Nisha Nair

Differential Methylation as a Biomarker of Response to Etanercept in Patients With Rheumatoid Arthritis

Biologic drug therapies represent a huge advance in the treatment of rheumatoid arthritis (RA). However, very good disease control is achieved in only 30% of patients, making identification of biomarkers of response a research priority. We undertook this study to test our hypothesis that differential DNA methylation patterns may provide biomarkers predictive of response to tumor necrosis factor inhibitor (TNFi) therapy in patients with RA.

CD4+ and B lymphocyte expression quantitative traits at rheumatoid arthritis risk loci in untreated early arthritis: implications for causal gene identification

Rheumatoid arthritis (RA) is a genetically complex disease of immune dysregulation. This study sought to gain further insight into the genetic risk mechanisms of RA by conducting an expression quantitative trait locus (eQTL) analysis of confirmed genetic risk loci in CD4+ T cells and B cells from carefully phenotyped patients with early arthritis who were naive to therapeutic immunomodulation.

DNA methylation as a marker of response in rheumatoid arthritis

Rheumatoid arthritis (RA) is a complex disease affecting approximately 0.5-1% of the population. While there are effective biologic therapies, in up to 40% of patients, disease activity remains inadequately controlled. Therefore, identifying factors that predict, prior to the initiation of therapy, which patients are likely to respond best to which treatment is a research priority and DNA methylation is increasingly being explored as a potential theranostic biomarker. DNA methylation is thought to play a role in RA disease pathogenesis and in mediating the relationship between genetic variants and patient outcomes. The role of DNA methylation has been most extensively explored in cancer medicine, where it has been shown to be predictive of treatment response. Studies in RA, however, are in their infancy and, while showing promise, further investigation in well-powered studies is warranted.

05.10 Comparison of cd4+ and b lymphocyte expression quantitative trait associations at ra risk loci in untreated early arthritis patients

Background Rheumatoid arthritis (RA) is a genetically complex disease of immune dysregulation. Genome-wide association scans (GWAS) have shown common variants at approximately 100 genetic loci to be associated with RA. Single nucleotide polymorphisms (SNPs) are typically intergenic and causative disease genes remain ill-defined. Examining how RA-associated SNPs influence gene expression in relevant biological contexts will begin to address this. Methods Patients naïve to immunomodulatory therapy attending the Newcastle Early Arthritis Clinic donated RNA and DNA, extracted from purified peripheral blood CD4+ T- and B-lymphocytes within 4 hours of blood draw. Detailed baseline and longitudinal clinical data were recorded for all participants, each followed up for >1 year. Genotyping and global gene expression measurement was carried out using the Illumina Human CoreExome array, and either HT12v4 or WG6v3 BeadChip arrays, respectively, and expression data was batch-corrected and normalised using standard algorithms. Data from both cell types were analysed using the R package. Variants in linkage disequilibrium (LD) with 100 confirmed RA- SNPs (r2 >0.8) were included in analyses, seeking evidence of cis- and trans- eQTLs according to whether associated probes were or were not within 4 MB of these LD blocks. Results Cell-type specific gene expression data from 351 genotyped white Caucasian early arthritis patients were available for analysis (including paired CD4+/B lymphocyte data for 160 of these). Genes subject to cis eQTL effects common to both CD4+ and B-lymphocytes at RA risk loci included FADS1, FCRL3, PIPL3, ORMDL3 and GSDMB. Cis eQTLs acting on BLK, IKZF3 and PADI4 were, by contrast, unique to CD4+ lymphocytes in this population, and equivalent B-lymphocyte-specific effects were seen for IRF5 and FAM167. Evidence emerged that the 12q13 RA risk variant regulates STX1B gene expression on chromosome 7 of B-lymphocytes, but no trans eQTLs achieved experiment-wide significance thresholds in CD4+ lymphocytes. Linear modelling could not identify a significant influence of biological co-variates (diagnosis, systemic inflammation, age) upon eQTL effect sizes. Conclusions We present the first detailed eQTL analysis in the pathophysiologically relevant setting of early arthritis lymphocytes, free of confounding immunomodulatory treatment. The findings should help refine understanding of candidate causal genes in RA pathogenesis.

