A large and growing list of genetic associations with rheumatoid arthritis (RA) has emerged from genome-wide association studies (GWAS) performed in the last few years (1–6). The lists of putative risk genes have pointed to both the adaptive and innate immune systems as potential sources of biologic variation that predispose to disease, with surface and intracellular signaling molecules as well as cytokines making a major contribution. The first 2 confirmed non–major histocompatibility complex (non-MHC) associations involved the PADI4 locus in Asian populations (7) and PTPN22 in Europeans (8). Intriguingly, neither of these associations crosses over these 2 ethnic groups. The associations with PADI4 are extremely weak or absent in most European studies (4). Conversely, the PTPN22 risk allele, a causative amino acid change from arginine to tryptophan at codon 620 (R620W), is simply not found in Asian populations. PTPN22 encodes an intracellular phosphatase that plays a critical role in setting thresholds for receptor signaling in both T cells and B cells. Extensive resequencing of PTPN22 in Asian RA populations has failed to find evidence of any additional risk variants in this population (9). The PADI4 locus encodes a peptidyl deaminase that is directly involved in the citrullination of proteins, thereby generating a major autoantigen that is the target of a humoral response that is quite specific to RA in all major ethnic groups; nevertheless, associations at this locus are largely limited to Asians.
In contrast, other genetic associations appear to be common across Asian and European RA patients; among them are associations at the HLA–DRB1 locus (10) and STAT4 (11), although the specific HLA alleles involved differ somewhat among these and other ethnic groups. In order to explore more comprehensively the genetic differences and overlap between European and Asian RA, we undertook a GWAS of RA in the Korean population, with further replication of the most strongly associated markers. Our data revealed a complex picture of both shared and population-specific genetic risk, as well as evidence for a large background of modest risk that may be common to both populations.
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We performed a GWAS and replication study in the Korean RA population and compared the results to the accumulating evidence for multiple genetic susceptibility loci in Europeans. Overall, the data demonstrated a complex picture, with both shared and population-specific disease susceptibility. Because our GWAS was of modest sample size, statistical power was limited in the discovery phase. The expected presence of associations in the HLA–DRB1 and PADI4 regions demonstrated that our case–control sample was informative with regard to RA-associated loci. Accordingly, one could expect the presence of true signal below the formal genome-wide significance threshold. This notion was supported by our estimate of an excess of 14 true-positive associations among the 42 associated loci with SNPs having a significance of P < 10–04. The respective list of putative RA loci was further narrowed down by the results from the replication stage, where we found strong skew toward smaller P values.
We estimated that our study had 50% power to detect loci with a risk allele frequency of 40% and an OR 1.5 for the P value threshold of P < 5 × 10–08 and 95% power to detect such loci for a threshold of P < 10–04. Thus, it appears unlikely that many such loci exist beyond HLA–DRB1 and PADI4. In contrast, our study had less than 1% power to detect risk alleles with an allele frequency of 10% and an OR of 1.3 for the significance threshold of P < 5 × 10–08, 5% power to detect such loci for a threshold of P < 1 × 10–04, and 60% power to detect such loci for a threshold of P < 5 × 10–02. Notably, it is exactly this threshold range for which the study was most powerful, where we see the strongest overlap with RA loci identified in a much larger meta-analysis of European RA loci (Figure 3). This formally confirms the impression obtained from the presence of several weaker associations signals in Koreans that were found for European RA loci (Table 2).
It is therefore likely that the extent of overlapping risk factors between the 2 populations is greater than that suggested by the list of the very top associations from the GWAS stage (Table 1). However, our present study mainly examined the overlap between loci. It will be interesting in future studies to perform a more detailed analysis of whether the same or different susceptibility mutations underlie these loci that are shared across populations.
Because a role of mutations for autoimmune susceptibility in Europeans has already been established for BLK, AFF3, and CCL21, the associations of these genes with RA in Koreans are the most likely to be true positives. Conversely, it was also interesting to examine which of the Korean RA loci show subthreshold associations in Europeans, since this would, in turn, increase the confidence in the association findings we obtained in the Korean sample. Therefore, we looked up the results for the associated markers at PTPN2, FLI1, ARHGEF3, LCP2, GPR137B, TRHDE, and GGA1 in a recent meta-analysis of RA (4). This showed fairly strong evidence for PTPN2 (P = 7.4 × 10–05 for rs657555) and weaker evidence for FLI1 (P = 0.003 for rs4936059) in this large European RA meta-analysis.
FLI1 has been implicated in the risk of murine lupus due to regulatory polymorphisms acting in T cells (23), and it shares similar regulatory regions with humans (24). Interestingly, markers from the neighboring ETS1 gene were recently associated with systemic lupus erythematosus (SLE) in Chinese (25). These associations of ETS1 with SLE are only 130 kb away from the association of FLI1 with RA we observed in the present study. Because linkage disequilibrium between markers in FLI1 and ETS1 is weak (Supplementary Figure S7; available online at http://www.biorep.org/supplementary/freudenberg2010/index.html), we would consider these to represent independent signals for RA and SLE susceptibility in Asians. Indeed, none of the ETS1 markers associated with SLE in Chinese showed any association with RA in our study of Koreans.
Another gene with a possible role for RA in both European and Asian populations is CCR6 (4, 6). Our GWAS data supported an association of the SNP rs3093024 with RA in Koreans (P = 0.004, OR 1.23). However, we also saw differences in the allele frequencies; the A allele attained a frequency of 45.9% in RA cases and 40.8% in controls in our study, whereas it attained a frequency of 52% in RA cases and 46% in controls in the Japanese population (6). Thus, rs3093024 seems to be a SNP with a fairly large allele frequency difference between the Japanese and Korean populations. Interestingly, this SNP was reported to be in strong linkage disequilibrium with a presumably functional insertion/deletion polymorphism in Japanese (6).
Among the remaining candidate genes shown in Table 3, LCP2 is of particular interest, since it encodes SLP-76, a critical adaptor protein for receptor signaling in T cells and several other hematopoietic cells types (26). The associated SNP, rs4867947, is located ∼50 kb downstream of LCP2, and therefore, much work remains before the functionally relevant locus in this region is definitively identified.
In summary, we have presented support for associations with 10 different novel putative RA genes in the Korean population. Despite the fact that none of these new associations reaches generally accepted levels of genome-wide significance, we estimate that a large proportion of these associations are likely to be true positives. We further showed that the overlap between non-MHC loci that are associated with RA is significantly larger than expected by chance and, thus, at least a subset of RA loci are shared between European and Asian populations. We therefore believe that the list of associations provided herein are likely to be helpful for further fine-mapping studies and future meta-analyses of RA in Asians as well as across populations.
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- PATIENTS AND METHODS
- AUTHOR CONTRIBUTIONS
- Supporting Information
All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Drs. Gregersen and Bae had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Study conception and design. Freudenberg, H.-S. Lee, A. T. Lee, Gregersen, Bae.
Acquisition of data. H.-S. Lee, Han, Shin, Kang, Sung, Shim, Choi, A. T. Lee, Gregersen, Bae.
Analysis and interpretation of data. Freudenberg, H.-S. Lee, Shin, A. T. Lee, Gregersen, Bae.