Abstract
Objectives: TNF-alpha inhibitors are widely used in rheumatoid arthritis (RA) with varying success. Response to TNF-alpha inhibition may reflect the evolution of rheumatoid inflammation through fluctuating stages of TNF-alpha dependence. Our aim was to assess plasma concentrations of Th-17-related cytokines and the presence of circulating effector T-cells to identify predictors of response to TNF-alpha inhibitors.
Methods: Ninety-three people with RA were seen prior to and 4-6 months after commencing etanercept or adallmumab. Plasma concentrations of Th17-related cytokines, circulating effector T-cells, their production of relevant transcription factors and intracellular cytokines were measured at baseline. EULAR response criteria were used to define poor (Delta DAS28 <= 1.2 and/or DAS28 > 3.2) and good (Delta DAS28 > 1.2 and DAS28 <= 3.2) responders. Multivariate logistic regression was used to identify predictors of response.
Results: Participants with plasma IL-23 present at baseline were more likely to be poor responders [15/20 (75%) of IL-23(+) versus 36/73 (49.3%) of IL-23(-); p = 0.041]. While frequencies ofTh1,Th17, ex-Th17 and T-reg cell populations were similar between good and poor responders to anti-TNF therapy, IL-17A(+)IFN gamma(+) ex-Th17 cells were more prevalent in good responders (0.83% of ex-T(H)17 cells) compared to poor responders (0.24% of ex-Th17 cells), p = 0.023. Both plasma IL-23 cytokine status (OR = 0.17 (95% Cl 0.04-0.73)) and IL-17A(+)IFN gamma(+) ex-Th17 cell frequency (OR = 1.64 (95% Cl 1.06 to 2.54)) were independently associated with a good response to anti-TNF therapy. Receiver operator characteristic (ROC) analysis, including both parameters, demonstrated an area under the ROC curve (AUC) of 0.70 (95% Cl 0.60-0.82; p = 0.001).
Conclusions: Plasma IL-23 and circulating IL-17A(+)IFN gamma(+) ex-Th17 cells are independently associated with response to anti-TNF therapy. In combination, plasma IL-23 and circulating IL-17A(+)IFN gamma(+) ex-Th17 cells provide additive value to the prediction of response to anti-TNF therapy in RA.