PURPOSE: To determine if plasma metabolic profiles can detect differences 
between patients with neovascular age-related macular degeneration (NVAMD) and 
similarly-aged controls.
METHODS: Metabolomic analysis using liquid chromatography with Fourier-transform 
mass spectrometry (LC-FTMS) was performed on plasma samples from 26 NVAMD 
patients and 19 controls. Data were collected from mass/charge ratio (m/z) 85 to 
850 on a Thermo LTQ-FT mass spectrometer, and metabolic features were extracted 
using an adaptive processing software package. Both non-transformed and log2 
transformed data were corrected using Benjamini and Hochberg False Discovery 
Rate (FDR) to account for multiple testing. Orthogonal Partial Least 
Squares-Discriminant Analysis was performed to determine metabolic features that 
distinguished NVAMD patients from controls. Individual m/z features were matched 
to the Kyoto Encyclopedia of Genes and Genomes database and the Metlin 
metabolomics database, and metabolic pathways associated with NVAMD were 
identified using MetScape.
RESULTS: Of the 1680 total m/z features detected by LC-FTMS, 94 unique m/z 
features were significantly different between NVAMD patients and controls using 
FDR (q = 0.05). A comparison of these features to those found with log2 
transformed data (n = 132, q = 0.2) revealed 40 features in common, reaffirming 
the involvement of certain metabolites. Such metabolites included di- and 
tripeptides, covalently modified amino acids, bile acids, and vitamin D-related 
metabolites. Correlation analysis revealed associations among certain 
significant features, and pathway analysis demonstrated broader changes in 
tyrosine metabolism, sulfur amino acid metabolism, and amino acids related to 
urea metabolism.
CONCLUSIONS: These data suggest that metabolomic analysis can identify a panel 
of individual metabolites that differ between NVAMD cases and controls. Pathway 
analysis can assess the involvement of certain metabolic pathways, such as 
tyrosine and urea metabolism, and can provide further insight into the 
pathophysiology of AMD.