The orthogonal least square-discriminative analysis (OPLS-DA) of metabolomic profiles of synovial fluids of Behcet’s disease (BD) with arthritis and seronegative arthritis (SNA).

<p>(A) The score plot of the OPLS-DA model for the BD with arthritis and SNA groups (t[<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135856#pone.0135856.ref001" target="_blank">1</a>], score of the non-orthogonal component; to[<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135856#pone.0135856.ref002" target="_blank">2</a>], score of the orthogonal component). The generated explained variation values, 0.45 of <i>R</i>^<i>2</i><i>X</i> and 0.91 of <i>R</i>^<i>2</i><i>Y</i>, and the predictive capability, 0.64 of <i>Q</i>^<i>2</i> indicated the excellence in modeling and prediction of the OPLS-DA model, respectively, with clear discrimination between BD with arthritis and SNA groups. (B) V-plot with p(corr) and VIP values of 123 different metabolites in OPLS-DA. The metabolites with p(corr) < 0 were those decreased in the BD with arthritis group while the metabolites with p(corr) > 0 were those increased in the BD with arthritis group. The metabolites with VIP > 1 were represented in Fig 1B.</p

Identification of 123 metabolites from synovial fluid samples of 24 patients with Behcet’s disease with arthritis and seronegative arthritis using BinBase.

<p>Identification of 123 metabolites from synovial fluid samples of 24 patients with Behcet’s disease with arthritis and seronegative arthritis using BinBase.</p

Receiver operating characteristic (ROC) curve of 3 combined biomarkers for distinguishing Behcet’s disease (BD) with arthritis from seronegative arthritis (SNA) groups.

<p>Glutamate, citramalate, and valine were selected and validated as putative biomarkers for BD with arthritis for distinguishing BD with arthritis from SNA groups by ROC curve analysis. The sensitivity and specificity were 100% and 61.1%, respectively, and the value of the area under curve (AUC) was 0.870.</p

The intensities of metabolites related to amino acid metabolism (A) and fatty acid metabolism (B).

<p>The intensities of metabolites related to amino acid metabolism (A) and fatty acid metabolism (B).</p

PCA score (A) and loading plots (B) of RA fibroblast-like synoviocytes (FLS), which were not stimulated (Control), stimulated with TNF-α (TNF), and treated with curcumin (Curcumin).

<p>(A) Principal component (PC)1 explained the significant separation of metabolite profiles between the TNF-α-stimulated group on the negative region of the PC1, and the control and curcumin-treated groups on the positive region of the PC1. Further, the control group was clearly separated from the curcumin-treated group on PC2. (B) PC1 was explained by 84 metabolites that correlated positively with the axis, and 35 metabolites that correlated negatively.</p

Hierarchical clustering analysis of 119 identified metabolites from RA FLS.

<p>The results of heat mapping generated through metabolomic analysis and the relevant changes discovered. A heat map showed that the metabolite profiles of controls were similar to those of the curcumin-treated group. Red color reflects an increase, and blue color a decrease.</p