The now well-established overlap of genetic susceptibility risk factors across quite clinically and phenotypically different autoimmune diseases has been an exciting discovery that has emerged from the GWAS era. It suggests there will be shared pathogenic pathways and the potential for shared therapies for these diseases. Furthermore, it can be exploited as a strategy for the identification of novel risk factors for related autoimmune diseases, including JIA. There is already compelling evidence that many susceptibility loci are shared between RA and JIA (PTPN22
amongst others). In this study we have identified and validated association with three novel loci, originally associated with RA.
One of these identifies a new JIA susceptibility gene, CD247
, a good candidate for JIA as it encodes the zeta chain of the T-cell receptor–CD3 complex and adds another gene to the list of JIA susceptibility loci that play a role in T-cell activation and signalling (PTPN22
). In addition to the reported associations with RA, SNP within CD247
have also been associated with coeliac disease22
and with systemic sclerosis.23
The JIA-associated SNP is in complete linkage disequilibrium (LD) (r2
=1) with the SNP associated with systemic sclerosis (rs2056626) and in strong LD (r2
=0.86) with the SNP most significantly associated with coeliac disease (rs864537). The risk variant of the SNP has also been correlated with cis
gene expression of CD247.22
We found strong evidence for association of a SNP, rs7234029, in the protein tyrosine phosphatase non-receptor 2 (PTPN2
) gene with JIA in our UK cohort. There is already replicated evidence for association of SNP within this gene with JIA in US and German cohorts.5
In the US study, the SNP with the strongest association was also rs7234029, and it reached genome-wide levels of significance; in addition there was association with four additional SNP. Meta-analysis of the UK JIA cohort study with the US data further established PTPN2
as an important JIA susceptibility locus (combined p value 8.1×10−13
). The PTPN2
gene has been associated with multiple autoimmune diseases, including T1DM,25
and coeliac disease.26
In T1DM, fine-mapping suggests there are two independently associated SNP, rs45450798 and rs478582.26
These SNP are only in modest LD with rs7234029. Further fine-mapping of the gene in RA and JIA will be required to identify the causal variant, whether there are multiple independent effects and whether the associations are the same across the different autoimmune diseases. PTPN2
encodes a protein tyrosine phosphatase, similar to PTPN22
, which also plays a role in the activation and regulation of T and B cells.
SNP within IL2RA
have previously been shown to be associated with JIA using these same UK and US cohorts4
as well as many other autoimmune diseases such as RA,19
and multiple sclerosis,29
but the association is complex with multiple independent effects and different associations across the different diseases. The novel SNP associated here is in only weak LD with the most associated SNP from the previous study, rs2104286, r2
=0.24. However, conditional logistic regression analysis in the UK dataset suggests that rs2104286 is driving the association with JIA. After conditioning on rs2104286 there was no significant association at rs706778, whereas after conditioning on rs706778, there was still significant association at rs2104286 (data not shown). Meta-analysis of the UK and US studies found highly significant evidence for association with JIA (combined p value 3.3×10−8
), which now brings this locus to a genome-wide significance level.
In the initial analysis of the UK cohort only the most significant association was for a SNP in the protein-tyrosine phosphatase receptor type C (PTPRC
) gene, which again is a promising candidate gene. This gene encodes the common leucocyte antigen, CD45, which is a haemopoietic cell-specific tyrosine phosphatase. CD45 is essential for the activation of T and B cells by mediating cell-to-cell contacts and regulating protein-tyrosine kinases involved in signal transduction.30
However, this was not validated in the US cohort; in fact, there was a trend towards an association but in the opposite direction. There are a number of possible reasons for this, including a false positive in the initial UK dataset, a false negative in the US dataset, unrecognised population stratification, phenotypic heterogeneity and different environmental exposures. Analysis of this SNP in additional larger cohorts is required to confirm or refute association with this locus.
The JIA association findings were not validated in the US cohort for CD2, RBPJ, BLK and ORMDL3, and only ORMDL3 remained significant in the combined analysis. The US cohort was underpowered to detect an effect with all of these loci apart from ORMDL3 (see supplementary table 3, available online only), therefore further validation is needed.
In addition it should be noted that for the 16 SNP that were not significantly associated with JIA in this study, we had between 29% and 99% power to detect an association; therefore, for some of these SNP, larger datasets and meta-analyses will be required to exclude association with JIA completely.
JIA is a heterogeneous disease and it may be expected that there are genetic differences across the JIA subtypes and some subtype-specific effects have been identified.31
In this study our strategy was to look for shared autoimmune or inflammatory arthritis susceptibility loci, and it would be interesting to investigate whether these associations are common to all JIA subtypes or are restricted to some subtypes. However, stratified analysis leads to small sample sizes for many of the subtypes and further issues with multiple testing. Larger cohorts of the ILAR subtypes are required to improve the power to detect any subtype-specific effects. We have stratified our analysis just to investigate the oligoarthritis and rheumatoid factor-negative polyarthritis subtypes as these were the subtypes comprising the validation cohort.
For all these loci identified for JIA we have only tested one SNP, the SNP most significantly associated with RA from GWAS. In most cases for the genes identified to date for RA and other autoimmune diseases, the actual causal variant has yet to be identified, which may reduce the power of this study even further, so further fine-mapping of the genes/regions is now required.
In conclusion, the strategy of testing loci identified in other autoimmune diseases, such as RA, for association with JIA is proving successful in the identification of novel JIA loci and is a complementary approach to the hypothesis-free methods of GWAS. In the past few years we have investigated 45 loci that confer susceptibility to RA for association with JIA.7
Of these, 22 show association (p<0.05) with JIA in our UK cohort and 11 of these show validated association with JIA in independent cohorts.5
Clearly, there is a selection bias given the strategy used to select SNP to test; however, there still remains quite considerable overlap between two distinct clinical entities. Many of these loci also confer susceptibility to other autoimmune diseases and may thus represent genes controlling general immune function, the defects of which may lead to an enhanced autoimmune response. Despite the success of this approach in identifying novel JIA loci, large well-powered GWAS will be required to identify disease-specific loci for JIA and its subtypes.