Replication of Reported Genetic Associations of PADI4, FCRL3

J Hum Genet (2008) 53:163–173 DOI 10.1007/s10038-007-0232-4

ORIGINAL ARTICLE

Replication of reported genetic associations of PADI4, FCRL3, SLC22A4 and RUNX1 genes with rheumatoid arthritis: results of an independent Japanese population and evidence from meta-analysis of East Asian studies

Yoichiro Takata Æ Hiroshi Inoue Æ Aya Sato Æ Kazue Tsugawa Æ Katsutoshi Miyatake Æ Daisuke Hamada Æ Fumio Shinomiya Æ Shunji Nakano Æ Natsuo Yasui Æ Toshihito Tanahashi Æ Mitsuo Itakura

Received: 30 October 2007 / Accepted: 19 November 2007 / Published online: 18 December 2007 Ó The Japan Society of Human Genetics and Springer 2007

Abstract We conducted population-based association magnitudes of effects were apparently much weaker than tests for the four selected SNPs (rs2240340/padi4_94, those reported in the initial positive reports, and there were rs7528684/fcrl3_3, rs3792876/slc2F2 and rs2268277/ substantial levels of inter-study OR heterogeneity, we runx1) previously reported to be associated with rheuma- concluded that additional studies are needed to fully toid arthritis (RA). The study population consisted of 950 understand the present results. unrelated Japanese subjects with RA and 507 controls, none of whom had previously been tested for these vari- Keywords Rheumatoid arthritis Á PADI4 Á FCRL3 Á ants. Only the SNP rs2240340/padi4_94 was modestly SLC22A4 Á RUNX1 Á Single nucleotide polymorphisms Á associated with RA [allele odds ratio (OR) 1.22, 95% Genetic association study Á Meta-analysis confidence interval (CI) 1.04–1.43, P = 0.012]. The most significant association effect was found for genotype contrast between minor and major allele homozygotes (OR Introduction 1.53, 95% CI 1.10–2.12, P = 0.010). No other SNPs showed a statistically significant association with RA in Rheumatoid arthritis (RA) is a common autoimmune/ our population. Meta-analysis of published studies and our inflammatory condition, characterized by chronic, new data confirmed a highly significant association destructive and debilitating arthritis (Harris 1990). The between PADI4 gene SNPs and increased risk of RA in etiology of RA is still largely unknown, but there is thought East Asian populations (allele fixed-effects summary OR to be a major genetic influence. The importance of the 1.31, 95% CI 1.22–1.41, P \ 0.0001). We found some human leukocyte antigen (HLA)-DRB1 gene has been evidence for an association of either rs7528684/fcrl3_3 or confirmed in nearly every population: i.e., carriage of rs3792876/slc2F2 with RA; however, because the certain alleles, collectively termed ‘‘shared epitope (SE),’’ confers a two- to threefold increased risk of RA (Reveille 1998). Non-HLA genes are also thought to be involved in Electronic supplementary material The online version of this RA susceptibility. However, definitive identification of the article (doi:10.1007/s10038-007-0232-4) contains supplementary material, which is available to authorized users. responsible gene(s) has been challenging. Recently, the genetic association between a non-synonymous SNP in the Y. Takata Á H. Inoue (&) Á A. Sato Á K. Tsugawa Á PTPN22 gene (R620W; rs2476601) and the development T. Tanahashi Á M. Itakura of RA in Europeans has been widely replicated (Begovich Division of Genetic Information, Institute for Genome Research, et al. 2004; Gregersen et al. 2006). It is noteworthy that this The University of Tokushima, 3-18-15 Kuramoto-cho, Tokushima, Tokushima 770-8503, Japan variant appears not to be present or is extremely rare in e-mail: [email protected] Asian populations, and haplotypic analysis of other PTPN22 SNPs has revealed no clear evidence for an Y. Takata Á K. Miyatake Á D. Hamada Á F. Shinomiya Á association (Ikari et al. 2006a), suggesting etiological S. Nakano Á N. Yasui Department of Orthopedics, Institute of Health Biosciences, complexity and ethnic heterogeneity of RA (Mori et al. The University of Tokushima, Tokushima, Japan 2005). More recently, association studies have identified 123 164 J Hum Genet (2008) 53:163–173 four different, highly interesting genes, PADI4, FCRL3, collection in a separate study (Ikari et al. 2006b), while a SLC22A4 and RUNX1, with convincing evidence of asso- large study of Korean subjects failed to demonstrate a ciations with RA in the Japanese population (Suzuki et al. significant effect (Choi et al. 2006). Several studies have 2003; Kochi et al. 2005; Tokuhiro et al. 2003). assessed the role of fcrl3_3 in the development of RA in The PADI4 gene encodes the type IV peptidylarginine Caucasians, and many failed to replicate the earlier results deiminase (PADI) enzyme, one of five known human PADI (Martinez et al. 2006a; Eyre et al. 2006; Newman et al. isoforms. PADI activity appears to be implicated in the 2006; Thabet et al. 2007). A recent meta-analysis involving generation of anti-cyclic citrullinated peptide (CCP) anti- more than 10,000 white subjects provided no evidence of body, which is highly specific to patients with RA. It has association (Begovich et al. 2007). also been demonstrated that, in RA patients, the presence Through an association study and fine mapping of the of the HLA-DRB1 SE alleles was exclusively associated candidate chromosome region on 5q31, Tokuhiro et al. with anti-CCP antibody seropositivity (de Vries et al. (2003) found SNPs within the SLC22A4 gene encoding the 2005). Thus, PADI4 is an excellent candidate gene for RA. cation transporter OCTN1 to be strongly associated with Recently, Suzuki et al. (2003) reported a strong genetic RA in a Japanese population. The SNP slc2F1 showed the association between the PADI4 SNPs and RA in a Japanese most significant effect (maximum OR 1.98, P = 0.000034, population. The highest association was observed for a under a recessive model). Expression of SLC22A4 was SNP located in intron 3 of PADI4 (padi4_94; revealed to be specific in hematological and immunological P = 0.000008). Further analyses revealed the susceptible tissues, and was also observed in the synovial tissues of RA haplotype marked by disease-associated SNPs to be func- patients. An intron 1 SNP of SLC22A4, slc2F2, which was tional, affecting the stability of PADI4 mRNA, and its in very strong linkage disequilibrium (LD) with slc2F1 (D frequency was associated with the development of anti- or r2 [ 0.97) and occurred within a putative RUNX1 CCP antibody-positive RA. The genetic association binding site, was shown to affect the transcriptional effi- between PADI4 and RA was replicated in another Japanese ciency of SLC22A4. RUNX1 is a transcription factor that group (Ikari et al. 2005) and in a Korean population (Kang belongs to the runt-domain gene family, and is known to be et al. 2006), although many studies of Caucasian subjects important for hematopoiesis and osteogenesis. Intriguingly, yielded conflicting findings (Barton et al. 2005a; Harney a genetic variant of the RUNX1 gene itself was also found et al. 2005; Martinez et al. 2005; Plenge et al. 2005; Hoppe to be implicated in RA susceptibility, where an intronic et al. 2006). Recent meta-analyses of PADI4 SNPs, how- SNP, designated runx1, was strongly associated with RA ever, hinted at an association in European RA patients risk (maximum OR 1.48, P = 0.00035, under a dominant (Iwamoto et al. 2006; Lee et al. 2007). model) (Tokuhiro et al. 2003). To date, the findings of The human FCRL3 gene maps to chromosome 1q21–23, Tokuhiro and colleagues have not been replicated in either the genomic region encompassing a gene cluster of Fc-like Japanese or Caucasian populations (Kuwahara et al. 