Behcet's Disease with Active Uveitis: Detection of Serum Protein Biomarkers Using MALDI-TOF-MS

Authors

  • Xin Wang,

    1. Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
    2. Department of Abdominal Surgery, Cancer Institute and Hospital, Chinese Academy of Medical Sciences, Beijing, China
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    • X. Wang and M. F. Zhang authors contributed equally to this work.

  • Mei Fen Zhang,

    1. Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
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    • X. Wang and M. F. Zhang authors contributed equally to this work.

  • Jing Xie,

    1. Clinical Research Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
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  • Zhi Li Li,

    1. Department of Biophysics, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
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  • Peng Wang

    Corresponding author
    1. Clinical Research Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
    • Clinical Research Lab, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
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Errata

This article is corrected by:

  1. Errata: Erratum Volume 295, Issue 9, 1404, Article first published online: 30 July 2012

Abstract

Behcet's Disease (BD) is a multisystem autoimmune disorder that lacks sensitive and specific diagnostic methods. The aim of this study was to identify potential biomarkers specific for BD and to establish a diagnostic model. Serum samples from patients with BD, Vogt-Koyanagi-Harada syndrome (VKH), and healthy controls (HC) were randomly divided into a training set (49 BD, 31 VKH, and 48 HC) and a testing set (13 BD, 10 VKH, and 11 HC). Proteomic mass spectra were generated by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Thirty-nine differential m/z peaks associated with BD were identified, and the m/z peaks at 1,644, 1,711, 2,023, 4,347, 6,628, and 8,559 were used to construct a model for the diagnosis of BD. This diagnostic model can distinguish BD from non-BD controls with a sensitivity of 83.67% (41/49) and a specificity of 89.87% (71/79). BD was detected in our blinded testing set with good sensitivity and specificity of 84.6 and 90.48%, respectively. The results suggested that proteomic fingerprint technology combining magnetic beads with MALDI-TOF-MS has potential for the diagnosis of BD. The biomarker classification model was suitable for preliminary identification of BD and could potentially serve as a useful tool for BD diagnosis and differential diagnosis. Anat Rec, 2012. © 2012 Wiley Periodicals, Inc.

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