FRI0005 CHROMATIN CONTACTS AND TRANSCRIPTOMICS IN CD4+ T-CELLS REVEAL GENES IMPLICATED IN RHEUMATOID ARTHRITIS. (June 2019)

• Record Type: Journal Article
• Authors: Gaddi, Vasanthi Priyadarshini; Mcgovern, Amanda; Ding, James; Iqbal, Nadia; Shi, Chenfu; Katopodi, Theoni; Acosta-Herrera, Marialbert; Vargas, Sofia; Duffus, Kate; Yarwood, Annie; Raya, Enrique; Ibanez, Javier Martin; Martin, Paul; Orozco, Gisela
• Is Part Of: Annals of the rheumatic diseases. Volume 78(2019)Supplement 2
• Page Start: 663
• Page End: 664
• Publication Date: 2019-06
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2019-eular.3211
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by inflammation of synovial joints. RA is a clinically heterogeneous disease and treatment response varies between individuals. The pathogenesis of RA is not completely understood yet, but it has been shown that the largest factor influencing disease susceptibility is genetics. Genome-wide association studies have successfully characterized genetic variants that are associated with RA, with the vast majority of them mapping to non-coding regulatory elements. Understanding the mechanisms by which this phenomenon leads to disease is essential to translate results from genetic association studies to the clinic. Objectives: There is evidence showing that autoimmune diseases are the consequence of erroneous wiring of the regulatory circuitry between enhancers and their target genes. The aim of this study is to characterize non-coding regions containing RA-associated variants, in order to determine the genes and pathways by which these regions act to increase the risk of disease. Methods: We isolated CD4+ T-cells from blood obtained from RA patients. We stratified patients in two subgroups, high disease activity (DAS28>5.1, n=18) and low disease activity (DAS28<3.2, n=33). All samples were genotyped using Illumina Infinium Exome-24 v1.0 BeadChip arrays. RNA-Seq Libraries were generated for matching RNA samples using the Lexogen QuantSeq Library Prep kit and sequenced on an Illumina NextSeq500. For a subset of 6 samples (3 high disease activity and 3 low disease activity patients), capture Hi-C was performed to characterize chromatin interactions between all RA associated loci and their potential target genes. Results: We observed numerous chromatin interactions between RA variants and potential causal genes. Preliminary results show that a number of disease-associated SNPs interact with compelling candidate genes situated several megabases away. Whilst some of these chromatin interactions are common to both patients groups, subsets of them are specific to each disease subgroup, which are correlated with differential gene expression. Conclusion: These results suggests that there might be different biological pathways contributing to disease in RA patients with inactive disease compared to patients with high disease activity. Disclosure of Interests: None declared