellSebastian Bühren, Sofia M. Calado, Johanna M. Colijn, Audrey Cougnard-Grégoire, Eiko de Jong, Berta De la Cerda, Cécile Del-Court, F. J. Diaz-Corrales, Sigrid Diether, Eszter Emri, Tanja Ender-Mann, Lucia Ferraro, Míriam Garcia, Thomas J. Heesterbeek, Sabina Honisch, Roberto Iacone, Ellen Kilger, Caroline C.W. Klaver, Hanno Langen, Imre Lengyel, Phil Luthert, Cyrille Maugeais, Magda Meester-Smoor, Benedicte Merle, Jordi Monés, Everson Nogoceke, Tunde Peto, Fran Pool, Eduardo Rodríguez, Karl Ulrich Bartz-Schmidt, Timo Verzijden

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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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.

Original languageEnglish
Article numbere0218457
JournalPLoS ONE
Volume14
Issue number6
DOIs
Publication statusPublished - 1 Jun 2019

Bibliographical note

Funding Information:
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 634479 (EYE-RISK). La Roche AG provided support in the form of salary for S.F., but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of S.F. are articulated in the ‘author contributions’ section.

Publisher Copyright:
© 2019 Kersten et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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