Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Rheumatoid arthritis: a view of the current genetic landscape


The field of genetics and autoimmune diseases is undergoing a rapid and unprecedented expansion with new genetic findings being reported at an astounding pace. It is now clear that multiple genes contribute to each of the major autoimmune disorders, with significant genetic overlaps among them. Rheumatoid arthritis (RA) is no exception to this, and emerging data are beginning to reveal the outlines of new diagnostic subgroups, complex overlapping relationships with other autoimmune disorders and potential new targets for therapy. This review describes the evolving genetic landscape of RA, with the full knowledge that our current view is far from complete. However, with the first round of genome-wide association scans now completed, it is reasonable to begin to take stock of the direction in which the major common genetic risk factors are leading us.


Rheumatoid arthritis (RA) is the most common single cause of chronic synovitis, affecting multiple diarthroidial joints in a characteristic distribution, and leading to pain, deformities and a reduced quality of life. The precise aetiology of RA has not been established, but epidemiologic data as well as the current genetic data clearly reflect a complex genetic component, along with a largely unknown, and presumably variable contributions by environmental factors.1, 2 The diagnosis of RA continues to be based on clinical criteria established over two decades ago3 and it is quite likely that these criteria mask considerable underlying heterogeneity in both genetic background and disease mechanisms. This is most clearly demonstrated by the discovery of antibodies to citrullinated peptides as being quite specific to a major subset of RA,4 with distinct genetic and clinical outcomes as discussed in this review.

Although much of the recent excitement in the field has resulted from the utilization of genome-wide association studies (GWAS)5, 6 to search for genes outside the major histocompatibility complex (MHC), it is important to remember that the single most important contribution to genetic risk for RA clearly still resides within the MHC.6, 7 Somewhat similar to the genetic associations with type 1 diabetes, a general pattern has emerged where most of the non-MHC associations are far more modest in terms of odds ratios, compared with the well-established human leukocyte antigen (HLA) class II associations.8, 9 The MHC associations with RA also provide the clearest demonstration that the presence of anti-cylclic citrullinated peptide (anti-CCP) antibodies constitutes a distinct genetic subgroup of RA.10 Therefore, we begin this review with a discussion of the MHC, highlighting evidence for additional genetic complexity, beyond the well-defined associations with the HLA-DRB1 locus.

RA associations in the MHC region: going beyond the ‘shared epitope’

The original description of HLA-DR4 associations with RA in the 1970s11 evolved during the 1980 and 1990s to include associations with a variety of distinct HLA-DRB1 alleles.8, 9 This complex pattern of associations led to the proposal of the shared epitope (SE) hypothesis in 1987, based on the observation that there is a shared common sequence among the DRB1 associated with RA.12 This hypothesis has remained a significant driving force for experimental attempts to identify the causal explanations for these disease associations. The location of the SE on the DRB1 structure is consistent with a variety of hypotheses, but the recent demonstration that SE alleles are specifically associated with anti-citrulline antibody production10, 13, 14 provides support for the idea that alleles bearing this determinant are acting at least in part as a classic immune response elements, as originally described by the seminal studies of McDevitt and colleagues.15 Other hypotheses16 remain viable as alternative or additional mechanisms. In addition, it is now clear that there is a complex hierarchy of risk conferred by the various DRB1 genoypes,17 and this cannot be entirely accounted for by the SE hypothesis alone. However, given the very strong associations with various DRB1 alleles, it is highly likely that these molecules are directly involved in pathogenesis at some level. On the other hand, the advent of high throughput single-nucleotide polymorphism (SNP) mapping has now shown that the DRB1 locus is not the only gene in the MHC that is involved in RA disease susceptibility. Early hints of this additional complexity emerged over the last decade.18, 19, 20, 21 Several recent studies using dense SNP mapping across the MHC have provided further confirmation, although the details and identification of specific causative loci remain to be established.10, 22

Ding et al.10 have demonstrated a striking difference in the patterns of association across the MHC when comparing anti-CCP+ and anti-CCP− RA. Using a panel of 2221 SNP markers, a case–control analysis of over 1200 anti-CCP+ cases and 1700 controls shows strong evidence of association across a broad region of the MHC (Figure 1a). In contrast, a similar analysis of CCP− RA (over 600 cases and 600 controls) shows minimal evidence of association, with no significant association after correction for multiple testing. This is quite consistent with previous data showing that the HLA-DRB1 associations are overwhelmingly observed in the anti-CCP+ disease subset.13, 14

Figure 1

Case–control analysis for 2221 single-nucleotide polymorphisms spanning 10.7 Mb from 6p22.2 (26.03 Mb) to 6p21.31 (36.80 Mb) across the extended major histocompatibility complex region. Chromosome position is shown on the x axis; the y axis shows the –log P-value. (a) Case–control association statistics by Amitage trend test for anti-CCP+ RA vs control group. (b) Case–control association statistics by Amitage trend test for the anti-CCP− RA vs control group. Taken from Ding et al.10

As can be seen in Figure 1a, there is a broad group of significant association signals surrounding the DRB1 locus in anti-CCP+ RA, extending out over several megabases. Indeed, nearly 300 SNPs reached locus wide significance in this study. To sort out whether these signals can be explained by linkage disequilibrium with the known DRB1 risk alleles, a conditional analysis based on DRB1 genotype was carried out. Because there is a hierarchy of risk levels with the various DRB1 genotypes, a conditional analysis must be performed with some care; simple stratification on the presence or absence of the SE alone will not adequately control for the variable patterns of linkage disequilibrium that may exist for different SE alleles. Using several different approaches, Ding et al. provide convincing evidence for a second locus of association with RA, centromeric to DR and DQ, with maximal signal at the DPB1 locus. Additional signals were also observed in the central MHC and the class I region at MICA.

An alternative approach to conditioning the analysis on DRB1 was taken by Lee et al.,22 in which cases and controls were matched 1:1 on the basis of DRB1 genotype.22 This was carried out on a US cohort of CCP+ RA samples, a subset of the data set reported by Ding et al. (which contained both Swedish and US samples). In addition, a somewhat different set of SNPs were utilized, all of which are present on the Illumina 550K HapMap chip. The results of this analysis are shown in Figure 2, for 372 cases matched with 372 controls. Note that the χ2=0 for the DRB1 locus in this analysis, as the samples are completely matched by DRB1 genotype. Strikingly, several significant association signals are present, including the regions centromeric to DR observed by Ding et al. In addition, a strong signal is observed at the border between the class I region and the central MHC, with other weaker signals farther out in the class I region. This is consistent with previous studies based on microsatellite typing.20

Figure 2

Chi-square test (χ2) statistics from the 2-by-2 allele count table of 744 case–control samples matched 1:1 by DRB1 genotype (372 cases and 372 controls). Note that χ2 value=0 at DRB1, as these samples are matched at this locus. The signals are divided into + and − according to whether the single-nucleotide polymorphisms are characteristically found on the common A1-B8-DR3 haploytpes (see Lee et al.22 for details).

These data clearly demonstrate the complexity of the MHC associations and confirm that DRB1 is not the only risk locus in the region. The additional signals in class I are reminiscent of recent findings in type 1 diabetes, in which HLA-B39 has been shown to be an independent risk factor.23 The lack of extensive class I typing data in RA has not permitted a detailed examination of the classical class I alleles in this regard. Overall, these data raise a number of new hypotheses, including the possibility that interactions with killer inhibitor receptor loci may contribute to RA susceptibility, as has been suggested in one report on rheumatoid vasculitis.24 The more centromeric effects may be due to DPB1, DOB or other loci in the region that influence peptide binding and presentation. These observations must now be confirmed and refined in larger data sets.

Non-MHC genes associated with RA

Candidate gene studies and GWAS have led to the identification of numerous genes associated with RA outside of the MHC. Two recent large genome-wide association scans have contributed substantially in this regard.5, 6 In some cases, linkage data have led to gene identification; this is the case for signal transducer and activator of transcription 4 (STAT4)25 and to some extent PTPN22.26 More recently, candidate gene studies based on the results of genome-wide studies in other autoimmune disorders have been useful for finding new associations with RA; the recent reports of RA associations in the region of 4q27 are an example of this.27

We will review here the most significant findings as we see them now, fully aware that the field is rapidly producing convincing evidence for additional associations. Many findings that are now considered of borderline significance will likely be confirmed and implicate important new disease pathways, whereas other intriguing reports that are emerging in the literature may fail to be replicated when statistically well-powered studies are performed. In addition, as discussed below, there are clearly important differences among the major ethnic groups with regard to the sets of genes underlying RA, and this issue has not yet been addressed in a comprehensive manner. Finally, the identification of clinical subsets of RA is going to be important for understanding the genetics of RA, as is clearly demonstrated by the consideration of MHC association in the context of anti-CCP antibody status. Additional fine-grained phenotyping for immunological subgroups, disease biomarkers and clinical outcome are likely to substantially enhance the value of comprehensive genetic studies.


