Rheumatoid Arthritis Loci Research Articles

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

BackgroundEvidence 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.ObjectiveTo investigate single nucleotide polymorphisms...

Locus category based analysis of a large genome-wide association study of rheumatoid arthritis.

To pinpoint true positive single-nucleotide polymorphism (SNP) associations in a genome-wide association study (GWAS) of rheumatoid arthritis (RA), we categorize genetic loci by external knowledge. We test both the 'enrichment of associated loci' in a locus category and the 'combined association' of a locus category. The former is quantified by the odds ratio for the presence of SNP associations at the loci of a category, whereas the latter is quantified by the number of loci in a category that have SNP associations. These measures are compared with their expected values as obtained from the permutation of the affection status. To account for linkage disequilibrium (LD) among SNPs, we view each LD block as a genetic locus. Positional candidates were defined as loci implicated by earlier GWAS results, whereas functional candidates were defined by annotations regarding the molecular roles of genes, such as gene ontology categories. As expected, immune-related categories show the largest enrichment signal, although it is not very strong. The intersection of positional and functional candidate information predicts novel RA loci near the genes TEC/TXK, MBL2 and PIK3R1/CD180. Notably, a combined association signal is not only produced by immune-related categories, but also by most other categories and even randomly defined categories. The unspecific quality of these signals limits the possible conclusions from combined association tests. It also reduces the magnitude of enrichment test results. These unspecific signals might result from common variants of small effect and hardly concentrated in candidate categories, or an inflated size of associated regions from weak LD with infrequent mutations.

Update on the genetic risk factors for rheumatoid arthritis

Rheumatoid arthritis (RA) is a complex disease, meaning that multiple genetic variants, environmental factors and random events interact to trigger pathological pathways. Although many of these etiological factors have not yet been identified, recent groundbreaking advances have expanded our knowledge about the genetic factors that contribute to RA. Here, we review the most recent findings on the genetic risk factors for RA. First, we give an overview of the genetics of RA and briefly describe the susceptibility loci discovered prior to the availability of genome-wide association studies (GWAS). Second, we focus on the newly discovered RA loci that have arisen from GWAS in populations of European ancestry. Through these studies, the number of established RA susceptibility loci has now grown to 13. Third, we discuss several important issues emerging from GWAS, such as ethnic heterogeneity and shared autoimmunity risk loci. Finally, we discuss what still needs to be accomplished before a more complete picture of the genetic risk to RA can be attained.

Peter Julius Denison Heaf

<h3>ABSTRACT</h3> Identifying genomic annotations that differentiate causal from associated variants is critical to fine-map disease loci. While many studies have identified non-coding annotations overlapping disease variants, these annotations colocalize, complicating...

Identification of novel putative rheumatoid arthritis susceptibility genes via analysis of rare variants

Established loci for rheumatoid arthritis (RA), including HLA-DRB1 and PTPN22, do not fully account for the genetic component of susceptibility to the disease. One possible source of as yet undiscovered susceptibility genes are those mediated through effects of rare variants. We present a novel method for gene-based genome-wide scans of whole-genome association (WGA) data to identify accumulations of rare variants associated with disease. We apply our method to WGA SNP genotype data obtained from 868 RA cases and 1194 controls. Our results highlight novel putative RA susceptibility genes that have not previously been identified in large-scale WGA studies.

Use of supplementary phenotype to identify additional rheumatoid arthritis loci in a linkage analysis of 342 UK affected sibling pair families

BackgroundAlthough rheumatoid arthritis has been shown to have moderately strong genetic component, both linked loci identified in linkage analyses and susceptibility variants from association studies are short of adequately accounting for a comprehensive catalogue of the molecular factors underlying this complex disease. The objective of this study was to use supplementary phenotype based on cumulative hazard of rheumatoid arthritis to identify linkage evidence for new and additional rheumatoid arthritis loci in a genome-wide linkage analysis of 342 affected sibling pair families from the United Kingdom.MethodsUsing proportional hazards model, we estimated cumulative hazard of rheumatoid arthritis and then used it as a quantitative trait in a non-parametric multipoint variance component linkage analysis with 353 microsatellite markers distributed across the 22 autosomal chromosomes.ResultsWe identified 3 new loci with genome-wide suggestive linkage evidence for rheumatoid arthritis on 9q21.13, 15p11.1 and 20q13.33. Our results also confirmed previously reported linkage evidence in the HLA-DRB1 region on chromosome 6 and on locus 1q32.1.ConclusionThis study demonstrates the potential for information gain through the use of supplementary phenotypes in genetic study of complex diseases to identify new and additional potential linked loci that are not detected by linkage analysis of traditional phenotypes; and our results provide further evidence of the involvement of multiple loci in the genetic aetiology of rheumatoid arthritis.

