March 2012
Volume 53, Issue 14
Free
ARVO Annual Meeting Abstract  |   March 2012
Vitreous Metabolomic Profiling in Patients with Diabetic Retinopathy
Author Affiliations & Notes
  • Allison J. Ferreira
    Vanderbilt Eye Institute, Vanderbilt University, Nashville, Tennessee
  • Megan B. Parks
    Vanderbilt Eye Institute, Vanderbilt University, Nashville, Tennessee
  • Melissa P. Osborn
    Vanderbilt Eye Institute, Vanderbilt University, Nashville, Tennessee
  • Youngja Park
    Department of Medicine, Emory University, Atlanta, Georgia
  • Dean P. Jones
    Department of Medicine, Emory University, Atlanta, Georgia
  • Milam A. Brantley, Jr.
    Vanderbilt Eye Institute, Vanderbilt University, Nashville, Tennessee
  • Footnotes
    Commercial Relationships  Allison J. Ferreira, None; Megan B. Parks, None; Melissa P. Osborn, None; Youngja Park, None; Dean P. Jones, None; Milam A. Brantley, Jr., None
  • Footnotes
    Support  NIH Grant P30 EY008126; and an unrestricted departmental grant from Research to Prevent Blindness
Investigative Ophthalmology & Visual Science March 2012, Vol.53, 2879. doi:
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      Allison J. Ferreira, Megan B. Parks, Melissa P. Osborn, Youngja Park, Dean P. Jones, Milam A. Brantley, Jr.; Vitreous Metabolomic Profiling in Patients with Diabetic Retinopathy. Invest. Ophthalmol. Vis. Sci. 2012;53(14):2879.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: : The purpose of this study is to determine if metabolomic analysis of vitreous samples can detect metabolic alterations in patients with proliferative diabetic retinopathy (PDR) compared to non-diabetic controls.

Methods: : Metabolomic analysis with liquid chromatography-Fourier-transform mass spectrometry was performed on vitreous samples collected from 19 PDR patients and 44 non-diabetic controls at the Vanderbilt Eye Institute. Data were collected by reverse phase C18 liquid chromatography coupled with a Thermo LTQ-Orbitrap Velos mass spectrometer from mass/charge ratio (m/z) 85 to 2000 over 10 minutes. Peak extraction and quantification of ion intensities were performed by an adaptive processing software package (apLCMS). Individual features were matched to the Madison Metabolomics Consortium and Metlin metabolomics databases. A Benjamini and Hochberg False Discovery Rate (FDR) of 0.05 was employed to account for multiple testing. Principle component analysis and orthogonal partial least squares discriminatory analysis were performed to isolate metabolic features that differentiate PDR patients from controls.

Results: : LC-MS analysis detected a total of 5930 unique m/z features in the vitreous samples. OPLS-DA identified 296 features most closely related to each phenotype. Using a FDR of 0.05, 163 of these features were found to be significantly different between PDR patients and controls. KEGG pathway analysis revealed the highest number of hits in the pentose and glucuronate interconversions, arginine and proline metabolism, and ABC transporters pathways.

Conclusions: : These data can be used to design metabolomic analyses targeting metabolic pathways that are differentially regulated in patients with proliferative diabetic retinopathy. Identifying biochemical profiles that are characteristic of diabetics who develop DR will yield new insights into the underlying pathophysiology of DR, pointing to new directions for therapies to treat or prevent DR-related vision loss.

Keywords: diabetic retinopathy • clinical (human) or epidemiologic studies: risk factor assessment • vitreous 
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