Background In recent years there has been increasing interest in biomarkers in axial spondyloarthritis, for diagnosis, disease prognostication, and to monitor treatment effect.^{1 2} Many biomarkers have been evaluated, but the role each of these plays and how they may interact is unclear.

Objectives Our aim was to evaluate a broad panel of serum biomarkers in a large mixed cohort of patients, with Ankylosing Spondylitis (AS), non radiographic axial Spondyloarthritis (nr-axSpA), mechanical back pain (MBP) and healthy controls (HC), in order to identify any potential biomarkers for diagnosis by assessing the differences between the groups.

Methods Cross sectional evaluation of 46 serum biomarkers was undertaken by Myriad RBM using multiplexed immunoassays of Multi-Analyte Panels, in a cohort of patients from a tertiary referral centre, consented as part of the Bath Spondyloarthritis BioBank. Validated patient reported outcomes (including BASDAI, BASFI) and BASMI were completed. 50 HC blood samples were also collected at University College London for biomarker analysis.

Results 331 patients were included in the study, of which 59.5% AS, 8.2% nr-axSpA, 15.7% mechanical back pain, 15.1% HC. 64.7% were male, mean age 44.2 years (SD 16.6), mean disease duration in the AS group of 22.4 years (SD 13.6) with 84% HLA B27 positive.

IL1 alpha and beta, IL1 receptor antagonist, IL2, 3, 4, 5, 7, 10, 15, 17, IL12 subunit p70, factor VII, GMCSF, IFN gamma, MMP9, TNF beta were the only biomarkers not to show statistical differences across the diagnostic groups (table 1.). 12 biomarkers showed a statistical difference between genders (table 1, column 1, p value significance indicated with *<0.05, **<0.01 using Mann Whitney U, in addition to Factor VII*).

Conclusions Serum biomarkers have been shown to vary with gender and diagnosis. Further work is planned to evaluate their relationship to disease activity using outcome measures such as the BASDAI, and radiographic scoring, to better understand the role of each factor and combination of factors, and any causal link.

References [1] Maksymowych WP. An update on biomarker discovery and use in axial spondyloarthritis. Expert Rev Mol Diagn [Internet]. 2017Nov;217(11):965–74. [cited 2017 Dec 7]. Available from: https://www.tandfonline.com/doi/full/10.1080/14737159.2017.1381562

[2] Reveille JD. Biomarkers for diagnosis, monitoring of progression, and treatment responses in ankylosing spondylitis and axial spondyloarthritis. Clin Rheumatol [Internet]2015Jun 5;34(6):1009–18. [cited 2017 Jul 10]. Available from: http://link.springer.com/10.1007/s10067-015-2949-3

Acknowledgements This study was undertaken as part of an ongoing piece of work that is being funded by Celgene.

Disclosure of Interest None declared