The intracellular phosphatase, PTPN22, exhibits the strongest and most consistent association with RA, second only to the MHC. The original PTPN22 association with type 1 diabetes resulted from a candidate gene analysis and initiated a flood of studies of this locus.28 At about the same time, Ann Begovich et al.29 initiated a ‘functional’ genome-wide SNP scan of several thousand likely candidate genes, and the prioritization was informed by linkage data, including linkage at chromosome 1p13,30 the chromosomal location of PTPN22. Thus, the discovery of the association of PTPN22 with type 1 diabetes and RA actually emerged from two separate and complementary approaches to gene identification. The association of PTPN22 with RA has been confirmed by numerous studies in various Caucasian populations,31 including both major GWAS.5, 6

The PTPN22 risk allele is due to a 1885C>T polymorphism (rs2476601), encoding an amino acid change from Arg to Trp at amino acid position 620. This polymorphism resides in a rather large haplotype block encompassing the entire PTPN22 gene as well as several flanking loci. Indeed, in the recent WGA scan reported by the Welcome Trust, the PTPN22 association was actually picked up by a maker that is outside of the PTPN22 gene itself.5 Thus, as with all association studies, the question is whether the polymorphism used to identify the association is actually the causative variant. Resequencing of the PTPN22 locus by Carlton et al.32 showed that the 620W allele was the only variant that distinguished the risk haplotype from a second non-associated haplotype. Modest evidence for associations with additional haplotypes in this report has not been replicated. The importance of the 620W allele is further supported by the fact that there is no association with PTPN22 in the Asian population, and indeed Asian populations rarely carry the 620W variant. Recently, a small study of Asiatic Indians with rheumatoid factor-positive RA showed an association of the 1885C>T polymorphism with RA;33 in this population the allele frequency of the risk allele was lower than in Caucasians. Attempts to identify additional PTPN22 variants that may associate with RA in Asian population have not been successful34, 35 Thus, although the genetic data are not totally comprehensive across the entire risk haplotype, it is highly likely that the 620W allele is directly responsible for the associations with RA.

A striking aspect of the PTPN22 620W allele is the fact that it is associated with a wide variety of autoimmune disorders, with some interesting exceptions. Positively associated diseases includes Grave's disease,36, 37, 38 Hashimoto thyroiditis,39 Myasthenia Gravis40 systemic sclerosis,41 generalized vitiligo42 Addison's disease43 and alopecia areata.44 Associations with juvenile idiopathic arthritis45, 46, 47 and systemic lupus48, 49 have generally been weaker than for RA and type 1 diabetes. Strikingly, there is no evidence of association with multiple sclerosis29, 50 and the 620W allele actually appears to be protective for Crohn's Disease.51 These contrasting patterns of association are likely to reflect fundamental differences in the mechanisms underlying the pathogenesis of these disorders. In general, it appears that an important feature of the PTPN22-associated diseases is that they all have a prominent component of humoral autoimmunity.

Knockout animals for PEP (the mouse ortholog of PTPN22) exhibit enhanced T-cell activation in combination with an increased production of antibodies.52 This is consistent with the ability of PTPN22 to dephosphorylate Lck at the activating phosphotyrosine 394. Yet, somewhat surprisingly, it is increasingly apparent that the consequence of the 620W risk allele is a lower degree of T-cell activation (an increased threshold for TcR signalling).53, 54 The immediate biochemical consequence of the 620W polymorphism is to reduce the binding of PTPN22 with the intracellular kinase, Csk.26, 28 Indeed, amino acid position 620 of PTPN22 is located within one of several SH3-binding sites in the PTPN22 molecule. An important role of Csk is to inhibit LcK activity by phosphorylation of aa 508 of the Lck molecule.55 It is not clear if this particular activity is affected by the 620W polymorphism in PTPN22. Bottini and co-workers have proposed a model for interactions between Lck, PTPN22 and Csk that may explain the elevation of thresholds for TCR signalling (Bottini et al., manuscript submitted), with the overall implication that reduced rather than elevated T-cell triggering may be part of the phenotypic predisposition to autoimmunity. A similar tendency to increased thresholds for receptor triggering has also been reported in B cells.54 It should be pointed out that PTPN22 is widely expressed in many hematopoietic cell types, and the function of PTPN22 in these cells is largely unknown. PTPN22 has also been reported to be involved in the activation of endogenous cannabinoids.56 Thus, the exact mechanism for this genetic association is still unresolved, and indeed there could be multiple mechanisms. In this respect, the PTPN22 is an excellent example of how gene discovery is hypothesis generating, and the number of hypotheses can be quite large, even for a single-genetic association.

Finally, the study of PTPN22 is instructive because it emphasizes the importance of taking population substructure into account when performing case–control analysis. Just as the 620W allele shows dramatic frequency differences among the major racial groups (the allele is virtually absent in Asians), this variant shows a striking gradient of increasing frequency going south to north in European populations,26 as illustrated in Figure 3. This emphasizes that matching cases and controls by ancestry, even within the major racial groups, is essential for carrying out reliable genetic association studies. Thus, candidate gene association studies that do not attempt to take account of ancestry are likely to be flawed, especially when modest effects are being examined. Ancestry determination by self-report is not a reliable method of doing this, and in any case, this information is frequently not available. Fortunately, recent advances in the analysis of European population substructure57, 58 now permit the selection of panels of SNP markers that can correct for this source of error analytically;59 hopefully these marker sets will soon become available as standard products for genetic studies.

Figure 3

Map showing the distribution of PTPN22 minor allele frequencies across Europe for the R620W (1858C>T) variant. Taken from Gregersen et al.31

The TRAF1-C5 region

On the basis of recent whole-genome association data,6 the TRAF1-C5 region appears to be the next most important association with RA, after PTPN22. This association was simultaneously detected by the North American/Swedish genome-wide association study as well as a Dutch group using a candidate gene approach.6, 60 The most strongly associated SNPs, rs3761847 in the genome-wide approach and rs10818488 in the candidate gene study, showed a P-value of 4 × 10−14 and 1.4 × 10−8, respectively. Although the association of the TRAF1-C5 region with RA is now confirmed, the WTCCC genome-wide association study did not detect significant association in this region.5 However, in the WTCCC study neither rs3761847 nor rs10818488 were genotyped. In addition, the phenotypic background of the patients since the WTCCC study was not restricted to anti-CCP+ patients. A recent replication study in a large British cohort in combination with imputed data from the WTCCC genome-wide scan has confirmed the association of the TRAF1-C5 region with RA,61 with stronger evidence of association for the anti-CCP+ RA patients. These results emphasize the importance of sample size and phenotypic subtyping when trying to detect genetic signals of relatively modest effect. Unless sample sizes are extremely large, the confidence intervals for these modest associations tend to be broad, making type II error a distinct possibility even with sample sizes in the thousands.

The maximal genetic signals from the current studies are located between the TRAF1 and C5 genes, and also potentially implicate a third gene in the region, PHD finger protein 19 (PHF19). Both TRAF1 and C5 are compelling candidate genes for RA. C5 codes for complement component 5 that could contribute to the development of RA through tissue destruction as well as the mobilization of inflammatory and synovial cells.62 C5-deficient mice as well as mice treated with antibodies directed against C5a are protected from collagen-induced arthritis.63, 64 Complement components and regulatory molecules have long been known to be present in synovial tissues.65, 66, 67 Indeed, inhibition of C5a receptor signalling is an appealing therapeutic target, although recent human trials have been disappointing.68 Nevertheless, the central role of complement in the inflammatory process makes C5 a plausible candidate gene in this region.

