title: Metabolome-wide association study of neovascular age-related macular degeneration.
abstract: OBJECTIVE
  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.
authors.affiliation: Vanderbilt Eye Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
authors.forename: Melissa P
authors.initials: MP
authors.lastname: Osborn
authors.forename: Youngja
authors.initials: Y
authors.lastname: Park
authors.forename: Megan B
authors.initials: MB
authors.lastname: Parks
authors.forename: L Goodwin
authors.initials: LG
authors.lastname: Burgess
authors.forename: Karan
authors.initials: K
authors.lastname: Uppal
authors.forename: Kichun
authors.initials: K
authors.lastname: Lee
authors.forename: Dean P
authors.initials: DP
authors.lastname: Jones
authors.forename: Milam A
authors.initials: MA
authors.lastname: Brantley
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D016022:Case-Control Studies; D030561:Databases, Nucleic Acid; D030562:Databases, Protein; D005260:Female; D006801:Humans; D008268:Macular Degeneration / Q000097:blood* / Q000503:physiopathology; D008297:Male; D013058:Mass Spectrometry; D055442:Metabolome; D008875:Middle Aged