Overlap of disease susceptibility loci for rheumatoid arthritis and juvenile idiopathic arthritis

BackgroundGenome-wide association studies (GWAS) have been extremely successful in the search for susceptibility risk factors for complex genetic autoimmune diseases. As more studies are published, evidence is emerging of considerable...

Common and different genetic background for rheumatoid arthritis and coeliac disease

Recent genome-wide association studies (GWAS) have revealed genetic risk factors in autoimmune and inflammatory disorders. Several of the associated genes and underlying pathways are shared by various autoimmune diseases. Rheumatoid arthritis (RA) and coeliac disease (CD) are two autoimmune disorders which have commonalities in their pathogenesis. We aimed to replicate known RA loci in a Dutch RA population, and to investigate whether the effect of known RA and CD risk factors generalize across the two diseases. We selected all loci associated to either RA or CD in a GWAS and confirmed in an independent cohort, with a combined P-value cut-off P < 5 x 10(-6). We genotyped 11 RA and 11 CD loci in 1368 RA patients, 795 CD patients and 1683 Dutch controls. We combined our results in a meta-analysis with UK GWAS on RA (1860 cases; 2938 controls) and CD (767 cases; 1422 controls). In the Dutch RA cohort, the PTPN22 and IL2/IL21 variants showed convincing association (P = 3.4 x 10(-12) and P = 2.8 x 10(-4), respectively). Association of RA with the known CD risk variant in the SH2B3 was also observed, predominantly in the subgroup of rheumatoid factor-positive RA patients (P = 0.0055). In a meta-analysis of Dutch and UK data sets, shared association with six loci (TNFAIP3, IL2/IL21, SH2B3, LPP, MMEL1/TNFRSF14 and PFKFB3/PRKCQ) was observed in both RA and CD cohorts. We confirmed two known loci and identified four novel ones for shared CD-RA genetic risk. Most of the shared loci further emphasize a role for adaptive and innate immunity in these diseases.

Genome‐wide association study of rheumatoid arthritis in the Spanish population: KLF12 as a risk locus for rheumatoid arthritis susceptibility

To identify new genes associated with susceptibility to rheumatoid arthritis (RA), using a 2-stage genome-wide association study. Following a liability-based study design, we analyzed 317,503 single-nucleotide polymorphisms (SNPs) in 400 patients with RA and 400 control subjects. We selected a group of candidate SNPs for replication in an independent group of 410 patients with RA and 394 control subjects. Using data from the 3 previous genome-wide association studies in RA, we also looked for genomic regions showing evidence of common association signals. Finally, we analyzed the presence of genome-wide epistasis using the binary test implemented in the PLINK program. We identified several genomic regions showing evidence of genome-wide association (P < 1 x 10(-5)). In the replication analysis, we identified KLF12 SNP rs1324913 as the most strongly associated SNP (P = 0.01). In our study, we observed that this SNP showed higher significance than PTPN22 SNP rs2476601, in both the genome-wide association studies and the replication analyses. Furthermore, the integration of our data with those from previous genome-wide association studies showed that KLF12 and PTPRT are the unique loci that are commonly associated in 3 different studies (P = 0.004 and P = 0.002 for KLF12 in the Wellcome Trust Case Control Consortium study and the Brigham and Women's Rheumatoid Arthritis Sequential Study genome-wide association study, respectively). The genome-wide epistasis analysis identified several SNP pairs close to significance after multiple test correction. The present genome-wide association study identified KLF12 as a new susceptibility gene for RA. The joint analysis of our results and those from previous genome-wide association studies showed genomic regions with a higher probability of being genuine susceptibility loci for RA.

