Comprehensive Association Study of Genetic Variants in the IL-1 Gene Family in Systemic Juvenile Idiopathic Arthritis

Home , IL1A, IL1F10, IL1RL1, Interleukin 18, Interleukin 6

ORIGINAL ARTICLE Comprehensive association study of genetic variants in the IL-1 gene family in systemic juvenile idiopathic arthritis

CJW Stock1, EM Ogilvie1, JM Samuel1, M Fife1, CM Lewis2 and P Woo1 1Centre for Paediatric and Adolescent Rheumatology, Windeyer Institute for Medical Sciences, University College London, London, UK and 2Guy’s, Kings and St Thomas’ School of Medicine, London, UK

Patients with systemic juvenile idiopathic arthritis (sJIA) have a characteristic daily spiking fever and elevated levels of inflammatory cytokines. Members of the interleukin-1 (IL-1) gene family have been implicated in various inflammatory and autoimmune diseases, and treatment with the IL-1 receptor antagonist, Anakinra, shows remarkable improvement in some patients. This work describes the most comprehensive investigation to date of the involvement of the IL-1 gene family in sJIA. A two-stage case–control association study was performed to investigate the two clusters of IL-1 family genes using a tagging single nucleotide polymorphism (SNP) approach. Genotyping data of 130 sJIA patients and 151 controls from stage 1 highlighted eight SNPs in the IL1 ligand cluster region and two SNPs in the IL1 receptor cluster region as showing a significant frequency difference between the populations. These 10 SNPs were typed in an additional 105 sJIA patients and 184 controls in stage 2. Meta-analysis of the genotypes from both stages showed that three IL1 ligand cluster SNPs (rs6712572, rs2071374 and rs1688075) and one IL1 receptor cluster SNP (rs12712122) show evidence of significant association with sJIA. These results indicate that there may be aberrant control of the activity of the IL-1 family in sJIA patients causing the increased susceptibility to the disease. Genes and Immunity (2008) 9, 349–357; doi:10.1038/gene.2008.24; published online 17 April 2008

Keywords: sJIA; IL-1; genetic association

Introduction sJIA is with the anti-inflammatory cytokines IL-10 and IL-20, including an association with a low-expressing Juvenile idiopathic arthritis (JIA) is a clinically hetero- 7 1 IL10 genotype. geneous disease with seven subtypes. It is thought that IL-1 is a pro-inflammatory cytokine that affects nearly this clinical diversity reflects a difference in the under- every cell type, often working in concert with tumor lying pathology and genetic heterogeneity. Despite a necrosis factor (TNF). It can also upregulate host spectrum of disease activity, systemic JIA (sJIA) can be defences and function as one of the key cytokines the most severe of the subtypes, and is potentially fatal. mediating the innate immunity response.8 Located There are currently no disease-specific markers for sJIA together on a locus on chromosome 2q139,10 are the and diagnosis may be difficult as exclusion of other genes for the two naturally occurring forms of IL-1: IL-1a diagnoses by an extensive investigative work up is b 2 and IL-1 , and for the naturally occurring IL-1 receptor essential. antagonist, IL-1Ra. Also within the same locus are the six There is much evidence that patients with sJIA have an recently discovered genes belonging to the IL-1 family, altered cytokine profile, a possible cause for pathogenic named IL-1F5–IL-1F1011–13 (Figure 1). The function of chronic inflammation, when compared to patients with 2 these new family members is still to be elucidated but other JIA subtypes and to healthy individuals. A there is evidence that some may act through IL-1RL2 and number of cytokine candidate gene associations have IL-1RAcP14,15 and that IL-1F7 may be important in IL-18 been found that are specific to the systemic subtype of antagonism.16 JIA. This includes an association with interleukin-6 (IL-6) The genes for the IL-1 receptor family are also located gene polymorphisms3,4 and a macrophage migration 5 together in a cluster on chromosome 2q11.2, along with inhibitory factor gene polymorphism, which may also the genes for the two IL-18 receptors (IL-18R1 and be a predictor of poorer outcome after intra-articular IL-18RAcP) also members of the IL-1 receptor family17 injections.6 The most recent association to be shown with (Figure 1). The type 1 IL-1 receptor (IL-1R1) is required for signal transduction, while the type 2 IL-1 receptor Correspondence: Professor P Woo, Centre for Paediatric and (IL-1R2) is a non-signal transducing, decoy receptor.18 Adolescent Rheumatology, 3rd Floor, Windeyer Institute for There are also an additional two members of the IL-1 Medical Sciences, University College London, 46 Cleveland Street, receptor family, IL-1RL1 and IL-1RL2, neither of which London W1T 4JF, UK. 19 E-mail: [email protected] binds IL-1 but IL-1RL2 has been shown to be the Received 19 December 2007; revised 25 February 2008; accepted 25 receptor through which the IL-1F6, 8 and 9 ligands February 2008; published online 17 April 2008 induce a signal.14 Comprehensive study of IL-1 gene family in sJIA CJW Stock et al 350

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IL1A IL1B IL1F7 IL1F9 IL1F6 IL1F8 IL1F5 IL1F10 IL1RN

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IL1R2 IL1R1IL1RL2 IL1RL1 IL18R1 IL18RAP

Figure 1 Graphical representation of the linkage disequilibrium (LD) patterns across the candidate loci from Haploview. Shown is the organization of the interleukin-1 (IL-1) family genes in the two clusters on chromosome 2 as well as the single nucleotide polymorphism (SNP) coverage of the initial SNP set. The LD between these SNPs is shown (r2) for those o150 kb apart. Key: white square, r2 ¼ 0; grey square, 0or2o1; black square, r2 ¼ 1.

