Identification of a regulatory pathway governing TRAF1 via an arthritis-associated non-coding variant.

TRAF1/C5 was among the first loci shown to confer risk for inflammatory arthritis in the absence of an associated coding variant, but its genetic mechanism remains undefined. Using Immunochip data from 3,939 patients with juvenile idiopathic arthritis (JIA) and 14,412 control individuals, we identified 132 plausible common non-coding variants, reduced serially by single-nucleotide polymorphism sequencing (SNP-seq), electrophoretic mobility shift, and luciferase studies to the single variant rs7034653 in the third intron of TRAF1. Genetically manipulated experimental cells and primary monocytes from genotyped donors establish that the risk G allele reduces binding of Fos-related antigen 2 (FRA2), encoded by FOSL2, resulting in reduced TRAF1 expression and enhanced tumor necrosis factor (TNF) production. Conditioning on this JIA variant eliminated attributable risk for rheumatoid arthritis, implicating a mechanism shared across the arthritis spectrum. These findings reveal that rs7034653, FRA2, and TRAF1 mediate a pathway through which a non-coding functional variant drives risk of inflammatory arthritis in children and adults.

Combined genetic analysis of juvenile idiopathic arthritis clinical subtypes identifies novel risk loci, target genes and key regulatory mechanisms.

OBJECTIVES: Juvenile idiopathic arthritis (JIA) is the most prevalent form of juvenile rheumatic disease. Our understanding of the genetic risk factors for this disease is limited due to low disease prevalence and extensive clinical heterogeneity. The objective of this research is to identify novel JIA susceptibility variants and link these variants to target genes, which is essential to facilitate the translation of genetic discoveries to clinical benefit. METHODS: We performed a genome-wide association study (GWAS) in 3305 patients and 9196 healthy controls, and used a Bayesian model selection approach to systematically investigate specificity and sharing of associated loci across JIA clinical subtypes. Suggestive signals were followed-up for meta-analysis with a previous GWAS (2751 cases/15 886 controls). We tested for enrichment of association signals in a broad range of functional annotations, and integrated statistical fine-mapping and experimental data to identify target genes. RESULTS: Our analysis provides evidence to support joint analysis of all JIA subtypes with the identification of five novel significant loci. Fine-mapping nominated causal single nucleotide polymorphisms with posterior inclusion probabilities ≥50% in five JIA loci. Enrichment analysis identified RELA and EBF1 as key transcription factors contributing to disease risk. Our integrative approach provided compelling evidence to prioritise target genes at six loci, highlighting mechanistic insights for the disease biology and IL6ST as a potential drug target. CONCLUSIONS: In a large JIA GWAS, we identify five novel risk loci and describe potential function of JIA association signals that will be informative for future experimental works and therapeutic strategies.

Broadening our understanding of the genetics of Juvenile Idiopathic Arthritis (JIA): Interrogation of three dimensional chromatin structures and genetic regulatory elements within JIA-associated risk loci.

OBJECTIVE: The risk loci for juvenile idiopathic arthritis (JIA) consist of extended haplotypes that include functional elements in addition to canonical coding genes. As with most autoimmune diseases, the risk haplotypes for JIA are highly enriched for H3K4me1/H3K27ac histone marks, epigenetic signatures that typically identify poised or active enhancers. In this study, we test the hypothesis that genetic risk for JIA is exerted through altered enhancer-mediated gene regulation. METHODS: We mined publically available HiC and other chromatin conformation data to determine whether H3K27ac-marked regions in 25 JIA risk loci showed physical evidence of contact with gene promoters. We also used in vitro reporter assays to establish as proof-of-concept the idea that genetic variants in linkage disequilibrium with GWAS-identified tag SNPs alter enhancer function. RESULTS: All 25 loci examined showed multiple contact sites in the 4 different cell lines that we queried. These regions were characterized by HiC-defined loop structures that included 237 immune-related genes. Using in vitro assays, we found that a 657 bp, H3K4me1/H3K27-marked region within the first intron of IL2RA shows enhancer activity in reporter assays, and this activity is attenuated by SNPs on the IL2RA haplotype that we identified using whole genome sequencing of children with JIA. Similarly, we identified a 1,669 bp sequence in an intergenic region of the IL6R locus where SNPs identified in children with JIA increase enhancer function in reporter assays. CONCLUSIONS: These studies provide evidence that altered enhancer function contributes to genetic risk in JIA. Further studies to identify the specific target genes of genetically altered enhancers are warranted.

