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Int. J. Mol. Sci. 2017, 18(11), 2309; https://doi.org/10.3390/ijms18112309

Urinary Metabolomic Profiling to Identify Potential Biomarkers for the Diagnosis of Behcet’s Disease by Gas Chromatography/Time-of-Flight−Mass Spectrometry

1
Division of Rheumatology, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul 03181, Korea
2
Department of Biotechnology, Graduate School, Korea University, Seoul 02841, Korea
3
Department of Internal Medicine, National Police Hospital, Seoul 05715, Korea
4
Division of Rheumatology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
These authors contributed equally to this work.
*
Authors to whom correspondence should be addressed.
Received: 22 September 2017 / Revised: 22 October 2017 / Accepted: 31 October 2017 / Published: 2 November 2017
(This article belongs to the Special Issue Rare Diseases: Molecular Mechanisms and Therapeutic Strategies)
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Abstract

Diagnosing Behcet’s disease (BD) is challenging because of the lack of a diagnostic biomarker. The purposes of this study were to investigate distinctive metabolic changes in urine samples of BD patients and to identify urinary metabolic biomarkers for diagnosis of BD using gas chromatography/time-of-flight–mass spectrometry (GC/TOF−MS). Metabolomic profiling of urine samples from 44 BD patients and 41 healthy controls (HC) were assessed using GC/TOF−MS, in conjunction with multivariate statistical analysis. A total of 110 urinary metabolites were identified. The urine metabolite profiles obtained from GC/TOF−MS analysis could distinguish BD patients from the HC group in the discovery set. The parameter values of the orthogonal partial least squared-discrimination analysis (OPLS-DA) model were R2X of 0.231, R2Y of 0.804, and Q2 of 0.598. A biomarker panel composed of guanine, pyrrole-2-carboxylate, 3-hydroxypyridine, mannose, l-citrulline, galactonate, isothreonate, sedoheptuloses, hypoxanthine, and gluconic acid lactone were selected and adequately validated as putative biomarkers of BD (sensitivity 96.7%, specificity 93.3%, area under the curve 0.974). OPLS-DA showed clear discrimination of BD and HC groups by a biomarker panel of ten metabolites in the independent set (accuracy 88%). We demonstrated characteristic urinary metabolic profiles and potential urinary metabolite biomarkers that have clinical value in the diagnosis of BD using GC/TOF−MS. View Full-Text
Keywords: Behcet’s disease; diagnosis; metabolomics; gas chromatography-mass spectrometry; biomarker; urine Behcet’s disease; diagnosis; metabolomics; gas chromatography-mass spectrometry; biomarker; urine
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Ahn, J.K.; Kim, J.; Hwang, J.; Song, J.; Kim, K.H.; Cha, H.-S. Urinary Metabolomic Profiling to Identify Potential Biomarkers for the Diagnosis of Behcet’s Disease by Gas Chromatography/Time-of-Flight−Mass Spectrometry. Int. J. Mol. Sci. 2017, 18, 2309.

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