Short Communication

Genes and Immunity (2011) 12, 235–238; doi:10.1038/gene.2010.67; published online 20 January 2011

CIITA is not associated with risk of developing rheumatoid arthritis

P G Bronson1, P P Ramsay1, M F Seldin2, P K Gregersen3, L A Criswell4 and L F Barcellos1

  1. 1Division of Epidemiology, Genetic Epidemiology and Genomics Laboratory, School of Public Health, University of California, Berkeley, CA, USA
  2. 2Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, CA, USA
  3. 3Robert S Boas Center for Genomic and Human Genetics, The Feinstein Institute for Medical Research, Manhasset, NY, USA
  4. 4Rosalind Russell Medical Research Center for Arthritis, Department of Medicine, University of California, San Francisco, CA, USA

Correspondence: Dr LF Barcellos, Division of Epidemiology, Genetic Epidemiology and Genomics Laboratory, School of Public Health, University of California, 209 Hildebrand Hall, Berkeley, CA 94720-7356, USA. E-mail: lbarcellos@genepi.berkeley.edu

Received 5 July 2010; Revised 8 September 2010; Accepted 9 September 2010; Published online 20 January 2011.

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Abstract

The major histocompatibility complex (MHC) class II transactivator gene (CIITA) encodes an important transcription factor regulating genes required for human leukocyte antigen (HLA) class II MHC-restricted antigen presentation. MHC genes, particularly HLA class II, are strongly associated with risk of developing rheumatoid arthritis (RA). Given the strong biological relationship between CIITA and HLA class II genes, a comprehensive investigation of CIITA variation in RA was conducted. This study tested 31 CIITA single-nucleotide polymorphisms in 2542 RA cases and 3690 controls (N=6232). All individuals were of European ancestry, as determined by ancestry informative genetic markers. No evidence for association between CIITA variation and RA was observed after a correction for multiple testing was applied. This is the largest study to fully characterize common genetic variation in CIITA, including an assessment of haplotypes. Results exclude even a modest role for common CIITA polymorphisms in susceptibility to RA.

Keywords:

rheumatoid arthritis; autoimmunity; CIITA; MHC2TA

Rheumatoid arthritis (RA) is the most common systemic autoimmune disease with a prevalence of 1%.1 This chronic inflammatory disease can cause substantial disability from the erosive and deforming processes in joints.2 RA has a strong genetic component, as demonstrated by twin studies.3 Major histocompatibility complex (MHC) genes, particularly the class II human leukocyte antigen (HLA)-DRB1 locus, as well as variants within other MHC regions, are strongly associated with risk of developing RA.4, 5, 6, 7, 8

The MHC class II transactivator gene (CIITA, also called MHC2TA) encodes the CIITA protein, a transcription factor required for the expression of HLA class II molecules.9, 10, 11, 12 CIITA spans 48kb on chromosome 16p13, and has four alternate first exons in a 12kb promoter region (I–IV).13 Mutations in CIITA cause a rare and severe immunodeficiency characterized by HLA class II deficiency (bare lymphocyte syndrome).14 In addition, CIITA is located on 16p13, a region that has been implicated in RA linkage studies.15 Thus, CIITA is an attractive candidate for genetic studies of autoimmune diseases for which HLA associations have been well established. A comprehensive haplotype-based investigation of CIITA as a candidate RA gene was conducted. The study sample consisted of 682 RA cases and 752 controls collected by the North American RA Consortium (RA1), and 1860 RA cases and 2938 controls collected by the Wellcome Trust Case Control Consortium RA Group in the United Kingdom (RA2; total N=6232; Table 1).


Genotypes for 5 CIITA single-nucleotide polymorphisms (SNPs) in RA1 (Illumina HumanHap550 BeadChip; San Diego, CA, USA) and 19 CIITA SNPs in RA2 (Affymetrix GeneChips Mapping 500K Array Set; Santa Clara, CA, USA) were derived from genome-wide association (GWA) studies, as previously described.16, 17, 18 Two intronic SNPs in RA2 (rs7404615 and rs8062961) were excluded from analysis because of low minor allele frequency (<0.01). Deviation from Hardy–Weinberg equilibrium was examined in controls separately for each cohort using the exact test (PLINK v. 1.05; Boston, MA, USA).19, 20 There was no evidence for deviation from Hardy–Weinberg equilibrium in the RA1 or RA2 controls (P<0.01).