Association mapping of susceptibility loci for rheumatoid arthritis

We analyzed a case-control data set for chromosome 18q from the Genetic Analysis Workshop 15 to detect susceptibility loci for rheumatoid arthritis (RA). A total number of 460 cases and 460 unaffected controls were genotyped on 2300 single-nucleotide polymorphisms (SNPs) by the North American Rheumatoid Arthritis Consortium. Using a multimarker approach for association mapping under the framework of the Malecot model and composite likelihood, we identified a region showing significant association with RA (p < 0.002) and the predicted disease locus was at a genomic location of 53,306 kb with a 95% confidence interval (CI) of 53,295-53,331 kb. A common haplotype in this region was protective against RA (p = 0.002). In another region showing nominal significant association (51,585 kb, 95% CI: 51,541-51,628 kb, p = 0.037), a haplotype was also protective (p = 0.002). We further demonstrated that reducing SNP density decreased power and accuracy of association mapping. SNP selection based on equal linkage disequilibrium (LD) distance generally produced higher accuracy than that based on equal kilobase distance or tagging.

Analyses of single marker and pairwise effects of candidate loci for rheumatoid arthritis using logistic regression and random forests

Using parametric and nonparametric techniques, our study investigated the presence of single locus and pairwise effects between 20 markers of the Genetic Analysis Workshop 15 (GAW15) North American Rheumatoid Arthritis Consortium (NARAC) candidate gene data set (Problem 2), analyzing 463 independent patients and 855 controls. Specifically, our work examined the correspondence between logistic regression (LR) analysis of single-locus and pairwise interaction effects, and random forest (RF) single and joint importance measures. For this comparison, we selected small but stable RFs (500 trees), which showed strong correlations (r~0.98) between their importance measures and those by RFs grown on 5000 trees. Both RF importance measures captured most of the LR single-locus and pairwise interaction effects, while joint importance measures also corresponded to full LR models containing main and interaction effects. We furthermore showed that RF measures were particularly sensitive to data imputation. The most consistent pairwise effect on rheumatoid arthritis was found between two markers within MAP3K7IP2/SUMO4 on 6q25.1, although LR and RFs assigned different significance levels.Within a hypothetical two-stage design, pairwise LR analysis of all markers with significant RF single importance would have reduced the number of possible combinations in our small data set by 61%, whereas joint importance measures would have been less efficient for marker pair reduction. This suggests that RF single importance measures, which are able to detect a wide range of interaction effects and are computationally very efficient, might be exploited as pre-screening tool for larger association studies. Follow-up analysis, such as by LR, is required since RFs do not indicate high-risk genotype combinations.

Linkage analysis of rheumatoid arthritis in US and UK families reveals interactions between HLA–DRB1 and loci on chromosomes 6q and 16p

HLA is the most strongly associated locus in rheumatoid arthritis (RA), accounting for up to one-third of the genetic contribution. Conditioning on the effect of true disease loci such as HLA can lead to increased power to detect effects at other loci and, in addition, allows investigation of the underlying disease models, including interactions. The aim of this study was to detect susceptibility loci for RA by conditioning on HLA in a large sample of affected sibling pairs (ASPs) and to test for evidence of interaction between novel loci and HLA. Genotype data from 3 whole-genome linkage scans for RA in a US population and a UK population were pooled, resulting in a combined data set of 886 ASPs. This pooling of data increased the power to detect loci showing low levels of heterogeneity. Nonparametric linkage analysis was performed to identify regions of interest. Joint 2-locus analysis was then performed for HLA and each of the loci that demonstrated evidence of linkage in the 886 ASPs. Evidence for linkage was most significant at HLA (P = 4 x 10(-16)), with 7 non-HLA loci showing some evidence for linkage (P = 0.05-0.003). Joint modeling of these loci with HLA provided evidence for linkage at a genome-wide significance level for loci on 6q (P = 2.7 x 10(-6)) and 16p (P = 2 x 10(-4)). These data provide the most convincing evidence to date that 6q and 16p harbor susceptibility genes. In addition, these loci may interact with HLA, facilitating the search for candidate genes within this region.

Development of rheumatoid arthritis is not associated with two polymorphisms in the Crohn's disease gene CARD15.

