Original Article

Genes and Immunity (2011) 12, 169–175; doi:10.1038/gene.2010.57; published online 3 February 2011

HLA-DPB1-COL11A2 and three additional xMHC loci are independently associated with RA in a UK cohort

G Orozco1, A Barton1, S Eyre1, B Ding2, J Worthington1, X Ke1,3,4 and W Thomson1,4

  1. 1Arthritis Research UK Epidemiology Unit, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
  2. 2Karolinska Institute, Stockholm, Sweden
  3. 3Institute of Child Health, University College London, London, UK

Correspondence: Dr G Orozco, Arthritis Research UK Epidemiology Unit, Manchester Academic Health Science Centre, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, UK. E-mail: gisela.orozco@manchester.ac.uk

4These authors share senior authorship.

Received 26 April 2010; Revised 25 June 2010; Accepted 25 June 2010; Published online 3 February 2011.

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Abstract

The aim of this study was to investigate the complex association pattern of the extended major histocompatibility complex (xMHC) region with rheumatoid arthritis (RA) susceptibility to identify effects independent of HLA-DRB1. A total of 1804 RA cases and 1474 controls were included. High-resolution HLA-DRB1 typing was performed. Subjects were genotyped for 1546 single-nucleotide polymorphisms (SNPs) using Affymetrix GeneChip 500K (Santa Clara, CA, USA) as part of the Wellcome Trust Case Control Consortium Study. Statistical analysis was carried out using PLINK. To avoid confounding by RA-associated HLA-DRB1 alleles, we analyzed xMHC SNPs using a data set with pairwise matching of cases and controls on DRB1 genotypes. A total of 594 case–control pairs with identical DRB1 genotypes were identified. After this adjustment, 104 SNPs remained significantly associated with RA (P<0.05), suggesting that additional RA loci independent of HLA-DRB1 can be found in the xMHC region. Of these, four loci showed the strongest associations with RA (P<0.005): ZNF391, the olfactory receptor (OR) gene cluster, C6orf26-RDBP and HLA-DPB1-COL11A2. An additional locus mapping to the BTN (butyrophilin) cluster showed independent association with RA in anti-cyclic citrullinated peptide-positive patients exclusively. We have validated the previously described independent association of the HLA-DPB1-COL11A2 locus with RA. In addition, association with three novel independent RA loci in the xMHC region (ZNF391, OR2H1 and C6orf26-RDBP) has been detected.

Keywords:

rheumatoid arthritis; xMHC; susceptibility; HLA-DRB1

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Introduction

Rheumatoid arthritis (RA) is a common disease, affecting around 1% of the population worldwide. It is an inflammatory, autoimmune, systemic disease and is characterized by the chronic inflammation and progressive destruction of the joints that leads to disability.1 RA is a complex disease, meaning that multiple genetic variants, environmental factors and random events interact to trigger pathological pathways. Although many of these etiological factors have not yet been identified, recent groundbreaking advances such as the availability of genome-wide association studies have expanded our knowledge about the genetic factors that contribute to RA, such that 26 loci have now been confirmed (P<5 × 10−8).2

However, the HLA-DRB1 locus identified long before the advent of genome-wide association studies remains the major RA susceptibility locus. The association of HLA-DRB1 alleles with RA was described for the first time in the 1970s.3, 4 Subsequent molecular typing methods revealed that the association of the HLA-DRB1 locus with RA is complex, with a variety of specific alleles conferring different risks. These alleles share a sequence in the third hypervariable region of the gene termed the shared epitope.5 Since then, countless studies have demonstrated that HLA-DRB1 is consistently linked and associated with RA in every population studied.6 HLA-DRB1 lies within the major histocompatibility complex (MHC) on chromosome 6p21. The classical extended MHC (MHCx) encompasses a region of ~3.6Mb and it is divided into three subregions (classes I, II and III), whereas the xMHC encompasses a ~7.8Mb. It is characterized by its great variability and gene density. Many of these genes have immunological functions, and variation within the MHC has been found to be associated with the majority of autoimmune diseases.7 The region is also characterized by the presence of strong linkage disequilibrium (LD).

