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Author Notes:

Milam A. Brantley Jr, Vanderbilt Eye Institute, Vanderbilt University Medical Center, 2311 Pierce Avenue, Nashville, TN 37232-8808, USA; milam.brantley@vumc.org.

SLM and KU contributed equally to the work presented here and should therefore be regarded as equivalent authors.

The authors thank all patients who generously participated in this study.

Disclosure: S.L. Mitchell, None; K. Uppal, None; S.M. Williamson, None; K. Liu, None; L.G. Burgess, None; V. Tran, None; A.C. Umfress, None; K.L. Jarrell, None; J.N. Cooke Bailey, None; A. Agarwal, None; M. Pericak-Vance, None; J.L. Haines, None; W.K. Scott, None; D.P. Jones, None; M.A. Brantley Jr, None


Research Funding:

Supported by National Institutes of Health (NIH; Bethesda, MD, USA) Grants R01 EY22618 (MAB) and R01 EY012118 (MP-V, JLH, WKS, and AA) and an unrestricted departmental award from Research to Prevent Blindness, and by the Clinical and Translational Science Collaborative of Cleveland, KL2TR000440 from the National Center for Advancing Translational 419 Sciences (NCATS) component of the NIH and NIH roadmap for Medical Research (JNCB).


  • Science & Technology
  • Life Sciences & Biomedicine
  • Ophthalmology
  • metabolomics
  • age-related macular degeneration
  • long-chain acylcarnitines
  • carnitine shuttle
  • RISK

The Carnitine Shuttle Pathway is Altered in Patients With Neovascular Age-Related Macular Degeneration

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Journal Title:

Investigative Ophthalmology & Visual Science


Volume 59, Number 12


, Pages 4978-4985

Type of Work:

Article | Final Publisher PDF


PURPOSE. To identify metabolites and metabolic pathways altered in neovascular age-related macular degeneration (NVAMD). METHODS. We performed metabolomics analysis using high-resolution C18 liquid chromatography-mass spectrometry on plasma samples from 100 NVAMD patients and 192 controls. Data for mass/charge ratio ranging from 85 to 850 were captured, and metabolic features were extracted using xMSanalyzer. Nested feature selection was used to identify metabolites that discriminated between NVAMD patients and controls. Pathway analysis was performed with Mummichog 2.0. Hierarchical clustering was used to examine the relationship between the discriminating metabolites and NVAMD patients and controls. RESULTS. Of the 10,917 metabolic features analyzed, a set of 159 was identified that distinguished NVAMD patients from controls (area under the curve of 0.83). Of these features, 39 were annotated with confidence and included multiple carnitine metabolites. Pathway analysis revealed that the carnitine shuttle pathway was significantly altered in NVAMD patients (P = 0.0001). Tandem mass spectrometry confirmed the molecular identity of five carnitine shuttle pathway acylcarnitine intermediates that were increased in NVAMD patients. Hierarchical cluster analysis revealed that 51% of the NVAMD patients had similar metabolic profiles, whereas the remaining 49% displayed greater variability in their metabolic profiles. CONCLUSIONS. Multiple long-chain acylcarnitines that are part of the carnitine shuttle pathway were significantly increased in NVAMD patients compared to controls, suggesting that fatty acid metabolism may be involved in NVAMD pathophysiology. Cluster analysis suggested that clinically indistinguishable NVAMD patients can be separated into distinct subgroups based on metabolic profiles.

Copyright information:

© 2018 The Authors.

This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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