IL-1 inhibitory activity was found in the serum of sJIA significant difference in the production of IL-6 and TNF patients at the height of fever20 and there has been shown between patients and controls in the same cultures.22 to be a significant difference (10-fold increase) between Further evidence that IL-1 is important in the pathogen- the plasma levels of IL-1Ra in control individuals and esis of sJIA comes from both papers and anecdotal in sJIA patients.21 Pascual et al.22 found that when peri- evidence that treatment with a recombinant IL-1 antago- pheral blood mononuclear cells (PBMCs) from healthy nist, Anakinra, shows remarkable improvement in some individuals were incubated with serum from active sJIA sJIA patients.22 However, there is evidence that there patients several members of the IL-1 and IL-1R family: may be at least two sJIA patient subpopulations: IL1B, IL1RN, IL1R1 and IL1R2, showed a more than Anakinra-responsive and non-responsive; in a trial of twofold increased gene expression compared to PBMCs French patients approximately half were responsive.23 incubated without culture or with autologous serum. Comparable findings were also observed in an Italian Additionally, they found that IL-1b and IL-1R2 proteins cohort and also in a UK cohort (unpublished observa- were over-expressed in the PBMCs of patients compared tions). Similar results have been seen with the receptor to healthy controls, PBMCs from sJIA patients also had a based IL-1 blocker, IL-1 TRAP (Rilonacept).24 greater capacity to secrete IL-1b after stimulation with A number of associations of IL-1 ligand and receptor phorbol myristate acetate-ionomycin than PBMCs from gene polymorphisms have been found with various healthy individuals (15-fold increase) but there was no inflammatory and autoimmune diseases, including

Genes and Immunity Comprehensive study of IL-1 gene family in sJIA CJW Stock et al 351 osteoarthritis,25 severity of rheumatoid arthritis (RA)26 confidence in genotype calling. An additional four SNPs and the severity of chronic polyarthritis.27 There have in the IL1 ligand cluster and six SNPs in the IL1 receptor also been a number of associations shown with ankylos- cluster were dropped from analysis due to the controls ing spondylitis,28,29 susceptibility and severity of alopecia significantly violating Hardy–Weinberg equilibrium. All areata,30 periodontitis31 and type 1 diabetes (including the SNPs in stage 2 were in Hardy–Weinberg equilibrium circulating plasma levels in an allele dose effect).32 IL-1 and there was no significant difference found in the family associations of particular note include a poly- genotype calling of the two platforms used (97.8% morphism in the IL1A promoter region with early onset concordance). oligoarticular arthritis,33 although this was not replicated 34 in a subsequent cohort. A variable number tandem Stage 1 association analysis repeat in IL1RN has been associated with JIA as a whole, In the initial individual analysis of the stage 1 data 11 when the subtypes were examined separately this was SNPs in the IL1 ligand region showed significant allele also significant in the subtypes of extended oligoarthritis, frequency differences between the two populations enthesitis-related arthritis and other arthritis, but (Po0.05). Conditional analysis showed that the observed 35 not sJIA. significance of three of these SNPs was due to their being To date no IL-1 family associations have been found in significant LD with another of the SNPs, and so 33,35,36 with the systemic subtype of JIA specifically, they were removed from the model. Significant allele however, these studies were designed to investigate JIA frequency differences between the sJIA cases and as a whole and therefore in subgroup analyses the the healthy controls were observed for SNP1 (rs6712572, systemic subtype was underpowered. Previous associa- P ¼ 0.0045), SNP4 (rs2071374, P ¼ 0.006), SNP5 (rs3783516, tion studies of the IL-1 family have also only looked at P ¼ 0.0053), SNP7 (rs4848123, P ¼ 0.003), SNP10 (rs3917368, limited polymorphic diversity in one or two of the family P ¼ 0.0096), SNP64 (rs1688075, P ¼ 0.00089), SNP80 members while a complete screen of all the members is (rs4849159, P ¼ 0.04) and SNP81 (rs6760120, P ¼ 0.02) necessary to be able to fully understand the involvement (Table 1). of IL-1 in disease susceptibility. We report here the most Of the 123 tSNPs typed in the IL1 receptor region, comprehensive gene association study to date of all the 9 showed significant association in the initial analysis, all known genes within the two IL-1 gene family clusters in of which were located around IL1R2. Conditional and sJIA patients, using tagging single nucleotide poly- haplotype analysis determined that the effect shown by morphisms (tSNPs). these nine SNPs was explained by two of them, SNP8 and SNP23 (rs12712122, P ¼ 0.003 and rs4851531, P ¼ 0.009 respectively) (Table 1). The alternative like- Results lihoods of the analyses of this haplotype, with and Tagging SNP selection without interactions, were exactly the same, showing Genotype data were publicly available for a total of 998 that the best model for the association is that of no SNPs in the two clusters that satisfied the criteria of interaction, suggesting that the two markers contribute minor allele frequency (MAF)X0.05 in Caucasians. Due independently to disease risk but do not interact in to the significant linkage disequilibrium (LD; Figure 1) an epistatic manner. These SNPs show odds ratios between these SNPs, tSNP selection identified 211 SNPs (ORs) ¼ 1.52 and 1.59 respectively, with OR ¼ 2 for the capable of capturing all of the variation contained within two combined. the full set, 88 for the ligand cluster and 123 for the No haplotypes examined showed stronger significance receptor cluster. than individual SNPs and so results are not presented here. Genotyping These 10 SNPs from the two candidate regions In stage 1 five SNPs in the IL1 ligand cluster and one in showing evidence of association in stage 1 were pursued the IL1 receptor cluster were dropped due to low for further investigation in stage 2 of the study.

