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dc.rights.licenseopenen_US
dc.contributor.authorACAR, I. E.
dc.contributor.authorLORES-MOTTA, L.
dc.contributor.authorCOLIJN, J. M.
dc.contributor.authorMEESTER-SMOOR, M. A.
dc.contributor.authorVERZIJDEN, T.
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorCOUGNARD-GREGOIRE, Audrey
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorAJANA, Soufiane
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorMERLE, Benedicte
dc.contributor.authorDE BREUK, A.
dc.contributor.authorHEESTERBEEK, T. J.
dc.contributor.authorVAN DEN AKKER, E.
dc.contributor.authorDAHA, M. R.
dc.contributor.authorCLAES, B.
dc.contributor.authorPAULEIKHOFF, D.
dc.contributor.authorHENSE, H. W.
dc.contributor.authorVAN DUIJN, C. M.
dc.contributor.authorFAUSER, S.
dc.contributor.authorHOYNG, C. B.
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorDELCOURT, Cecile
dc.contributor.authorKLAVER, C. C. W.
dc.contributor.authorGALESLOOT, T. E.
dc.contributor.authorDEN HOLLANDER, A. I.
dc.contributor.authorCONSORTIUM, Eye-Risk
dc.date.accessioned2021-03-08T11:31:07Z
dc.date.available2021-03-08T11:31:07Z
dc.date.issued2020-12
dc.identifier.issn1549-4713 (Electronic) 0161-6420 (Linking)en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/26457
dc.description.abstractEnOBJECTIVE: In the current study we aimed to identify metabolites associated with age-related macular degeneration (AMD) by performing the largest metabolome association analysis in AMD to date. In addition, we aimed to determine the effect of AMD-associated genetic variants on metabolite levels, and aimed to investigate associations between the identified metabolites and activity of the complement system, one of the main AMD-associated disease pathways. DESIGN: Case-control assocation analysis of metabolomics data. SUBJECTS: 2,267 AMD cases and 4,266 controls from five European cohorts. METHODS: Metabolomics was performed using a high-throughput H-NMR metabolomics platform, which allows the quantification of 146 metabolite measurements and 79 derivative values. Metabolome-AMD associations were studied using univariate logistic regression analyses. The effect of 52 AMD-associated genetic variants on the identified metabolites was investigated using linear regression. In addition, associations between the identified metabolites and activity of the complement pathway (defined by the C3d/C3 ratio) were investigated using linear regression. MAIN OUTCOME MEASURES: Metabolites associated with AMD RESULTS: We identified 60 metabolites that were significantly associated with AMD, including increased levels of large and extra-large HDL subclasses and decreased levels of VLDL, amino acids and citrate. Out of 52 AMD-associated genetic variants, seven variants were significantly associated with 34 of the identified metabolites. The strongest associations were identified for genetic variants located in or near genes involved in lipid metabolism (ABCA1, CETP, APOE, LIPC) with metabolites belonging to the large and extra-large HDL subclasses. In addition, 57 out of 60 metabolites were significantly associated with complement activation levels, and these associations were independent of AMD status. Increased large and extra-large HDL levels and decreased VLDL and amino acid levels were associated with increased complement activation. CONCLUSIONS: Lipoprotein levels were associated with AMD-associated genetic variants, while decreased essential amino acids may point to nutritional deficiencies in AMD. We observed strong associations between the vast majority of the AMD-associated metabolites and systemic complement activation levels, independent of AMD status. This may indicate biological interactions between the main AMD disease pathways, and suggests that multiple pathways may need to be targeted simultaneously for successful treatment of AMD.
dc.language.isoENen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.title.enIntegrating metabolomics, genomics and disease pathways in age-related macular degeneration: The EYE-RISK Consortium
dc.title.alternativeOphthalmologyen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1016/j.ophtha.2020.06.020en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed32553749en_US
bordeaux.journalOphthalmology: Journal of The American Academy of Ophthalmologyen_US
bordeaux.page1693-1709en_US
bordeaux.volume127en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - UMR 1219en_US
bordeaux.issue12en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.teamLEHA_BPH
bordeaux.teamHEALTHY_BPH
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-03162162
hal.version1
hal.date.transferred2021-03-08T11:31:12Z
hal.exporttrue
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