Association of SLCO1B1 *14 Allele with Poor Response to Methotrexate in Juvenile Idiopathic Arthritis Patients.

OBJECTIVE: Variants in the SLCO1B1 gene, encoding a hepatic methotrexate (MTX) transporter, affect clearance of high-dose MTX. We tested whether in the *14 and *15 alleles of SLCO1B1 influenced the response to low-dose MTX in juvenile idiopathic arthritis (JIA) patients. METHODS: The study included 310 JIA patients genotyped for three single nucleotide polymorphisms (SNPs) in SLCO1B1 (rs4149056, rs2306283, and rs11045819). A patient's SLCO1B1 diplotype was determined by combining the SNPs into the *1a, *1b, *4, *5, *14, and *15 alleles. Number of active joints at follow-up (visit closest to 6 months of treatment and prior to starting a tumor necrosis factor inhibitor) was used as the dependent variable in a negative binomial regression model that included active joint count at baseline as a covariate. RESULTS: The SLCO1B1*14 allele was associated with less response to MTX (P = 0.024) and the *15 allele was not associated with response to MTX (P = 0.392). CONCLUSION: SLCO1B1 alleles may be associated with poor response to MTX in JIA patients. The *14 allele has been associated with fast clearance (low exposure) after high-dose MTX in patients with leukemia. Thus, the SLCO1B1 gene may be informative for precision dosing of MTX in JIA patients. Patients carrying the *14 allele may require a higher dose than noncarriers to achieve a similar response to MTX.

Brief Report: The Genetic Profile of Rheumatoid Factor-Positive Polyarticular Juvenile Idiopathic Arthritis Resembles That of Adult Rheumatoid Arthritis.

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.

Genome-Wide Association Meta-Analysis Reveals Novel Juvenile Idiopathic Arthritis Susceptibility Loci.

OBJECTIVE: Juvenile idiopathic arthritis (JIA) is the most common childhood rheumatic disease and has a strong genomic component. To date, JIA genetic association studies have had limited sample sizes, used heterogeneous patient populations, or included only candidate regions. The aim of this study was to identify new associations between JIA patients with oligoarticular disease and those with IgM rheumatoid factor (RF)-negative polyarticular disease, which are clinically similar and the most prevalent JIA disease subtypes. METHODS: Three cohorts comprising 2,751 patients with oligoarticular or RF-negative polyarticular JIA were genotyped using the Affymetrix Genome-Wide SNP Array 6.0 or the Illumina HumanCoreExome-12+ Array. Overall, 15,886 local and out-of-study controls, typed on these platforms or the Illumina HumanOmni2.5, were used for association analyses. High-quality single-nucleotide polymorphisms (SNPs) were used for imputation to 1000 Genomes prior to SNP association analysis. RESULTS: Meta-analysis showed evidence of association (P < 1 × 10-6 ) at 9 regions: PRR9_LOR (P = 5.12 × 10-8 ), ILDR1_CD86 (P = 6.73 × 10-8 ), WDFY4 (P = 1.79 × 10-7 ), PTH1R (P = 1.87 × 10-7 ), RNF215 (P = 3.09 × 10-7 ), AHI1_LINC00271 (P = 3.48 × 10-7 ), JAK1 (P = 4.18 × 10-7 ), LINC00951 (P = 5.80 × 10-7 ), and HBP1 (P = 7.29 × 10-7 ). Of these, PRR9_LOR, ILDR1_CD86, RNF215, LINC00951, and HBP1 were shown, for the first time, to be autoimmune disease susceptibility loci. Furthermore, associated SNPs included cis expression quantitative trait loci for WDFY4, CCDC12, MTP18, SF3A1, AHI1, COG5, HBP1, and GPR22. CONCLUSION: This study provides evidence of both unique JIA risk loci and risk loci overlapping between JIA and other autoimmune diseases. These newly associated SNPs are shown to influence gene expression, and their bounding regions tie into molecular pathways of immunologic relevance. Thus, they likely represent regions that contribute to the pathology of oligoarticular JIA and RF-negative polyarticular JIA.

Dense genotyping of immune-related disease regions identifies 14 new susceptibility loci for juvenile idiopathic arthritis.

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.

Autoinflammatory gene polymorphisms and susceptibility to UK juvenile idiopathic arthritis.