Table 1 Stage 1 results for the 10 SNPs from the two candidate regions pursued in stage 2

Candidate region SNP rs number Case frequency Control frequency OR (95% CI) P-value

IL1 ligand cluster 1 rs6712572 0.600 0.479 1.62 (1.16–2.29) 0.0045 4 rs2071374 0.387 0.277 1.65 (1.15–2.37) 0.0060 5 rs3783516 0.515 0.397 1.64 (1.15–2.27) 0.0053 7 rs4848123 0.411 0.291 1.70 (1.19–2.44) 0.0030 10 rs3917368 0.454 0.346 1.57 (1.11–2.22) 0.0096 64 rs1688075 0.115 0.041 3.04 (1.58–5.85) 0.0089 80 rs4849159 0.869 0.804 1.61 (1.02–2.54) 0.040 81 rs6760120 0.657 0.561 1.49 (1.06–2.21) 0.020

IL1 receptor cluster 8 rs12712122 0.396 0.277 1.71 (1.21–2.41) 0.0031 23 rs4851531 0.664 0.553 1.59 (1.11–2.28) 0.0087

Abbreviations: CI, confidence intervals; IL1, interleukin 1; OR, odds ratios; SNP, single nucleotide polymorphism. The frequencies in the case and control populations of the allele conferring increased risk are shown. The OR, 95% CI and P-values for each SNP are also shown.

Genes and Immunity Comprehensive study of IL-1 gene family in sJIA CJW Stock et al 352 Stage 2 association analysis (P ¼ 0.047; Table 3). Both of the IL1 receptor cluster SNPs The frequencies of the 10 SNPs typed in the stage 2 tested in both stages of the study showed a significant samples are shown in Table 2. None of the SNPs show a difference between the effect sizes observed in the two significant frequency difference in this sample set alone. groups (BD Po0.05). SNP8 is tagging four other SNPs: 8a The meta-analysis of the data from the two stages of (rs1010329), 8b (rs2190361), 8c (rs2190360) and 8d 2 the association study identified three SNPs within the IL1 (rs740044), with r ¼ 0.86, 1, 1 and 0.82 respectively. All ligand cluster that showed evidence of association five of these significant SNPs are located upstream of (Po0.05), SNP1 (P ¼ 0.025), SNP4 (P ¼ 0.002) and IL1R2 at, in chromosomal order, À43236, À37208, À16309 SNP64 (P ¼ 0.002) (Table 3). The table also shows that and À8137, relative to start of transcription (Figure 3). As these three IL1 ligand cluster SNPs did not have SNPs 8a and 8d are not in total LD with SNP 8 they were significant (Po0.05) Breslow–Day (BD) P-values, while also both subsequently typed directly. They both showed the four SNPs which did not show evidence of a significant frequency difference in the stage 1 samples association overall did show evidence of significant (P ¼ 0.0062 and P ¼ 0.02), but not in the stage 2 samples differences between the ORs in the two groups tested. (P ¼ 0.52 and P ¼ 0.81), nor in the meta-analysis of the SNPs1 and 2 are not tagging any other SNPs within the two stages (P ¼ 0.11 and P ¼ 0.13) (data not shown). region, but SNP64 is tagging two other SNPs: SNPs 64a (rs28928309) and 64b (rs315925), both with r2 ¼ 1. SNP1 is located 22.29 kb downstream of IL1A and SNP4 is within Discussion intron 4 of IL1A. SNP64a is located at position þ 4844 relative to the start of transcription of IL1F10, SNP64 is at The recent publication of large genotype databases has position À26942 and SNP64b at À19771, both relative to made it possible for more comprehensive association the start of transcription of IL1RN (Figure 2). studies to be performed by enabling investigation of the SNP8 in the IL1 receptor gene region showed evidence LD between SNPs in candidate genes, facilitating of association in the meta-analysis of the two stages the use of tSNP approaches. This significantly reduces

Table 2 Stage 2 results for the 10 SNPs from the two candidate regions

Candidate region SNP rs number Case frequency Control frequency OR (95% CI) P-value

IL1 ligand cluster 1 rs6712572 0.52 0.51 1.05 (0.74–1.49) 0.77 4 rs2071374 0.34 0.28 1.33 (0.93–1.89) 0.13 5 rs3783516 0.38 0.41 0.87 (0.60–1.26) 0.45 7 rs4848123 0.29 0.33 0.81 (0.55–1.20) 0.27 10 rs3917368 0.33 0.36 0.85 (0.58–1.24) 0.36 64 rs1688075 0.08 0.06 1.37 (0.70–2.67) 0.34 80 rs4849159 0.76 0.8 0.78 (0.52–1.19) 0.24 81 rs6760120 0.57 0.58 0.98 (0.68–1.40) 0.89

IL1 receptor cluster 8 rs12712122 0.37 0.38 0.97 (0.68–1.40) 0.87 23 rs4851531 0.6 0.63 0.89 (0.63–1.26) 0.52

Abbreviations: CI, confidence intervals; IL1, interleukin 1; OR, odds ratios; SNP, single nucleotide polymorphism. The frequencies in the case and control populations of the allele conferring increased risk in stage 1 are shown. The ORs, 95% CI and P-values for each SNP are also shown.