The tumor necrosis factor (TNF) receptor-associated factor 1 (TRAF1) is a member of the TNF receptor-associated factor (TRAF) family, a group of adaptor proteins that link TNF receptor family members (for example, TNF-α) to downstream signalling.69 The molecules are involved in signalling pathways that play a role in cell proliferation and differentiation, apoptosis, bone remodelling and activation or inhibition of cytokines. The role of TRAF1 in apoptosis has been demonstrated in mice, where overexpression of TRAF1 resulted in a reduced antigen-induced apoptosis of the CD8+ T-lymphocytes.70 TRAF1 also has a antiproliferative effect: TRAF1 knock-out mice respond to TNF signalling through the TNF receptor 2 with an enhanced T-cell proliferation and activation of the nuclear factor (NF)-κB signalling pathway.71 TRAF1 is also regulated by, and has a role in, CD40 signalling,72 a provocative fact given that CD40 is likely to be associated with risk for RA.73 Such studies suggest that associations in the TRAF1/C5 region with RA may be related to alterations in the regulatory activity of TRAF1.

Finally, the plant homeodomain-finger protein 19 (PHF19) involved in differentiation and cell cycle regulations is also in linkage disequilibrium with the SNPs RA associated in the TRAF1-C5 region. Based on its function,74 PHF19 does not seem to be an obvious candidate an RA susceptibility gene, although additional studies will clearly be necessary to determine which gene/variant in the TRAF1-C5 region is ultimately responsible for the increased susceptibility to RA.

Signal transducer and activator of transcription 4

In comparison with PTPN22 and even TRAF1, the RA association with STAT4 is quite modest, with an estimated relative risk of approximately 1.25.25 The discovery of the STAT4 associations with RA was the result of genetic mapping efforts focused on a linkage peak on chromosome 2q. While linkage peaks in RA have historically been challenging to replicate using traditional microsatellite markers, a replication of linkage using a more robust SNP genotyping methodology revealed significant linkage on chromosome 2q7. Follow-up dense association mapping in the region led to definitive evidence for association with STAT4 in both RA and systemic lupus.25

Interestingly, the GWAS in RA have not pointed strongly to STAT4 as a risk gene, and this undoubtedly relates to the very modest odds ratios for this association. In contrast, the odds ratios for STAT4 associations with lupus are considerably stronger, and thus STAT4 emerges as a prominent association signal in genome-wide association scans in systemic lupus erythematosus.48, 49 Unlike PTPN22, the STAT4 associations with both RA and lupus are also observed in Asian populations,75, 76 thus confirming STAT4 as an important common risk gene for these two diseases in both Caucasian and Asian populations. STAT4 is also associated with Sjogren's syndrome;77 it seems likely that STAT4 will be involved in other autoimmune disorders as well, although definitive studies have not yet been published.

Fine mapping and resequencing of the STAT4 risk haplotype continues to support the view that the causative alleles are likely to be located within the third intron of this gene (EF Remmers et al., unpublished data). The risk haploype is common in the Caucasian populations, with a frequency of 0.22, and this background population frequency is quite stable across various European sub-populations. The intronic location of the associated SNPs is consistent with functional changes in either the splice patterns or levels of expression.

Signal transducer and activator of transcription 4 is a member of the STAT family of transcription factors, of which there are six main members, each with distinct roles in cytokine receptor signalling.78 STAT4 is a key molecule for interleukin (IL)-12 signalling in T cells and natural killer cells, leading to the production of interferon-γ and differentiation of CD4T cells into a Th1 phenotype79). Upon IL-12R binding by IL-12, STAT4 is phosphorylated and forms homodimers. These homodimers are translocated in the nucleus where they initiate transcription of STAT4 target genes, including interferon-γ.80 Thus, STAT4 −/− mice, do not respond to IL-12, lack Th1 responses and have a predominantly Th2 immune response phenotype.81 Interestingly, these mice are also resistant to experimental arthritis.82

Relatively little is known about how the expression of STAT4 itself is regulated at the transcriptional level. STAT4 is expressed in resting CD4+ T cells and natural killer cells and in Jurkat cells. STAT4 transcription has been shown to be regulated in part by Ikaros, a zinc-finger transcription factor known to be involved in hematopoietic cell differentiation.83 In contrast, STAT4 is not constitutively expressed by monocytes or immature dendritic cells, but can be induced upon activation and maturation.84 In the case of dendritic cells, NF-κB/Rel proteins have been shown to upregulate STAT4 transcription during the differentiation into mature human dendritic cells in response to lipopolysaccharide, CD40 stimulation or other activators.85 In this case, the induction of STAT4 transcription in these cells is dependent on the combination of TNF-α and IL-1β. The published work on STAT4 transcriptional regulation is focused on the promoter region 5′ to the gene85 and there is no information concerning the potential role of intronic regions in the regulation of STAT4. Specifically, the SNPs that we have found to be associated with RA and systemic lupus erythematosus are over 50 kb distant from the 5′ promoter region and show no evidence of linkage disequilibrium with SNPs that are more 5′ in the gene. It is nevertheless intriguing that a recent study reports that a different level of expression of STAT4 in osteoblasts, but not T cells, is correlated with the STAT4 risk haplotype.86 Thus, intronic variation in STAT4 may influence cell type-specific gene expression through mechanisms that are yet to be defined. Interestingly, Balb/c mice demonstrate significant differences in STAT4 expression from other strains,87 but this difference appears to be restricted to macrophages, again emphasizing the importance of examining the relevant cell type when attempting to correlate changes in expression with genotype.

Targeting STAT4 by inhibitory oligodeoxynucleotides or antisense oligonucleotides results in suppression of the disease in arthritis models,82 and as mentioned above, STAT4 knock-out mice are highly resistant to the induction of proteoglycan-induced arthritis. In RA patients, the high expression of STAT4 in dendritic cells in the synovium disappears after treatment with disease modifying anti-rheumatic drugs.88, 89 These studies and the association of STAT4 with RA suggest that STAT4 might be a potential therapeutic target.

6q23 region

The association of the 6q23 region with rheumatoid arthritis has been reported by two independent groups of investigators in the UK and the US.5, 90 The original association found in the WTCCC report has been replicated to achieve genome wide levels of significance, and the association is predominantly found in the CCP+ disease subgroup in a UK replication study.91 The same region was found in a study analyzing only 397 anti-CCP+ RA patients using the Affymetrix 100K GeneChip microarray.90 The top 90 non-MHC genes found associated with RA were used for a replication study in two additional cohorts, resulting in the confirmation of the association of SNP rs10499194 in the 6q23 region with RA. The SNP rs6920220 identified in the WTCCC study is located only 4 kb away from marker rs10499194. However, fine mapping of the region followed by regression analysis showed that these two signals are independent, and a haplotype analysis using these two SNPs showed that a two-allele model of risk provided the strongest risk predictor (P=2.8 × 10−12). Construction of a haplotype tree indicated the haplotype tagged by rs1099194 as protective, whereas the haplotype tagged by rs6920220 is the risk haplotype.90

The RA-associated SNPs in the 6q23 region are located at more than 150 kb distance from the nearest genes, TNF-α-induced protein 3 and oligodendrocyte transcription factor 3. All studies published so far point to a role of oligodendrocyte transcription factor 3 in the development of neuronal cells, without any specific involvement in immune function.92, 93 In contrast, TNF-α-induced protein 3, also known as A20, is an attractive candidate gene for autoimmunity. A20 is a TNF-inducible zinc-finger protein that acts in the cytoplasm to regulate and restrict the duration of both TNF and Toll-like receptor-induced NF-κB signals.94, 95, 96 Overexpression of the protein leads to a block of NF-κB activation including that of the TNF and Toll-like receptor signalling pathways, while A20-deficient mice show severe inflammation affecting multiple organs including the joints.97 A very recent analysis of the associations of A20 in lupus98 show that at least three independent genetic effects exist with the A20 locus, and one of these variant results in an amino acid changes in the A20 protein (phe127cys). Preliminary studies suggest that this amino acid change has functional consequences in terms of the ability to inhibit TNF-induced NF-kB activation. These findings suggest that TNF-α-induced protein 3/A20 plays a critical role in autoimmunity, including RA, and may act in pathways suggested by other genetic findings such as CD40 and TRAF1.

Peptidylarginine deiminases citrullinating enzyme 4

An association between RA and peptidylarginine deiminases citrullinating enzyme 4 (PADI4) was originally reported in a large Japanese case–control study, initiated as a fine-mapping study of a linkage region on chromosome 1p36.99 This has been replicated in both Japanese and Korean RA studies, and must be considered a confirmed association in Asian populations. In contrast, it has been difficult to demonstrate an association with PADI4 in Caucasian populations, and it clearly has a much weaker genetic effect in this racial group.100 This is of course reminiscent of the contrasting (but reversed) pattern of the PTPN22 associations with RA in these two racial groups. In the case of PTPN22, the causative risk allele is simply not present in Asian populations. However, in the case of PADI4, the causative alleles have not been established, so that the reason for these racial differences are not necessarily related to differing patterns of allelic diversity in the two racial groups.