THU0003 CD4+ and B lymphocyte expression quantitative traits at rheumatoid arthritis risk loci in untreated early arthritis: implications for causal gene identification?

Background Rheumatoid arthritis (RA) is a genetically complex disease of immune dysregulation. Genome-wide association scans (GWAS) have confirmed its association with variants at >100 genetic loci. Outside of the HLA region, accumulating data now highlight an overlap between these risk loci and cell-specific enhancer elements that is maximal in CD4+ lymphocytes, followed by B lymphocytes Objectives Seeking insight into genetic risk mechanisms, we conducted and compared expression quantitative trait locus (eQTL) analyses of risk loci in CD4+ T cells and B cells from carefully phenotyped early arthritis patients naïve to therapeutic immunomodulation. Methods 254 patients donated RNA and DNA from purified B and/or CD4+ T-cells within 4 hours of blood draw. Genotyping and global gene expression measurement were carried out using the Illumina Human CoreExome array and either HT12v4 or WG6v3 BeadChip arrays respectively. Variants in linkage disequilibrium (LD) with 101 confirmed non-HLA RA- SNPs (r2>0.8) were analysed, seeking evidence of cis- or trans- eQTLs according to whether associated probes were or were not within 4MB of these LD blocks. Results Genes subject to cis eQTL effects common to both CD4+ and B-lymphocytes at RA risk loci were FADS1, FADS2, BLK, FCRL3, ORMDL3 and GSDMB. At the 8p23 BLK-FAM167A locus, we found adjacent genes subject to eQTLs whose activity differed markedly between cell types, the FAM167A effect displaying striking B-lymphocyte specificity. By contrast, cis eQTLs acting on METTL21B, IKZF3, and PADI4 were unique to CD4+ lymphocytes, the latter two of these being identified for the first time in this cell subset. No trans eQTLs approached experiment-wide significance, and linear modelling did not identify a significant influence of biological co-variates (diagnosis, systemic inflammation, age) upon eQTL effect sizes. Conclusions Our findings refine understanding of candidate causal genes in RA pathogenesis, providing an important platform from which downstream functional studies may be prioritised and directed towards particular cell types. References Okada Y, Wu D, Trynka G, Raj T, Terao C, Ikari K, et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature. 2014 Feb 20; 506(7488):376–381. Acknowledgements Wellcome Trust, Academy of Medical Sciences, JGW Patterson Foundation, National Institute of Health Research, Pfizer. Newcastle researchers received infrastructural support via the Arthritis Research UK Centre of Excellence for the RA pathogenesis (RACE). JM and NN are funded by an MRC/Arthritis Research UK stratified medicine award (MR/K015346/1). Disclosure of Interest N. Thalayasingam: None declared, J. Massey: None declared, A. Anderson: None declared, N. Nair: None declared, A. Skelton: None declared, D. Lendrem: None declared, L. Reynard: None declared, H. Cordell: None declared, S. Eyre: None declared, A. Barton: None declared, J. Isaacs: None declared, A. Pratt Grant/research support from: Pfizer

