Purchase this article with an account.
Samantha Williamson, Youngja Park, Karan Uppal, ViLinh Tran, J. Allie McGrath, Anita Agarwal, Margaret Pericak-Vance, Jonathan Haines, Dean Jones, Milam Brantley; Metabolomic profiles distinguish Age-related Macular Degeneration patients. Invest. Ophthalmol. Vis. Sci. 2013;54(15):4114.
Download citation file:
© ARVO (1962-2015); The Authors (2016-present)
To identify metabolic profiles that distinguish AMD patients from controls and discriminate among AMD stages.
We used high-resolution liquid chromatography-Fourier transform mass spectrometry to analyze plasma samples from 178 AMD patients and 196 controls, including a subset comparative analysis of 83 intermediate AMD and 95 Neovascular AMD (NVAMD). Data were collected from 85-2000 m/z on a Thermo LTQ-Orbitrap Velos mass spectrometer, and metabolic features were extracted using an adaptive processing software package. Benjamini and Hochberg False Discovery Rate (FDR) correction was used to account for multiple testing. Principal Component Analysis and Orthogonal Partial Least Squares-Discriminant Analysis were performed to reveal features that differentiated between AMD patients and controls. Individual metabolites were identified by matching m/z features to the Metlin metabolomics database.
Comparison of 178 AMD patients and 196 controls using FDR (q = 0.05) identified 91 metabolic features that significantly differed between the two groups. Metlin matched 50 of the 91 features and included tripeptides, modified amino acids, and flavinoids. Analysis of the intermediate AMD and NVAMD comparison using FDR (q=0.1) identified 18 discriminating features, including 25-OH hydroxyvitamin D2, methylated flavonols, and multiple compounds related to apoptosis. Four of these features overlapped the 91 features separating AMD from control patients, indicating certain metabolites may be critical to all AMD stages.
These data show metabolomic profiling can discriminate not only between AMD cases and controls but also among AMD disease stages. By providing a quantitative measurement of environmental contributions and by incorporating analysis of metabolic pathways, this method can produce biochemical profiles of AMD patients that will provide targets for therapeutic intervention and insights into rational clinical management.
This PDF is available to Subscribers Only