Peptidylarginine deiminases citrullinating enzyme 4 is one of several isoenzymes that carry the posttranslational conversion of arginine residues to citrulline, and this may be related to the production of anti-citrulline antibodies that are a characteristic of a major subset of RA4. PADI4 is highly expressed in bone marrow and peripheral blood leukocytes and is also present in the sublining of synovial tissue.101 The catalytic activity of PADI4 is highly dependent on Ca2+ and pH. During apoptosis the cellular Ca2+ levels increase leading to the activation PADI4. Apoptosis is detected in fibrin deposits in the synovium of RA patients, in addition fibrin present in the synovium is citrullinated and co-localizes with PADI4.102 In the original report of the PADI4 association with RA, an increased expression of anti-CCP related to the PADI4 risk haplotype was reported.101 More recently, Hung et al.103 showed a higher activity of PADI4 and apoptosis in cells containing the three non-synomynous SNPs from the RA-susceptibility haplotype compared to the non-susceptibility haplotype. The higher activity might be caused by the higher stability of the protein encoded by the susceptibility haplotype. A Korean study detected an association between the risk haplotype and the level of anti-CCP expression only in early RA.104 Thus, the mechanism and relationship of PADI4 susceptibility haplotypes to disease pathogenesis warrants further investigation.

Given the likely importance of anti-citrulline antibodies in the pathogenesis of anti-CCP+ RA, the PADI4 association with RA in Asians is gratifying, and it is in fact somewhat disconcerting that this same association is not present more pominently in Caucasian groups. One explanation may relate to differences in environmental factors in these populations. It is clear that smoking is a risk factor for anti-CCP+ disease.105, 106 Conceivably such environmental risk factors for developing anti-CCP antibodies may predominate in Western female populations, and mask the effects of more modest genetic predisposition that is operative in Asian societies. Further detailed epidemiologic studies of this issue are clearly warranted.

4q27 region

The chromosome 4q27 region was originally associated with the inflammatory disorders coeliac disease and type I diabetes in two GWAS, suggesting a general role of this region with autoimmune disorders.107, 108 This hypothesis was strengthened by a subsequent study confirming the role of the region in type I diabetes and detecting an association with RA27. The 4q27 region is also associated with psoriatic arthritis and Grave's disease.107, 109 Thus, the 4q27 region provides a reprise of the general theme that common genes provide risk for multiple autoimmune disorders.

The associated region contains 4 genes: KIAA1109, Tenr, IL-2 and IL-21. Tenr is exclusively expressed in the testis;110 KIAA1109 is more widely expressed, but the function of this gene is unknown. In contrast, both IL-2 and IL-21 have obvious potential relevance to the pathogenesis of RA. Recent data have especially highlighted IL-21 as a likely candidate gene and potential pathway for therapeutic intervention. IL-21 is produced by activated CD4+ and NKT cells, co-stimulates the proliferation and differentiation of T and B cells and natural killer cells.111 IL-21 has recently been implicated in the development of Th17 cells,112 and appears to be uniquely required for the initiation of this differentiation pathway in naive CD4 cells. Peripheral blood and synovial T cells of RA patients show higher proliferation as well as an enhanced secretion of the proinflammatory cytokines TNF-α and interferon-γ after stimulation with IL-21 than T cells from healthy individuals and patients with osteoarthritis.113 Arthritis mouse and rat models treated with IL-21 receptor Fc fusion proteins show an improvement of the disease-related symptoms and histologic parameters.114 These studies suggest a direct role of IL-21 in the development of RA, and also utility as a potential therapeutic target.

Although IL-2 was originally identified as a growth factor for T cells, animals lacking this cytokine have fairly normal development to their immune system. However, knockout animals for IL-2 itself or its receptors (CD25 and CD122) develop lethal autoimmune and autoinflammatory syndromes.115 This is due to defects in T-regulatory cell growth and development. Therefore, IL-2 pathways are clearly a prime candidate for causative risk alleles in human autoimmunity, including RA. In addition to evidence for involvement of IL-2 from associations on chromosome 4q, the WTCCC study provided evidence of association of the IL-2 receptor with RA as well as type 1 diabetes.5 Thus, both IL-2 and IL-21 are leading candidate genes for RA susceptibility in the 4q27 region.

Other genes associated with RA

In addition to the associations discussed above, several other genes have been reported as associated with RA susceptibility, with variable degrees of statistical evidence. In many instances, this is likely to reflect a real, but modest, effect on risk. For example, a cytotoxic T-lymphocyte-associated protein 4 is highly likely to contain true risk alleles for RA. In a cohort comprising >4000 samples an OR of 1.23 (P=0.001) was found, and the association was stronger in anti-CCP+ patients.100 A recently completed large genome scan and extension study has confirmed the cytotoxic T-lymphocyte-associated protein 4 association at genome-wide levels of significance (PK Gregersen et al., unpublished). Such small risk increases can only be detected in very large cohorts explaining the lack of unequivocal association in smaller cohorts, including the major published GWAS.

A recent meta-analysis73 of published GWAS in RA has revealed evidence for additional risk loci. The evidence for association with CD40 achieves genome-wide significance (OR =0.89, P=5.1 × 10−9), and the evidence for association with alleles in the CCL21 locus on chromosome 9p13 and near the TNFRSF14 locus on 1p36 is also suggestive, among others. Thus, it is highly likely that multiple additional associations remain to be discovered.


In this review, we have focused on recent genetic findings in RA for which robust statistical evidence exists. In many cases, such as PTPN22, STAT4 and PADI4, it is likely that the genes are somehow directly involved in disease pathogenesis, although only for PTPN22 a causative allele has been identified. For other regions of confirmed association, the causative locus is still in question. For some groups of genes, such as TRAF1, TNF-α-induced protein 3 and CD40, hints of common interlocking pathways and relationships are emerging, even if the causative variants are not definitively established. An additional advance has been the clear demonstration that the MHC region contains multiple risk loci in addition to DRB1.

All of these disease associations involve relatively common genetic variants. It may well be that multiple rare variants explain some of these associations. The investigation of the contribution of rare variation to risk for common complex disorders is challenging, and there is currently only one clear example of this for the common autoimmune disorders.116 Similarly, the role of copy number variation in autoimmunity is only beginning to be explored. There is evidence that this area is more likely to be of considerable relevance to autoimmunity, including copy number variation at the Fcgr3 locus as a risk factor for systemic autoimmunity in humans,117 and copy number variation at the β-defensin locus has been associated with risk for Crohn's disease. 118Another example involves segmental duplications in the CCL3L1 gene and susceptibility to human immunodeficiency virus/AIDS119 and similar findings have been found in Kawasaki's disease.120 Recent reports suggest that CNVs in the CCL3L1 gene may also contribute to risk for RA and type 1 diabetes.121

As we move forward with additional genetic discoveries, it is imperative that these new findings be applied to phenotypic subgroups of disease with longitudinal follow up of patients to permit the analysis of disease outcomes and response to therapies. We have recently begun to apply whole-genome analysis to the analysis of response to anti-TNF therapy.122 However, the size of the currently available cohorts is inadequate, and a major challenge for the field will be the establishment of large, well-characterized populations of patients who are followed prospectively so that the full fruits of the coming genetic harvest can be fully realized.


  1. 1

    Oliver JE, Silman AJ . Risk factors for the development of rheumatoid arthritis. Scand J Rheumatol 2006; 35: 169–174.

    Google Scholar 

  2. 2

    Firestein GS . Evolving concepts of rheumatoid arthritis. Nature 2003; 423: 356–361.

    Google Scholar 

  3. 3

    Arnett FC, Edworthy SM, Bloch DA, McShane DJ, Fries JF, Cooper NS et al. The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis. Arthritis Rheum 1988; 31: 315–324.

    Google Scholar 

  4. 4

    Schellekens GA, Visser H, de Jong BA, van den Hoogen FH, Hazes JM, Breedveld FC et al. The diagnostic properties of rheumatoid arthritis antibodies recognizing a cyclic citrullinated peptide. Arthritis Rheum 2000; 43: 155–163.

    Google Scholar 

  5. 5

    Wellcome Trust Case Control Consortium. Genome-wide association study of 14 000 cases of seven common diseases and 3000 shared controls. Nature 2007; 447: 661–678.