02.32 Exploring the role of bcl-3 in cd4+t cells

Background Rheumatoid arthritis (RA) is a disease of immune dysregulation whose pathogenesis remains incompletely understood. We previously identified an IL-6 mediated, STAT3 target gene-enriched ‘signature’ in circulating CD4+ T cells of untreated arthritis patients that predicted progression to RA. BCL-3 was the most differentially expressed of these genes between RA patients and disease controls1. This atypical IκB molecular product appears to be important in murine T-cell biology. In this project we aim to explore the function of BCL-3 in human primary CD4+ T cells, and its potential relevance to RA pathogenesis. Materials and methods Highly purified CD4+ T-cells were isolated from human peripheral blood using magnetic beads. Phospho-STAT3 (pSTAT3) and paired BCL-3 gene expression were measured in cells from 161 untreated arthritis patients using flow cytometry and microarray technology, respectively. To study BCL-3 kinetics, CD4+ T-cells isolated from healthy volunteers were stimulated with cytokines or TCR ligands; gene and protein expression were analysed by Taqman Real-Time PCR and Western Blotting respectively. To overexpress BCL-3 two methods were compared: use of our previously developed murine mimetic peptide, and lentiviral transduction. The phenotype of CD4+ T-cells by means of proliferation, activation and intracellular cytokines were assessed by CFSE labelling, surface and intracellular flow cytometry respectively. Results Intracellular pSTAT3 correlates strongly with paired BCL-3 gene expression in circulating CD4+ T-cells of early arthritis patients. In vitro kinetics experiments show its expression is induced by IL-6, but becomes maximal after TCR stimulation for 72 hours; protein peaks later at 5 days. A limited effect of the mimetic peptide on cultured CD4+ T-cell phenotype likely reflects incomplete homology of murine and human peptides. Transduction of CD4+ T-cells with rLV-hBCL3-IRES-ZsGreen1 lentivirus results in 6-fold upregulation of BCL-3 gene expression that remains detectable 6 days post transduction. Conclusions Enhanced STAT3 signalling accounts for increased BCL-3 expression in circulating CD4+ T cells of early RA patients, and the kinetics of IL-6- and CD3/28-mediated BCL-3 induction in these cells have been defined, Having optimised a robust means of over-expressing BCL-3 by lentiviral transduction of primary human CD4+ T cells, its specific functional role will now be explored.

OP0235 Identification of Novel Cd4+ Lymphocyte Expression Quantitative Trait Loci in Untreated Early Arthritis Patients

Background Rheumatoid arthritis (RA) is a CD4+ lymphocyte-mediated disease of immune dysregulation. Genome-wide association scans (GWAS) have shown common variants at approximately 100 genetic loci to be associated with RA. However, the associated single nucleotide polymorphisms (SNPs) often lie in intergenic regions and the gene upon which they act has not been defined. Examining how RA-associated SNPs influence gene expression in relevant biological contexts will begin to address this. Objectives To map cis eQTLs at established RA risk loci in CD4+ lymphocytes of a well-characterised early arthritis cohort, and so gain insight into mechanisms of genetic risk. Methods Patients attending the Newcastle Early Arthritis Clinic, naïve to immunomodulatory therapy, donated high integrity RNA and DNA extracted from 98% pure CD4+ lymphocytes within 4 hours of blood draw. Detailed baseline and longitudinal clinical data were recorded for all participants, who were followed up for ≥1 year. Genotyping and global gene expression measurement was carried out using the Illumina Human CoreExome array, and either HT12v4 or WG6v3 BeadChip arrays, respectively, and expression data was batch-corrected and normalised using standard algorithms. Data were analysed using the R package. Variants in linkage disequilibrium (LD) with >100 confirmed RA- SNPs1 (r2>0.8), and probes within 4MB of these LD blocks, were included in the analysis, seeking evidence of cis-eQTLs. Results Data from 249 white Caucasian early arthritis patients were available for analysis; diagnoses (confirmed at follow-up) were RA (n=88), spondyloarthropathy/other inflammatory arthritis (n=86), osteoarthritis/other non-inflammatory arthralgia (n=70) and undifferentiated arthritis. Analysis of 1,247 SNPs and 8,023 probes identified strong evidence for cis-eQTLs at a number of RA risk loci in this population overall (experiment-wide p<0.05). Previously observed genes subject to eQTLs in primary human CD4+ lymphocytes replicated by our study include BLK, FADS1 and FADS2. Genes whose expression specifically in these cells has, to our knowledge, been associated with RA risk variants for the first time include RPS26, RNF167 and IKZF3. Conclusions We present the first detailed eQTL analysis in the pathophysiologically relevant setting of early arthritis CD4+ lymphocytes, free of confounding immunomodulatory treatment. Interactions of clinical parameters (including disease phenotype) with eQTL effects remains the subject of ongoing analyses, to be presented. Our findings have the potential to modify the biological candidate gene landscape of RA. References Okada Y et al. 2014 Nature. 506(7488):376–81 Disclosure of Interest None declared