2005; receptors (FCRL1–5) and a family of Fcc receptor II/III Barton et al. 2005b; Newman et al. 2005; Martinez et al. (FCGR2–3) genes. This locus has previously been impli- 2006b; Orozco et al. 2006), while it is interesting to note cated in susceptibility to several autoimmune diseases. In a that, in Caucasian populations, a nonsynonymous substi- large-scale association mapping study in a Japanese pop- tution (1672C [ T; rs1050152) causing an amino-acid ulation, four FCRL3 SNPs were found to be strongly change (L503F) in the SLC22A4 was proposed as a associated with RA (Kochi et al. 2005). The SNP fcrl3_3, potential causal variant for Crohn’s disease, a chronic located at position -169, relative to the transcriptional start inflammatory bowel disease with immunologically medi- site of FCRL3, showed the most significant association ated processes (Fisher et al. 2006). with RA (maximum OR 2.15, P = 0.00000085, under a In the development of RA, as in other complex diseases, recessive model), association of which was replicated in individual effect sizes of non-HLA susceptibility genes are the same study in another cohort of RA patients. In addi- likely to be modest (ORs generally in the range of 1.2–1.5), tion, significant genetic associations with the development making it difficult to detect or confirm associations unless of systemic lupus erythematosus and autoimmune thyroid thousands of subjects are assessed. Recent studies showing disease were also found. Among RA patients, the suscep- inconsistencies among association results also highlight the tibility allele of fcrl3_3 was linked to both elevated serum importance of accounting for ethnic differences in the rheumatoid factor (RF) and anti-CCP positivity. This SNP pursuit of a real connection between gene(s) and RA. The was found to occur within a consensus binding site for the above-mentioned four genes were initially identified in the transcription factor NF-jB, resulting in a functional alter- Japanese populations as being strongly associated with ation of the NF-jB binding as well as altered FCRL3 gene susceptibility to RA; however, there also appears to be an transcription. The association between fcrl3_3 and RA was inconsistency within the same ethnic background. Thus, replicated in an independent Japanese case-control sample further examination of additional population samples, 123 J Hum Genet (2008) 53:163–173 165 either in more individuals per particular racial/ethnic group previously been shown to be strongly associated with RA or in distinct populations having different genetic back- in the Japanese population. The general information on the grounds, is still needed to clarify these genetic associations selected SNPs is summarized in ESM Table 2. All SNPs and evaluate possible mechanism(s) of disease suscepti- were genotyped using the TaqMan allelic discrimination bility. In this study, we first undertook a case-control assay with allele-specific fluorescent MGB probes, association analysis attempting to replicate previously obtained from Applied Biosystems (Foster City, CA). The identified associations in a completely independent Japa- reaction was conducted with a TaqMan Universal Master nese population, consisting of 1,457 subjects (950 RA Mix buffer (Applied Biosystems), with primer concentra- cases and 507 controls). In addition, we performed a meta- tions of 900 nM and MGB-probe concentrations of analysis using the present data and those from previously 200 nM, in a total reaction volume of 4 ll. Five nanograms published studies, focusing on East Asian populations. of genomic DNA were used as a template. After the reaction, 384-well assay plates were transferred to ABI PRISM 7900HT instruments (Applied Biosystems), and the Subjects and methods fluorescence intensity in each well was read. Fluorescence data were first analyzed by automated allele-calling soft- Study subjects ware of the instrument (SDS version 2.1) and were then independently reviewed by two experienced operators This study was conducted in accordance with the tenets of (Y.T. and A.S.). Our high-throughput genotyping was the Declaration of Helsinki and approved by the Ethics performed satisfactorily, and the overall genotyping suc- Committee for Human Genome and Gene Research at the cess rate was more than 99%. University of Tokushima. Written informed consent was obtained from all participants prior to enrollment in the study. A total of 950 unrelated Japanese patients with RA Statistical analysis [79.1% females; mean ± SD (standard deviation) age at enrollment 61.8 ± 12.5 years, mean ± SD age at RA For each SNP, Hardy-Weinberg equilibrium (HWE) was diagnosis 49.0 ± 14.9 years] were recruited through the assessed in the case and control groups separately, using the hospital clinic at Tokushima University and its affiliates. exact test (Wigginton et al. 2005). Allelic frequencies of the Detailed information on patients and control subjects was SNPs in the case and control groups were compared using a previously described [Hamada et al. 2005; Takata et al. v2 test (allele 1 [common] vs. allele 2 [minor]). Analyses 2007; see also Electronic supplementary material (ESM) were also performed under various types of genetic con- Table 1]. All patients satisfied the revised criteria of the trasts including the contrast of homozygotes (genotype 11 American College of Rheumatology (Arnett et al. 1988), vs. 22), and the dominant (11 vs. [12 + 22]) and recessive with a minimum disease duration of 3 years. Five hundred [(11 + 12) vs. 22] models. In addition, Armitage’s trend and seven unrelated healthy controls (74.6% females; test, which takes into account the individuals’ genotypes mean ± SD age at enrollment 39.8 ± 16.9 years) were rather than just alleles (Sasieni 1997), was performed using mostly employees of the University of Tokushima and the DeFinetti program provided as an online source related hospitals. Our previous study (Takata et al. 2007) (http://ihg.gsf.de/cgi-bin/hw/hwa1.pl). The significance included a total of 443 DNA samples, derived from unrelated level for statistical tests was set at 0.05. Corrections for volunteers and established by the Pharma SNP consortium multiple comparisons have not been made, since all the (PSC) (Kamatani et al. 2004), which were excluded from the SNPs were selected from highly plausible candidate genes current study because some samples could possibly have previously reported as playing a role in RA, and were been used in recent genetic association studies by other potentially functional variants, providing a priori hypothe- investigators (Drs. K. Ikari and N. Kamatani, personal ses for their association. The crude odds ratios (ORs), their communication). Blood specimens were collected from all 95% confidence intervals (CIs) and their corresponding P subjects, and genomic DNA was extracted from peripheral values were calculated. Logistic regression models were blood leukocytes according to standard methods. used to calculate adjusted ORs, controlling for age and sex as covariables. All data management and statistical com- putations were performed using SNPAlyze Pro software Selection and genotyping of SNPs (version 5.1; Dynacom, Yokohama, Japan) and SPSS for Windows (version 12.0; SPSS Inc., Tokyo, Japan). Statis- Four SNPs, rs2240340/padi4_94, rs7528684/fcrl3_3, tical power to detect an association was determined with rs3792876/slc2F2 and rs2268277/runx1, were selected for the PS power and sample-size program (available at investigation because, on single-locus analyses, they had http://www.mc.vanderbilt.edu/prevmed/ps). 123 166 J Hum Genet (2008) 53:163–173