Table 3 Two-stage meta-analysis results for the 10 SNPs investigated in stage 2 of the study

Candidate region SNP rs number CMH w2 CMH P-value OR (95% CI) BD P-value

IL1 ligand cluster 1 rs6712572 4.986 0.025 1.32 (1.04–1.67) 0.076 4 rs2071374 9.137 0.002 1.48 (1.15–1.92) 0.411 5 rs3783516 2.28 0.131 1.21 (0.93–1.54) 0.0142 7 rs4848123 1.952 0.162 1.20 (0.93–1.5) 0.005 10 rs3917368 1.583 0.208 1.17 (0.92–1.5) 0.015 64 rs1688075 9.263 0.002 2.04 (1.29–3.24) 0.098 80 rs4849159 0.283 0.595 0.92 (0.68–1.25) 0.022 81 rs6760120 2.432 0.119 0.82 (0.64–1.05) 0.088

IL1 receptor cluster 8 rs12712122 3.957 0.047 1.29 (1.01–1.66) 0.029 23 rs4851531 2.072 0.15 0.83 (0.65–1.07) 0.023

Abbreviations: BD, Breslow–Day; CI, confidence intervals; CMH, Cochran–Mantel–Haenszel; IL1, interleukin 1; OR, odds ratios; SNP, single nucleotide polymorphism. The results of the CMH test for meta-analysis are shown, as are the ORs and 95% CI. Also shown are the results for the BD test for homogeneity of the ORs from the two stages.

Genes and Immunity Comprehensive study of IL-1 gene family in sJIA CJW Stock et al 353

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IL 1A IL 1B IL 1F7 IL 1F9 IL 1F6 IL 1F8 IL 1F5 IL 1F10 IL 1RN

1 4 64a64 64b

Figure 2 Positions of the associated single nucleotide polymorphisms (SNPs) within the interleukin-1 (IL1) ligand cluster region. The positions of the associated SNPs (indicated in black), and of the SNPs that they are tagging (indicated in grey), within the IL1 ligand cluster region are shown.

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IL 1R2 IL 1R1 IL 1RL2 IL 1RL1 IL18R1 IL 18RAP

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Figure 3 Positions of the associated single nucleotide polymorphism (SNP) within the interleukin-1 (IL1) receptor cluster region. The positions of the associated SNP (indicated in black), and of the SNPs that it is tagging (indicated in grey), within the IL1 receptor cluster region are shown. the amount of redundancy by removing polymorphisms lead to decreased levels of IL-1 antagonism, resulting in that are in high LD with each other, and capturing the enhanced IL-1 cell signalling. If this is the case it could variation contained within a large number of poly- account for the improvement seen in some sJIA patients morphisms using a subset. It is, therefore, now possible when treated with the recombinant IL-1 receptor to carry out more comprehensive investigations of antagonist Anakinra, as the balance between activation regions containing candidate genes by investigating all and repression of the IL-1 response would be restored of the known sequence variations present, rather than, closer to the non-inflammatory state. the often subjective, selection of candidate SNPs with The only SNPs in the IL1 receptor cluster that showed known or predicted functionality. This approach also evidence of a significant association with disease were all facilitates the discovery of novel regions that may affect in the region of IL1R2, increasing the confidence that this gene activity and impact on disease status through any association is true. Although this association shows only findings of disease association of SNPs within unanno- borderline significance in the meta-analysis, we believe tated sequence. that this association is still interesting and warrants The SNPs showing evidence of association with sJIA in further investigation. SNP8 and the four SNPs it is the IL1 ligand cluster region are located within, or in the tagging are all located upstream of IL1R2, suggesting surrounding sequence of, IL1A, IL1F10 and IL1RN. that they are involved in regulation of transcription. As However, as SNP64a is located 1.3 kb downstream from IL-1R2 has a short cytosolic domain that is non-signal the 30-end of IL1F10 and 50.4 kb upstream of the 50-end of transducing it is a functionally negative receptor and acts IL1RN, it is possible that it may be involved in the as a decoy, sequestering IL-1 and preventing it from regulation of IL1RN and not of IL1F10. Consequently, it is binding to the signal transducing IL-1R1. Thus, alteration possible that these associated polymorphisms are only in the level of expression of IL-1R2 will in turn affect the involved with the major forms of IL-1 and that the novel, activity level of IL-1 during inflammation. Proteolytic less widely expressed IL-1 family members are not cleavage of the membrane bound IL-1R2, so that the involved in sJIA susceptibility. ProIL-1a is biologically extracellular domain is released into the circulation, active and, as well as being found on the cell membrane, yields a soluble form of the protein (sIL-1R2), which is is released from cells during disease, where it is a key found in the circulation and urine of healthy subjects, but activator of innate immunity and acute inflammatory elevated in patients with sepsis and with active RA.8 responses. Although the effects of IL-1b are more widely sIL-1R2 interacts with secreted IL-1RAcP to form a high- investigated there is evidence that IL-1a is important in affinity IL-1 scavenger, with an approximately 100-fold arthritis development and progression. This includes the increased affinity for IL-1a and IL-1b compared to observation that levels of membrane-bound IL-1a, but sIL-1R2 alone, but no increased affinity for IL-1Ra.39 This not serum IL-1a or IL-1b, correlate with the severity of complex binds to IL-1b with a dissociation rate of 2 h,8 arthritis in a mouse model,37 and that RA patients furthering the importance of IL-1R2 in the neutralization producing anti-IL-1a antibodies develop a less destruc- of IL-1. Should these associated SNPs cause a reduction tive disease.38 Dysregulation of the IL1A gene could lead in transcription then this could account for the increased to a perpetuation of the local inflammatory process, levels of IL-1 and the chronic inflammation seen in active contributing to the development of a chronic inflamma- sJIA patients. tory state. IL1RN encodes the IL-1 receptor antagonist The SNPs used in this study are acting as tSNPs for IL-1Ra, alterations in the expression of this gene could other polymorphisms within the regions, therefore those