A variety of approaches have been used to determine whether additional RA susceptibility loci reside within the MHC region, but interpretation of these associations is made difficult by the strong LD and insufficient coverage of the region in many of the studies.8, 9, 10, 11, 12, 13 More recently, dense single-nucleotide polymorphism (SNP)-mapping studies have identified several loci conferring RA susceptibility independently of HLA-DRB1 risk alleles using novel statistical approaches to avoid confounding.14, 15, 16 Validation in independent data sets is particularly important to confirm new RA loci in the MHC. The Wellcome Trust Case Control Consortium (WTCCC) Study provides an ideal data source for this purpose.17 In the present study, this large and well-characterized data set was examined for the identification and validation of HLA-DRB1-independent RA risk loci.

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Results

In the initial unmatched analysis, we found 745 SNPs significantly associated with RA (P trend<0.05; Figure 1a). Of these, 192 markers reached genome-wide significance (P<5 × 10−7, as defined in the original WTCCC Study17) and 269 were significant after Bonferroni correction of the xMHC region (P<3.2 × 10−5). Many of the strongest associations were observed in the vicinity of the HLA-DRB1 locus, although a number of suggestive additional signals closer to the telomere were detected.

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

Unmatched association analysis of 1546 SNPs in the xMHC region using the whole RA cohort (1804 RA patients and 1474controls) (a), anti-CCP+ (1042 RA patients and 1804 controls) (b) and anti-CCP− (270 RA patients and 1804 controls) (c) patients only. Red line indicates P-value significance threshold (P<5 × 10−7).

Full figure and legend (106K)

To avoid confounding by RA-associated HLA-DRB1 alleles, we performed HLA-DRB1 case–control matching at a ratio 1:1, as previously described.14 Given the stringent selection strategy, we expected a decrease in the statistical power, as the number of individuals included in the analysis was reduced significantly (594 case–control pairs). A significance threshold was set at P<0.005, and five loci were identified to be associated with RA independently of HLA-DRB1, that is, ZNF391, OR2H1-OR2H2, HLA-G-HLA-A, C6orf26-RDBP and HLA-DPB1-COL11A2 (Table 1 and Figure 2a).

Figure 2.
Figure 2 - 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

Plots showing significantly associated SNPs in the xMHC region after pairwise matching on HLA-DRB1 genotype in the whole RA cohort (a), in CCP+ patients (b) and in CCP− patients (c). Red line indicates P-value significance threshold (P<0.005).

Full figure and legend (145K)


To further test whether these five loci represent effects independent of each other and the rest of the region, we performed conditional logistic regression analysis for the strongest associated SNP within each locus, conditioning on all the SNPs analyzed across the xMHC region. This analysis also allows the visual display of the independence of a locus (a dip and/or a spike against the xMHC), as shown in Supplementary Figure 2. A very complex association pattern was found for the HLA-G-HLA-A locus, whereas the other four showed stronger evidence of individual independent effects (Supplementary Figure 2). Therefore, we have found at least four xMHC loci associated with RA independently of HLA-DRB1:

  • Locus 1: close to ZNF391 in the extended class I region;
  • Locus 2: close to OR2H1 in the extended class I region;
  • Locus 3: close to C6orf26-RDBP in the class III region; and
  • Locus 4: HLA-DPB1-COL11A2 in the class II region.

It has been shown that HLA alleles are differentially associated with anti-cyclic citrullinated peptide (CCP)-positive and -negative disease. Therefore, we next analyzed the unmatched data in anti-CCP-positive and anti-CCP-negative patients separately. The anti-CCP+ subgroup showed a similar pattern of association compared with the whole data set, with the strongest associations around the HLA-DRB1 locus and evidence of additional signals (Figure 1b). On the contrary, only the HLA-DRB1 region surpassed the GW significance threshold in the anti-CCP− subgroup (Figure 1c).