Identification of novel expression quantitative trait loci in CD4+ T cells of untreated early arthritis patients

Background Rheumatoid arthritis (RA) is a CD4+ T-cell-mediated disease of immune dysregulation. Genome-wide association scans (GWAS) have shown common variants at approximately 100 genetic loci to be associated with RA. In many cases, however, the associated single nucleotide polymorphisms (SNPs) lie in intergenic regions and the gene upon which they act has not yet been defined. Examining how RA-associated SNPs influence gene expression in relevant biological contexts will begin to address this. Methods Patients attending the Newcastle Early Arthritis Clinic, naïve to immunomodulatory therapy, donated high integrity RNA and DNA extracted from 98% pure CD4+ T cells within 4 h of blood draw. Detailed baseline and longitudinal clinical data were recorded for all participants, who were followed up for ≥1 year. Genotyping and global gene expression measurement was carried out using the Illumina Human CoreExome array, and either HT12v4 or WG6v3 BeadChip arrays, respectively, and expression data was batch-corrected and normalised using standard algorithms. Data were analysed using the R package. Variants in linkage disequilibrium (LD) with 100 confirmed RA- SNPs (r2 >0.8), and probes within 4MB of these LD blocks, were included in the analysis, seeking evidence of cis-eQTLs. Results Data from 249 white Caucasian early arthritis patients were available for analysis; diagnoses (confirmed at follow-up) were RA (n = 88), spondyloarthropathy/other inflammatory arthritis (n = 86), osteoarthritis/other non-inflammatory arthralgia (n = 70) and undifferentiated arthritis. Analysis of 1,247 SNPs and 8,023 probes identified strong evidence for cis-eQTLs at a number of RA risk loci in this population overall (experiment-wide p < 0.05). Previously observed genes subject to eQTLs in primary human CD4+ T cells replicated by our study include BLK, FADS1 and FADS2. Genes whose expression specifically in these cells has, to our knowledge, been associated with RA risk variants for the first time include RPS26, RNF67 and IKZF3. Conclusions We present the first detailed eQTL analysis in the pathophysiologically relevant setting of early arthritis CD4+ T cells, free of confounding immunomodulatory treatment. Interactions of clinical parameters (including disease phenotype) with eQTL effects remains the subject of ongoing analyses, to be presented. Our findings have the potential to modify the biological candidate gene landscape of RA.

SAT0009 Investigation of Differential Methylation as A Potential Biomarker of Methotrexate Response in Patients with Rheumatoid Arthritis

Background Methotrexate (MTX) is the first-line disease modifying anti-rheumatic drug (DMARD) for the treatment of rheumatoid arthritis (RA). By two years of treatment only 55% of patients remain on the drug, implying that many do not respond adequately or experience adverse effects (1,2). Therefore, identifying blood-based biomarkers that predict treatment response is an important research priority. DNA methylation is an epigenetic marker that modifies but does not alter DNA sequence, and should be considered for evaluation as potential biomarkers for treatment response. The mechanisms of action of MTX are unclear. However, it is thought that MTX promotes adenosine release and interferes with the intracellular methyl donor status leading to DNA hypomethylation (3). Objectives To identify differential DNA methylation signatures in whole blood, which may act as biomarkers predictive of response to MTX in patients with RA. Methods Epigenome-wide DNA methylation levels were measured using the HumanMethylation450 BeadChip (Illumina) in whole blood-derived DNA samples from individuals recruited to the Rheumatoid Arthritis Medication Study (RAMS), a one year observational study including patients with RA starting MTX for the first time, who had EULAR good response (n=36) or EULAR poor response (n=36) to MTX. DNA was taken from blood samples pre-treatment and following four weeks on therapy. Response was determined at six months using the DAS28 score. Differentially methylated positions (DMPs) were identified using linear regression, adjusting for gender, age, cell composition, and baseline DAS28 score. Results Although no probe reached study-wide significance, 16 DMPs suggestive loci were associated with MTX response in the pre-treatment samples (arbitrary p<10–4), including a DMP close to the IL6R gene (cg15633035, p=5.24x10–5). At four weeks, 20 DMPs were associated with response, with no overlap with the DMPs reported in the pre-treatment sample. In good responders, 10 DMPs were differentially methylated between pre-treatment and four week samples. In poor responders, 17 DMPs were differentially methylated between time-points. There was no overlap of DMPs between good and poor responders Conclusions These preliminary results suggest DNA methylation may provide a useful source of biomarkers of MTX response and now require replication in an independent dataset. Furthermore, investigation of differential methylation between baseline and four weeks reveals the potential of DNA methylation in pharmacodynamic modelling of MTX response. Further analysis is being conducted and significant findings will be validated in the total RAMS population using pyrosequencing. References Barrera P et al, Drug survival, efficacy and toxicity of monotherapy with a fully human anti-tumour necrosis factor-alpha antibody compared with methotrexate in long-standing rheumatoid arthritis. Rheumatology. 2002 Apr;41(4):430–9 Verstappen SMM, et al, Prediction of response and adverse events to methotrexate treatment in patients with rheumatoid arthritis. Int. J. Clin. Rheu. 2012;7(5):559–567 Kim Y, et al, DNA hypomethylation in inflammatory arthritis: reversal with methotrexate. J. Lab. Clin. Med. 1996;128:165–172 Disclosure of Interest None declared