Genes and Immunity Comprehensive study of IL-1 gene family in sJIA CJW Stock et al 354 showing evidence of association are not necessarily interpreting these results, and replication of the findings directly responsible for the effect seen, rather a SNP is essential before any definite conclusions can be drawn. being tagged could be the functional polymorphism The observation that just under half of patients treated affecting disease susceptibility. Although the initial SNP with Anakinra show a positive response23 suggests that coverage was as comprehensive as possible at the time, it there may be at least two different populations of sJIA did not include the total genetic diversity across the patients; in only some of whom the main underlying candidate loci; therefore it is possible that the SNPs cause for disease is a defect in IL-1 regulation. This identified in this study as being associated with sJIA are means that the associations observed in this study may in LD with an unknown, hidden, functional polymor- only have a significant effect in those patients responsive phism responsible for the effect seen. to Anakinra, potentially confounding the results due to One potential limitation of this study is the small admixture. It is however not possible to stratify the data sample size, and therefore its low power to detect in this study by Anakinra response as currently it is only associations. As a result it is possible that there are other prescribed to patients who are refractory to the standard associated SNPs with smaller effect that were not anti-inflammatory drugs, and so only a very small detected in this study. sJIA is a rare disease with a proportion of the patients used in this study have been prevalence of approximately only 16 children in 100 000, treated with Anakinra. A study to investigate the effects and only approximately 20 new patients being seen a of these associated SNPs in patients responsive and year at Great Ormond Street Hospital (GOSH). For these refractory to Anakinra treatment is currently being reasons larger patient cohort numbers are extremely planned. difficult to collect. This study has already utilized a UK If there is a higher proportion of patients who are IL-1- repository of sJIA patients, further to which it would not blockade responsive in one group than in the other it be possible to collect a sufficiently large number of may explain why six of the ten SNPs typed in both stages additional patients to significantly increase the power of of this study had significant BD P-values; showing that this study. However, previous case–control studies there is a significant difference in the effect sizes in the investigating sJIA have used similar, and smaller, sample two groups tested. The majority of the SNPs in this study sizes, for example 92 patients,3 the results of which were showing evidence of heterogeneity of ORs are not confirmed in a larger family study,40 so this study is significantly associated with disease status; these nega- favourably comparable to previous work done on this tive findings could potentially be positive associations disease. The two-staged meta-analysis approach used in when stratified by Anakinra response, or it is possible this study is one that minimizes population stratification that the frequency differences for these SNPs observed in in small samples, and therefore the SNPs that are found stage 1 were spurious false-positive findings, abrogated to be associated with sJIA after this analysis are more when the additional samples from stage 2 are included in likely to be true disease susceptibility/severity genes in the analysis. sJIA. Comparison of the genotype frequencies in the In conclusion, this study has found a number of SNPs patient populations from this study with the frequencies in IL1R2, IL1A, IL1F10 and IL1RN to show evidence of in the control population from the Welcome Trust Case association with sJIA. This is the first study to show Control Consortium41 (available as direct genotyping genetic associations between members of the IL-1 gene data for SNPs 5 and 81, and as imputed genotyping family and the systemic subtype of JIA, indicating that the data42 for all others, except SNP4 that is not represented) IL-1 family is important in the development of disease shows the same pattern of significant differences as severity and susceptibility. These finding give a better reported here, that is significant frequency differences understanding of the underlying aetiological cause of observed with the stage 1 patients, and with all the systemic JIA and could lead to new diagnostic, pharma- patients pooled together, but not with the patients from cogenetic and therapeutic targets to be developed. stage 2 alone. The fact that similar results are observed using this larger control cohort (n ¼ 2936), which pro- vides greater sensitivity, indicates that the associations found in this study are most likely to be real. To confirm Materials and methods the findings of this study, replication using a larger, Selection of tSNPs for typing independent patient cohort is necessary. Genotyping data for all the SNPs within the candidate A potential problem created by this high-density regions were obtained from the International HapMap marker approach is that of multiple testing; a necessity project44 for the Centre d’Etude du Polymorphisme in studies with a low prior probability. However, it is Humain (CEPH; Utah residents with ancestry from widely accepted that correcting for multiple testing using northern and western Europe) population (HapMap traditional methods such as Bonferroni correction is not data release no. 18/phase II Sept. 05, on NCBI B34 appropriate in studies such as this, as it assumes that all assembly, dbSNPb124). These regions covered the gene of the variables being tested are independent. The result and the surrounding sequences both upstream and is that correction of the P-values would be overly downstream to the next flanking genes. In addition, conservative since the SNPs are in some amount of LD genotyping data for the population of European descent with each other.43 Other correction methods such as were obtained from the Programmes for Genomic Bayesian inference and false-positive reporting prob- Applications (www.nhlbi.nih.gov/resources/pga) for ability also pose difficulties as they depend on prior all of the candidate genes that they had re-sequenced probability, appropriate values for which are impossible (all candidate genes except IL1RL1 and IL18R2). As there to determine when neither the number of genes involved was overlap in the individuals typed by the two data in a complex disease, nor their effect sizes, is known. This sources all of the genotyping data were combined into issue must therefore be taken into consideration when one data file with more complete SNP coverage.

Genes and Immunity Comprehensive study of IL-1 gene family in sJIA CJW Stock et al 355 The LD between each of these SNPs that had an MAF stage 2 of the study was performed by KBioscience of at least 0.05 was calculated using the Haploview using Applied Biosystems TaqMan assays. A proportion programme (version 3.2).45 The LD data were then (18) of the sJIA samples used in the initial study were used in the Tagger program46 within Haploview to also re-typed to confirm there were no discrepancies select tSNPs, examining for pairwise tagging with a between the two genotyping methods. minimum r2 value of 0.8.