BACKGROUND: To investigate the autoinflammatory hereditary periodic fever syndrome genes MVK and TNFRSF1A, and the NLRP1 and IL1 genes, for association with juvenile idiopathic arthritis (JIA). METHODS: For MVK, TNFRSF1A and NLRP1 pair-wise tagging SNPs across each gene were selected and for IL1A SNPs from a prior meta-analysis were included. 1054 UK Caucasian JIA patients were genotyped by Sequenom iPlex MassARRAY and allele and genotype frequencies compared with 5380 unrelated healthy UK Caucasian controls. RESULTS: Four SNPs were significantly associated with UK JIA: rs2071374 within intron 4 of IL1A (ptrend=0.006), rs2228576 3' of TNFRSF1A (ptrend=0.009) and 2 SNPs, rs11836136 and rs7957619, within MVK (ptrend=0.006, ptrend=0.005 respectively). In all cases the association appeared to be driven by the systemic-onset JIA (SoJIA) subtype. Genotype data for the two MVK SNPs was available in a validation cohort of 814 JIA (oligoarticular and RF negative polyarticular) cases and 3058 controls from the US. Replication was not confirmed, however, further suggesting that this association is specific to SoJIA. CONCLUSIONS: These findings extend the observations of the relevance of studying monogenic loci as candidates for complex diseases. We provide novel evidence of association of MVK and TNFRSF1A with UK JIA, specifically driven by association with SoJIA and further confirm that the IL1A SNP association with SoJIA is subtype specific. Replication is required in independent cohorts.

Susceptibility to childhood-onset rheumatoid arthritis: investigation of a weighted genetic risk score that integrates cumulative effects of variants at five genetic loci.

OBJECTIVE: Children with childhood-onset rheumatoid arthritis (RA) include those with rheumatoid factor or anti-citrullinated protein antibody-positive juvenile idiopathic arthritis. To test the hypothesis that adult-onset RA-associated variants are also associated with childhood-onset RA, we investigated RA-associated variants at 5 loci in a cohort of patients with childhood-onset RA. We also assessed the cumulative association of these variants in susceptibility to childhood-onset RA using a weighted genetic risk score (wGRS). METHODS: A total of 155 children with childhood-onset RA and 684 healthy controls were genotyped for 5 variants in the PTPN22, TRAF1/C5, STAT4, and TNFAIP3 loci. High-resolution HLA-DRB1 genotypes were available for 149 cases and 373 controls. We tested each locus for association with childhood-onset RA via logistic regression. We also computed a wGRS for each subject, with weights based on the natural log of the published odds ratios (ORs) for the alleles investigated, and used logistic regression to test the wGRS for association with childhood-onset RA. RESULTS: Childhood-onset RA was associated with TNFAIP3 rs10499194 (OR 0.60 [95% confidence interval 0.44-0.83]), PTPN22 rs2476601 (OR 1.61 [95% confidence interval 1.11-2.31]), and STAT4 rs7574865 (OR 1.41 [95% confidence interval 1.06-1.87]) variants. The wGRS was significantly different between cases and controls (P < 2 × 10(-16) ). Individuals in the third to fifth quintiles of wGRS had a significantly increased disease risk compared to baseline (individuals in the first quintile). Higher wGRS was associated with increased risk of childhood-onset RA, especially among males. CONCLUSION: The magnitude and direction of the association between TNFAIP3, STAT4, and PTPN22 variants and childhood-onset RA are similar to those observed in RA, suggesting that adult-onset RA and childhood-onset RA share common genetic risk factors. Using a wGRS, we have demonstrated the cumulative association of RA-associated variants with susceptibility to childhood-onset RA.

Investigation of rheumatoid arthritis susceptibility loci in juvenile idiopathic arthritis confirms high degree of overlap.

OBJECTIVES: Rheumatoid arthritis (RA) shares some similar clinical and pathological features with juvenile idiopathic arthritis (JIA); indeed, the strategy of investigating whether RA susceptibility loci also confer susceptibility to JIA has already proved highly successful in identifying novel JIA loci. A plethora of newly validated RA loci has been reported in the past year. Therefore, the aim of this study was to investigate these single nucleotide polymorphisms (SNP) to determine if they were also associated with JIA. METHODS: Thirty-four SNP that showed validated association with RA and had not been investigated previously in the UK JIA cohort were genotyped in JIA cases (n=1242), healthy controls (n=4281), and data were extracted for approximately 5380 UK Caucasian controls from the Wellcome Trust Case-Control Consortium 2. Genotype and allele frequencies were compared between cases with JIA and controls using PLINK. A replication cohort of 813 JIA cases and 3058 controls from the USA was available for validation of any significant findings. RESULTS: Thirteen SNP showed significant association (p<0.05) with JIA and for all but one the direction of association was the same as in RA. Of the eight loci that were tested, three showed significant association in the US cohort. CONCLUSIONS: A novel JIA susceptibility locus was identified, CD247, which represents another JIA susceptibility gene whose protein product is important in T-cell activation and signalling. The authors have also confirmed association of the PTPN2 and IL2RA genes with JIA, both reaching genome-wide significance in the combined analysis.

