OP0212 Analysis of the immunochip in a large cohort of oligo- and polyarthritis juvenile idiopathic arthritis (JIA) cases confirms previous and identifies novel associations. (23rd January 2014)

• Record Type: Journal Article
• Authors: Hinks, A.; Cobb, J.; Bowes, J.; Sudman, M.; Steel, K.; Marion, M.; Keddache, M.; Bohnsack, J.; Guthery, S.; Wedderburn, L.; Glass, D.; Haas, J.P.; Prahalad, S.; Langefeld, C.D.; Thomson, W.; Thompson, S.D.
• Is Part Of: Annals of the rheumatic diseases. Volume 71(2012)Supplement 3
• Page Start: 127
• Page End: 127
• Publication Date: 2014-01-23
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2012-eular.1895
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: Genome wide association studies (GWAS) have been hugely successful in identifying susceptibility loci for autoimmune diseases. One interesting outcome of GWAS is the observation that many of the loci are shared across these diseases. The regions identified now require more detailed fine-mapping to localize the association signal and identify putative functional variants. The Immunochip consortium was established to pool confirmed loci from 12 diseases onto a custom genotyping chip investigating ∼200 established autoimmune susceptibility loci. For each locus, all known genetic variation from multiple sources was included. Juvenile idiopathic arthritis (JIA) is the most common arthritic disease of childhood. Candidate gene studies have identified a number of common autoimmune genes that confer susceptibility to JIA, however JIA has been less well studied using large-scale approaches. Objectives: To use the Immunochip to fine-map previously associated regions and to identifying novel loci for JIA. Methods: Genotyping was performed using the Immunochip, in a large cohort from the UK, US and Germany comprising 1749 JIA oligoarthritis and RF negative polyarthritis cases and 8854 controls. All raw genotyping data was combined for clustering and QC. SNPs failed QC based on a call rate <98% and/or cluster separation score <0.4. Samples failed QC based on a call rate <98%. Outliers of mean heterozygosity, related individuals and ancestral outliers were removed. Final sample size after QC was 1609 cases and 7153 controls. Analysis was performed using logistic regression adjusting for the top 5 principal components in PLINK 1.07. Results: Initial analysis has not only confirmed previously associated JIA loci ( HLA, PTPN22, IL2, STAT4, PTPN2 and SH2B3/ATXN2 ) but has strengthened their association, such that all now reach genome-wide significance. A number of novel loci have been identified, some of which showed weak evidence previously, such as IL2RA, IL7R and IRF1, and others which have never been associated with JIA, such as RUNX1, FAS and ANKRD55 . These will require validation in independent cohorts. Conclusions: The Immunochip project enables cost-effective fine-mapping of autoimmune loci in diseases such as JIA. This preliminary analysis has confirmed and strengthened the association of a number of previously associated genes as well as the identification of novel susceptibility loci for JIA. Further analysis of this data will help characterize all associated variants and identify the likely causal variants for future functional studies. Acknowledgements: Childhood Arthritis Prospective Study (CAPS), Childhood Arthritis Response to Medication Study (SPARKS-CHARMS), BSPAR study group, UK JIA Genetics Consortium (UKJIAGC), Cincinnati Registry for Juvenile Arthritis Genetics (CRJAG), Consortium for Juvenile Arthritis Genetics (CJAG), and USA-Juvenile Arthritis Genetics Cohort (USA-JAGC). Disclosure of Interest: None Declared