Study strategy Genotype data checking To maximize the power of the study given the limited The genotypes for the control populations were checked resources available a two-stage study design47,48 was for Hardy–Weinberg equilibrium using a w2-test with a adopted. In this strategy a group of patient and control significant P-value cut-off of 0.05. To check that the samples were typed for all of the SNPs of interest in stage control population used for genotyping and the CEPH 1, and another group of patients and controls from a population used to select the tSNPs were comparable, different source were typed in stage 2 only for those the distribution of the populations between the three SNPs that showed evidence of association in stage 1. Due possible genotypes for each SNP was compared using to the samples used in the two stages having been a w2 contingency table with a significant P-value cut-off collected from different sources they cannot be combined of 0.05. into a single analysis; therefore the results from both stages of the study were analysed together by meta- analysis, as discussed below. Stage 1 association analysis The power of this meta-analysis strategy is difficult to Association analysis of the genotyping data was per- estimate. As a guide, a two-stage study design, given the formed using the COCAPHASE module of UNPHASED number, and proportion of samples and SNPs genotyped (v2.403 and v3.0), which performs unconditional logistic in each stage, gives 84% power to detect an SNP with a regression likelihood ratio tests under a log-linear frequency of 0.3 giving a relative risk of 1.7 using model.49 Both single marker and haplotype analyses a multiplicative model (CaTS power calculator for 48 were performed and haplotype frequencies were esti- two-stage association analysis). mated by an expectation-maximization algorithm in COCAPHASE. When multiple SNPs in the same region Patient and control samples showed a significant difference they were separated into DNA from Caucasian sJIA patients, collected from the clusters according to their LD, both D0 and r2, patterns. British Society for Paediatric and Adolescent Rheumatol- A stepwise conditional regression approach50 was then ogy Study Group National DNA repository at the used within each LD cluster to identify the SNPs Arthritis Research Campaign Epidemiology Unit in showing primary effects. The stepwise conditional Manchester and the University College London Centre regression was then repeated with the primary effect for Paediatric and Adolescent Rheumatology at both SNPS from each LD cluster to determine if their effects GOSH and the Middlesex Hospital, was used in stage 1 were independent or related to each other. Nested (n ¼ 130). DNA from further Caucasian patients from conditional analysis was also performed to ensure that GOSH in London, Wexham Park Hospital, Berkshire, all of the primary SNPs were required to fully explain the United Kingdom, and Necker Hospital in Paris was used effects seen. for stage 2 (n ¼ 105). Ethical approval for the study was obtained (Great Ormond Street Hospital for Children NHS Trust and Institute of Child Health, Research Ethics Stage 2 association analysis Committee reference 02RU06) and parents gave in- The genotyping data from the two stages of the formed consent. Control DNA used in stage 1 was association study were analysed for association using collected from an ethnically matched population of 16 to the Cochran–Mantel–Haenszel test for meta-analysis, 30-year olds from a GP practice in a stable population of and the BD test for homogeneity of ORs between the the west Midlands (n ¼ 151), and that used in stage 2 two stages, using the software PLINK.51 from Caucasian first-time blood donors from the national blood transfusion centre in London (n ¼ 184). Genotyping Acknowledgements Genotyping for stage 1 of the study was done with the Illumina Golden Gate assay genotyping platform (cus- We thank BSPAR study group members: Dr M tom 384 SNP panel, 96-sample Sentrix array matrix). Abinun, Dr M Becker, Dr A Bell, Professor A Craft, Automatic clustering of the samples and genotype Dr E Crawley, Dr J David, Dr H Foster, Dr J Gardener- calling was done with the Illumina BeadStudio software Medwin, Dr J Griffin, Dr A Hall, Dr M Hall, Dr A (version 2.1.8.32932). Determination of the validity of the Herrick, Dr P Hollingworth, Dr L Holt, Dr S Jones, genotyping of each SNP was based on both the software- Dr G Pountain, Dr C Ryder, Professor T Southwood, generated Gen Train score (based on the shapes of the Dr I Stewart, Dr H Venning, Dr L Wedderburn, Professor clusters and the relative distance between them) and P Woo and Dr S Wyatt; Dr AM Prieur and the French visual examination of the genotype clustering; any SNPs association Kourir; Dr J Packham, for the contribution of without three easily identifiable, compact and well- patient DNA and Dr Ele Zeggini for assistance with spaced clusters were considered to have failed genotyp- analysis. This work was funded by the Nuffield ing. All clustering and genotype calling was confirmed Foundation Oliver Bird Rheumatism Program and the independently by two investigators. Genotyping for Arthritis Research Campaign (arc).