For the meta-analysis, we performed an NCBI PubMed tested for the selected SNPs, and were thus completely literature search (http://www.ncbi.nlm.nih.gov/sites/entrez/), independent of those previously reported by other investi- from the first publications of each gene up to 28 September gators. The statistical power of our study to detect 2007, using the search terms rheumatoid arthritis, gene, genotype differences of the magnitude reported in the ini- association, single nucleotide polymorphisms, FCRL3, tial positive studies was more than 90% (type I error rate PADI4, SLC22A4, OCTN1 and RUNX1. Once articles had 0.05). been collected, bibliographies were further searched man- Genotype and allele frequencies of the selected SNPs in ually for additional references. Data were extracted using our study population are shown in Table 1. None of the standardized forms. If incomplete data were presented in a SNPs showed any deviations from HWE in either the case particular report, the corresponding authors were contacted or the control group. Only the allele and genotype fre- about provision of data in a usable format. The meta- quencies of rs2240340/padi4_94 showed weak but analysis was performed employing the Mantel–Haenszel significant (P \ 0.05) associations with RA. The minor approach as a fixed-effects model test and the DerSimo- allele frequency of rs2240340/padi4_94 was 0.447 in cases nian-Laird method as a random-effects model test, using and 0.399 in controls, yielding an allelic OR of 1.22 (95% StatsDirect statistical software (version 2.6.2; StatsDirect CI 1.04–2.12, P = 0.012). Armitage’s trend test yielded Ltd, Sale, UK). We selected a nominal P value of 0.05 as similar values (OR 1.23, P = 0.011). The highest signifi- significant to maximize confidence in a true-positive cant OR was found for the genotype contrast of association and to minimize false-positive results. The homozygotes (genotype 11 vs. 22; OR 1.53, 95% CI 1.10– Cochran Q test for heterogeneity was used to assess whe- 2.12, P = 0.010). Logistic regression analysis revealed that ther variability among studies was greater than expected by associations between rs2240340/padi4_94 and RA chance alone. When the ORs are homogeneous, the Q remained statistically significant after adjustment for age follows a v2 distribution with r - 1(r is the number of and sex (data not shown). In the remaining SNPs studies) degrees of freedom (df). If P \ 0.10, then heter- (rs7528684/fcrl3_3, rs3792876/slc2F2 and rs2268277/ ogeneity was considered statistically significant. In runx1), no significant difference in either allele or genotype addition, the I2 metric [I2 =(Q–df)/Q] was used to frequencies was observed in our case-control sample set. describe the percentage of variation across studies due to heterogeneity rather than chance. The I2 takes values between 0 and 100% with higher values denoting a greater Meta-analysis of East Asian population studies degree of heterogeneity (I2 = 0–25%, absence; 25–50%, moderate; 50–75%, large; 75–100%, extreme heterogene- We summarized the data from the current study, compared ity). Publication bias was not assessed because of the small them with those from previous association studies and number of studies available. carried out meta-analyses (the descriptive characteristics and results of each of the prior studies are tabulated in ESM Table 3). We considered only the East Asian populations Results for the meta-analysis and included four previously published case-control association studies of RA on PADI4, A replication case-control study of the selected RA- three each on FCRL3 and SLC22A4, and two on RUNX1 candidate SNPs genes. All except for the three Korean reports were Japa- nese population studies. The ORs, which were recalculated For the present study, we chose one SNP from each of four for each individual study, are shown in ESM Table 4. In highly plausible RA-susceptibility genes: rs2240340/ each one of the PADI4 and SLC22A4 reports, genotype padi4_94 for PADI4, rs7528684/fcrl3_3 for FCRL3, data on the selected SNPs were unavailable because they rs3792876/slc2F2 for SLC22A4, and rs2268277/runx1 for used different SNPs for the association analyses. For the RUNX1 (see ESM Table 2 for general information on the meta-analysis of PADI4, we decided to pool genotype data selected SNPs). These SNPs display either the highest for the two SNPs, rs2240340/padi4_94 and rs874881/ association signals in the original studies or a near com- padi4_92, because the latter (a nonsynonymous PADI4 plete pairwise LD with the most significantly associated [G112A] SNP) is separated by only 2.14 kb from the for- SNPs. In addition, potential functional effects for at least mer, and the two SNPs were found to be in complete LD three SNPs were described previously. Initially, in an among our 507 unrelated Japanese control subjects (pair- attempt to replicate the reported effects of the selected wise r2 = 1; Y.T., unpublished data). For a similar reason, SNPs, we genotyped a case-control sample set consisting we pooled data for the two SLC22A4 SNPs, rs2073838/ of 950 unrelated Japanese RA patients and 507 controls. slc2F1 and rs3792876/slc2F2, previously reported to be in Our case and control subjects had not previously been almost complete LD (D or r2 [ 0.97) (Tokuhiro et al. 123 u ee 20)53:163–173 (2008) Genet Hum J Table 1 Genotype and allele frequencies of RA-candidate SNPs and their association results Gene SNP (alias) No. of Genotype (frequency) HWE MAF OR (95%CI)/P value Armitage’s subjects (P trend test value) Allele Genotype (frequency) 11 12 22 1 versus 2 11 versus 22 11 versus (11 + 12) (12 + 22) versus 22