Sufficient power for this study was confirmed with PGA v.2.0 (Bethesda, MD, USA; minor allele frequency 0.1–0.5, two-sided α=2.9 × 10−3).21 Haplotype blocks were estimated in RA1 and RA2 controls and HapMap samples of northern and western European origin (CEU) separately (Haploview v.4.1; Cambridge, MA, USA).22 Percent of CIITA variation captured in this study was based on r2 greater than or equal to0.8 in CEU using two- and three-marker haplotypes (Haploview).

We conducted allelic tests of association for five SNPs and global haplotype tests (one haplotype block encompassing two SNPs) in 682 anti-cyclic citrullinated peptide-positive (anti-CCP positive) RA cases and 752 controls (N=1434, RA1). All results were negative after correcting for multiple testing (Figure 1, Supplementary Table 1). Next, we conducted allelic tests of 17 SNPs and global haplotype tests (two haplotype blocks encompassing 11 SNPs) in the second RA dataset comprised of 1860 RA cases and 2938 controls (N=4798, RA2). No evidence for association was present (Figure 1, Supplementary Table 1). Furthermore, allelic tests of 31 imputed SNPs within CIITA derived for the combined RA sample (2542 cases and 3690 controls, total N=6232, RA1+RA2) revealed no evidence for disease association (Figure 1, Supplementary Table 1).

Figure 1.
Figure 1 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

P-values from allelic and haplotype tests of CIITA SNPs in RA.

Full figure and legend (36K)

Association between the −168A/G variant in the type III CIITA promoter region (rs3087456) and RA was previously reported.23 However, a recent meta-analysis of 10 studies including more than 15000 individuals revealed no evidence for association between the −168A/G variant and RA.24 Negative findings from the meta-analysis have been further supported by additional reports.25, 26 This study did not examine the −168A/G variant, as the data were not available from either previous GWA study, nor could genotypes be imputed using CEU samples from HapMap.

Modest association between RA and a haplotype containing the −168A/G variant and the +1614G/C missense mutation (rs4774) has been reported in two independent Spanish populations.27, 28 Martinez et al.27 report a global haplotype test result of P=0.04, and the odds ratio and 95% confidence interval for the −168G/+1614C haplotype versus all other haplotypes was 1.60 (1.05–2.44; P=0.02). Martinez et al.28 did not report a global haplotype test result, and the odds ratio and 95% confidence interval for the −168G/+1614C haplotype versus all other haplotypes was 1.93 (1.10–3.45; P=0.02). Genotype data and imputed genotypes were available for the +1614G/C variant in RA2 and RA1, respectively, and our study was well powered to detect a modest effect size, with 80% power to detect an allelic odds ratio as low as 1.22. However, similar to previous studies, we did not observe any evidence for association between the +1614G/C variant and RA.23, 27, 28 Some possible explanations for conflicting findings include that associations reported by Martinez et al. do not achieve significance after correction for multiple testing. It is also possible that phenotypic differences may have contributed to the observed disparity between the results. In this study, 85, 84 and 87% of our combined patients were positive for the shared epitope (SE), rheumatoid factor and anti-CCP, respectively. In contrast, 59 and 75% of patients in the Martinez et al.27 study were positive for the SE and rheumatoid factor, respectively; anti-CCP positivity was not described. In the Martinez et al.28 study, 57%, 67 and 50% of patients were positive for the SE, rheumatoid factor and anti-CCP, respectively. Furthermore, in contrast to this study, Martinez et al. did not estimate European ancestry proportions in cases and controls to help protect against spurious association due to population stratification effects.

Although rare variants in CIITA were not directly investigated here, for the first time all common genetic variation within CIITA was interrogated for a role in RA susceptibility. The 31 SNPs in the combined RA sample captured 94% of common variation based on Caucasian HapMap population (CEU) data (see Figure 1 legend). The combined sample tagged all (N=32) but two of the common HapMap variants (rs6498122 (intronic variant) and rs8046121 (missense mutation)). The data used in this study were taken from two GWA studies that did not identify CIITA as a risk locus for RA based on strict significance criteria. A focused candidate gene study that captures a much larger portion of genetic variation when compared with initial GWA results is a useful and complementary strategy. Interestingly, CIITA seems to be important for other autoimmune diseases. Recent GWA studies have identified CIITA and the extended CIITA-CLEC16A-SOCS1 gene region as a susceptibility locus for ulcerative colitis and celiac disease, respectively.29, 30 Though CIITA has not previously reached genome-wide significance in GWA studies of multiple sclerosis, a recent candidate gene study showed evidence for association between multiple sclerosis and CIITA in the presence of the multiple sclerosis risk allele HLA-DRB1*1501.31

In conclusion, this is the first genetic study in RA to fully characterize common genetic variation in CIITA, including an assessment of haplotypes. Results do not provide evidence that common variation in CIITA has a role in susceptibility to RA.

