Localized and systemic proteome fingerprints of inflammation in juvenile arthritis

Introduction and aim Synovial fluid (SF) is a potential source of novel biomarkers for many arthritic disorders involving joint inflammation, including juvenile idiopathic arthritis (JIA)1 . We first compared the distinctive protein ‘fingerprints’ of local joint inflammation in SF with systemic profiles within matched plasma samples. Preliminary investigations were performed into whether local or systemic proteome expression patterns could distinguish between oligoarticular, extended oligoarticular and polyarticular forms of this chronic juvenile disease. Method In this study we analysed matched SF and plasma samples obtained from 10 newly diagnosed JIA patients (<6 months disease duration): 3 with oligoarticular arthritis, 3 extended oligoarticular and 4 polyarticular disease. Matched samples were taken at the initial inflammatory episode. We profiled the SF and plasma proteomes using a two-dimensional difference gel electrophoresis (DIGE) approach. Progenesis PG240 software analysis of plasma and SF gel scans was used to highlight joint-specific and plasma proteins differentially expressed across the study group. Protein spots of interest were identified by nanoelectrospray-ionisation with a ThermoFinnegan LCQ Deca ion trap-mass spectrometer. Results 2D DIGE reveals 799 spots per gel within the pH 4–7 range for synovial fluid and plasma. Comparison of plasma and synovial gel scans, revealed a subpopulation of 143 spots with at least twofold expression differences between the two body fluids. Hierarchical clustering based on the expression levels of a set of 54 proteins matched across the three clinical subgroups segregates the synovial fluid from the plasma samples. Proteolytic fragments of antiinflammatory proteins inter-alpha trypsin inhibitor, alpha-1 antitrypsin, transthyretin and apolipoprotein A-1 were differentially expressed amongst these samples. Conclusions Localized and systemic aspects of this disease can been differentiated, using proteomics. This method could allow us to identify biomarkers useful in the prediction of disease progression. This could enable earlier and more appropriate therapeutic intervention. Definition of protein profiles which discriminate clinical subgroups of arthritic disease may assist in the diagnosis of juvenile arthritis at an earlier stage than is currently possible.