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Ines Lains, Rachel S. Kelly, John B Miller, João Gil, Marco Marques, Rebecca Silverman, Demetrios Vavvas, Ivana Kim, Joaquim N Murta, Jessica Lasky-Su, Rufino Martins Silva, Joan W Miller, Deeba Husain; Human Plasma Metabolomics in Age-related Macular Degeneration – Results of Two Distinct Cohorts. Invest. Ophthalmol. Vis. Sci. 2018;59(9):4946.
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Biomarkers of age-related macular degeneration (AMD) are still lacking and, considering AMD’s multifactorial nature, their identification is challenging. Metabolomics, the study of all metabolites (<1 KDa) in a biological sample, is well suited to address this challenge. Metabolites are the downstream products of the genome, but also reflect environmental interactions, thus closely mirroring phenotype. This study aimed to compare the plasma metabolomic profiles of AMD patients and controls in two distinct cohorts, and to identify new potential biomarker targets.
Prospective, cross-sectional study. In two sites (Boston, US and Coimbra, Portugal), we included subjects with AMD and controls without any vitreoretinal disease (> 50 years). All participants were imaged with color fundus photographs, used for AMD staging according to the AREDS classification scheme. Fasting blood samples were collected and analyzed by Metabolon Inc., using ultra-performance liquid chromatography (UPLC) and high-resolution mass spectrometry (MS). Metabolon’s software was used for peak identification and quality control. Multivariate analysis, including partial-least square discriminant analysis (PLS-DA), was performed to assess clustering between AMD and controls. The discriminatory ability of the identified significantly different metabolites was assessed using receiver operator curve analysis.
We included 505 subjects: 207 in Boston, 77% with AMD (n= 160) and 23% (n= 47) controls; and 298 in Coimbra, 82% with AMD (n= 244) and 18% (n= 54) controls. Using UPLC-MS, 411 named endogenous plasma metabolites were identified. In both cohorts, PLS-DA revealed a clear separation between AMD patients and controls, with the top 15 metabolites (mostly lipids and amino acids) presenting a variable importance in projection (VIP) score ≥ 2.5. Three of these metabolites were common to both cohorts. The top 15 metabolites presented a discriminatory ability (Area Under the Curve) of 82% (95% CI: 0.7-0.9) and 73% (95% CI: 0.6-0.8) in Boston and Coimbra, respectively.
In two independent cohorts, AMD patients presented a distinct plasma metabolomic profile as compared to subjects with a normal macula. Some of the identified metabolites are common to both cohorts, thus supporting the development of plasma-based metabolomics biomarkers of AMD.
This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.
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