One group of interest would be those with two T cell abnormalities and a high specificity (but low sensitivity) for progression. 0.63 and 0.66), although the presence of 2 T cell abnormalities had high specificity. Three models were compared: model-1 used T cell subsets only, model-2 used previously published medical guidelines, model-3 combined medical data and T cell data. Model-3 performed the best (AUC 0.79 (95% CI 0.70 to 0.89)) compared with magic size-1 (0.75 (0.65 to 0.86)) and particularly with magic size-2 (0.62 (0.54 to 0.76)) demonstrating the added value of T cell subsets. Time to progression differed significantly between high-risk, moderate-risk and low-risk organizations from model-3 (p=0.001, median 15.4 months, 25.8 months and 63.4?weeks, respectively). Conclusions T cell subset dysregulation in ACPA+ individuals predates the onset of IA, predicts the risk and faster progression to Rabbit Polyclonal to APOBEC4 IA, with added value over previously published medical predictors of progression. Keywords: Arthritis, Synovitis, T Cells Intro Ko-143 Over recent years our understanding of the immune pathways and relationships involved in the pathogenesis of rheumatoid arthritis (RA) has developed substantially. This has experienced a notable impact on drug development targeting specific pathways. Early RA medical trials possess aided the translation of findings and resulted in a vast body of evidence supporting early analysis and immediate treatment to improve outcomes of individuals with RA.1C4 However despite early treatment at RA analysis, a proportion of individuals fails conventional therapy and continues with immune dysregulation and active inflammation.5C7 This has led investigators to focus on identifying disease at its earliest stage.8 By identifying individuals at a higher risk of future RA, it is hoped that outcomes can be improved. Several groups including our own have Ko-143 reported on cohorts at high risk to RA.9C15 The most notable of these are individuals with RA-associated anticitrullinated protein antibody (ACPA) autoantibodies and musculoskeletal pain. However, autoantibodies alone are not sufficient to forecast progression to inflammatory arthritis (IA) with only 50% overall progression over 4?years.14 In recent years there has been increased desire for the recognition of biomarkers that assist the prediction of disease onset in such cohorts.16C26 The ability to risk stratify individuals is an attractive option particularly in light of current strategies concerning personalised medicine. By identifying those at very best risk, the use of immunomodulating therapies could be targeted to prevent progression to disease. In RA, T cell subset quantification provides an insight into the immune status of the patient.27 Although regulatory T cells (Treg) have been the Ko-143 focus of many studies including our own, we have demonstrated that CD4+ T cells are an important T cell biomarker.7 28,C32 Inflammation causes the cells to differentiate into additional subsets driven by proinflammatory cytokines such as interleukin Ko-143 (IL) 6 and tumour necrosis factor Ko-143 (TNF) with the appearance of a novel T cell subset called inflammation related cells (IRCs).29 To date, we have demonstrated the role of T cell subset analysis in predicting relapse in DMARD-induced remission,7 the safe discontinuation of TNF blockers31 and, more recently, methotrexate-induced remission in early RA.32 We hypothesised that in ACPA+ individuals with nonspecific symptoms, those with the greatest T cell subset dysregulation (as determined using na?ve CD4+ T cells, IRC and Treg quantification) would have a greater propensity for progression to arthritis. The aim of this study was to statement on the degree of T cell subset dysregulation in ACPA+ individuals and to determine the potential of T cell subset analysis like a biomarker of long term progression to medical arthritis. The confounding effect of medical parameters previously shown to be predictive inside a medical model14 was also investigated. Methods Individuals As previously explained,14 individuals with ACPA+ and non-specific.
