S. Lamberth

Integrative genomic deconvolution of rheumatoid arthritis GWAS loci into gene and cell type associations

BackgroundAlthough genome-wide association studies (GWAS) have identified over 100 genetic loci associated with rheumatoid arthritis (RA), our ability to translate these results into disease understanding and novel therapeutics is limited. Most RA GWAS loci reside outside of protein-coding regions and likely affect distal transcriptional enhancers. Furthermore, GWAS do not identify the cell types where the associated causal gene functions. Thus, mapping the transcriptional regulatory roles of GWAS hits and the relevant cell types will lead to better understanding of RA pathogenesis.ResultsWe combine the whole-genome sequences and blood transcription profiles of 377 RA patients and identify over 6000 unique genes with expression quantitative trait loci (eQTLs). We demonstrate the quality of the identified eQTLs through comparison to non-RA individuals. We integrate the eQTLs with immune cell epigenome maps, RA GWAS risk loci, and adjustment for linkage disequilibrium to propose target genes of immune cell enhancers that overlap RA risk loci. We examine 20 immune cell epigenomes and perform a focused analysis on primary monocytes, B cells, and T cells.ConclusionsWe highlight cell-specific gene associations with relevance to RA pathogenesis including the identification of FCGR2B in B cells as possessing both intragenic and enhancer regulatory GWAS hits. We show that our RA patient cohort derived eQTL network is more informative for studying RA than that from a healthy cohort. While not experimentally validated here, the reported eQTLs and cell type-specific RA risk associations can prioritize future experiments with the goal of elucidating the regulatory mechanisms behind genetic risk associations.

Modular Analysis of Peripheral Blood Gene Expression in Rheumatoid Arthritis Captures Reproducible Gene Expression Changes in Tumor Necrosis Factor Responders

To establish whether the analysis of whole‐blood gene expression is useful in predicting or monitoring response to anti–tumor necrosis factor (anti‐TNF) therapy in patients with rheumatoid arthritis (RA).

Subcutaneous golimumab for children with active polyarticular-course juvenile idiopathic arthritis: results of a multicentre, double-blind, randomised-withdrawal trial

Objective This report aims to determine the safety, pharmacokinetics (PK) and efficacy of subcutaneous golimumab in active polyarticular-course juvenile idiopathic arthritis (polyJIA). Methods In this three-part randomised double-blinded placebo-controlled withdrawal trial, all patients received open-label golimumab (30 mg/m2 of body surface area; maximum: 50 mg/dose) every 4 weeks together with weekly methotrexate during Part 1 (weeks 0–16). Patients with at least 30% improvement per American College of Rheumatology Criteria for JIA (JIA ACR30) in Part 1 entered the double-blinded Part 2 (weeks 16–48) after 1:1 randomisation to continue golimumab or start placebo. In Part 3, golimumab was continued or could be restarted as in Part 1. The primary outcome was JIA flares in Part 2; secondary outcomes included JIA ACR50/70/90 responses, clinical remission, PK and safety. Results Among 173 patients with polyJIA enrolled, 89.0% (154/173) had a JIA ACR30 response and 79.2%/65.9%/36.4% demonstrated JIA ACR50/70/90 responses in Part 1. At week 48, the primary endpoint was not met as treatment groups had comparable JIA flare rates (golimumab vs placebo: 32/78=41% vs 36/76=47%; p=0.41), and rates of clinical remission were comparable (golimumab vs placebo: 10/78=12.8% vs 9/76=11.8%). Adverse event and serious adverse event rates were similar in the treatment groups during Part 2. Injection site reactions occurred with <1% of all injections. PK analysis confirmed adequate golimumab dosing for polyJIA. Conclusion Although the primary endpoint was not met, golimumab resulted in rapid, clinically meaningful, improvement in children with active polyJIA. Golimumab was well tolerated, and no unexpected safety events occurred. Clinical Trial Registration NCT01230827; Results.

Group-based variant calling leveraging next-generation supercomputing for large-scale whole-genome sequencing studies

MotivationNext-generation sequencing (NGS) technologies have become much more efficient, allowing whole human genomes to be sequenced faster and cheaper than ever before. However, processing the raw sequence reads associated with NGS technologies requires care and sophistication in order to draw compelling inferences about phenotypic consequences of variation in human genomes. It has been shown that different approaches to variant calling from NGS data can lead to different conclusions. Ensuring appropriate accuracy and quality in variant calling can come at a computational cost.ResultsWe describe our experience implementing and evaluating a group-based approach to calling variants on large numbers of whole human genomes. We explore the influence of many factors that may impact the accuracy and efficiency of group-based variant calling, including group size, the biogeographical backgrounds of the individuals who have been sequenced, and the computing environment used. We make efficient use of the Gordon supercomputer cluster at the San Diego Supercomputer Center by incorporating job-packing and parallelization considerations into our workflow while calling variants on 437 whole human genomes generated as part of large association study.ConclusionsWe ultimately find that our workflow resulted in high-quality variant calls in a computationally efficient manner. We argue that studies like ours should motivate further investigations combining hardware-oriented advances in computing systems with algorithmic developments to tackle emerging ‘big data’ problems in biomedical research brought on by the expansion of NGS technologies.

