PT - JOURNAL ARTICLE AU - Nadia Howard Tripp AU - Jessica Tarn AU - Andini Natasari AU - Colin Gillespie AU - Sheryl Mitchell AU - Katie L Hackett AU - Simon J Bowman AU - Elizabeth Price AU - Colin T Pease AU - Paul Emery AU - Peter Lanyon AU - John Hunter AU - Monica Gupta AU - Michele Bombardieri AU - Nurhan Sutcliffe AU - Costantino Pitzalis AU - John McLaren AU - Annie Cooper AU - Marian Regan AU - Ian Giles AU - David A Isenberg AU - Vadivelu Saravanan AU - David Coady AU - Bhaskar Dasgupta AU - Neil McHugh AU - Steven Young-Min AU - Robert Moots AU - Nagui Gendi AU - Mohammed Akil AU - Bridget Griffiths AU - Dennis W Lendrem AU - Wan-Fai Ng TI - Fatigue in primary Sjögren's syndrome is associated with lower levels of proinflammatory cytokines AID - 10.1136/rmdopen-2016-000282 DP - 2016 Jul 01 TA - RMD Open PG - e000282 VI - 2 IP - 2 4099 - http://rmdopen.bmj.com/content/2/2/e000282.short 4100 - http://rmdopen.bmj.com/content/2/2/e000282.full SO - RMD Open2016 Jul 01; 2 AB - Objectives This article reports relationships between serum cytokine levels and patient-reported levels of fatigue, in the chronic immunological condition primary Sjögren's syndrome (pSS).Methods Blood levels of 24 cytokines were measured in 159 patients with pSS from the United Kingdom Primary Sjögren's Syndrome Registry and 28 healthy non-fatigued controls. Differences between cytokines in cases and controls were evaluated using Wilcoxon test. Patient-reported scores for fatigue were evaluated, classified according to severity and compared with cytokine levels using analysis of variance. Logistic regression was used to determine the most important predictors of fatigue levels.Results 14 cytokines were significantly higher in patients with pSS (n=159) compared to non-fatigued healthy controls (n=28). While serum levels were elevated in patients with pSS compared to healthy controls, unexpectedly, the levels of 4 proinflammatory cytokines—interferon-γ-induced protein-10 (IP-10) (p=0.019), tumour necrosis factor-α (p=0.046), lymphotoxin-α (p=0.034) and interferon-γ (IFN-γ) (p=0.022)—were inversely related to patient-reported levels of fatigue. A regression model predicting fatigue levels in pSS based on cytokine levels, disease-specific and clinical parameters, as well as anxiety, pain and depression, revealed IP-10, IFN-γ (both inversely), pain and depression (both positively) as the most important predictors of fatigue. This model correctly predicts fatigue levels with reasonable (67%) accuracy.Conclusions Cytokines, pain and depression appear to be the most powerful predictors of fatigue in pSS. Our data challenge the notion that proinflammatory cytokines directly mediate fatigue in chronic immunological conditions. Instead, we hypothesise that mechanisms regulating inflammatory responses may be important.