PADI4 rs2240340 Case 288 470 188 0.90 0.447 1.22 1.53 1.25 1.39 1.23 (padi4_94) (n = 946) (0.30) (0.50) (0.20) (1.04–1.43) (1.10–2.12) (0.99–1.57) (1.04–1.87) Control 178 249 76 0.52 0.399 P = 0.012 P = 0.010 P = 0.055 P = 0.025 P = 0.011 (n = 503) (0.35) (0.50) (0.15) FCRL3 rs7528684 Case 331 438 170 0.25 0.414 1.01 1.04 0.99 1.06 1.01 (fcrl3_3) (n = 939) (0.35) (0.47) (0.18) (0.87–1.18) (0.76–1.43) (0.79–1.24) (0.80–1.41) Control 176 241 87 0.78 0.412 P = 0.89 P = 0.81 P = 0.90 P = 0.69 P = 0.90 (n = 504) (0.35) (0.48) (0.17) SLC22A4 rs3792876 Case 432 415 93 0.71 0.320 1.11 1.18 1.15 1.11 1.10 (slc2F2) (n = 940) (0.46) (0.44) (0.10) (0.94–1.31) (0.80–1.74) (0.92–1.43) (0.76–1.61) Control 247 208 45 0.91 0.298 P = 0.23 P = 0.40 P = 0.21 P = 0.58 P = 0.23 (n = 500) (0.49) (0.42) (0.09) RUNX1 rs2268277 Case 341 456 147 0.84 0.397 0.99 1.01 0.96 1.04 1.00 (runx1) (n = 944) (0.36) (0.48) (0.16) (0.85–1.16) (0.73–1.41) (0.77–1.20) (0.77–1.41) Control 178 252 76 0.41 0.399 P = 0.92 P = 0.95 P = 0.72 P = 0.78 P = 0.92 (n = 506) (0.35) (0.50) (0.15) Statistically signiﬁcant values are displayed in bold letters 1 represents the major, 2 the minor, allele. SNP genotypes are coded as 11 (major allele homozygotes), 12 (heterozygotes) and 22 (minor allele homozygotes) HWE Hardy-Weinberg equilibrium; MAF minor allele frequency; OR odds ratio; 95% CI 95% conﬁdence interval Armitage’s trend test was performed by using the DeFinetti program (http://ihg.gsf.de/cgi-bin/hw/hwa1.pl) 123 167 168 J Hum Genet (2008) 53:163–173

