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Objective: Juvenile idiopathic arthritis (JIA) comprises 7 heterogeneous categories of chronic childhood arthritides. Approximately 5% of children with JIA have rheumatoid factor (RF)–positive arthritis, which phenotypically resembles adult rheumatoid arthritis (RA). Our objective was to compare and contrast the genetics of RF‐positive polyarticular JIA with those of RA and selected other JIA categories, to more fully understand the pathophysiologic relationships of inflammatory arthropathies. Methods: Patients with RF‐positive polyarticular JIA (n = 340) and controls (n = 14,412) were genotyped using the Immunochip array. Single‐nucleotide polymorphisms were tested for association using a logistic regression model adjusting for admixture proportions. We calculated weighted genetic risk scores (wGRS) of reported RA and JIA risk loci, and we compared the ability of these wGRS to predict RF‐positive polyarticular JIA. Results: As expected, the HLA region was strongly associated with RF‐positive polyarticular JIA (P = 5.51 × 10−31). Nineteen of 44 RA risk loci and 6 of 27 oligoarticular/RF‐negative polyarticular JIA risk loci were associated with RF‐positive polyarticular JIA (P < 0.05). The RA wGRS predicted RF‐positive polyarticular JIA (area under the curve [AUC] 0.71) better than did the oligoarticular/RF‐negative polyarticular JIA wGRS (AUC 0.59). The genetic profile of patients with RF‐positive polyarticular JIA was more similar to that of RA patients with age at onset 16–29 years than to that of RA patients with age at onset ≥70 years. Conclusion: RF‐positive polyarticular JIA is genetically more similar to adult RA than to the most common JIA categories and thus appears to be a childhood‐onset presentation of autoantibody‐positive RA. These findings suggest common disease mechanisms, which could lead to novel therapeutic targets and shared treatment strategies. [ABSTRACT FROM AUTHOR]

We used the Immunochip array to analyze 2,816 individuals with juvenile idiopathic arthritis (JIA), comprising the most common subtypes (oligoarticular and rheumatoid factor-negative polyarticular JIA), and 13,056 controls. We confirmed association of 3 known JIA risk loci (the human leukocyte antigen (HLA) region, PTPN22 and PTPN2) and identified 14 loci reaching genome-wide significance (P < 5 × 10−8) for the first time. Eleven additional new regions showed suggestive evidence of association with JIA (P < 1 × 10−6). Dense mapping of loci along with bioinformatics analysis refined the associations to one gene in each of eight regions, highlighting crucial pathways, including the interleukin (IL)-2 pathway, in JIA disease pathogenesis. The entire Immunochip content, the HLA region and the top 27 loci (P < 1 × 10−6) explain an estimated 18, 13 and 6% of the risk of JIA, respectively. In summary, this is the largest collection of JIA cases investigated so far and provides new insight into the genetic basis of this childhood autoimmune disease. [ABSTRACT FROM AUTHOR]

To identify new genetic risk factors for rheumatoid arthritis, we conducted a genome-wide association study meta-analysis of 5,539 autoantibody-positive individuals with rheumatoid arthritis (cases) and 20,169 controls of European descent, followed by replication in an independent set of 6,768 rheumatoid arthritis cases and 8,806 controls. Of 34 SNPs selected for replication, 7 new rheumatoid arthritis risk alleles were identified at genome-wide significance (P < 5 × 10−8) in an analysis of all 41,282 samples. The associated SNPs are near genes of known immune function, including IL6ST, SPRED2, RBPJ, CCR6, IRF5 and PXK. We also refined associations at two established rheumatoid arthritis risk loci (IL2RA and CCL21) and confirmed the association at AFF3. These new associations bring the total number of confirmed rheumatoid arthritis risk loci to 31 among individuals of European ancestry. An additional 11 SNPs replicated at P < 0.05, many of which are validated autoimmune risk alleles, suggesting that most represent genuine rheumatoid arthritis risk alleles. [ABSTRACT FROM AUTHOR]

In the last few years, with the emergence of genome-wide association studies (GWAS), there has been an explosion of genetic discoveries for many complex genetic autoimmune diseases such as Crohn's disease, type 1 diabetes, multiple sclerosis, and rheumatoid arthritis. Indeed, more genetic risk factors were identified for common diseases in 2007 than had been collectively reported before that year. Studies on juvenile idiopathic arthritis (JIA) are following in the footsteps of those studies, and the next few years look set to be exciting times in the search for JIA-susceptibility loci with large, well-powered international collaborative GWAS being performed. In this review, I will explain how the recent advances in genetic technologies, methodologies, and research in other autoimmune diseases has already led to a greater understanding of JIA genetic susceptibility. I will describe how this information can help not only in the understanding of JIA disease pathogenesis, but also in the classification of this heterogeneous disorder. Ultimately, genetics may also identify new disease pathways for therapeutic intervention, help predict outcome of disease, and additionally help predict response to treatment. [ABSTRACT FROM AUTHOR]

To discover new rheumatoid arthritis (RA) risk loci, we systematically examined 370 SNPs from 179 independent loci with P < 0.001 in a published meta-analysis of RA genome-wide association studies (GWAS) of 3,393 cases and 12,462 controls. We used Gene Relationships Across Implicated Loci (GRAIL), a computational method that applies statistical text mining to PubMed abstracts, to score these 179 loci for functional relationships to genes in 16 established RA disease loci. We identified 22 loci with a significant degree of functional connectivity. We genotyped 22 representative SNPs in an independent set of 7,957 cases and 11,958 matched controls. Three were convincingly validated: CD2-CD58 (rs11586238, P = 1 × 10−6 replication, P = 1 × 10−9 overall), CD28 (rs1980422, P = 5 × 10−6 replication, P = 1 × 10−9 overall) and PRDM1 (rs548234, P = 1 × 10−5 replication, P = 2 × 10−8 overall). An additional four were replicated (P < 0.0023): TAGAP (rs394581, P = 0.0002 replication, P = 4 × 10−7 overall), PTPRC (rs10919563, P = 0.0003 replication, P = 7 × 10−7 overall), TRAF6-RAG1 (rs540386, P = 0.0008 replication, P = 4 × 10−6 overall) and FCGR2A (rs12746613, P = 0.0022 replication, P = 2 × 10−5 overall). Many of these loci are also associated to other immunologic diseases. [ABSTRACT FROM AUTHOR]

The WTCCC study identified 49 SNPs putatively associated with rheumatoid arthritis at P = 1 × 10−4 − 1 × 10−5 (tier 3). Here we show that three of these SNPs, mapping to chromosome 10p15 (rs4750316), 12q13 (rs1678542) and 22q13 (rs3218253), are also associated (trend P = 4 × 10−5, P = 4 × 10−4 and P = 4 × 10−4, respectively) in a validation study of 4,106 individuals with rheumatoid arthritis and an expanded reference group of 11,238 subjects, confirming them as true susceptibility loci in individuals of European ancestry. [ABSTRACT FROM AUTHOR]

The Wellcome Trust Case Control Consortium (WTCCC) identified nine single SNPs putatively associated with rheumatoid arthritis at P = 1 × 10−5 − 5 × 10−7 in a genome-wide association screen. One, rs6920220, was unequivocally replicated (trend P = 1.1 × 10−8) in a validation study, as described here. This SNP maps to 6q23, between the genes oligodendrocyte lineage transcription factor 3 (OLIG3) and tumor necrosis factor-α–induced protein 3 (TNFAIP3). [ABSTRACT FROM AUTHOR]