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Contains fulltext : 118482.pdf (Publisher’s version ) (Open Access) BACKGROUND: Treatment strategies blocking tumour necrosis factor (anti-TNF) have proven very successful in patients with rheumatoid arthritis (RA). However, a significant subset of patients does not respond for unknown reasons. Currently, there are no means of identifying these patients before treatment. This study was aimed at identifying genetic factors predicting anti-TNF treatment outcome in patients with RA using a genome-wide association approach. METHODS: We conducted a multistage, genome-wide association study with a primary analysis of 2 557 253 single-nucleotide polymorphisms (SNPs) in 882 patients with RA receiving anti-TNF therapy included through the Dutch Rheumatoid Arthritis Monitoring (DREAM) registry and the database of Apotheekzorg. Linear regression analysis of changes in the Disease Activity Score in 28 joints after 14 weeks of treatment was performed using an additive model. Markers with p

ObjectivesSystemic lupus erythematosus (SLE) is a chronic multisystem genetically complex autoimmune disease characterised by the production of autoantibodies to nuclear and cellular antigens, tissue inflammation and organ damage. Genome-wide association studies have shown that variants within the major histocompatibility complex (MHC) region on chromosome 6 confer the greatest genetic risk for SLE in European and Chinese populations. However, the causal variants remain elusive due to tight linkage disequilibrium across disease-associated MHC haplotypes, the highly polymorphic nature of many MHC genes and the heterogeneity of the SLE phenotype.MethodsA high-density case-control single nucleotide polymorphism (SNP) study of the MHC region was undertaken in SLE cohorts of Spanish and Filipino ancestry using a custom Illumina chip in order to fine-map association signals in these haplotypically diverse populations. In addition, comparative analyses were performed between these two datasets and a northern European UK SLE cohort. A total of 1433 cases and 1458 matched controls were examined.ResultsUsing this transancestral SNP mapping approach, novel independent loci were identified within the MHC region in UK, Spanish and Filipino patients with SLE with some evidence of interaction. These loci include HLA-DPB1, HLA-G and MSH5 which are independent of each other and HLA-DRB1 alleles. Furthermore, the established SLE-associated HLA-DRB1*15 signal was refined to an interval encompassing HLA-DRB1 and HLA-DQA1. Increased frequencies of MHC region risk alleles and haplotypes were found in the Filipino population compared with Europeans, suggesting that the greater disease burden in non-European SLE may be due in part to this phenomenon.ConclusionThese data highlight the usefulness of mapping disease susceptibility loci using a transancestral approach, particularly in a region as complex as the MHC, and offer a springboard for further fine-mapping, resequencing and transcriptomic analysis.

Idiopathic inflammatory myopathies (IIMs) may present as a primary autoimmune disorder, or overlap with other autoimmune/connective tissue diseases. The aetiology of IIM likely includes interactions between genetic and environmental factors. Several genetic variants common to multiple autoimmune disorders have been identified in recent genome-wide association studies (GWAS). A Myositis Genetics Consortium dermatomyositis (DM) GWAS also suggests genetic overlap with other autoimmune disorders.1 We sought to extend these findings to identify novel genetic risk factors in a large cohort of adult/juvenile patients with DM and polymyositis (PM), by genotyping immune-related single nucleotide polymorphisms (SNPs) not captured through the DM GWAS.1 SNPs significantly associated (p