2003). In addition, since there was an overlap of case SLC22A4 subjects in the two Korean studies of PADI4 SNPs (Kang et al. 2006; Cha et al. 2007), we excluded duplicate/over- Based on the allele distributions, no heterogeneity was lapping data for the meta-analysis (data provided courtesy observed (Q test P = 0.37, I2 = 0%; 2,626 cases and of Dr. C. Kang). The meta-analysis results are presented in 2,096 controls), and the summary ORs were significant Table 2, and the forest plots, illustrating the study-specific (fixed-effects OR 1.14, 95% CI 1.04–1.24, P = 0.0036; and summary ORs with 95% CIs, are shown in Fig. 1 random-effects OR 1.14, 95% CI 1.04–1.24, P = 0.0034; (allelic association) and ESM Fig. 1a–c (genotypic Table 2, Fig. 1c). However, there were substantial levels contrasts). of inter-study heterogeneities in either the genotype contrast of the homozygotes or the recessive model (Q test P = 0.10 and 0.040, I2 = 55.9 and 68.9%, respectively). PADI4 This appeared to be driven primarily by the excess of minor allele homozygotes among cases in the original In total, the PADI4 SNPs studies for the meta-analysis study by Tokuhiro et al. (2003), which also showed a included 3,713 RA cases and 2,485 controls (Table 2). The significant departure from HWE (P = 0.000037; ESM summary OR calculated for allele distributions was 1.31 Table 4), since this heterogeneity disappeared when the (95% CI 1.22–1.41, P \ 0.0001) under a fixed-effects study was excluded. When restricted to replication series model, and 1.32 (95% CI 1.20–1.45, P \ 0.0001) under a only (1,807 cases and 1,440 controls), the summary ORs random-effects model (Fig. 1a). There was no obvious under both fixed- and random-effects models were not inter-study OR heterogeneity (Q test P = 0.22, significant for any of the allele/genotype contrasts I2 = 31.5%). The genotype contrast of the homozygotes examined. (11 vs. 22) produced a maximum OR (fixed-effects OR 1.72, 95% CI 1.48–2.01, P \ 0.0001; random-effects OR 1.73, 95% CI 1.46–2.05, P \ 0.0001), while the dominant RUNX1 [11 vs. (12 + 22)] and recessive [(11 + 12) vs. 22] models also showed significant effects. With the exclusion of data Meta-analysis of the allele and genotype contrasts of from the initial positive study, thus restricting the analysis rs2268277/runx1 revealed extreme heterogeneity between to replication series only (2,891 cases and 1,839 controls), studies (Q test P \ 0.01, I2 [ 75%; Table 2). In a random- the summary ORs decreased slightly, but remained highly effects model, the summary OR was not significant significant. (P [ 0.05). When the first positive study (1,813 cases and 1,453 controls) was excluded, the heterogeneity disappeared (Q test P [ 0.1), while the summary ORs remained FCRL3 non-significant, with the trend actually being in the oppo- site direction (Fig. 1d). Across all five studies, the minor allele of the rs7528684/ fcrl3_3 was positively associated with RA, with a random- effects summary OR of 1.16 (95% CI 1.06–1.28, Discussion P = 0.0022; 4,111 cases and 3,420 controls; Table 2, Fig. 1b), although a moderate to large inter-study hetero- In the current study, we performed population-based geneity was noted (Q test P = 0.075, I2 = 52.9%). After association tests for the PADI4, FCRL3, SLC22A4 and exclusion of the initial samples used by Kochi et al. (2005), RUNX1 genes, all of which had prior strong evidence of in which a deviation from HWE at the 5% significance level associations with RA. We selected one SNP from each was detected in controls (P = 0.037; ESM Table 4), the gene (rs2240340/padi4_94, rs7528684/fcrl3_3, rs3792876/ heterogeneity disappeared (Q test P = 0.44, I2 = 0%), and slc2F2 and rs2268277/runx1) and tested in an independent the ORs were still significant (fixed-effects OR 1.12, 95% replication panel, consisting of a total of 1,457 Japanese CI 1.04–1.20, P = 0.0034; random-effects OR 1.12, 95% CI subjects (950 RA cases and 507 controls). Our results 1.04–1.20, P = 0.0032). The genotype contrast of the ho- demonstrated that only SNP rs2240340/padi4_94 in the mozygotes (11 vs. 22) produced the maximum OR under PADI4 gene showed significant, reproducible allelic and both fixed- and random-effects models (ORs 1.24–1.40); genotypic associations, whereas no statistically significant however, the magnitude of associations was considerably differences between cases and controls were observed for smaller than the effect estimated in the initial positive study the remaining SNPs in either allele or genotype (i.e., homozygosity OR 2.24) (Kochi et al. 2005). frequencies.

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Table 2 Meta-analysis of RA-candidate SNPs and their genetic associations with RA Gene Studies (no.) Genetic No. of Cochran QI2 (95% CI) Fixed effects Random effects constrasts subjects (case/ Q (df) P OR (95% CI) P value OR (95% CI) P value control) value

PADI4 All (4) 1 versus 2 3,713/ 4.38 (3) 0.22 31.5% (0– 1.31 (1.22– \0.0001 1.32 (1.20– \0.0001 2,485 77.0) 1.41) 1.44) 11 versus 22 1,853/ 3.59 (3) 0.31 16.5% (0– 1.72 (1.48– \0.0001 1.73 (1.46– \0.0001 1,296 72.9) 2.01) 2.05) 11 versus 3,713/ 4.40 (3) 0.22 31.9% (0– 1.42 (1.27– \0.0001 1.42 (1.25– \0.0001 (12 + 22) 2,485 77.1) 1.58) 1.63) (11 + 12) 3,713/ 1.63 (3) 0.65 0% (0–67.9) 1.46 (1.27– \0.0001 1.46 (1.27– \0.0001 versus 22 2,485 1.67) 1.67) Replication 1 versus 2 2,891/ 3.33 (2) 0.19 39.9% (0– 1.28 (1.18– \0.0001 1.29 (1.16– \0.0001 (3) 1,839 82.3) 1.40) 1.44) 11 versus 22 1,446/955 2.65 (2) 0.27 24.4% (0– 1.65 (1.39– \0.0001 1.66 (1.36– \0.0001 78.9) 1.97) 2.04) 11 versus 2,891/ 3.51 (2) 0.17 43.1% (0– 1.37 (1.21– \0.0001 1.39 (1.17– 0.0001 (12 + 22) 1,839 83.0) 1.56) 1.64) (11 + 12) 2,891/ 1.11 (2) 0.58 0% (0–72.9) 1.42 (1.21– \0.0001 1.42 (1.21– \0.0001 versus 22 1,839 1.66) 1.66) FCRL3 All (5) 1 versus 2 4,111/ 8.48 (4) 0.075 52.9% (0– 1.16 (1.09– \0.0001 1.16 (1.06– 0.0022 3,420 80.7) 1.24) 1.28) 11 versus 22 2,120/ 12.7 (4) 0.013 68.5% (0– 1.39 (1.21– \0.0001 1.40 (1.09– 0.0088 1,762 85.7) 1.59) 1.80) 11 versus 4,111/ 3.41 (4) 0.49 0% (0–64.1) 1.18 (1.08– 0.0007 1.18 (1.07– 0.0006 (12 + 22) 3,420 1.30) 1.30) (11 + 12) 4,111/ 15.4 (4) 0.0039 74.0% (0.3– 1.29 (1.14– \0.0001 1.31 (1.02– 0.036 versus 22 3,420 87.6) 1.47) 1.68) Replication 1 versus 2 3,287/ 2.70 (3) 0.44 0% (0–67.9) 1.12 (1.04– 0.0034 1.12 (1.04– 0.0032 (4) 2,771 1.20) 1.20) 11 versus 22 1,670/ 2.90 (3) 0.41 0% (0–67.9) 1.24 (1.07– 0.0063 1.24 (1.07– 0.0056 1,431 1.45) 1.45) 11 versus 3,287/ 2.85 (3) 0.42 0% (0–67.9) 1.16 (1.04– 0.0071 1.16 (1.04– 0.0066 (12 + 22) 2,771 1.29) 1.29) (11 + 12) versus 3,287/ 2.58 (3) 0.46 0% (0–67.9) 1.16 (1.01– 0.045 1.16 (1.01– 0.041 22 2,771 1.33) 1.33) SLC22A4 All (3) 1 versus 2 2,626/ 2.00 (2) 0.37 0% (0–72.9) 1.14 (1.04– 0.0036 1.14 (1.04– 0.0034 2,096 1.24) 1.24) 11 versus 22 1,507/ 4.53 (2) 0.10 55.9% (0– 1.43 (1.17– 0.0005 1.42 (1.05– 0.022 1,178 85.8) 1.74) 1.92) 11 versus 2,626/ 0.33 (2) 0.85 0% (0–72.9) 1.10 (0.98– 0.12 1.10 (0.98– 0.11 (12 + 22) 2,096 1.24) 1.24) (11 + 12) 2,626/ 6.42 (2) 0.040 68.9% (0– 1.42 (1.18– 0.0003 1.40 (1.00– 0.053 versus 22 2,096 88.8) 1.71) 1.98) Replication 1 versus 2 1,807/ 0.04 (1) 0.84 – 1.09 (0.98– 0.11 1.09 (0.98– 0.11 (2) 1,440 1.21) 1.21) 11 versus 22 1,009/810 0.050 (1) 0.82 – 1.22 (0.96– 0.12 1.22 (0.96– 0.10 1.56) 1.56) 11 versus 1,807/ 0.32 (1) 0.57 – 1.09 (0.95– 0.22 1.09 (0.95– 0.21 (12 + 22) 1,440 1.26) 1.26) (11 + 12) 1,807/ 0.21 (1) 0.65 – 1.19 (0.94– 0.16 1.19 (0.94– 0.14 versus 22 1,440 1.50) 1.50)

