Anne Hinks

Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci

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.

Rheumatoid arthritis association at 6q23

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).

Genetic variants at CD28, PRDM1, and CD2/CD58 are associated with rheumatoid arthritis risk

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.

Whole-Genome Scan, in a Complex Disease, Using 11,245 Single-Nucleotide Polymorphisms: Comparison with Microsatellites

Despite the theoretical evidence of the utility of single-nucleotide polymorphisms (SNPs) for linkage analysis, no whole-genome scans of a complex disease have yet been published to directly compare SNPs with microsatellites. Here, we describe a whole-genome screen of 157 families with multiple cases of rheumatoid arthritis (RA), performed using 11,245 genomewide SNPs. The results were compared with those from a 10-cM microsatellite scan in the same cohort. The SNP analysis detected HLA*DRB1, the major RA susceptibility locus (P=.00004), with a linkage interval of 31 cM, compared with a 50-cM linkage interval detected by the microsatellite scan. In addition, four loci were detected at a nominal significance level (P<.05) in the SNP linkage analysis; these were not observed in the microsatellite scan. We demonstrate that variation in information content was the main factor contributing to observed differences in the two scans, with the SNPs providing significantly higher information content than the microsatellites. Reducing the number of SNPs in the marker set to 3,300 (1-cM spacing) caused several loci to drop below nominal significance levels, suggesting that decreases in information content can have significant effects on linkage results. In contrast, differences in maps employed in the analysis, the low detectable rate of genotyping error, and the presence of moderate linkage disequilibrium between markers did not significantly affect the results. We have demonstrated the utility of a dense SNP map for performing linkage analysis in a late-age-at-onset disease, where DNA from parents is not always available. The high SNP density allows loci to be defined more precisely and provides a partial scaffold for association studies, substantially reducing the resource requirement for gene-mapping studies.

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.

CD226 Gly307Ser association with multiple autoimmune diseases

Genome-wide association studies provide insight into multigenic diseases through the identification of susceptibility genes and etiological pathways. In addition, the identification of shared variants among autoimmune disorders provides insight into common disease pathways. We previously reported an association of a nonsynonymous single nucleotide polymorphism (SNP) rs763361/Gly307Ser in the immune response gene CD226 on chromosome 18q22 with type 1 diabetes (T1D) susceptibility. Here, we report efforts toward identifying the causal variant by exonic resequencing and tag SNP mapping of the 18q22 region in both T1D and multiple sclerosis (MS). In addition to the analysis of newly available samples in T1D (2088 cases and 3289 controls) and autoimmune thyroid disease (AITD) (821 cases and 1920 controls), resulting in strong support for the Ser307 association with T1D (P=3.46 × 10−9) and continued potential evidence for AITD (P=0.0345), we provide evidence for association of Gly307Ser with MS (P=4.20 × 10−4) and rheumatoid arthritis (RA) (P=0.017). The Ser307 allele of rs763361 in exon 7 of CD226 predisposes to T1D, MS, and possibly AITD and RA, and based on the tag SNP analysis, could be the causal variant.

Rheumatoid arthritis susceptibility loci at chromosomes 10p15, 12q13 and 22q13.

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.

Re-evaluation of putative rheumatoid arthritis susceptibility genes in the post-genome wide association study era and hypothesis of a key pathway underlying susceptibility

Rheumatoid arthritis (RA) is an archetypal, common, complex autoimmune disease with both genetic and environmental contributions to disease aetiology. Two novel RA susceptibility loci have been reported from recent genome-wide and candidate gene association studies. We, therefore, investigated the evidence for association of the STAT4 and TRAF1/C5 loci with RA using imputed data from the Wellcome Trust Case Control Consortium (WTCCC). No evidence for association of variants mapping to the TRAF1/C5 gene was detected in the 1860 RA cases and 2930 control samples tested in that study. Variants mapping to the STAT4 gene did show evidence for association (rs7574865, P = 0.04). Given the association of the TRAF1/C5 locus in two previous large case–control series from populations of European descent and the evidence for association of the STAT4 locus in the WTCCC study, single nucleotide polymorphisms mapping to these loci were tested for association with RA in an independent UK series comprising DNA from >3000 cases with disease and >3000 controls and a combined analysis including the WTCCC data was undertaken. We confirm association of the STAT4 and the TRAF1/C5 loci with RA bringing to 5 the number of confirmed susceptibility loci. The effect sizes are less than those reported previously but are likely to be a more accurate reflection of the true effect size given the larger size of the cohort investigated in the current study.

Study of the common genetic background for rheumatoid arthritis and systemic lupus erythematosus

Background Evidence is beginning to emerge that there may be susceptibility loci for rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) that are common to both diseases. Objective To investigate single nucleotide polymorphisms that have been reported to be associated with SLE in a UK cohort of patients with RA and controls. Methods 3962 patients with RA and 9275 controls were included in the study. Eleven SNPs mapping to confirmed SLE loci were investigated. These mapped to the TNFSF4, BANK1, TNIP1, PTTG1, UHRF1BP1, ATG5, JAZF1, BLK, KIAA1542, ITGAM and UBE2L3 loci. Genotype frequencies were compared between patients with RA and controls using the trend test. Results The SNPs mapping to the BLK and UBE2L3 loci showed significant evidence for association with RA. Two other SNPs, mapping to ATG5 and KIAA1542, showed nominal evidence for association with RA (p=0.02 and p=0.02, respectively) but these were not significant after applying a Bonferroni correction. Additionally, a significant global enrichment in carriage of SLE alleles in patients with RA compared with controls (p=9.1×10−7) was found. Meta-analysis of this and previous studies confirmed the association of the BLK and UBE2L3 gene with RA at genome-wide significance levels (p<5×10−8). Together, the authors estimate that the SLE and RA overlapping loci, excluding HLA-DRB1 alleles, identified so far explain ∼5.8% of the genetic susceptibility to RA as a whole. Conclusion The findings confirm the association of the BLK and UBE2L3 loci with RA, thus adding to the list of loci showing overlap between RA and SLE.

Combined effects of three independent SNPs greatly increase the risk estimate for RA at 6q23

The most consistent finding derived from the WTCCC GWAS for rheumatoid arthritis (RA) was association to a SNP at 6q23. We performed a fine-mapping of the region in order to search the 6q23 region for additional disease variants. 3962 RA patients and 3531 healthy controls were included in the study. We found 18 SNPs associated with RA. The SNP showing the strongest association was rs6920220 [P = 2.6 × 10−6, OR (95% CI) 1.22 (1.13–1.33)]. The next most strongly associated SNP was rs13207033 [P = 0.0001, OR (95% CI) 0.86 (0.8–0.93)] which was perfectly correlated with rs10499194, a SNP previously associated with RA in a US/European series. Additionally, we found a number of new potential RA markers, including rs5029937, located in the intron 2 of TNFAIP3. Of the 18 associated SNPs, three polymorphisms, rs6920220, rs13207033 and rs5029937, remained significant after conditional logistic regression analysis. The combination of the carriage of both risk alleles of rs6920220 and rs5029937 together with the absence of the protective allele of rs13207033 was strongly associated with RA when compared with carriage of none [OR of 1.86 (95% CI) (1.51–2.29)]. This equates to an effect size of 1.50 (95% CI 1.21–1.85) compared with controls and is higher than that obtained for any SNP individually. This is the first study to show that the confirmed loci from the GWA studies, that confer only a modest effect size, could harbour a significantly greater effect once the effect of additional risk variants are accounted for.