FRI0280 A molecular network for fatigue in primary sjÖgren’s syndrome

• Published in: Annals of the rheumatic diseases Vol. 77; no. Suppl 2; p. 678
• Main Authors: Bårdsen, K., Brede, C., Kvivik, I., Kvaløy, J.T., Jonsdottir, K., Tjensvoll, A.B., Ruoff, P., Omdal, R.
• Format: Journal Article
• Language: English
• Published: London BMJ Publishing Group LTD 01.06.2018
• Subjects: Cancer; Cerebrospinal fluid; Enzyme-linked immunosorbent assay; Fatigue; Inflammatory diseases; Interleukin 1; Interleukin 1 receptor antagonist; Interleukin 1 receptors; Interleukin 6; Neurodegeneration; Neuropeptides; Orexins; Pain; S100b protein; Sickness behavior; Signal transduction; Sjogren's syndrome; Sleep and wakefulness
• ISSN: 0003-4967; 1468-2060
• DOI: 10.1136/annrheumdis-2018-eular.3656

BackgroundFatigue is a common phenomenon in primary Sjögren’s syndrome (pSS) and other chronic inflammatory diseases, cancer, and neurodegeneration. The underlying mechanisms for fatigue are not completely understood, but increasing evidence point to a biological basis for the phenomenon.ObjectivesFollowing the sickness behaviour hypothesis for fatigue, where pro-inflammatory cytokines and particularly interleukin 1β (IL-1β) related signalling are essential, we wished to investigate how molecules that influence IL-1β activity may influence fatigue through complex networks (IL-1β, IL-1Ra, IL-1RII, IL-6 and S100B). We also hypothesised that the neuropeptide hypocretin-1 (Hcrt1), a regulator of sleep and wakefulness, could be an element in a network for fatigue.MethodsIn cerebrospinal fluid (CSF) from 49 patients with pSS, Hcrt1 was measured by RIA and the other proteins by ELISA. Fatigue was rated using the fatigue visual analogue scale (fVAS), and results analysed by univariate-, multiple regression, and principal component analysis (PCA).ResultsIt was not possible to measure IL-1b due to very low concentrations in CSF. In simple univariate regression analysis with fatigue as a dependent variable a significant association was observed for depression (R2=0.20, p<0.01), and pain (R2=0.23, p<0.01) and the biochemical variable IL-1Ra (R2=0.09, p=0.04). In multiple regression with fVAS as dependent variable a model was obtained with depression, pain, and IL-1Ra as significant contributors (R2=0.37; p<0.001). In PCA two significant components were revealed (figure 1a). The first component (PC1) was dominated by variables related to IL-1β activity. The second component (PC2) showed a negative correlation between IL-6 and Hcrt1. fVAS was then introduced as an additional variable. In this new model fVAS correlated with the IL-1β related variables on PC1 and to a lesser degree with Hcrt1 on PC2 (figure 1b).Abstract FRI0280 – Figure 1a) PCA of biochemical variables only. b) PCA of biochemical variables including fatigue. Biplot illustrates scores of individuals and variables for PC1 and PC2. Individual’s scores are illustrated by dots. Arrows illustrate correlations of the variables to the components. Longer arrows mean higher correlation and arrows close to a component has higher contribution in generation of the component.ConclusionsThe main findings in this study indicate a functional network in which several IL-1β related molecules in CSF influence fatigue in addition to the clinical factors depression and pain. The neuropeptide Hcrt1 seem to participate in fatigue signalling, but probably not through the IL-1 pathway.Disclosure of InterestNone declared