Next, we carried out HLA-DRB1-matched analysis stratified according to the presence or absence of anti-CCP antibodies. A total of 296 and 119 matched case–control pairs were available for the anti-CCP+ and anti-CCP− groups, respectively. Three loci were associated with anti-CCP+ RA, independently of HLA-DRB1, at P<0.005: the butyrophilin (BTN)-gene cluster locus (particularly in the BTN2A2-BTN3A1 region), HLA-B-HCP5 and HLA-DPB1-COL11A2 (Table 2 and Figure 2b). Conditional logistic regression analysis provided support that they represented true independent effects (Supplementary Figure 3). In addition, the olfactory receptor (OR) locus could also represent another independent effect (P=0.007) (Figure 2b). With regard to the anti-CCP-patient subgroup, ZNF391, the OR cluster, and HLA-DPB1-COL11A2 showed some evidence of association with RA (P=0.01), but the weaker association was primarily due to the smaller sample size, in comparison with the anti-CCP+ subgroup (Figure 2c), as none of the top SNPs in each of these loci showed significant heterogeneity by Breslow–Day test between anti-CCP+ and anti-CCP− groups after HLA-DRB1 matching (data not shown).


Next, we investigated in more detail the LD present in the ZNF391, OR2H1 and HLA-DPB1-COL11A2 loci, because they were the most strongly associated regions and contained multiple SNPs associated at the P<0.005 threshold in the HLA-DRB1-adjusted analysis (Figure 2a).

The SNP showing the strongest association with RA after pairwise matching on HLA-DRB1genotype, rs9468112, is located in the ZNF391 gene. A total of 13 SNPs, mapping to the same LD block and exhibiting very tight LD, were associated with RA (P<0.05) in this region (Figure 3a). We found one haplotype significantly increased in controls compared with RA patients (P=0.005), but the effect size was not increased compared with that found for rs9468112 or its proxies alone (odds ratio 0.76; 95% confidence interval 0.62–0.93 for the haplotype and 0.72–0.76 for the SNPs) (Table 1 and Supplementary Table 1).

Figure 3.
Figure 3 - 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

Association and LD plots for the ZNF391 (a), HLA-DPB1 (b) and OR2H1 (c) loci. Top hit from each region is marked with a red diamond.

Full figure and legend (152K)

The next most strongly associated SNP was rs3129248. This SNP is located in an intergenic region ~55Kb from the HLA-DPB1 gene (Figure 3b). A number of SNPs showed significant P-values in this locus. These associated SNPs seemed to be located in two differentiated LD blocks. The first contains the top hit within the region, rs3129248, and it is located ~21Kb upstream of the COL11A2 gene. The second block is closer to the HLA-DPB1 gene (~12Kb downstream), and overlaps with the HLA-DRB1-independent RA risk locus previously identified by Ding et al.14

With regard to the OR2H1 locus, there were a number of SNPs significantly associated with RA in the same LD block: the top hit rs2746149 (and its proxies rs2523443 and rs1233493), rs1233495 (and its proxy rs1233487) and rs2107192 (and its proxies rs1233490 and rs2107193) (Figure 3c). One haplotype, tagged by the minor G allele of rs1233490, was strongly associated with RA (P=6 × 10−4; odds ratio 0.72; 95% confidence interval 0.59–0.87), but the effect size was lower than that found for rs1233490 alone (odds ratio 0.77; 95% confidence interval 0.64–0.94; Table 1 and Supplementary Table 2). The haplotype tagged by the top hit in the region, rs2746149, was also associated with RA (P=0.03; odds ratio 1.28; 95% confidence interval 1.01−1.62), but again the effect of the haplotype was more modest than the SNP.

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Discussion

In this study, we have confirmed that multiple independent loci are associated with RA in the xMHC complex. The most convincing signals after HLA-DRB1 mapped to the MHC class II (HLA-DPB1-COL11A2) and extended class I (ZNF391 and OR2H1) regions.

