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Fig. 3 | Arthritis Research & Therapy

Fig. 3

From: Mass spectrometry-based proteomics identify novel serum osteoarthritis biomarkers

Fig. 3

Sparse partial least squares discriminant analysis (sPLS-DA) contribution to component 1. Serum samples were from controls (n=8), osteoarthritis (OA)-obese (n=10) and OA-non obese n=10) and analyzed by sPLS-DA. A The dot plot component 1 vs. component 2 allowed for the identification of component 1 discriminating both the OA-obese (o [blue]) and OA-non obese (Δ [orange]) groups from controls (+ [gray]). B Contribution of the 9 proteins in component 1; the plots display the loading weight and indicate the class (OA-obese [blue]; OA-non obese,[orange]) for which the selected protein has a maximal mean value; the negative value indicates contributions higher in the OA compared to the control group. C Box plots of each protein comprised in component 1. The intensity values for each protein and each sample were obtained from the mass spectrometry analysis, and the mean of the intensity values was calculated for each protein and transformed as Log2. Statistical analysis used the Limma method, and q<0.050 was considered statistically different. OA-obese (OA-ob. [hatched left]), OA-non obese (OA-non ob. [hatched right], and control (CTL [white]). CRTAC1, cartilage acidic protein 1; GC, vitamin D binding protein; C1R, complement C1r subcomponent; Serpin F1, pigment epithelium-derived factor; PROS1, vitamin K-dependent protein S; SEPP1, selenoprotein P; C1QC, complement C1q subcomponent subunit C; ITIH4, inter-alpha-trypsin inhibitor heavy chain 4; APCS, serum amyloid P

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