It has been proposed that genetic susceptibility loci for rheumatoid arthritis (RA) may be shared with other autoimmune/inflammatory diseases. Recently, common variation in the CARD15 (NOD2) gene on chromosome 16q12 has been associated with Crohn's disease (CD) in several independent populations. CARD15 is an excellent functional and positional candidate gene for RA. Genomic DNA was obtained from 392 RA cases and 471 ethnically matched healthy controls. All samples were genotyped for two polymorphisms in CARD15, 1007fs and R702W, using 5' nuclease reporter assays. Allele frequencies were compared between cases and controls using the chi(2) test. Estimated haplotype frequencies across the two mutations were determined using the EH program. The allele frequency of the 1007fs variant in RA cases was 1.8% compared with 1.6% in normal controls (not significant). The frequency of the R702W variant was 4.0% in both cases and controls. Haplotypes carrying either of the two mutations accounted for 5.6% of possible haplotypes. A haplotype carrying both mutations was rare, with estimated frequency <0.01%. This study provided high power to detect an association of similar magnitude to that in Crohn's disease. These data therefore exclude the possibility that the contribution of these mutations to RA is comparable to that seen in CD. Within defined statistical parameters, we excluded a role for the CARD15 1007fs and R702W variants in RA susceptibility. These data do not preclude a role for other polymorphisms in the CARD15 gene in RA susceptibility. Results from other autoimmune and inflammatory diseases will reveal whether the CARD15 gene is in fact a common autoimmune susceptibility locus.

Association between a Single-Nucleotide Polymorphism in the Promoter of the Human Interleukin-3 Gene and Rheumatoid Arthritis in Japanese Patients, and Maximum-Likelihood Estimation of Combinatorial Effect That Two Genetic Loci Have on Susceptibility to the Disease

Genetic variants of interleukin-3 (IL-3), a well-studied cytokine, may have a role in the pathophysiology of rheumatoid arthritis (RA); but reports on this association sometimes conflict. A case-control study was designed to investigate association between RA and a single-nucleotide polymorphism (SNP) in the IL-3 promoter region. Comparison of cases of RA versus control individuals yielded a chi(2) value of 14.28 (P=.0002), with a genotype odds ratio of 2.24 (95% confidence interval [95%CI] 1.44-3.49). When female cases with earlier onset were compared with female control individuals, the SNP revealed an even more significant correlation, with chi2=21.75 (P=.000004) and a genotype odds ratio of 7.27 (95%CI 2.80-18.89). The stronger association that we observed in this clinically distinct subgroup (females with early onset), within a region where linkage disequilibrium was not significantly extended, suggested that the genuine RA locus should locate either within or close to the IL-3 gene. Combined genotype data on SNPs on eight other candidate genes were combined with our IL-3 results, to estimate relationships between pairs of loci and RA, by maximum-likelihood analysis. The utility of combining the genotype data in this way to identify possible contributions of various genes to this disease is discussed.

New susceptibility locus for rheumatoid arthritis suggested by a genome-wide linkage study.

Rheumatoid arthritis (RA), the most common autoimmune disease, is associated in families with other autoimmune diseases, including insulin-dependent diabetes mellitus (IDDM). Its genetic component has been suggested by familial aggregation (lambdas = 5), twin studies, and segregation analysis. HLA, which is the only susceptibility locus known, has been estimated to account for one-third of this component. The aim of this paper was to identify new RA loci. A genome scan was performed with 114 European Caucasian RA sib pairs from 97 nuclear families. Linkage was significant only for HLA (P < 2.5.10(-5)) and nominal for 19 markers in 14 other regions (P < 0.05). Four of the loci implicated in IDDM potentially overlap with these regions: the putative IDDM6, IDDM9, IDDM13, and DXS998 loci. The first two of these candidate regions, defined in the RA genome scan by the markers D18S68-D18S61-D18S469 (18q22-23) and D3S1267 (3q13), respectively, were studied in 194 additional RA sib pairs from 164 nuclear families. Support for linkage to chromosome 3 only was extended significantly (P = 0.002). The analysis of all 261 families provided a linkage evidence of P = 0. 001 and suggested an interaction between this putative RA locus and HLA. This locus could account for 16% of the genetic component of RA. Candidate genes include those coding for CD80 and CD86, molecules involved in antigen-specific T cell recognition. In conclusion, this first genome scan in RA Caucasian families revealed 14 candidate regions, one of which was supported further by the study of a second set of families.