HLA-DPB1 alleles have been studied in the past as potential RA susceptibility markers, with conflicting results, possibly reflecting an underpowered study design and/or clinical heterogeneity.18, 19, 20, 21, 22, 23, 24, 25, 26 Our result in a UK cohort together with previous studies in Swedish and North American populations14, 15 provides strong evidence that HLA-DPB1-COL11A2 is a genuine RA risk locus independent of HLA-DRB1 and the rest of the xMHC region. Several SNPs were found to be associated with RA in this intergenic region, distributed in two different LD blocks. This pattern was similar to that found by Lee et al.15 Polymorphisms in COL11A2 have been implicated in susceptibility to skeletal and cartilage disorders, and hearing loss.27, 28, 29, 30, 31, 32 HLA-DPB1 is an attractive candidate gene for RA within this region, as it has an important role in the immune system by presenting peptides to CD4+ T cells. Furthermore, the other two genes encoding classical HLA class II molecules, HLA-DRB1 and HLA-DQA1, are established RA risk genes. Interestingly, this locus has also been shown to be associated with type 1 diabetes independently of HLA-DRB1/HLA-DQB1.33, 34 To formally assign this effect to HLA-DPB1, however, genotyping of HLA-DP is desirable in the relevant cohorts.

Additionally, we found evidence of new independent RA susceptibility loci within the MHC extended class I region. The top hit from our study maps to an intronic haplotype in the zinc finger protein 391 (ZNF391) gene. Zinc finger proteins have diverse functions, and can act as enzymes, storage proteins, replication proteins and transcription factors.35 The exact role of ZNF391 is currently unknown, but the similarity between its sequence and sequences of known proteins suggests that it may be involved in transcriptional regulation (UniProtKB/Swiss-Prot accession number Q9UJN7; http://www.uniprot.org).

The closest gene to the second RA-associated locus in the extended class I region is OR2H1 (olfactory receptor, family 2, subfamily H, member 1). Suggestive evidence for association with RA has been previously found for other members of the OR supercluster.15 The role that these highly polymorphic genes might be having in RA etiological pathways is not evident, as they are involved in the sensory perception of smell. Nevertheless, it has been proposed recently that olfactory abnormalities may be associated with autoimmune conditions involving the central nervous system.36 RA patients demonstrate a higher prevalence of psychiatric disorders, such as depression, than the normal population,37 and several studies show a link between depression and olfactory impairment.36 Other neighboring genes include the ubiquitin D pseudogene 1 (UBDP1) and MAS1 oncogene-like (MAS1L). Further validation, fine mapping and functional studies will be necessary to identify the etiological variants within these new potential RA loci and to elucidate their role in disease pathways.

With regard to the stratified analysis according to RA patients’ anti-CCP status, the pattern of association was in general similar to that found in the non-stratified analysis (Figures 2a, b and c) in contrast with previous studies.14 Although the BTN gene cluster appeared to be a risk locus exclusively for anti-CCP+ patients, a formal test of heterogeneity of all the top SNPs in the associated loci did not reveal significant heterogeneity between anti-CCP+ and anti-CCP− groups after HLA-DRB1 matching with controls. Interestingly, the BTN gene cluster has been also associated with type 1 diabetes.38 The BTN cluster encodes proteins of as yet unknown functions, but they are thought to have an immunological role, given that they show strong similarity with other xMHC genes and with CD80 and CD86 costimulatory receptors.39, 40 Regarding the association found in the HLA-B-HCP5 locus for anti-CCP+ patients, it is difficult to ascertain whether it represents a different effect from that found in Corf26-RDBP in the non-stratified analysis (Figures 2a and b). The lack of statistically significant associations mapping to the xMHC in the anti-CCP-negative group of patients is in accordance with previous studies.14 However, this seems to be a reflection of the modest sample size of this cohort (270 RA patients). Finally, stratified analysis results should be considered with caution, given the impossibility to recruit a sufficiently large number of RA patients with high-resolution HLA-DRB1 typing and anti-CCP data from the WTCCC cohort.