Genes and Immunity Comprehensive study of IL-1 gene family in sJIA CJW Stock et al 356 References 19 Subramaniam S, Stansberg C, Cunningham C. The interleukin 1 receptor family. Dev Comp Immunol 2004; 28: 415–428. 1 Petty RE. Growing pains: the ILAR classification of juvenile 20 Prieur AM, Roux-Lombard P, Dayer JM. Dynamics of fever idiopathic arthritis. J Rheumatol 2001; 28: 927–928. and the cytokine network in systemic juvenile arthritis. 2 Woo P. Systemic juvenile idiopathic arthritis: diagnosis, Rev Rhum Engl Ed 1996; 63: 163–170. management, and outcome. Nat Clin Pract Rheumatol 2006; 2: 21 Muller K, Herner EB, Stagg A, Bendtzen K, Woo P. 28–34. Inflammatory cytokines and cytokine antagonists in whole 3 Fishman D, Faulds G, Jeffery R, Mohamed-Ali V, Yudkin JS, blood cultures of patients with systemic juvenile chronic Humphries S et al. The effect of novel polymorphisms in the arthritis. Br J Rheumatol 1998; 37: 562–569. interleukin-6 (IL-6) gene on IL-6 transcription and plasma IL-6 22 Pascual V, Allantaz F, Arce E, Punaro M, Banchereau J. Role of levels, and an association with systemic-onset juvenile chronic interleukin-1 (IL-1) in the pathogenesis of systemic onset arthritis. J Clin Invest 1998; 102: 1369–1376. juvenile idiopathic arthritis and clinical response to IL-1 4 Ogilvie EM, Fife MS, Thompson SD, Twine N, Tsoras M, blockade. J Exp Med 2005; 201: 1479–1486. Moroldo M et al. The À174G allele of the interleukin-6 gene 23 Lequerre T, Quartier P, Rosellini D, Alaoui F, De Bandt M, confers susceptibility to systemic arthritis in children: a Mejjad O et al. Interleukin-1 receptor antagonist (anakinra) multicenter study using simplex and multiplex juvenile treatment in patients with systemic-onset juvenile idiopathic idiopathic arthritis families. Arthritis Rheum 2003; 48: arthritis or adult onset Still’s disease. Preliminary experience 3202–3206. in France. Ann Rheum Dis 2008; 67: 302–308. 5 Donn RP, Shelley E, Ollier WE, Thomson W. A novel 24 Lovell D, Giannini E, Kinura Y, Li S, Hashkes P, Reiff A et al. 50-flanking region polymorphism of macrophage migration Preliminary evidence for bioactivity of IL-1 TRAP (Rilona- inhibitory factor is associated with systemic-onset juvenile cept), a long acting IL-1 inhibitor, in systemic juvenile idiopathic arthritis. Arthritis Rheum 2001; 44: 1782–1785. idiopathic arthritis. Ann Rheum Dis 2006; 65 (Suppl II): 6 de Benedetti F, Meazza C, Vivarelli M, Rossi F, Pistorio A, 693.Ref Type: Abstract. Lamb R et al. Functional and prognostic relevance of the À173 25 Meulenbelt I, Seymour AB, Nieuwland M, Huizinga TW, van polymorphism of the macrophage migration inhibitory factor Duijn CM, Slagboom PE. Association of the interleukin-1 gene gene in systemic-onset juvenile idiopathic arthritis. Arthritis cluster with radiographic signs of osteoarthritis of the hip. Rheum 2003; 48: 1398–1407. Arthritis Rheum 2004; 50: 1179–1186. 7 Fife MS, Gutierrez A, Ogilvie EM, Stock CJ, Samuel JM, 26 Buchs N, di Giovine FS, Silvestri T, Vannier E, Duff GW, Thomson W et al. Novel IL10 gene family associations with Miossec P. IL-1B and IL-1Ra gene polymorphisms and disease systemic juvenile idiopathic arthritis. Arthritis Res Ther 2006; severity in rheumatoid arthritis: interaction with their plasma 8: R148. levels. Genes Immun 2001; 2: 222–228. 8 Dinarello CA. Biologic basis for interleukin-1 in disease. Blood 27 Jouvenne P, Chaudhary A, Buchs N, Giovine FS, Duff GW, 1996; 87: 2095–2147. Miossec P. Possible genetic association between interleukin- 9 Nicklin MJ, Barton JL, Nguyen M, FitzGerald MG, Duff GW, 1alpha gene polymorphism and the severity of chronic Kornman K. A sequence-based map of the nine genes of the polyarthritis. Eur Cytokine Netw 1999; 10: 33–36. human interleukin-1 cluster. Genomics 2002; 79: 718–725. 28 Timms AE, Crane AM, Sims AM, Cordell HJ, Bradbury LA, 10 Taylor SL, Renshaw BR, Garka KE, Smith DE, Sims JE. Abbott A et al. The interleukin 1 gene cluster contains a major Genomic organization of the interleukin-1 locus. Genomics susceptibility locus for ankylosing spondylitis. Am J Hum 2002; 79: 726–733. Genet 2004; 75: 587–595. 11 Smith DE, Renshaw BR, Ketchem RR, Kubin M, Garka KE, 29 van der PM, Crusius JB, Garcia-Gonzalez MA, Baudoin P, Sims JE. Four new members expand the interleukin-1 super- Kostense PJ, Alizadeh BZ et al. Interleukin-1beta and inter- family. J Biol Chem 2000; 275: 1169–1175. leukin-1 receptor antagonist gene polymorphisms in ankylos- 12 Kumar S, McDonnell PC, Lehr R, Tierney L, Tzimas MN, ing spondylitis. Rheumatology (Oxford) 2002; 41: 1419–1423. Griswold DE et al. Identification and initial characterization of 30 Tazi-Ahnini R, Cox A, McDonagh AJ, Nicklin MJ, di Giovine four novel members of the interleukin-1 family. J Biol Chem FS, Timms JM et al. Genetic analysis of the interleukin-1 2000; 275: 10308–10314. receptor antagonist and its homologue IL-1L1 in alopecia 13 Lin H, Ho AS, Haley-Vicente D, Zhang J, Bernal-Fussell J, Pace areata: strong severity association and possible gene interac- AM et al. Cloning and characterization of IL-1HY2, a tion. Eur J Immunogenet 2002; 29: 25–30. novel interleukin-1 family member. J Biol Chem 2001; 276: 31 Kinane DF, Hart TC. Genes and gene polymorphisms 20597–20602. associated with periodontal disease. Crit Rev Oral Biol Med 14 Debets R, Timans JC, Homey B, Zurawski S, Sana TR, Lo S 2003; 14: 430–449. et al. Two novel IL-1 family members, IL-1 delta and IL-1 32 Bergholdt R, Larsen ZM, Andersen NA, Johannesen J, epsilon, function as an antagonist and agonist of NF-kappa B Kristiansen OP, Mandrup-Poulsen T et al. Characterization of activation through the orphan IL-1 receptor-related protein 2. new polymorphisms in the 50 UTR of the human interleukin-1 J Immunol 2001; 167: 1440–1446. receptor type 1 (IL1R1) gene: linkage to type 1 diabetes 15 Towne JE, Garka KE, Renshaw BR, Virca GD, Sims JE. and correlation to IL-1RI plasma level. Genes Immun 2000; 1: Interleukin (IL)-1F6, IL-1F8, and IL-1F9 signal through 495–500. IL-1Rrp2 and IL-1RAcP to activate the pathway leading to 33 McDowell TL, Symons JA, Ploski R, Forre O, Duff GW. A NF-kappaB and MAPKs. J Biol Chem 2004; 279: 13677–13688. genetic association between juvenile rheumatoid arthritis and 16 Bufler P, Azam T, Gamboni-Robertson F, Reznikov LL, Kumar a novel interleukin-1 alpha polymorphism. Arthritis Rheum S, Dinarello CA et al. A complex of the IL-1 homologue IL- 1995; 38: 221–228. 1F7b and IL-18-binding protein reduces IL-18 activity. Proc 34 Donn RP, Farhan AJ, Barrett JH, Thomson W, Worthington J, Natl Acad Sci USA 2002; 99: 13723–13728. Ollier WE. Absence of association between interleukin 1 alpha 17 Dale M, Nicklin MJ. Interleukin-1 receptor cluster: gene and oligoarticular juvenile chronic arthritis in UK patients. organization of IL1R2, IL1R1, IL1RL2 (IL-1Rrp2), IL1RL1 Rheumatology (Oxford) 1999; 38: 171–175. (T1/ST2), and IL18R1 (IL-1Rrp) on human chromosome 2q. 35VencovskyJ,JarosovaK,RuzickovaS,NemcovaD,NiederlovaJ, Genomics 1999; 57: 177–179. Ozen S et al. Higher frequency of allele 2 of the interleukin-1 18 Stylianou E, O’Neill LA, Rawlinson L, Edbrooke MR, Woo P, receptor antagonist gene in patients with juvenile idiopathic Saklatvala J. Interleukin 1 induces NF-kappa B through its arthritis. Arthritis Rheum 2001; 44: 2387–2391. type I but not its type II receptor in lymphocytes. J Biol Chem 36 Sugiura T, Maeno N, Kawaguchi Y, Takei S, Imanaka H, 1992; 267: 15836–15841. Kawano Y et al. A promoter haplotype of the interleukin-18