123 170 J Hum Genet (2008) 53:163–173

Table 2 continued Gene Studies (no.) Genetic No. of Cochran QI2 (95% CI) Fixed effects Random effects constrasts subjects (case/ Q (df) P OR (95% CI) P OR (95% CI) P control) value value value

RUNX1 All (3) 1 versus 2 2,633/2,103 11.5 (2) 0.0032 82.6% (0– 1.04 (0.96– 0.39 1.05 (0.86– 0.65 92.5) 1.13) 1.28) 11 versus 22 1,318/1,091 9.29 (2) 0.0096 78.5% (0– 1.05 (0.88– 0.60 1.07 (0.73– 0.73 91.3) 1.25) 1.57) 11 versus 2,633/2,103 11.6 (2) 0.0030 82.8% (0– 1.09 (0.96– 0.19 1.09 (0.82– 0.55 (12 + 22) 92.6) 1.23) 1.47) (11 + 12) 2,633/2,103 4.70 (2) 0.095 57.4% (0– 1.00 (0.85– 0.98 1.01 (0.79– 0.95 versus 22 86.2) 1.17) 1.29) Replication 1 versus 2 1,813/1,453 0.66 (1) 0.42 – 0.94 (0.85– 0.28 0.94 (0.85– 0.27 (2) 1.04) 1.04) 11 versus 22 921/736 1.09 (1) 0.30 – 0.88 (0.71– 0.27 0.88 (0.71– 0.28 1.09) 1.10) 11 versus 1,813/1,453 0.05 (1) 0.82 – 0.94 (0.81– 0.44 0.94 (0.81– 0.41 (12 + 22) 1.09) 1.09) (11 + 12) 1,813/1,453 1.52 (1) 0.22 – 0.90 (0.75– 0.32 0.91 (0.72– 0.44 versus 22 1.09) 1.16) Statistically signiﬁcant values are displayed in bold letters 1 represents the major, 2 the minor, allele. SNP genotypes are coded as 11 (major allele homozygotes), 12 (heterozygotes) and 22 (minor allele homozygotes) OR odds ratio; 95% CI 95% conﬁdence interval; df degree of freedom

In our sample set, the association of rs2240340/ seemed to be much smaller than that in Asians, and further padi4_94 was only modest (allelic OR 1.22, P = 0.012; analysis with a much larger sample size is therefore needed Table 1). The most significant association with RA sus- to draw a conclusion (Iwamoto et al. 2006; Lee et al. 2007). ceptibility was observed in the contrast of homozygotes Unfortunately, the exact nature of causal variant(s) (genotype 11 vs 22; OR 1.53, P = 0.010), a consistent within the PADI4 gene responsible for RA susceptibility is observation already suggested in the original report by currently unknown. Suzuki et al. (2003) identified at least Suzuki et al. (2003). To our knowledge, our study is the three missense variants of PADI4, including G55S, V82A third follow-up replication cohort examining the relation- and G112A (rs874881/padi4_92), which are tightly linked ship between the PADI4 polymorphisms and RA in East with each other, and any of these may have functional Asians. In all studies, the association was ultimately found significance. In addition, it has been reported that the to be consistently significant (see Fig. 1a), reinforcing the susceptibility haplotype, which is marked by disease- notion that PADI4 gene polymorphisms contribute to the associated SNPs including rs2240340/padi4_94 and development of RA in this ethnic group. When published rs874881/padi4_92, affects the stability of PADI4 tran- genotype data of the two tightly linked SNPs, rs2240340/ scripts, raising the possibility that variants in intronic or padi4_94 and rs874881/padi4_92, were combined, the non-coding regions may alter transcriptional regulation, updated allelic summary OR was 1.31 (fixed-effects), a thus contributing to the pathogenic consequences. Further value similar to those from previous meta-analyses in East studies, including extensive genetic analyses in diverse Asians (Iwamoto et al. 2006; Lee et al. 2007). Although ethnic groups with different LD characteristics, as well as this study focused on East Asian populations, it is impor- biochemical evaluations, are warranted to identify actual tant to ascertain whether PADI4 SNPs confer RA risk in a causal variant(s) and to better understand the role of PADI4 race-specific manner. In white populations, previous asso- in the development of RA. ciation studies have produced inconsistent results (Barton Although we failed to detect significant associations for et al. 2005a; Harney et al. 2005; Martinez et al. 2005; the FCRL3, SLC22A4 and RUNX1 SNPs in our replication Plenge et al. 2005; Hoppe et al. 2006). However, recent sample set, the meta-analyses of East Asian studies ethnicity-specific meta-analyses have suggested that the showed evidence of FCRL3 and SLC22A4 associations padi4_94 SNP may be associated with increased risk of RA (P = 0.0022 and 0.0034, respectively; see Table 2, in Europeans, although the magnitude of association Fig. 1b, c). However, these results should be interpreted