AB0005 Weighted Gene Co-Expression Network Analysis Reveals Link between Protein Kinase Signalling and Response To Methotrexate in New-Onset Rheumatoid Arthritis

Background Methotrexate (MTX) is recommended as the first-line therapy in rheumatoid arthritis (RA). However, only 55% of patients remain on this inexpensive drug beyond 2 years after initiation of treatment. A stratified medicine approach therefore necessitates identification of reliable biomarkers of MTX response which are currently lacking. Objectives To identify gene co-expression networks in pre-treatment blood of new-onset RA patients that correlate with response to MTX at 6-months. Methods Patients with RA participating in the Rheumatoid Arthritis Medication Study (RAMS), a multi-centre one-year longitudinal observational study investigating predictors of response to MTX in the UK, who were EULAR good or poor responders at 6-months were included in this analysis. Total RNA was extracted from Tempus™ tubes using the Tempus Spin RNA isolation kit according to the manufacturers protocol. Following extraction, quantification and assessment of RNA integrity, RNA samples were labelled with biotin and amplified (Illumina TotalPrep RNA Amplification Kit) prior to being loaded onto an Illumina HumanHT-12 v4 BeadChip, which targets over 47,000 probes. Highly correlated genes were identified from the expression data and summarised with a modular eigengene using the weighted gene co-expression network analysis (WGCNA) bioconductor package. Pearsons correlation was used to assess the significance of the correlation between eigengene and improvement in disease activity, defined using EULAR response and change in CRP. Results Thirty-two good and 43 poor responders were included in this study [76% female; mean age 60 (SD 14) years, median symptom duration 6-months (IQR 3.7, 19) at MTX start]. Seventeen co-expression modules were identified. None of the modules were correlated with EULAR response at 6 months. However, one module including 1,840 genes was correlated with change in CRP between baseline and 6-months (corr 0.37, p=0.001). Furthermore, the genes most central to the module were also the most correlated with CRP difference (cor 0.5, p=5.6e-117). The most significant gene ontology (GO) molecular function term for this module was protein kinase (61 genes, 1.50 fold enrichment, p=4.2e-04, Benjamini p=0.04). Within this GO the expression of TYK2 was found to be correlated with CRP change (p=0.005). Patients with higher TYK2 expression at baseline experienced more improvement in CRP following MTX treatment. Conclusions These results suggest gene co-expression network analysis has the potential to reveal important insight into the biological effects of MTX therapy in RA. The assumption behind this analysis is that networks of genes are co-regulated e.g. by an environmental exposure, transcription factor of genetic variants. The next step will be to incorporate genome-wide single nucleotide polymorphism data to identify eigengene and gene expression quantitative trait loci. Disclosure of Interest None declared