Background Systemic sclerosis (SSc) is a complex multi-organ autoimmune disease that is caused by inflammation, vasculopathy and fibrosis. Clinical heterogeneity, unpredictable course, high mortality and resistance to treatment make physicians still frustrated. Recently, there are unmet needs of useful biomarkers for diagnosis, disease activity and severity of SSc. Metabolomics is expected to be a useful tool for the identification of biomarkers and new therapeutic targets. Several researchers have applied metabolomics to autoimmune diseases such as systemic lupus erythematosus, and rheumatoid arthritis. Objectives To identify the biomarker candidates for the diagnosis of SSc using metabolomic analysis. Methods Fifty-five patients (48 females (87%); mean age 59.30 ± 11.44 years; disease duration 6.92 ± 4.36 years; 11 diffuse cutaneous SSc, 44 limited cutaneous SSc) and thirty age, gender matched healthy controls (HCs) were enrolled. Serum samples after 8 h of fasting were stored at -80° and analysed using nuclear magnetic resonance (NMR)-based metabolomics. Results Multivariate analysis showed metabolic differences between SSc and HCs using partial least squares discrimination analysis (PLS-DA: R2Y=0.654, Q2=0.482) and orthogonal partial least squares discrimination analysis (OPLS-DA: R2Y=0.83, Q2=0.674) (Figure 1). We identified nine discriminatory metabolites (p<0.05): isopropanol, lactate, 2-oxoisocaproate, glucose, and formate were increased and pyruvate, glutamate, methylguanidine, and methanol were decreased in SSc compared with those in the HCs. Using these metabolites for diagnosis of SSc, sensitivity was 96.36% and specificity was 80% by Leave-one-out analysis. Conclusions There are considerable differences in the serum metabolomic characteristics between SSc and HCs. We expect that metabolomic analysis can be a useful tool for identification of potential diagnostic biomarkers of SSc. Disclosure of Interest None declared

Background Axial spondyloarthropathies (axSpA) are chronic inflammatory diseases affecting the sacroiliac joint, spine, peripheral joint, and entheses. Entheses are emphasized as one of the primary targets of axSpA, but they show little signal on conventional clinical magnetic resonance (MR). Recently, the ultrashort echo time (UTE) sequence has been reported to be useful in detecting a signal from the tissues with short T2 such as the ligaments, periosteum, and cortical bone. Contrast enhancement study of UTE sequence showed increased enhancement as a consequence of angiogenesis in a diseased tendon and fibrocartilage. To our knowledge, no prior study has compared the diagnostic performances of post-contrast 3D UTE and conventional post-contrast fat suppressed T1 weighted sequence (FST1WI) for sacroiliitis in patients with axSpA. Objectives To compare the diagnostic performance of post-contrast 3D UTE and conventional FS1WI for sacroiliitis. Methods Total 16 patients with axSpA (asSpA group: 10 men, 6 women, mean age: 35.56 years [range: 24–52 years], human leukocyte antigen B 27 positivity 81.25%,) and 10 patients with mechanical back pain (control group: 2 men, 8 women, mean age: 58.6 years [range 34–74 years]) were enrolled in this prospective study. All patients underwent oblique coronal short tau inversion recovery sequence (STIR), pre/post contrast fat suppressed (FS) 3D UTE, and post contrast FST1WI. Active inflammation of the sacroiliac joint was quantitatively analyzed and scored on post-contrast FS 3D UTE and post contrast FST1WI for inflammatory findings, such as osteitis, synovitis, capsulitis, and enthesitis, by two musculoskeletal radiologists with a consensus. The score per active inflammatory finding of 3D UTE and post contrast FST1WI was compared between axSpA group and control group using Wilcoxon rank test. Results The axSpA group showed higher scores for osteitis and synovitis on both post-contrast FS 3D UTE (P =0.018, 0.025, respectively) and post-contrast FST1WI (P =0.003, 0.005, respectively) and for enthesitis on post-contrast FS 3D UTE with a statistical significance (P =0.004). Post-contrast FS 3D UTE showed statistically significant lower scores for all inflammatory findings than enhanced FS T1 WI sequences did (P <0.05). Conclusions Post contrast 3D UTE can differentiate axSpA and mechanical back pain, especially when considering enthesitis. Although it showed slightly lower diagnostic performance for the active inflammatory finding than post contrast FST1WI did, post contrast 3D UTE might play a supplementary diagnostic role for early diagnosis of axSpA. Disclosure of Interest K. H. Jung: None declared, Y. J. Kim: None declared, W. Park: None declared, M. J. Lim: None declared, M. Carl Employee of: GE Healthcare, D. E. Kim Employee of: GE healthcare, M. Hwang Employee of: GE Healthcare, J. G. Cha: None declared, S. Kwon: None declared

Background Systemic sclerosis (SSc) is a complex multi-organ autoimmune disease with chronic and heterogeneous clinical manifestations. There is an unmet need for a new biomarker for early diagnosis and classification of SSc. Recent technical advancements have indicated several biomarkers for SSc; among these, platelet factor 4 (PF4), also known as CXCL4, was suggested by a large-cohort proteomic study 1. PF4 is a chemokine released from activated platelets and is involved in coagulation, inflammation, and angiogenesis, which are influential in SSc pathogenesis. Therefore, PF4 may be an effective biomarker for SSc. Objectives To investigate the efficacy of PF4 as a biomarker for the diagnosis, activity and severity of patients with SSc. Methods Thirty-nine SSc patients (36 female and 3 male; mean age, 58.8±10.42 years; mean disease duration, 7.15±3.92 years; 11 diffuse cutaneous SSc cases and 28 limited cutaneous SSc cases) and 30 healthy controls (HC; 25 female and 5 male; mean age, 46.43±14.43 years) were enrolled. To estimate the circulating PF4 level, levels of platelet poor plasma (PPP) PF4 as well as serum PF4 were measured using an ELISA kit (R&D, Minneapolis, USA). SSc patients were divided into 2 subgroups according to disease activity and based on the presence/absence of interstitial lung disease (ILD), pulmonary hypertension, digital ulcers, and autoantibodies (anti-centromere Ab and anti-Scl70 Ab). Differences between SSc and HC groups were compared by Student9s t-test, and the subgroups were compared using the Mann-Whitney test. Predictive values of serum PF4 and PPP PF4 for SSc diagnosis were evaluated by the area under the receiver operating characteristic curve (AUROC). Results Serum PF4 levels of SSc were lower than those of HC (SSc, 5143.3±1777.5 ng/mL; HC, 5927.4±1348.5 ng/mL; p =0.048) but no significant differences were observed PPP PF4 levels (SSc, 407.2±486.6 ng/mL; HC, 297.3±141.5 ng/mL; p =0.187) between SSc patients and controls. Moreover, no significant differences were observed between active and inactive SSc subgroups and between subgroups with/without ILD, pulmonary hypertension, digital ulcers, and autoantibodies. The AUROC for serum PF4 and PPP PF4 levels was 0.628 (0.497–0.76, cuff of value 3998.5 ng/mL) and 0.491 (0.367–0.65, cuff of value 511.1 ng/mL), respectively. Conclusions In Korean patients with SSc, both serum PF4 and PPP PF4 levels are not efficient biomarkers for SSc diagnosis and do not appear to be associated with clinical activity and severity. References van Roon JA, Tesselaar K, Radstake TR. Proteome-wide analysis and CXCL4 in systemic sclerosis. N Engl J Med. 2014;370(16):1563–4. Disclosure of Interest None declared