123 J Hum Genet (2008) 53:163–173 171

Allele

a) PADI4 b) FCRL3

Suzuki, 2003 (Japanese) 1.40 (1.21-1.63) Kochi, 2005 (Japanese, set 1) 1.37 (1.18-1.60)

Kochi, 2005 (Japanese, set 2) 1.19 (1.01-1.41) Ikari, 2005 (Japanese) 1.23 (1.09-1.39) Ikari, 2006 (Japanese) 1.18 (1.02-1.35) Kang, 2007 (Korean) 1.48 (1.24-1.77) Choi, 2006 (Korean) 1.10 (0.96-1.27)

Takata, this study (Japanese) 1.22 (1.04-1.43) Takata, this study (Japanese) 1.01 (0.87-1.18)

All (fixed) 1.31 (1.22-1.41) All (fixed) 1.16 (1.09-1.24)

All (random) 1.32 (1.20-1.44) All (random) 1.16 (1.06-1.28)

Replication (fixed) 1.28 (1.18-1.40) Replication (fixed) 1.12 (1.04-1.20)

Replication (random) 1.29 (1.16-1.44) Replication (random) 1.12 (1.04-1.20)

1 2 0.5 1 2 OR (95% CI) OR (95% CI)

c) SLC22A4 d) RUNX1

Tokuhiro, 2003 (Japanese) 1.25 (1.07-1.46) Tokuhiro, 2003 (Japanese) 1.28 (1.10-1.48)

Kuwahara, 2005 (Japanese) 1.08 (0.94-1.24) Kawahara, 2005 (Japanese) 0.91 (0.80-1.04)

Takata, this study (Japanese) 1.11 (0.94-1.31) Takata, this study (Japanese) 0.99 (0.85-1.16)

All (fixed) 1.14 (1.04-1.24) All (fixed) 1.04 (0.96-1.13)

All (random) 1.14 (1.04-1.24) All (random) 1.05 (0.86-1.28)

Replication (fixed) 1.09 (0.98-1.21) Replication (fixed) 0.94 (0.85-1.04)

Replication (random) 1.09 (0.98-1.21) Replication (random) 0.94 (0.85-1.04)

0.5 1 2 0.5 1 2 OR (95% CI) OR (95% CI)

Fig. 1 Meta-analysis of the allelic association between selected summary ORs and their 95% CI were calculated separately for the candidate genes and RA in East Asian populations. A meta-analysis ‘‘All’’ and ‘‘Replication’’ studies, using fixed- and random-effects plot for the allelic associations (allele 1 vs. 2) is shown here. Black approaches, and are indicated by the unshaded diamonds. a PADI4 squares indicate the study-specific odds ratios (ORs), with the size of (rs2240340/padi4_94 or rs874881/padi4_92); b FCRL3 (rs7528684/ each square being inversely proportional to its variance, and fcrl3_3); c SLC22A4 (rs3792876/slc2F2 or rs2073838/slc2F1); and d horizontal lines represent the 95% confidence intervals (CIs). The RUNX1 gene (rs2268277/runx1) with much greater caution for several reasons. First, replication studies) greatly diminished the heterogeneities, although individual studies included in the meta-analysis and the FCRL3 SNP remained significant, whereas were relatively large with reasonable statistical powers SLC22A4 SNPs became non-significant. These procedures, and further power improvement can be expected by meta- however, could further reduce the available statistical analysis, power still appears to be inadequate to detect power and limit the capacity to detect small effects, and such a small genetic effect (i.e., OR \ 1.2). Unfortunately, may produce false-negative results. Third, the magnitudes power calculations for meta-analysis are controversial and of individual effects were likely to be much weaker than therefore were not conducted in this study. However, those reported in the first positive reports. In addition, the when statistical power is estimated simply using the updated allele fixed-effects summary OR for rs7528684/ summary ORs and their allele frequencies, over 6,000 (for fcrl3_3 was 1.16, showing a trend toward a decrease as FCRL3) and 8,000 (for SLC22A4) subjects (assuming compared with an OR of 1.20 for East Asian subjects, equal number of cases and controls) will be required to provided by a previously published meta-analysis (Bego- achieve 80% power to detect a true allelic association at vich et al. 2007). These are perhaps because the risk the 5% significance level. Thus, many more subjects are effects may have been overestimated in the first reports, apparently required for the assessment of SLC22A4 SNPs. consistent with a phenomenon known as the ‘‘winner’s Second, for each meta-analysis, there was a considerable curse’’ effect (Lohmueller et al. 2003). Lastly, several level of inter-study OR heterogeneity. The removal of other methodological limitations of a meta-analysis should initial positive reports (thus restricting this analysis to also be considered. A publication and reporting bias could

