May 1, 2014 - AUTOANTIBODY IN JUVENILE DERMATOMYOSITIS. REFLECTS DISEASE ACTIVITY: RESULTS OF A PILOT STUDY. Sarah L. Tansley1 ...
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Thursday 1 May 2014, 14.15–15.45
BSR and BHPR Oral Presentation of Abstracts
Thursday 1 May 2014, 14.15–15.45
BSR AND BHPR ORAL PRESENTATION OF ABSTRACTS 1
ORAL ABSTRACTS 10: CTD O55. PREVALENCE OF AUTOANTIBODIES TO HMGCR IN MYOSITIS PATIENTS Zoe E. Betteridge1, Hector Chinoy2, Meghna Jani2, Rachel Palmer1, Paul New3, Robert G. Cooper4 and Neil J. McHugh1 1 Pharmacoepidemiology Group, University of Bath, Bath, 2Centre for Musculoskeletal Research, University of Manchester, Manchester, 3 University of Manchester Rheumatic Diseases Centre, Salford Royal NHS Foundation Trust, Salford, 4MRC/ARUK Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK Background: Autoantibodies against 3-hydroxy-3-methylglutarylcoenzyme A reductase (HMGCR) have been shown to occur in necrotizing autoimmune myopathy patients and have a significant association with statin exposure. Here we report the presence of antiHMGCR autoantibodies in the UK myositis cohort (UKMyoNet). Methods: Plasma samples from 782 UK adult myositis patients (307 DM, 361 PM, 82 IBM) and 10 statin-induced myositis recruited to the UKMyoNet study were screened for known myositis specific or associated autoantibodies by radiolabelled immunoprecipitation (IPP) using K562-cell extracts. Additionally, samples were analysed for antiHMGCR autoantibodies by ELISA using recombinant HMGCR. Sera from 50 healthy controls were screened using identical methods. Clinical associations were determined and analysed using Fisher’s exact test. Results: IPP screening of the samples demonstrated myositis autoantibodies in 497 (63.6%) patients. ELISA screening found antiHMGCR autoantibodies in 48 patients (6.1%), 33 (4.2%) of which were IPP negative. Of the 15 samples that were positive by IPP and HMGCR ELISA, co-existing myositis autoantibodies included: PmScl, Jo-1, U1, RNA polymerase II, Ku, Ro60, La, Mi-2 and PL12. As reported in previous studies, anti-HMGCR autoantibodies were significantly associated with statin-induced myositis compared with other forms of myositis (33.3% (n ¼ 3) vs 5.8%, P ¼ 0.0191). However, antiHMGCR autoantibodies were also found in patients diagnosed with DM (n ¼ 8), DM-overlap (n ¼ 2), PM (n ¼ 27), PM-overlap (n ¼ 6) and undifferentiated myositis (n ¼ 2). They were not seen in any patient diagnosed with IBM or healthy controls. When anti-HMGCR positive patients were sub-divided into either strong (>10 S.D. above the mean of the healthy controls) or weak (3–10 S.D.) positive groups, there was no significant difference in statin exposure, gender or ethnicity between the two groups. However, patients with low anti-HMGCR autoantibody levels were more likely to have co-existing myositis autoantibodies (44.8% vs 11.1% P ¼ 0.0238) and cutaneous features of DM (37.0% vs 0.0%, P ¼ 0.0069) compared with patients with high anti-HMGCR autoantibody levels. Conclusion: We have confirmed the previously described frequency of anti-HMGCR autoantibodies and their strong association to statin exposure in our large cohort of UK adult myositis patients. Whilst this autoantibody was found to occur in statin-induced myositis patients, we also detected in it a number of patients diagnosed with PM and DM. Furthermore, we have also demonstrated that anti-HMGCR autoantibodies are not mutually exclusive from a range of other myositis autoantibodies. Since patients with lower levels of antiHMGCR are more likely to have either cutaneous features of DM, or co-existing autoantibodies, an autoantibody cut off level can be established that will help separate the statin-induced myositis phenotype from other myositis patients. Screening for anti-HMGCR autoantibodies above this cut-off will help diagnose patients with statin-induced myositis that have historically been mis-diagnosed as PM (or PM overlap). Disclosure statement: The authors have declared no conflicts of interest. O56. MICROARRAY TRANSCRIPTIONAL PROFILING OF LIMITED CUTANEOUS SYSTEMIC SCLEROSIS IDENTIFIES A VASCULAR GENE EXPRESSION SIGNATURE Emma Derrett-Smith1, Cecilia Chighizola2, Viktor Martyanov3, Pia Moinzadeh1, Tammara Wood3, Korsa Khan1, David Abraham1, Voon Ong1, Michael Whitfield1 and Christopher Denton1
Department of Inflammation, UCL Medical School, London, UK, Department of Rheumatology, University of Milan, Milan, Italy, Department of Genetics, Dartmouth Medical School, Hanover, NH, USA 2 3
Background: SSc is an uncommon autoimmune rheumatic disease with a high clinical burden that offers insight into fundamental processes of autoimmunity, vasculopathy and fibrosis. Analysis of gene expression profiling distinguishes scleroderma from normal skin, and can also detect different subsets of disease, with the potential to identify prognostic biomarkers of organ involvement or response to therapy. To complement published studies on the diffuse subset of SSc, we performed gene expression profiling in skin samples from patients with limited cutaneous SSc (lcSSc), expecting this to be more homogeneous than dcSSc and recognizing that gene expression signatures from clinically uninvolved skin have proven informative in earlier classification approaches. Methods: Total RNA was extracted from skin biopsies from 10 patients with SSc fulfilling the 2013 EULAR/ACR criteria and classified as lcSSc and 5 healthy controls. Gene expression profiling was performed on a DNA oligonucleotide microarray chip. Each sample was analysed in duplicate. Probes missing more than 20% of data were excluded. 3578 genes whose expression varied from median value by 2-fold in at least two experiments were identified and analysed by heuristic clustering, Wilcoxon test was used to select genes with a significant differential expression between lcSSc and control samples with correction for multiple testing. Consensus clustering and significance analysis of microarrays independently identified three common groups of genes. Results were validated by real time qualitative PCR in independent biological replicate samples. Results: All but one lcSSc samples clustered onto one branch in the resulting dendrogram. 469 probes with a false discovery rate of 0.1% were selected. We identified potential pathogenic mediators whose relevance in SSc pathogenesis has already been investigated including a vascular signature across lcSSc samples supporting prominent vascular involvement (Table 1), supported by pathways analysis and validated by gene expression by qPCR. In addition, we identified three common groups of genes by consensus clustering: normal-like; group 1 and group 2 of which normal-like and group 2 were well-defined and identified differentially expressed genes across these groups. Group 2 in particular identified potential pathogenic mediators of interest for future studies. Conclusion: Gene expression analysis of skin biopsies clearly differentiates lcSSc from healthy controls. Consistent with both clinical manifestations and previous scientific reports, we found a proangiogenic profile in lcSSc which will inform biomarker discovery and pathogenic mechanisms of SSc.
Disclosure statement: The authors have declared no conflicts of interest. O57. AUTOANTIBODY IN JUVENILE DERMATOMYOSITIS REFLECTS DISEASE ACTIVITY: RESULTS OF A PILOT STUDY Sarah L. Tansley1, Harsha Gunawardena2, Zoe E. Betteridge3, Katie Arnold4, Gavin Shaddick5, Lucy R. Wedderburn4 and Neil J. McHugh1 1 Department of Rheumatology, RNHRD, Bath, 2Department of Rheumatology, North Bristol NHS trust, Bristol, 3Department of