Modular Analysis of Peripheral Blood Gene Expression in Rheumatoid Arthritis Captures Reproducible Gene Expression Changes in TNF Responders

To establish whether the analysis of whole‐blood gene expression is useful in predicting or monitoring response to anti–tumor necrosis factor (anti‐TNF) therapy in patients with rheumatoid arthritis (RA).

FRI0009 Serum 14-3-3 ETA Is An RA Specific Mechanistic Marker

Background 14–3-3η is an emerging soluble Rheumatoid Arthritis (RA) biomarker that activates intracellular pathways that lead to the upregulation of inflammatory and joint damage factors. It is reported to be highly specific and sensitive for RA as a diagnostic marker, higher levels are associated with greater joint damage progression risk and 14–3-3ηs modulation with treatment suggests a role in disease monitoring. Objectives In this study, we examine the specificity of 14–3-3η in an independent, clinically well-characterized cohort of moderate to severe RA and disease control subjects. Methods Serum 14–3-3η levels were measured in a total of 147 patients using the Augurex 14–3-3η ELISA. The patient set comprised 36 with RA and 111 controls consisting of 20 with asthma (A), 20 with Crohns Disease (CD), 12 presumed healthy (H), 16 with psoriasis (PsO), 20 with sarcoid arthritis (S), and 23 with spondylarthropathies (SpA). Sample testing was done independently of Augurex. Mann-Whitney testing together with Kruskal-Wallis analysis with the post-hoc Dunns multiple comparison test was performed to assess group differences. Receiver operator characteristic curve (ROC) analysis was performed to assess the specificity of 14–3-3η for RA. Results Median (IQR) serum 14–3-3η levels were significantly higher in RA [2.35ng/ml (0.28–19.41)] than all controls [0 (0–0)], p<0.0001. ROC curve analysis further underscored this differential expression yielding a significant area under the curve (AUC) of 0.86, p<0.0001. At the diagnostic positivity cut-off of ≥0.19 ng/ml, the ROC curve delivered a sensitivity of 81% with a corresponding specificity of 84%. Kruskal-Wallis testing revealed that serum 14–3-3η levels were significantly higher in RA in comparison to all other diseases, p<0.0001. Conclusions Serum 14–3-3η is a highly specific RA biomarker. As a novel mechanistic disease factor, 14–3-3η is expected to provide new insights and approaches to RA management and clinical studies. References Arthritis Res Ther 2014; 16(2):R99; J Rheumatol 2014; 41(11):2104. Disclosure of Interest B. Dasgupta Employee of: Janssen R & D, LLC, Y. Cherkas Employee of: Janssen R & D, LLC, S. Lamberth Employee of: Janssen R & D, LLC, K. Hayden Employee of: Janssen R & D, LLC, C. Brodmerkel Employee of: Janssen R & D, LLC, A. Marotta Grant/research support from: Janssen R & D, LLC, M. Curran Employee of: Janssen R & D, LLC

Modular Analysis of Peripheral Blood Gene Expression in Rheumatoid Arthritis Captures Reproducible Gene Expression Changes in Tumor Necrosis Factor Responders: Whole-Blood Gene Expression Analysis and Response to Anti-TNF in RA

To establish whether the analysis of whole‐blood gene expression is useful in predicting or monitoring response to anti–tumor necrosis factor (anti‐TNF) therapy in patients with rheumatoid arthritis (RA).

OP0027 Identification of Molecular Disease Drivers Using eQTLS Derived from a Cohort of Rheumatoid Arthritis Patients