    Google Scholar 

  6. 6

    Plenge RM, Seielstad M, Padyukov L, Lee AT, Remmers EF, Ding B et al. TRAF1-C5 as a risk locus for rheumatoid arthritis—a genomewide study. N Engl J med 2007; 357: 1199–1209.

    Google Scholar 

  7. 7

    Amos CI, Chen WV, Lee A, Li W, Kern M, Lundsten R et al. High-density SNP analysis of 642 Caucasian families with rheumatoid arthritis identifies two new linkage regions on 11p12 and 2q33. Genes Immun 2006; 7: 277–286.

    Google Scholar 

  8. 8

    Hall FC, Weeks DE, Camilleri JP, Williams LA, Amos N, Darke C et al. Influence of the HLA-DRB1 locus on susceptibility and severity in rheumatoid arthritis. QJM 1996; 89: 821–829.

    Google Scholar 

  9. 9

    Nepom GT . Major histocompatibility complex-directed susceptibility to rheumatoid arthritis. Adv Immunol 1998; 68: 315–332.

    Google Scholar 

  10. 10

    Ding B, Padyukov L, Lundstrum E, Seielstad M, Plenge RM, Oksenberg JR et al. Different patterns of associations with ACPA-positive and ACPA-negative rheumatoid arthritis in the extended MHC region. Arthritis Rheum 2008 (in press).

  11. 11

    Stastny P . Association of the B-cell alloantigen DRw4 with rheumatoid arthritis. N Engl J Med 1978; 298: 869–871.

    Google Scholar 

  12. 12

    Gregersen PK, Silver J, Winchester RJ . The shared epitope hypothesis. An approach to understanding the molecular genetics of susceptibility to rheumatoid arthritis. Arthritis Rheum 1987; 30: 1205–1213.

    Google Scholar 

  13. 13

    van Gaalen FA, van Aken J, Huizinga TW, Schreuder GM, Breedveld FC, Zanelli E et al. Association between HLA class II genes and autoantibodies to cyclic citrullinated peptides (CCPs) influences the severity of rheumatoid arthritis. Arthritis Rheum 2004; 50: 2113–2121.

    Google Scholar 

  14. 14

    Irigoyen P, Lee AT, Wener MH, Li W, Kern M, Batliwalla F et al. Regulation of anti-cyclic citrullinated peptide antibodies in rheumatoid arthritis: contrasting effects of HLA-DR3 and the shared epitope alleles. Arthritis Rheum 2005; 52: 3813–3818.

    Google Scholar 

  15. 15

    Mozes E, McDevitt HO, Jaton JC, Sela M . The genetic control of antibody specificity. J Exp Med 1969; 130: 1263–1278.

    Google Scholar 

  16. 16

    Holoshitz J, Ling S . Nitric oxide signaling triggered by the rheumatoid arthritis shared epitope: a new paradigm for MHC disease association? Ann NY Acad Sci 2007; 1110: 73–83.

    Google Scholar 

  17. 17

    Gourraud PA, Boyer JF, Barnetche T, Abbal M, Cambon-Thomsen A, Cantagrel A et al. A new classification of HLA-DRB1 alleles differentiates predisposing and protective alleles for rheumatoid arthritis structural severity. Arthritis Rheum 2006; 54: 593–599.

    Google Scholar 

  18. 18

    Mulcahy B, Waldron-Lynch F, McDermott MF, Adams C, Amos CI, Zhu DK et al. Genetic variability in the tumor necrosis factor-lymphotoxin region influences susceptibility to rheumatoid arthritis. Am J Hum Genet 1996; 59: 676–683.

    Google Scholar 

  19. 19

    Ota M, Katsuyama Y, Kimura A, Tsuchiya K, Kondo M, Naruse T et al. A second susceptibility gene for developing rheumatoid arthritis in the human MHC is localized within a 70-kb interval telomeric of the TNF genes in the HLA class III region. Genomics 2001; 71: 263–270.

    Google Scholar 

  20. 20

    Jawaheer D, Li W, Graham RR, Chen W, Damle A, Xiao X et al. Dissecting the genetic complexity of the association between human leukocyte antigens and rheumatoid arthritis. Am J Hum Genet 2002; 71: 585–594.

    Google Scholar 

  21. 21

    Newton JL, Harney SM, Timms AE, Sims AM, Rockett K, Darke C et al. Dissection of class III major histocompatibility complex haplotypes associated with rheumatoid arthritis. Arthritis Rheum 2004; 50: 2122–2129.

    Google Scholar 

  22. 22

    Lee HS, Lee AT, Criswell LA, Seldin MF, Amos CI, Carulli JP et al. Several regions in the major histocompatibility complex confer risk for anti-CCP-antibody positive rheumatoid arthritis, independent of the DRB1 locus. Mol Med 2008; 14: 293–300.

    Google Scholar 

  23. 23

    Nejentsev S, Howson JM, Walker NM, Szeszko J, Field SF, Stevens HE et al. Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A. Nature 2007; 450: 887–892.

    Google Scholar 

  24. 24

    Yen JH, Moore BE, Nakajima T, Scholl D, Schaid DJ, Weyand CM et al. Major histocompatibility complex class I-recognizing receptors are disease risk genes in rheumatoid arthritis. J Exp Med 2001; 193: 1159–1167.

    Google Scholar 

  25. 25

    Remmers EF, Plenge RM, Lee AT, Graham RR, Hom G, Behrens TW et al. STAT4 and the risk of rheumatoid arthritis and systemic lupus erythematosus. N Engl J med 2007; 357: 977–986.

    Google Scholar 

  26. 26

    Begovich AB, Carlton VE, Honigberg LA, Schrodi SJ, Chokkalingam AP, Alexander HC et al. A missense single-nucleotide polymorphism in a gene encoding a protein tyrosine phosphatase (PTPN22) is associated with rheumatoid arthritis. Am J Hum Genet 2004; 75: 330–337.

    Google Scholar 

  27. 27

    Zhernakova A, Alizadeh BZ, Bevova M, van Leeuwen MA, Coenen MJ, Franke B et al. Novel association in chromosome 4q27 region with rheumatoid arthritis and confirmation of type 1 diabetes point to a general risk locus for autoimmune diseases. Am J Hum Genet 2007; 81: 1284–1288.

    Google Scholar 

  28. 28

    Bottini N, Musumeci L, Alonso A, Rahmouni S, Nika K, Rostamkhani M et al. A functional variant of lymphoid tyrosine phosphatase is associated with type I diabetes. Nat Genet 2004; 36: 337–338.

    Google Scholar 

  29. 29

    Begovich AB, Caillier SJ, Alexander HC, Penko JM, Hauser SL, Barcellos LF et al. The R620W polymorphism of the protein tyrosine phosphatase PTPN22 is not associated with multiple sclerosis. Am J Hum Genet 2005; 76: 184–187.

    Google Scholar 

  30. 30

    Jawaheer D, Seldin MF, Amos CI, Chen WV, Shigeta R, Etzel C et al. Screening the genome for rheumatoid arthritis susceptibility genes: a replication study and combined analysis of 512 multicase families. Arthritis Rheum 2003; 48: 906–916.

    Google Scholar 

  31. 31

    Gregersen PK, Lee HS, Batliwalla F, Begovich AB . PTPN22: setting thresholds for autoimmunity. Semin Immunol 2006; 18: 214–223.

    Google Scholar 

  32. 32

    Carlton VE, Hu X, Chokkalingam AP, Schrodi SJ, Brandon R, Alexander HC et al. PTPN22 genetic variation: evidence for multiple variants associated with rheumatoid arthritis. Am J Hum Genet 2005; 77: 567–581.

    Google Scholar 

  33. 33

    Mastana S, Gilmour A, Ghelani A, Smith H, Samanta A . Association of PTPN22 with rheumatoid arthritis among South Asians in the UK. J Rheumatol 2007; 34: 1984–1986.

    Google Scholar 

  34. 34

    Ikari K, Momohara S, Inoue E, Tomatsu T, Hara M, Yamanaka H et al. Haplotype analysis revealed no association between the PTPN22 gene and RA in a Japanese population. Rheumatology (Oxford) 2006; 45: 1345–1348.

    Google Scholar 

  35. 35

    Lee HS, Korman BD, Le JM, Kastner DA, Remmers E, Gregersen P et al. Lack of association of Caucasian rheumatoid arthritis susceptibility loci in a Korean population. Arthritis Rheum 2008 (in press).