Genome-wide association analysis of juvenile idiopathic arthritis identifies a new susceptibility locus at chromosomal region 3q13.

OBJECTIVE: In a genome-wide association study of Caucasian patients with juvenile idiopathic arthritis (JIA), we have previously described findings limited to autoimmunity loci shared by JIA and other diseases. The present study was undertaken to identify novel JIA-predisposing loci using genome-wide approaches. METHODS: The discovery cohort consisted of Caucasian JIA cases (n = 814) and local controls (n = 658) genotyped on the Affymetrix Genome-Wide SNP 6.0 Array, along with 2,400 out-of-study controls. In a replication study, we genotyped 10 single-nucleotide polymorphisms (SNPs) in 1,744 cases and 7,010 controls from the US and Europe. RESULTS: Analysis within the discovery cohort provided evidence of associations at 3q13 within C3orf1 and near CD80 (rs4688011) (odds ratio [OR] 1.37, P = 1.88 × 10(-6) ) and at 10q21 near JMJD1C (rs647989 [OR 1.59, P = 6.1 × 10(-8) ], rs12411988 [OR 1.57, P = 1.16 × 10(-7) ], and rs10995450 [OR 1.31, P = 6.74 × 10(-5) ]). Meta-analysis provided further evidence of association for these 4 SNPs (P = 3.6 × 10(-7) for rs4688011, P = 4.33 × 10(-5) for rs6479891, P = 2.71 × 10(-5) for rs12411988, and P = 5.39 × 10(-5) for rs10995450). Gene expression data on 68 JIA cases and 23 local controls showed cis expression quantitative trait locus associations for C3orf1 SNP rs4688011 (P = 0.024 or P = 0.034, depending on the probe set) and JMJD1C SNPs rs6479891 and rs12411988 (P = 0.01 or P = 0.04, depending on the probe set and P = 0.008, respectively). Using a variance component liability model, it was estimated that common SNP variation accounts for approximately one-third of JIA susceptibility. CONCLUSION: Genetic association results and correlated gene expression findings provide evidence of JIA association at 3q13 and suggest novel genes as plausible candidates in disease pathology.

The susceptibility loci juvenile idiopathic arthritis shares with other autoimmune diseases extend to PTPN2, COG6, and ANGPT1.

OBJECTIVE: To test for associations between non-major histocompatibility complex susceptibility loci previously reported in autoimmune diseases and juvenile idiopathic arthritis (JIA). METHODS: Published autoimmune disease genome-wide association studies were reviewed, and 519 single-nucleotide polymorphisms (SNPs) were selected for association testing. The initial cohort included 809 JIA cases and 3,535 controls of non-Hispanic, European ancestry. Of the SNPs, 257 were successfully genotyped, while 168 were imputed with quality. Based on findings in the initial cohort, replication was sought for 21 SNPs in a second cohort of 1,015 JIA cases and 1,569 controls collected in the US and Germany. For the initial cohort, tests for association were adjusted for potential confounding effects of population structure by including principal components derived from a genome-wide association study as covariates in logistic regression models. Odds ratios (ORs) and 95% confidence intervals were calculated. RESULTS: Testing for association of previously reported autoimmune disease genetic associations in the initial cohort suggested associations with JIA in 13 distinct loci. Of these, 7 were validated in the replication cohort. Meta-analysis results for the replicating loci included PTPN22 (rs6679677 [OR 1.58, P = 1.98 × 10(-12) ], rs2476601 [OR 1.64, P = 1.90 × 10(-13) ], and rs2488457 [OR 1.32, P = 6.74 × 10(-8) ]), PTPN2 (rs1893217 [OR = 1.33, P = 1.60 × 10(-9) ] and rs7234029 [OR 1.35, P = 1.86 × 10(-10) ]), ADAD1-IL2-IL21 (rs17388568 [OR 1.24, P = 1.13 × 10(-6) ] and rs13143866 [OR 0.83, P = 1.95 × 10(-4) ]), STAT4 (rs3821236 [OR = 1.27, P = 2.36 × 10(-6) ] and rs7574865 [OR = 1.31, P = 2.21 × 10(-6) ]), C12orf30 (rs17696736 [OR = 1.19, P = 2.59 × 10(-5) ]), COG6 (rs7993214 [OR = 0.76, P = 1.10 × 10(-5) ]), and ANGPT1 (rs1010824 [OR = 0.79, P = 2.91 × 10(-4) ]). These polymorphisms have been reported in diseases such as rheumatoid arthritis, type 1 diabetes mellitus, Crohn's disease, and multiple sclerosis. CONCLUSION: General susceptibility loci for autoimmunity are shared across diseases, including JIA, suggesting the potential for common therapeutic targets and mechanisms.