Background Genome wide association studies (GWAS) have yielded over 100 genetic loci associated with rheumatoid arthritis (RA). However, the utility of GWAS studies for drug discovery is limited because most GWAS hits do not reside in coding regions and have no known function. Elucidating potential transcriptional regulatory roles of GWAS hits will allow functional annotation of disease-related GWAS loci and lead to better understanding of RA etiology. Objectives To identify potential molecular drivers of RA by mapping expression quantitative trait loci (eQTLs) from gene expression and genotype data from a cohort of RA patients. Methods eQTLs were mapped using whole blood transcriptome data (Affymetrix microarray) from 377 RA patients with inadequate response to methotrexate enrolled in a clinical trial at baseline. Genotypes were generated from whole genome sequencing of DNA from the same subjects. eQTL mapping was performed by linear regression on adjusted data and FDR was estimated with a permutation method separately for local and distant associations. Results We report over 6,000 unique genes with significant eQTLs that represent potential molecular drivers. These eQTLs are enriched for genetic variants associated with RA. Additionally, the genes associated with these RA GWAS loci represent several disease-relevant biological pathways, including antigen presentation and B cell signaling. While there are multiple published eQTL datasets from non-RA cohorts, our analysis suggests that there is utility in detecting eQTLs from disease-relevant cohorts. Indeed, we identified several eQTLs overlapping with RA GWAS loci that have not been reported previously. We also demonstrate that integration with publicly available epigenomics datasets enables elucidation of cell-type-specific relationships. In particular, genes with expression driven by active enhancers in specific immune cell types (e.g., B cells and T helper cells) were identified, generating hypotheses that can be validated experimentally. Conclusions As one of the first studies to detect eQTLs from RA patients, this work provides a valuable resource to better understand the genetic basis for RA and aid in translating genetics research into therapeutic interventions. Overall, this analysis highlights the value of studying peripheral blood given the challenge of obtaining large numbers of synovial tissue biopsies from RA patients. Disclosure of Interest A. Walsh Employee of: Johnson & Johnson, J. Whitaker Employee of: Johnson & Johnson, C. Huang Employee of: Johnson & Johnson, Y. Cherkas Employee of: Johnson & Johnson, S. Lamberth Employee of: Johnson & Johnson, C. Brodmerkel Employee of: Johnson & Johnson, M. Curran Employee of: Johnson & Johnson, R. Dobrin Shareholder of: Johnson & Johnson, Employee of: Johnson & Johnson

FRI0271 Modular Analysis of Peripheral Blood Gene Expression in Rheumatoid Arthritis Captures Reproducible Gene Expression Changes in TNF Responders

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

FRI0038 Pharmacodynamic Effect of Intravenous Golimumab by Messenger RNA Expression Profiling

Background Rheumatoid Arthritis (RA) is a chronic systemic autoimmune disease resulting in joint inflammation and damage. Despite the current therapies available, only a small percentage of RA pts achieve remission. To improve care and treatment for RA pts, a deeper understanding of the mechanisms that drive disease and response to therapy are desirable. The molecular understanding of disease and treatment mechanisms of RA continues to evolve. Objectives To explore the utility of peripheral blood expression profiling for informing disease and treatment mechanisms, samples derived from the GO-FURTHER golimumab study in RA were evaluated. This study examines if whole blood (WB) gene expression profiles can be utilized to: identify a baseline disease profile (DP) for pts with moderate-to-severe RA elucidate the pharmacodynamic (PD) and response profile of golimumab IV treatment, and delineate the peripheral biological processes dysregulated in RA and modulated by golimumab IV. Methods mRNA from 487 WB samples collected in a Phase III study of golimumab IV (GO-FURTHER) in pts with active RA despite methotrexate (MTX) therapy was isolated and profiled using the Affymetrix HT HG-U133+ PM Array (Santa Clara, CA). Samples were collected at Wks 0 and 14 from pts treated with IV placebo + MTX (PBO; n=161) or IV golimumab 2mg/kg + MTX (GLM; n=326) administered at Wks 0, 4, and every 8 wks thereafter. Non-RA WB samples (healthy controls; n=22) were obtained from Bioreclamation (Hicksville, NY). Results A disease profile comparing baseline gene expression profiles of RA to healthy controls yielded about 2000 differentially expressed genes (DEGs), while comparison of post-treatment to pre-treatment samples generated a PD profile of about 3000 DEGs. Over 70% of genes in the DP are downregulated as well as humoral immune response and B and T cell receptor signaling pathways. Pathways upregulated in the DP include innate immune response, Toll-like receptor (TLR), and cell activation. Treatment with golimumab modulates more than 30% of the disease profile, while just over 25% of PD effect is shared with the DP. The above mentioned pathways are common between the DP and PD profiles and are reversed, in part, through changes in peripheral cell populations post-golimumab treatment. A significant decrease in neutrophils and increase in lymphocytes was observed in the periphery at Wk 12 and in gene expression profiles representative of these cells at Wk 14 post-treatment. In addition, response to golimumab at Wk 14 was associated with more gene changes in B and T cell receptor signaling pathways in comparison to nonresponders. Conclusions Gene expression from the periphery of RA pts can be used for identification of a DP as well as the PD effect and response profile to golimumab IV. The most significant biological pathways and functions associated with the DP or PD effect are related to immune response and function. At baseline, RA pts had an increased innate and decreased adaptive immune profile in the periphery and majority of these processes were reversed by treatment with golimumab IV. Defining the pathways dysregulated in RA and modified by effective treatment as well as those that remain dysregulated aids in defining novel areas for potential therapeutic intervention. Disclosure of Interest Y. Cherkas Employee of: Janssen Research & Development, LLC., C. Brodmerkel Employee of: Janssen Research & Development, LLC., M. Curran Employee of: Janssen Research & Development, LLC., S. Lamberth Employee of: Janssen Research & Development, LLC. DOI 10.1136/annrheumdis-2014-eular.2032