  36. 36

    Velaga MR, Wilson V, Jennings CE, Owen CJ, Herington S, Donaldson PT et al. The codon 620 tryptophan allele of the lymphoid tyrosine phosphatase (LYP) gene is a major determinant of Graves' disease. J Clin Endocrinol Metab 2004; 89: 5862–5865.

    Google Scholar 

  37. 37

    Skorka A, Bednarczuk T, Bar-Andziak E, Nauman J, Ploski R . Lymphoid tyrosine phosphatase (PTPN22/LYP) variant and Graves' disease in a Polish population: association and gene dose-dependent correlation with age of onset. Clin Endocrinol (Oxf) 2005; 62: 679–682.

    Google Scholar 

  38. 38

    Smyth D, Cooper JD, Collins JE, Heward JM, Franklyn JA, Howson JM et al. Replication of an association between the lymphoid tyrosine phosphatase locus (LYP/PTPN22) with type 1 diabetes, and evidence for its role as a general autoimmunity locus. Diabetes 2004; 53: 3020–3023.

    Google Scholar 

  39. 39

    Criswell LA, Pfeiffer KA, Lum RF, Gonzales B, Novitzke J, Kern M et al. Analysis of families in the multiple autoimmune disease genetics consortium (MADGC) collection: the PTPN22 620W allele associates with multiple autoimmune phenotypes. Am J Hum Genet 2005; 76: 561–571.

    Google Scholar 

  40. 40

    Vandiedonck C, Capdevielle C, Giraud M, Krumeich S, Jais JP, Eymard B et al. Association of the PTPN22*R620W polymorphism with autoimmune myasthenia gravis. Ann Neurol 2006; 59: 404–407.

    Google Scholar 

  41. 41

    Dieude P, Guedj M, Wipff J, Avouac J, Hachulla E, Diot E et al. The PTPN22 620W allele confers susceptibility to systemic sclerosis: findings of a large case–control study of European Caucasians and a meta-analysis. Arthritis Rheum 2008; 58: 2183–2188.

    Google Scholar 

  42. 42

    LaBerge GS, Bennett DC, Fain PR, Spritz RA . PTPN22 is genetically associated with risk of generalized vitiligo, but CTLA4 is not. J Invest Dermatol 2008; 128: 1757–1762.

    Google Scholar 

  43. 43

    Skinningsrud B, Husebye ES, Gervin K, Lovas K, Blomhoff A, Wolff AB et al. Mutation screening of PTPN22: association of the 1858T-allele with Addison's disease. Eur J Hum Genet 2008; 16: 977–982.

    Google Scholar 

  44. 44

    Betz RC, Konig K, Flaquer A, Redler S, Eigelshoven S, Kortum AK et al. The R620W polymorphism in PTPN22 confers general susceptibility for the development of alopecia areata. Br J dermatol 2008; 158: 389–391.

    Google Scholar 

  45. 45

    Hinks A, Barton A, John S, Bruce I, Hawkins C, Griffiths CE et al. Association between the PTPN22 gene and rheumatoid arthritis and juvenile idiopathic arthritis in a UK population: further support that PTPN22 is an autoimmunity gene. Arthritis Rheum 2005; 52: 1694–1699.

    Google Scholar 

  46. 46

    Viken MK, Amundsen SS, Kvien TK, Boberg KM, Gilboe IM, Lilleby V et al. Association analysis of the 1858C>T polymorphism in the PTPN22 gene in juvenile idiopathic arthritis and other autoimmune diseases. Genes immun 2005; 6: 271–273.

    Google Scholar 

  47. 47

    Seldin MF, Shigeta R, Laiho K, Li H, Saila H, Savolainen A et al. Finnish case–control and family studies support PTPN22 R620W polymorphism as a risk factor in rheumatoid arthritis, but suggest only minimal or no effect in juvenile idiopathic arthritis. Genes immun 2005; 6: 720–722.

    Google Scholar 

  48. 48

    Harley JB, Alarcon-Riquelme ME, Criswell LA, Jacob CO, Kimberly RP, Moser KL et al. Genome-wide association scan in women with systemic lupus erythematosus identifies susceptibility variants in ITGAM, PXK, KIAA1542 and other loci. Nat Genet 2008; 40: 204–210.

    Google Scholar 

  49. 49

    Hom G, Graham RR, Modrek B, Taylor KE, Ortmann W, Garnier S et al. Association of systemic lupus erythematosus with C8orf13-BLK and ITGAM-ITGAX. N Engl J med 2008; 358: 900–909.

    Google Scholar 

  50. 50

    De Jager PL, Sawcer S, Waliszewska A, Farwell L, Wild G, Cohen A et al. Evaluating the role of the 620W allele of protein tyrosine phosphatase PTPN22 in Crohn's disease and multiple sclerosis. Eur J Hum Genet 2006; 14: 317–321.

    Google Scholar 

  51. 51

    Barrett JC, Hansoul S, Nicolae DL, Cho JH, Duerr RH, Rioux JD et al. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease. Nat Genet 2008; 40: 955–962.

    Google Scholar 

  52. 52

    Hasegawa K, Martin F, Huang G, Tumas D, Diehl L, Chan AC . PEST domain-enriched tyrosine phosphatase (PEP) regulation of effector/memory T cells. Science 2004; 303: 685–689.

    Google Scholar 

  53. 53

    Vang T, Congia M, Macis MD, Musumeci L, Orru V, Zavattari P et al. Autoimmune-associated lymphoid tyrosine phosphatase is a gain-of-function variant. Nat Genet 2005; 37: 1317–1319.

    Google Scholar 

  54. 54

    Rieck M, Arechiga A, Onengut-Gumuscu S, Greenbaum C, Concannon P, Buckner JH . Genetic variation in PTPN22 corresponds to altered function of T and B lymphocytes. J Immunol 2007; 179: 4704–4710.

    Google Scholar 

  55. 55

    Vang T, Miletic AV, Arimura Y, Tautz L, Rickert RC, Mustelin T . Protein tyrosine phosphatases in autoimmunity. Annu Rev Immunol 2008; 26: 29–55.

    Google Scholar 

  56. 56

    Liu J, Wang L, Harvey-White J, Osei-Hyiaman D, Razdan R, Gong Q et al. A biosynthetic pathway for anandamide. Proc Natl Acad Sci USA 2006; 103: 13345–13350.

    Google Scholar 

  57. 57

    Price AL, Butler J, Patterson N, Capelli C, Pascali VL, Scarnicci F et al. Discerning the ancestry of European Americans in genetic association studies. PLoS Genet 2008; 4: e236.

    Google Scholar 

  58. 58

    Tian C, Plenge RM, Ransom M, Lee A, Villoslada P, Selmi C et al. Analysis and application of European genetic substructure using 300K SNP information. PLoS Genet 2008; 4: e4.

    Google Scholar 

  59. 59

    Seldin MF, Price AL . Application of ancestry informative markers to association studies in European Americans. PLoS Genet 2008; 4: e5.

    Google Scholar 

  60. 60

    Kurreeman FA, Padyukov L, Marques RB, Schrodi SJ, Seddighzadeh M, Stoeken-Rijsbergen G et al. A candidate gene approach identifies the TRAF1/C5 region as a risk factor for rheumatoid arthritis. PLoS Med 2007; 4: e278.

    Google Scholar 

  61. 61

    Barton A, Thomson W, Ke X, Eyre S, Hinks A, Bowes J et al. Re-evaluation of putative rheumatoid arthritis susceptibility genes in the post-genome wide association study era and hypothesis of a key pathway underlying susceptibility. Hum Mol Genet 2008; 17: 2274–2279.

    Google Scholar 

  62. 62

    Ravetch JV, Clynes RA . Divergent roles for Fc receptors and complement in vivo. Annu Rev Immunol 1998; 16: 421–432.

    Google Scholar 

  63. 63

    Wang Y, Rollins SA, Madri JA, Matis LA . Anti-C5 monoclonal antibody therapy prevents collagen-induced arthritis and ameliorates established disease. Proc Natl Acad Sci USA 1995; 92: 8955–8959.

    Google Scholar 

  64. 64

    Wang Y, Kristan J, Hao L, Lenkoski CS, Shen Y, Matis LA . A role for complement in antibody-mediated inflammation: C5-deficient DBA/1 mice are resistant to collagen-induced arthritis. J Immunol 2000; 164: 4340–4347.

    Google Scholar 

  65. 65

    Ward PA, Zvaifler NJ . Complement-derived leukotactic factors in inflammatory synovial fluids of humans. J Clin Invest 1971; 50: 606–616.