123 172 J Hum Genet (2008) 53:163–173 be present, because it has not been long since the first References reports of gene association and, to date, only a few publications are available. On the other hand, adverse effects Arnett FC, Edworthy SM, Bloch DA, McShane DJ, Fries JF, Cooper due to the differences in LD pattern across populations NS, Healey LA, Kaplan SR, Liang MH, Luthra HS, Medsger TAJ, Mitchell DM, Neustadt DH, Pinals RS, Schaller JG, Sharp will be less problematic, because (1) the present study JT, Wilder RL, Hunder GG (1988) The American Rheumatism population was eventually restricted to Japanese and Association 1987 revised criteria for the classification of Korean populations, which are geographically and his- rheumatoid arthritis. Arthritis Rheum 31:315–324 torically closely related and genetically quite similar to Barton A, Bowes J, Eyre S, Symmons D, Worthington J, Silman A (2005a) Investigation of polymorphisms in the PADI4 gene in each other (Kim et al. 2005), and (2) most of the selected determining severity of inflammatory polyarthritis. Ann Rheum SNPs were themselves proposed to be putative causal Dis 64:1311–1315 variants. It should also be mentioned that, due to limited Barton A, Eyre S, Bowes J, Ho P, John S, Worthington J (2005b) information, this meta-analysis was based on unadjusted Investigation of the SLC22A4 gene (associated with rheumatoid arthritis in a Japanese population) in a United Kingdom estimates, and a more precise analysis could be performed population of rheumatoid arthritis patients. Arthritis Rheum with adjustment for potential confounding factors (e.g., 52:752–758 gender, age, disease duration, SE allele and autoantibody Begovich AB, Carlton VE, Honigberg LA, Schrodi SJ, Chokkalingam status). Other possibilities include technical artifacts (e.g., AP, Alexander HC, Ardlie KG, Huang Q, Smith AM, Spoerke JM, Conn MT, Chang M, Chang SY, Saiki RK, Catanese JJ, genotyping error), unrecognized bias (due to differences in Leong DU, Garcia VE, McAllister LB, Jeffery DA, Lee AT, the ascertainment of either case or control populations, Batliwalla F, Remmers E, Criswell LA, Seldin MF, Kastner DL, clinical severity and genetic/familial loading of case Amos CI, Sninsky JJ, Gregersen PK (2004) A missense single- subjects, or an unmeasured variable), hidden population nucleotide polymorphism in a gene encoding a protein tyrosine phosphatase (PTPN22) is associated with rheumatoid arthritis. stratification or gene-environment interactions. Overall, Am J Hum Genet 75:330–337 we believe that more independent studies, with even larger Begovich AB, Chang M, Schrodi SJ (2007) Meta-analysis evidence of sample sizes and subsequent updates of the meta-analysis a differential risk of the FCRL3 -169T?C polymorphism in results will be required to determine the precise impacts of white and East Asian rheumatoid arthritis patients. Arthritis Rheum 56:3168–3171 these genes in RA susceptibility in East Asians. Cha S, Choi CB, Han TU, Kang CP, Kang C, Bae SC (2007) In summary, our results and meta-analysis do support Association of anti-cyclic citrullinated peptide antibody levels the hypothesis that PADI4 polymorphisms contribute sub- with PADI4 haplotypes in early rheumatoid arthritis and with stantially to the development of RA in East Asian shared epitope alleles in very late rheumatoid arthritis. Arthritis Rheum 56:1454–1463 populations. Our case-control study failed to replicate the Choi CB, Kang CP, Seong SS, Bae SC, Kang C (2006) The -169C/T reported associations for the FCRL3, SLC22A4 and RUNX1 polymorphism in FCRL3 is not associated with susceptibility to SNPs. We emphasize herein the importance of reporting rheumatoid arthritis or systemic lupus erythematosus in a case- non-significant results to avoid distorting the body of control study of Koreans. Arthritis Rheum 54:3838–3841 de Vries RR, Huizinga TW, Toes RE (2005) Redefining the HLA and publicly available data. While meta-analysis indicated RA association: to be or not to be anti-CCP positive. J some evidence of association between the FCRL3 and Autoimmun 25(Suppl):21–25 SLC22A4 SNPs and RA, their impact on RA in East Asians Eyre S, Bowes J, Potter C, Worthington J, Barton A (2006) seems much more limited than previously thought. Nev- Association of the FCRL3 gene with rheumatoid arthritis: a further example of population specificity? Arthritis Res Ther ertheless, even a small genetic risk may identify a gene 8:R117 with an important biological role that could yield new Fisher SA, Hampe J, Onnie CM, Daly MJ, Curley C, Purcell S, mechanistic insights and provide novel therapeutic targets. Sanderson J, Mansfield J, Annese V, Forbes A, Lewis CM, Finally, our results add to our understanding of the genetic Schreiber S, Rioux JD, Mathew CG (2006) Direct or indirect association in a complex disease: the role of SLC22A4 and basis of RA and emphasize the need for additional asso- SLC22A5 functional variants in Crohn disease. Hum Mutat ciation studies with greater statistical power and updated 27:778–785 meta-analysis. Gregersen PK, Lee HS, Batliwalla F, Begovich AB (2006) PTPN22: setting thresholds for autoimmunity. Semin Immunol 18:214– 223 Acknowledgments We would like to thank our patients and vol- Hamada D, Takata Y, Osabe D, Nomura K, Shinohara S, Egawa H, unteer blood donors for participating in this study. We thank Dr. Nakano S, Shinomiya F, Scafe CR, Reeve VM, Miyamoto T, Katsunori Ikari (Tokyo Women’s Medical University, Tokyo, Japan), Moritani M, Kunika K, Inoue H, Yasui N, Itakura M (2005) Professor Changwon Kang (Korea Advanced Institute of Science and Association between single-nucleotide polymorphisms in the Technology, Daejeon, Korea) and Professor Sang-Cheol Bae (Hany- SEC8L1 gene, which encodes a subunit of the exocyst complex, ang University, Seoul, Korea) for their generosity in providing and rheumatoid arthritis in a Japanese population. Arthritis additional information regarding the genotype information described Rheum 52:1371–1380 in their reports. We also thank the many past and present members of Harney SM, Meisel C, Sims AM, Woon PY, Wordsworth BP, Brown our research group for helpful discussions. This study was partially MA (2005) Genetic and genomic studies of PADI4 in rheuma- funded by grants from the Ministry of Education, Science and toid arthritis. Rheumatology (Oxford) 44:869–872 Technology (Knowledge Cluster Initiative).

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