Study subjects

RA cases met the American College of Rheumatology classification criteria for RA.32 RA1 controls were frequency matched by age and gender to the cases. RA2 controls consisted of 1480 controls from the British 1958 Birth Cohort (58BC; includes all births in England, Wales and Scotland that occurred during 1 week in 1958) and 1458 controls from the British National Blood Service (frequency matched by geographical region and gender to the 1958 Birth cohort so as to be nationally representative).16 On the basis of available genetic ancestry data for all individuals, and to apply the most stringent criteria possible for genetic analysis of CIITA, only subjects with European ancestry were analyzed. Northern European ancestry was estimated in RA1 using a Bayesian clustering algorithm (Structure v. 2.0) and data for 112 European and 246 Northern European ancestry informative markers, and only samples with greater than or equal to90% Northern European ancestry were included in this study.33, 34 For RA2, European ancestry was assessed by a two-stage principal components analysis as previously described, and 153 samples that were separate from the cluster containing the rest of the Wellcome Trust Case Control Consortium samples were excluded.16 The RA1 and RA2 cases differed in anti-CCP seropositivity (100 versus 79.8%, respectively) and SE positivity (97.7 versus 79.3%, respectively). Individual-level anti-CCP and SE positivity data were not publicly available for the RA2 cases.

Statistical analysis

Allelic association was tested by creating 2 × 2 contingency tables, and estimating odds ratios with Fisher's exact test (PLINK). Haplotypes were estimated with the expectation-maximization algorithm (Haploview). Maximum likelihood estimates of haplotype probabilities were computed with the expectation-maximization algorithm, and score statistics were used for global haplotype association tests, assuming a dominant genetic model (HaploStats v.1.4.4, Rochester, MN, USA; R v.2.10.1, Vienna, AT, USA).35 Haplotypes with inferred frequencies <5% were excluded. A significance threshold of P=2.9 × 10−3 was set using a Bonferroni correction for the number of CIITA haplotype blocks (four) and SNPs that were not located in haplotype blocks (13), based on CEU. Empirical P-values based on 10000 simulations were reported for all allelic and haplotype tests. Allelic and haplotype empirical P-values were estimated in PLINK (max(T) permutation procedure) and HaploStats, respectively, by permuting the ordering of the disease status, counting the number of times the permuted test was greater than the observed test, and dividing by the total number of simulations (10000).19, 35 Because there was no evidence of an association of age or gender with the polymorphisms of interest, we decided not to adjust for either.

To conduct a combined analysis of RA1+RA2, missing genotypes were imputed for 16 SNPs in RA1, four SNPs in RA2 and 11 SNPs in the combined RA sample. A hidden Markov Model based algorithm was used to infer missing genotypes from known haplotypes (IMPUTE, v.0.5.0; Oxford, UK).36 The robustness of the imputation accuracy rate for this standard imputation method has been demonstrated.37 Known haplotypes were obtained from publicly available genotype data for CEU, using observed linkage disequilibrium patterns (r2greater than or equal to0.8) in two 500kb regions adjacent to each side of CIITA.36 Association tests of imputed genotypes accounted for the uncertainty of imputed genotypes in missing data likelihood score tests, using the frequentist proper option and a dominant genetic model in SNPTEST (v.1.1.5; Oxford, UK). In all, 36 imputed genotypes with <90% probability were omitted. There was no evidence for deviation from Hardy–Weinberg equilibrium in the controls. After one SNP with low minor allele frequency that was imputed in RA1+RA2 (rs12925158) was omitted from further analyses, 31 SNPs in RA1+RA2 were tested for allelic association.

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Conflict of interest

The authors declare no conflict of interest.

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Acknowledgements

We thank Farren Briggs, Benjamin Goldstein, Alan Hubbard and Ira Tager for helpful discussion, as well as study participants. This work was supported by an Abbott Graduate Student Achievement Award (ACR REF), grants F31 AI075609, R01 AI065841 and R01 AI059829 (NIH/NIAID), and grants RO1 AR44422, NO1 AR22263, R01 AR050267, K24 AR02175 (NIH/NIAMS). The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views of the NIH, NIAID or NIAMS. This study makes use of data generated by the Wellcome Trust Case Control Consortium; a full list of the investigators who contributed to the generation of the data is available from http://www.wtccc.org.uk, and funding for the project was provided by the Wellcome Trust under award 076113. These studies were performed in part in the General Clinical Research Center, Moffitt Hospital, University of California, San Francisco, with funds provided by the National Center for Research Resources, 5 M01 RR-00079, United States Public Health Service.

Supplementary Information accompanies the paper on Genes and Immunity website