    Google Scholar 

  66. 66

    Gulati P, Guc D, Lemercier C, Lappin D, Whaley K . Expression of the components and regulatory proteins of the classical pathway of complement in normal and diseased synovium. Rheumatol Int 1994; 14: 13–19.

    Google Scholar 

  67. 67

    Neumann E, Barnum SR, Tarner IH, Echols J, Fleck M, Judex M et al. Local production of complement proteins in rheumatoid arthritis synovium. Arthritis Rheum 2002; 46: 934–945.

    Google Scholar 

  68. 68

    Vergunst CE, Gerlag DM, Dinant H, Schulz L, Vinkenoog M, Smeets TJ et al. Blocking the receptor for C5a in patients with rheumatoid arthritis does not reduce synovial inflammation. Rheumatology (Oxford) 2007; 46: 1773–1778.

    Google Scholar 

  69. 69

    Arch RH, Gedrich RW, Thompson CB . Tumor necrosis factor receptor-associated factors (TRAFs)—a family of adapter proteins that regulates life and death. Genes dev 1998; 12: 2821–2830.

    Google Scholar 

  70. 70

    Speiser DE, Lee SY, Wong B, Arron J, Santana A, Kong YY et al. A regulatory role for TRAF1 in antigen-induced apoptosis of T cells. J Exp Med 1997; 185: 1777–1783.

    Google Scholar 

  71. 71

    Tsitsikov EN, Laouini D, Dunn IF, Sannikova TY, Davidson L, Alt FW et al. TRAF1 is a negative regulator of TNF signaling. Enhanced TNF signaling in TRAF1-deficient mice. Immunity 2001; 15: 647–657.

    Google Scholar 

  72. 72

    Bishop GA . The multifaceted roles of TRAFs in the regulation of B-cell function. Nat Rev Immunol 2004; 4: 775–786.

    Google Scholar 

  73. 73

    Raychaudhuri S, Remmers EF, Lee AT, Hackett R, Guiducci C, Burtt NP et al. Common variants at CD40 and other loci confer risk of rheumatoid arthritis. Nat Genet 2008; 40: 1216–1223.

    Google Scholar 

  74. 74

    Wang S, Robertson GP, Zhu J . A novel human homologue of Drosophila polycomb-like gene is up-regulated in multiple cancers. Gene 2004; 343: 69–78.

    Google Scholar 

  75. 75

    Lee HS, Remmers EF, Le JM, Kastner DL, Bae SC, Gregersen PK . Association of STAT4 with rheumatoid arthritis in the Korean population. Mol Med 2007; 13: 455–460.

    Google Scholar 

  76. 76

    Kobayashi S, Ikari K, Kaneko H, Kochi Y, Yamamoto K, Shimane K et al. Association of STAT4 with susceptibility to rheumatoid arthritis and systemic lupus erythematosus in the Japanese population. Arthritis Rheum 2008; 58: 1940–1946.

    Google Scholar 

  77. 77

    Korman BD, Alba MI, Le JM, Alevizos I, Smith JA, Nikolov NP et al. Variant form of STAT4 is associated with primary Sjogren's syndrome. Genes immun 2008; 9: 267–270.

    Google Scholar 

  78. 78

    Levy DE, Darnell Jr JE . Stats: transcriptional control and biological impact. Nat Rev 2002; 3: 651–662.

    Google Scholar 

  79. 79

    Jacobson NG, Szabo SJ, Weber-Nordt RM, Zhong Z, Schreiber RD, Darnell Jr JE et al. Interleukin 12 signaling in T helper type 1 (Th1) cells involves tyrosine phosphorylation of signal transducer and activator of transcription (Stat)3 and Stat4. J Exp Med 1995; 181: 1755–1762.

    Google Scholar 

  80. 80

    Watford WT, Hissong BD, Bream JH, Kanno Y, Muul L, O'Shea JJ . Signaling by IL-12 and IL-23 and the immunoregulatory roles of STAT4. Immunol Rev 2004; 202: 139–156.

    Google Scholar 

  81. 81

    Kaplan MH, Sun YL, Hoey T, Grusby MJ . Impaired IL-12 responses and enhanced development of Th2 cells in Stat4-deficient mice. Nature 1996; 382: 174–177.

    Google Scholar 

  82. 82

    Hildner KM, Schirmacher P, Atreya I, Dittmayer M, Bartsch B, Galle PR et al. Targeting of the transcription factor STAT4 by antisense phosphorothioate oligonucleotides suppresses collagen-induced arthritis. J Immunol 2007; 178: 3427–3436.

    Google Scholar 

  83. 83

    Yap WH, Yeoh E, Tay A, Brenner S, Venkatesh B . STAT4 is a target of the hematopoietic zinc-finger transcription factor Ikaros in T cells. FEBS Lett 2005; 579: 4470–4478.

    Google Scholar 

  84. 84

    Fukao T, Frucht DM, Yap G, Gadina M, O′Shea JJ, Koyasu S . Inducible expression of Stat4 in dendritic cells and macrophages and its critical role in innate and adaptive immune responses. J Immunol 2001; 166: 4446–4455.

    Google Scholar 

  85. 85

    Remoli ME, Ragimbeau J, Giacomini E, Gafa V, Severa M, Lande R et al. NF-{kappa}B is required for STAT-4 expression during dendritic cell maturation. J Leukoc Biol 2007; 81: 355–363.

    Google Scholar 

  86. 86

    Sigurdsson S, Nordmark G, Garnier S, Grundberg E, Kwan T, Nilsson O et al. A common STAT4 risk haplotype for systemic lupus erythematosus is over-expressed, correlates with anti-dsDNA production and shows additive effects with two IRF5 risk alleles. Hum Mol Genet 2008; 17: 2868–2876.

    Google Scholar 

  87. 87

    Kuroda E, Kito T, Yamashita U . Reduced expression of STAT4 and IFN-gamma in macrophages from BALB/c mice. J Immunol 2002; 168: 5477–5482.

    Google Scholar 

  88. 88

    Walker JG, Ahern MJ, Coleman M, Weedon H, Papangelis V, Beroukas D et al. Expression of Jak3, STAT1, STAT4, and STAT6 in inflammatory arthritis: unique Jak3 and STAT4 expression in dendritic cells in seropositive rheumatoid arthritis. Ann Rheum Dis 2006; 65: 149–156.

    Google Scholar 

  89. 89

    Walker JG, Ahern MJ, Coleman M, Weedon H, Papangelis V, Beroukas D et al. Changes in synovial tissue Jak-STAT expression in rheumatoid arthritis in response to successful DMARD treatment. Ann Rheum Dis 2006; 65: 1558–1564.

    Google Scholar 

  90. 90

    Plenge RM, Cotsapas C, Davies L, Price AL, de Bakker PI, Maller J et al. Two independent alleles at 6q23 associated with risk of rheumatoid arthritis. Nat Genet 2007; 39: 1477–1482.

    Google Scholar 

  91. 91

    Thomson W, Barton A, Ke X, Eyre S, Hinks A, Bowes J et al. Rheumatoid arthritis association at 6q23. Nat Genet 2007; 39: 1431–1433.

    Google Scholar 

  92. 92

    Muller T, Anlag K, Wildner H, Britsch S, Treier M, Birchmeier C . The bHLH factor olig3 coordinates the specification of dorsal neurons in the spinal cord. Genes Dev 2005; 19: 733–743.

    Google Scholar 

  93. 93

    Ding L, Takebayashi H, Watanabe K, Ohtsuki T, Tanaka KF, Nabeshima Y et al. Short-term lineage analysis of dorsally derived Olig3 cells in the developing spinal cord. Dev Dyn 2005; 234: 622–632.

    Google Scholar 

  94. 94

    Wertz IE, O′Rourke KM, Zhou H, Eby M, Aravind L, Seshagiri S et al. De-ubiquitination and ubiquitin ligase domains of A20 downregulate NF-kappaB signalling. Nature 2004; 430: 694–699.

    Google Scholar 

  95. 95

    Boone DL, Turer EE, Lee EG, Ahmad RC, Wheeler MT, Tsui C et al. The ubiquitin-modifying enzyme A20 is required for termination of Toll-like receptor responses. Nat Immunol 2004; 5: 1052–1060.

    Google Scholar 

  96. 96

    Hitotsumatsu O, Ahmad RC, Tavares R, Wang M, Philpott D, Turer EE et al. The ubiquitin-editing enzyme A20 restricts nucleotide-binding oligomerization domain containing 2-triggered signals. Immunity 2008; 28: 381–390.