Juvenile idiopathic arthritis and HLA class I and class II interactions and age-at-onset effects.

OBJECTIVE: The aim of this study was to quantitate risk and to examine heterogeneity for HLA at high resolution in patients with the most common subtypes of juvenile idiopathic arthritis (JIA), IgM rheumatoid factor-negative polyarticular JIA and oligoarticular JIA. Use of 4-digit comprehensive HLA typing enabled great precision, and a large cohort allowed for consideration of both age at disease onset and disease subtype. METHODS: Polymerase chain reaction-based high-resolution HLA typing for class I and class II loci was accomplished for 820 patients with JIA and 273 control subjects. Specific HLA epitopes, potential interactions of alleles at specific loci and between loci (accounting for linkage disequilibrium and haplotypic associations), and an assessment of the current International League of Associations for Rheumatology classification criteria were considered. RESULTS: An HLA-DRB1/DQB1 effect was shown to be exclusively attributable to DRB1 and was similar between patients with oligoarticular JIA and a younger subgroup of patients with polyarticular JIA. Furthermore, patients with polyarticular JIA showed age-specific related effects, with disease susceptibility in the group older than age 6 years limited to an effect of the HLA-DRB1*08 haplotype, which is markedly different from the additional susceptibility haplotypes, HLA-DRB1*1103/1104, found in the group with oligoarticular JIA and the group of younger patients with polyarticular JIA. Also in contrast to findings for oligoarticular JIA, patients with polyarticular arthritis had no evidence of an HLA class I effect. Markers associated with a reduced risk of disease included DRB1*1501, DRB1*0401, and DRB1*0701. DRB1*1501 was shown to reduce risk across the whole cohort, whereas DRB1*0401 and DRB1*0701 were protective for selected JIA subtypes. Surprisingly, the disease predisposition mediated by DPB1*0201 in individuals without any disease-predisposing DRB1 alleles was great enough to overcome even the very strong protective effect observed for DRB1*1501. CONCLUSION: Inherited HLA factors in JIA show similarities overall as well as differences between JIA subtypes.

A genome-wide scan for juvenile rheumatoid arthritis in affected sibpair families provides evidence of linkage.

OBJECTIVE: Juvenile rheumatoid arthritis (JRA) represents a heterogeneous group of disorders with a complex genetic component. A genome scan was performed to detect linkage to JRA in 121 families containing 247 affected children in North America (the JRA Affected Sibpair [ASP] Registry). METHODS: Genotype data collected for HLA-DR and 386 microsatellite markers were subjected to multipoint nonparametric linkage analysis. Following analysis of the entire set of families, additional analyses were performed after a priori stratification by disease onset type, age at onset, disease course, and selected HLA-DRB1 alleles. RESULTS: Linkage of JRA to the HLA region was confirmed (logarithm of odds [LOD] score 2.26). Additional evidence supporting linkage of JRA was observed at 1p36 (D1S214; LOD 1.65), 19p13 (D19S216; LOD 1.72), and 20q13 (D20S100; LOD 1.75). For early-onset polyarticular disease, evidence of linkage was found at chromosome 7q11 (D7S502; LOD 3.47). For pauciarticular disease, evidence supporting linkage was observed on chromosome 19p13 (D19S216; LOD 2.98), the same marker that supported linkage to the "JRA" phenotype. Other regions supporting linkage with JRA disease subtype included 20q13, 4q24, 12q24, and Xp11. Stratification of families based on the presence of the HLA-DR8 allele in affected siblings resulted in significant linkage observed at 2p25 (D2S162/D2S305; LOD 6.0). CONCLUSION: These data support the hypothesis that multiple genes, including at least 1 in the HLA region, influence susceptibility to JRA. These findings for JRA are consistent with findings for other autoimmune diseases and support the notion that common genetic regions contribute to an autoimmune phenotype.