TY - JOUR
T1 - Metabolomics in serum of patients with non-advanced age-related macular degeneration reveals aberrations in the glutamine pathway
AU - Kersten, Eveline
AU - Dammeier, Sascha
AU - Ajana, Soufiane
AU - Groenewoud, Joannes M.M.
AU - Codrea, Marius
AU - Klose, Franziska
AU - Lechanteur, Yara T.
AU - Fauser, Sascha
AU - Ueffing, Marius
AU - Delcourt, Cécile
AU - Hoyng, Carel B.
AU - de Jong, Eiko
AU - Den Hollander, Anneke I.
AU - EYE-RISK consortium
AU - Arango-Gonzalez, Blanca
AU - Arndt, Verena
AU - Bhatia, Vaibhav
AU - Bhatta-Charya, Shomi S.
AU - Biarnés, Marc
AU - Borrell, Anna
AU - Bühren, Sebastian
AU - Calado, Sofia M.
AU - Colijn, Johanna M.
AU - Cougnard-Grégoire, Audrey
AU - de Jong, Eiko
AU - De la Cerda, Berta
AU - Del-Court, Cécile
AU - Diaz-Corrales, F. J.
AU - Diether, Sigrid
AU - Emri, Eszter
AU - Ender-Mann, Tanja
AU - Ferraro, Lucia
AU - Garcia, Míriam
AU - Heesterbeek, Thomas J.
AU - Honisch, Sabina
AU - Iacone, Roberto
AU - Kilger, Ellen
AU - Klaver, Caroline C.W.
AU - Langen, Hanno
AU - Lengyel, Imre
AU - Luthert, Phil
AU - Maugeais, Cyrille
AU - Meester-Smoor, Magda
AU - Merle, Benedicte
AU - Monés, Jordi
AU - Nogoceke, Everson
AU - Peto, Tunde
AU - Pool, Fran
AU - Rodríguez, Eduardo
AU - Bartz-Schmidt, Karl Ulrich
AU - van Leeuwen, Elisabeth M.
PY - 2019/6/20
Y1 - 2019/6/20
N2 - 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.
AB - 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.
U2 - 10.1371/journal.pone.0218457
DO - 10.1371/journal.pone.0218457
M3 - Article
C2 - 31220133
AN - SCOPUS:85067441837
SN - 1932-6203
VL - 14
JO - PLoS ONE
JF - PLoS ONE
IS - 6
M1 - e0218457
ER -