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

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.

Biomarkers in Vasculitides of the Nervous System

“…The fact that not only blood but also other body fluids can contribute to the development of new biomarkers was underlined by Ahn et al, who distinguished BD patients from healthy individuals by employing a group of 10 urine derived metabolites, i.e., guanine, pyrrole-2-carboxylate, 3-hydroxypyridine, mannose, l-citrulline, galactonate, isothreonate, sedoheptulose, hypoxanthine, and gluconic acid lactone (155). Similarly, a panel of five metabolic markers derived from serum, i.e., decanoic acid, fructose, tagatose, linoleic acid, and oleic acid, were found to be potential biomarkers of BD with a sensitivity of 100% and a specificity of 97.1% (156).…”

Serum Metabolomic Profiling of Patients with Non-Infectious Uveitis

“…Thus, we tried to explore novel biomarkers showing discrimination ability among these three diseases. Although several previous studies analysed serum metabolites, all these studies compared patients having a particular disease with HCs [18][19][20]. To our knowledge, this study represents the first time the three diseases are compared.…”

“…Conversely, blood is one of the biofluids that can easily be sampled, enabling frequent testing. Previously, gas chromatography-mass spectrometry with a PLS-DA has been used to discriminate BD patients from healthy controls (HCs) [18]. NMR with principal component analysis (PCA) has been used to analyse serum samples to discriminate sarcoidosis patients from HCs [19].…”

Application of GC/MS-Based Metabonomic Profiling in Studying the Therapeutic Effects of Aconitum carmichaeli with Ampelopsis japonica Extract on Collagen-Induced Arthritis in Rats

“…Partial least squares discriminant analysis (PLS-DA) is used to select the differential metabolites from two groups (VIP >1) combined with p -value < 0.05 ( t test). Cross-validation can detect if the model established by the pattern recognition method is over-fitting [48,49,50]. The SVM method could diagnose the sample classification ability of pattern recognition methods and provide a quantitative assessment of the classification ability.…”