Genes and Immunity Comprehensive study of IL-1 gene family in sJIA CJW Stock et al 357 gene is associated with juvenile idiopathic arthritis in the 43 Lewis CM. Genetic association studies: design, analysis and Japanese population. Arthritis Res Ther 2006; 8: R60. interpretation. Brief Bioinform 2002; 3: 146–153. 37 Niki Y, Yamada H, Kikuchi T, Toyama Y, Matsumoto H, 44 The International HapMap Consortium. The International Fujikawa K et al. Membrane-associated IL-1 contributes to HapMap Project. Nature 2003; 426: 789–796. chronic synovitis and cartilage destruction in human IL-1 45 Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and alpha transgenic mice. J Immunol 2004; 172: 577–584. visualization of LD and haplotype maps. Bioinformatics 2005; 38 Graudal NA, Svenson M, Tarp U, Garred P, Jurik AG, 21: 263–265. Bendtzen K. Autoantibodies against interleukin 1alpha in 46 de Bakker PI, Yelensky R, Pe’er I, Gabriel SB, Daly MJ, rheumatoid arthritis: association with long term radiographic Altshuler D. Efficiency and power in genetic association outcome. Ann Rheum Dis 2002; 61: 598–602. studies. Nat Genet 2005; 37: 1217–1223. 39 Smith DE, Hanna R, Della F, Moore H, Chen H, Farese AM 47 Satagopan JM, Venkatraman ES, Begg CB. Two-stage designs et al. The soluble form of IL-1 receptor accessory protein for gene-disease association studies with sample size enhances the ability of soluble type II IL-1 receptor to inhibit constraints. Biometrics 2004; 60: 589–597. IL-1 action. Immunity 2003; 18: 87–96. 48 Skol AD, Scott LJ, Abecasis GR, Boehnke M. Joint analysis is 40 Ogilvie EM, Fife MS, Thompson SD, Twine N, Tsoras M, more efficient than replication-based analysis for two-stage Moroldo M et al. The À174G allele of the interleukin-6 gene genome-wide association studies. Nat Genet 2006; 38: 209–213. confers susceptibility to systemic arthritis in children: a 49 Dudbridge F. Pedigree disequilibrium tests for multilocus multicenter study using simplex and multiplex juvenile haplotypes. Genet Epidemiol 2003; 25: 115–121. idiopathic arthritis families. Arthritis Rheum 2003; 48: 50 Cordell HJ, Clayton DG. A unified stepwise regression 3202–3206. procedure for evaluating the relative effects of polymorphisms 41 Wellcome Trust Case Control Consortium. Genome-wide within a gene using case/control or family data: application to association study of 14,000 cases of seven common diseases HLA in type 1 diabetes. Am J Hum Genet 2002; 70: 124–141. and 3,000 shared controls. Nature 2007; 447: 661–678. 51 Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, 42 Marchini J, Howie B, Myers S, McVean G, Donnelly P. A new Bender D et al. PLINK: a tool set for whole-genome association multipoint method for genome-wide association studies by and population-based linkage analyses. Am J Hum Genet 2007; imputation of genotypes. Nat Genet 2007; 39: 906–913. 81: 559–575.

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