Background Idiopathic inflammatory myopathies (IIM) may present as a primary disorder, or may overlap with connective tissue diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE) or systemic sclerosis. The aetiology of IIM is largely unknown, but is thought to include a combination of genetic and environmental factors. To generate ethnically homogeneous IIM cohorts of sufficient size given its rarity, one of the largest European IIM initiatives has enabled Europe wide ascertainment of cases with EUMYONET. Numerous genome-wide association studies (GWAS) have identified many genetic variants associated with autoimmune disorders, several common to multiple disorders. This is supported by our recent dermatomyositis (DM) GWAS, suggesting genetic overlap with other autoimmune disorders1. Objectives We sought to identify additional novel genetic risk factors in adult and juvenile polymyositis (PM) and DM (not previously identified by DM GWAS), shared with other autoimmune disorders. Methods SNPs significantly associated with SLE, RA, juvenile idiopathic arthritis, coeliac disease, Crohn's disease, ulcerative colitis, psoriasis, type 1 diabetes, multiple sclerosis or systemic sclerosis were identified from published Caucasian GWAS and from the national human genome research institute catalogue of published GWAS. 233 unique SNPs were identified ( p 5% missing genotype data were excluded, resulting in 1149 cases and 3572 controls. Outside the MHC region, a non-synonymous SNP rs2304256 in the TYK2 gene was identified reaching Bonferroni-corrected significance in IIM and DM (β= -0.21, p value=0.00027; β= -0.25, p value=0.00020 respectively). Two further SNPs within the BLK gene and 2335bp 5' of BLK were associated with DM (rs2618476, β=0.24, p value=0.00062; rs13277113, β=0.25 p value=0.00045 respectively) but not with PM, supporting the results of our DM GWAS. Conclusions We have identified TYK2 as a novel association for DM, suggesting genetic overlap of DM with other autoimmune disorders, and indicating genetic heterogeneity between PM and DM. TYK2 has been associated previously with SLE, type 1 diabetes and multiple sclerosis. Further associations of the BLK gene with DM, suggests a role of B cells in its development. References 1. Miller FW et al. Arthritis Rheum. 2013 Dec; 65(12):3239-3247 Acknowledgements Funding: Arthritis Research UK (grants 18474; 14518), Intramural Research Program of the NIH, Wellcome Trust (076113; 085860). We thank all other members of the EUMYONET and Myositis Genetics Consortium (MYOGEN). Disclosure of Interest None declared DOI 10.1136/annrheumdis-2014-eular.2877

Background The use of whole blood gene expression to predict and follow the response to TNF inhibition therapy in RA has been challenging due to the complex nature of the data. Objectives Here we employ an approach to gene expression analysis that is based on gene expression “modules” previously reported by Chaussabel, et al. (1) Methods Whole blood RNA (PAXgene) was obtained at baseline and 12 weeks on two cohorts of rheumatoid arthritis patients beginning anti-TNF therapy. The initial cohort was enrolled by the Autoimmune Biomarkers Collaborative Network (ABCoN) and contains 50 subjects stratified by EULAR Good Responders (N=14), Moderate Responders (N=21) and Non Responders (N=15) at 12 weeks after starting therapy. Results Good and Moderate Responders exhibited highly significant changes in multiple modules using a hypergeometric analysis. These included dramatic decreases in modules related to the myeloid lineage and inflammation, along with increases in B cell and plasma cell modules as well as in a number of modules related to the MHC and ribosomal proteins and other “undefined” module groups. Strikingly, Non Responders exhibited very little change in any modules. We have replicated these data in patients enrolled in a clinical trial of Simponi®, with full expression data available on 29 Good Responders, and 37 Moderate Responders. We observed nearly identical modular changes to those identified in the ABCoN Responders after 14 weeks of treatment. Only 6 Non Responders were available for study in this dataset, making convincing replication difficult for this subgroup. Several other replication datasets are currently being analyzed. Conclusions These data suggest that using gene expression modules related to inflammatory disease may provide a valuable method of characterizing the responder status of RA patients treated with TNF inhibitors. References Chaussabel D, Quinn C, Shen J, Patel P, Glaser C, Baldwin N, Stichweh D, Blankenship D, Li L, Munagala I, Bennett L, Allantaz F, Mejias A, Ardura M, Kaizer E, Monnet L, Allman W, Randall H, Johnson D, Lanier A, Punaro M, Wittkowski KM, White P, Fay J, Klintmalm G, Ramilo O, Palucka AK, Banchereau J, Pascual V. A modular analysis framework for blood genomics studies: application to systemic lupus erythematosus. Immunity. 2008 Jul 18;29(1):150-64. doi: 10.1016/j.immuni.2008.05.012. Disclosure of Interest M. Curran Employee of: Janssen Research & Development, LLC., M. Oswald Grant/research support: Janssen Research & Development, LLC., A. Lee Grant/research support: Janssen Research & Development, LLC., Y. Cherkas Employee of: Janssen Research & Development, LLC., C. Brodmerkel Employee of: Janssen Research & Development, LLC., S. Lamberth Employee of: Janssen Research & Development, LLC., P. Gregersen Grant/research support: Janssen Research & Development, LLC. DOI 10.1136/annrheumdis-2014-eular.3724