    Google Scholar 

  97. 97

    Lee EG, Boone DL, Chai S, Libby SL, Chien M, Lodolce JP et al. Failure to regulate TNF-induced NF-kappaB and cell death responses in A20-deficient mice. Science 2000; 289: 2350–2354.

    Google Scholar 

  98. 98

    Musone SL, Taylor KE, Lu TT, Nititham J, Ferreira RC, Ortmann W et al. Multiple polymorphisms in the TNFAIP3 region are independently associated with systemic lupus erythematosus. Nat Genet 2008; 40: 1062–1064.

    Google Scholar 

  99. 99

    Suzuki A, Yamada R, Chang X, Tokuhiro S, Sawada T, Suzuki M et al. Functional haplotypes of PADI4, encoding citrullinating enzyme peptidylarginine deiminase 4, are associated with rheumatoid arthritis. Nat Genet 2003; 34: 395–402.

    Google Scholar 

  100. 100

    Plenge RM, Padyukov L, Remmers EF, Purcell S, Lee AT, Karlson EW et al. Replication of putative candidate-gene associations with rheumatoid arthritis in >4,000 samples from North America and Sweden: association of susceptibility with PTPN22, CTLA4, and PADI4. Am J Hum Genet 2005; 77: 1044–1060.

    Google Scholar 

  101. 101

    Suzuki A, Yamada R, Chang X, Tokuhiro S, Sawada T, Suzuki M et al. Functional haplotypes of PADI4, encoding citrullinating enzyme peptidylarginine deiminase 4, are associated with rheumatoid arthritis. Nat Genet 2003; 34: 395–402.

    Google Scholar 

  102. 102

    Chang X, Yamada R, Suzuki A, Sawada T, Yoshino S, Tokuhiro S et al. Localization of peptidylarginine deiminase 4 (PADI4) and citrullinated protein in synovial tissue of rheumatoid arthritis. Rheumatology (Oxford) 2005; 44: 40–50.

    Google Scholar 

  103. 103

    Hung HC, Lin CY, Liao YF, Hsu PC, Tsay GJ, Liu GY . The functional haplotype of peptidylarginine deiminase IV (S55G, A82 V and A112G) associated with susceptibility to rheumatoid arthritis dominates apoptosis of acute T leukemia Jurkat cells. Apoptosis 2007; 12: 475–487.

    Google Scholar 

  104. 104

    Cha S, Choi CB, Han TU, Kang CP, Kang C, Bae SC . Association of anti-cyclic citrullinated peptide antibody levels with PADI4 haplotypes in early rheumatoid arthritis and with shared epitope alleles in very late rheumatoid arthritis. Arthritis Rheum 2007; 56: 1454–1463.

    Google Scholar 

  105. 105

    Klareskog L, Padyukov L, Ronnelid J, Alfredsson L . Genes, environment and immunity in the development of rheumatoid arthritis. Curr Opin Immunol 2006; 18: 650–655.

    Google Scholar 

  106. 106

    Costenbader KH, Chang SC, De Vivo I, Plenge R, Karlson EW . Genetic polymorphisms in PTPN22, PADI-4, and CTLA-4 and risk for rheumatoid arthritis in two longitudinal cohort studies: evidence of gene-environment interactions with heavy cigarette smoking. Arthritis Res Ther 2008; 10: R52.

    Google Scholar 

  107. 107

    Todd JA, Walker NM, Cooper JD, Smyth DJ, Downes K, Plagnol V et al. Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes. Nat Genet 2007; 39: 857–864.

    Google Scholar 

  108. 108

    van Heel DA, Franke L, Hunt KA, Gwilliam R, Zhernakova A, Inouye M et al. A genome-wide association study for celiac disease identifies risk variants in the region harboring IL2 and IL21. Nat Genet 2007; 39: 827–829.

    Google Scholar 

  109. 109

    Liu Y, Helms C, Liao W, Zaba LC, Duan S, Gardner J et al. A genome-wide association study of psoriasis and psoriatic arthritis identifies new disease Loci. PLoS Genet 2008; 4: e1000041.

    Google Scholar 

  110. 110

    Schumacher JM, Lee K, Edelhoff S, Braun RE . Distribution of Tenr, an RNA-binding protein, in a lattice-like network within the spermatid nucleus in the mouse. Biol Reprod 1995; 52: 1274–1283.

    Google Scholar 

  111. 111

    Leonard WJ, Spolski R . Interleukin-21: a modulator of lymphoid proliferation, apoptosis and differentiation. Nat Rev Immunol 2005; 5: 688–698.

    Google Scholar 

  112. 112

    Yang L, Anderson DE, Baecher-Allan C, Hastings WD, Bettelli E, Oukka M et al. IL-21 and TGF-beta are required for differentiation of human T(H)17 cells. Nature 2008; 454: 350–352.

    Google Scholar 

  113. 113

    Li J, Shen W, Kong K, Liu Z . Interleukin-21 induces T-cell activation and proinflammatory cytokine secretion in rheumatoid arthritis. Scand J Immunol 2006; 64: 515–522.

    Google Scholar 

  114. 114

    Young DA, Hegen M, Ma HL, Whitters MJ, Albert LM, Lowe L et al. Blockade of the interleukin-21/interleukin-21 receptor pathway ameliorates disease in animal models of rheumatoid arthritis. Arthritis Rheum 2007; 56: 1152–1163.

    Google Scholar 

  115. 115

    Malek TR . The biology of interleukin-2. Annu Rev Immunol 2008; 26: 453–479.

    Google Scholar 

  116. 116

    Lee-Kirsch MA, Gong M, Chowdhury D, Senenko L, Engel K, Lee YA et al. Mutations in the gene encoding the 3′-5′ DNA exonuclease TREX1 are associated with systemic lupus erythematosus. Nat Genet 2007; 39: 1065–1067.

    Google Scholar 

  117. 117

    Yang Y, Chung EK, Wu YL, Savelli SL, Nagaraja HN, Zhou B et al. Gene copy-number variation and associated polymorphisms of complement component C4 in human systemic lupus erythematosus (SLE): low copy number is a risk factor for and high copy number is a protective factor against SLE susceptibility in European Americans. Am J Hum Genet 2007; 80: 1037–1054.

    Google Scholar 

  118. 118

    Fellermann K, Stange DE, Schaeffeler E, Schmalzl H, Wehkamp J, Bevins CL et al. A chromosome 8 gene-cluster polymorphism with low human beta-defensin 2 gene copy number predisposes to Crohn disease of the colon. Am J Hum Genet 2006; 79: 439–448.

    Google Scholar 

  119. 119

    Gonzalez E, Kulkarni H, Bolivar H, Mangano A, Sanchez R, Catano G et al. The influence of CCL3L1 gene-containing segmental duplications on HIV-1/AIDS susceptibility. Science 2005; 307: 1434–1440.

    Google Scholar 

  120. 120

    Burns JC, Shimizu C, Gonzalez E, Kulkarni H, Patel S, Shike H et al. Genetic variations in the receptor-ligand pair CCR5 and CCL3L1 are important determinants of susceptibility to Kawasaki disease. J Infect Dis 2005; 192: 344–349.

    Google Scholar 

  121. 121

    McKinney C, Merriman ME, Chapman PT, Gow PJ, Harrison AA, Highton J et al. Evidence for an influence of chemokine ligand 3-like 1 (CCL3L1) gene copy number on susceptibility to rheumatoid arthritis. Ann Rheum Dis 2008; 67: 409–413.

    Google Scholar 

  122. 122

    Liu C, Batliwalla F, Li W, Lee A, Roubenoff R, Beckman E et al. Genome-wide association scan identifies candidate polymorphisms associated with differential response to anti-TNF treatment in rheumatoid arthritis. Mol Med 2008; 14: 575–581.

    Google Scholar 

Download references


MC is supported by a grant from the Netherlands Organization for Scientific Research (Grant 916.76.020). PKG is supported by grants from the NIH (RO1 AR44422, RO1-AI-68759, NO1-AR-2-2263, NO1-AR-1-2256), the American College of Rheumatology, the Eileen Ludwig Greenland Fund and The Muriel Fusfeld Foundation.

Author information



Corresponding author

Correspondence to P K Gregersen.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Coenen, M., Gregersen, P. Rheumatoid arthritis: a view of the current genetic landscape. Genes Immun 10, 101–111 (2009).

Download citation


  • Rheumatoid arthritis
  • polymorphism
  • genome-wide association

Further reading


Quick links