@article {Howard Trippe000282, author = {Nadia Howard Tripp and Jessica Tarn and Andini Natasari and Colin Gillespie and Sheryl Mitchell and Katie L Hackett and Simon J Bowman and Elizabeth Price and Colin T Pease and Paul Emery and Peter Lanyon and John Hunter and Monica Gupta and Michele Bombardieri and Nurhan Sutcliffe and Costantino Pitzalis and John McLaren and Annie Cooper and Marian Regan and Ian Giles and David A Isenberg and Vadivelu Saravanan and David Coady and Bhaskar Dasgupta and Neil McHugh and Steven Young-Min and Robert Moots and Nagui Gendi and Mohammed Akil and Bridget Griffiths and Dennis W Lendrem and Wan-Fai Ng}, title = {Fatigue in primary Sj{\"o}gren{\textquoteright}s syndrome is associated with lower levels of proinflammatory cytokines}, volume = {2}, number = {2}, elocation-id = {e000282}, year = {2016}, doi = {10.1136/rmdopen-2016-000282}, publisher = {BMJ Specialist Journals}, abstract = {Objectives This article reports relationships between serum cytokine levels and patient-reported levels of fatigue, in the chronic immunological condition primary Sj{\"o}gren{\textquoteright}s syndrome (pSS).Methods Blood levels of 24 cytokines were measured in 159 patients with pSS from the United Kingdom Primary Sj{\"o}gren{\textquoteright}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{\textemdash}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){\textemdash}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.}, URL = {https://rmdopen.bmj.com/content/2/2/e000282}, eprint = {https://rmdopen.bmj.com/content/2/2/e000282.full.pdf}, journal = {RMD Open} }