A previous work investigating SNPs in the MHC region conducted in a UK population found two different loci associated with RA, mapping to the VARS2L gene and upstream of HLA-B.16 As mentioned above, we found a signal downstream HLA-B in anti-CCP+ patients, but it was almost 100Kb away from that found by Vignal et al. (rs2442728).16 No SNPs in LD with rs2442728 were tested in our data set; the closest proxy (rs887464, r2=0.47) was not significantly associated with RA. However, our results are difficult to compare with Vignal et al.'s,16 because the methods to control confounding by HLA-DRB1 were different in both studies. Whereas the previous UK study adjusted the results for the number of shared epitope copies, we used the DRB1 matching approach.

The matching of cases and controls 1:1 according to HLA-DRB1 genotypes has been proposed as the optimal way to adjust for confounding by the effect of DRB1 genotype, and has proved successful in the identification of new independent RA susceptibility loci in the xMHC region.14, 15 The advantage of this approach over adjusting for the carriage of shared epitope alleles is that it avoids the residual confounding that might exist in the latter, given the complexity of the DRB1 locus and the fact that different shared epitope alleles confer different disease risks. However, the DRB1 matching has the implicit drawback of a significant reduction of the sample size and, consequently, of the statistical power, making meta-analysis of multiple studies desirable.

In conclusion, the HLA-DPB1-COL11A2 locus has been confirmed as an independent RA risk locus in our study. Furthermore, our results identified other additional effects in the xMHC region, supporting the long-standing hypothesis that additional non-DRB1 effects contribute to RA disease susceptibility. With the availability of multiple dense SNP and HLA genotype data in large well-characterized case–control cohorts, a more detailed picture of these effects can be established.

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Patients and methods

Patients

RA cases and controls cohorts were part of the WTCCC Study and have been described elsewhere.17 Briefly, a total of 1804 RA patients satisfying the 1987 American College of Rheumatology Criteria for RA modified for genetic studies 41, 42 and 1474 controls from the 1958 Birth Cohort (http://www.b58cgene.sgul.ac.uk/) were included in the study. All subjects were Caucasian from the United Kingdom and were recruited after providing informed consent. In all, 75% of the patients were female, the age of onset was 46.3±14.6 years and 84% were positive for rheumatoid factor. Anti-CCP data were available for 1313 RA patients, of which 1042 (79%) were anti-CCP-positive and 271 (21%) were negative. This cohort is therefore representative of a hospital-based series of patients with RA. None of the samples was included in any previous study on HLA associations with RA.

Anti-CCP antibody titer was measured at one point in time using a commercially available kit (Diastat Anti-CCP Kit; Axis-Shield Diagnostics Limited, Dundee, UK). Patients with titers greater than or equal to5Uml−1 were defined as positive for anti-CCP antibodies.

Genotyping

High-resolution HLA-DRB1 typing was performed using Dynal RELI SSO kits (DYNAL Biotech, Bromborough, UK), and was available for 1536 patients and 1126 controls. Subjects were genotyped using the Affymetrix GeneChip 500K, as part of the WTCCC Study.17 After data quality control,17 1580 SNPs spanning a region of ~7.8Mb within chromosome 6p, encompassing the xMHC (Chr6:25751771–33537930, NCBI build 35) were selected (Supplementary Figure 1). To guard against spurious associations, a stringent Hardy–Weinberg equilibrium threshold (P<0.001) was further applied, leaving a total of 1546 SNPs for the subsequent analyses.

Statistical analysis

Association of HLA-DRB1 alleles with RA was interrogated by logistic regression. Statistical analysis of the SNPs mapping to the xMHC region was carried out in three stages:

  1. Unmatched association analysis: Genotype counts in cases and controls were analyzed using the χ2-test for trend.
  2. Adjustment of the association results for HLA-DRB1 alleles: High-resolution HLA-DRB1 typing was used to perform case–control matching at a ratio 1:1, as previously described.14, 15 Using this approach, 594 case–control pairs with identical DRB1 genotypes were identified. Logistic regression was used to perform the association analysis in this data set.
  3. Conditional logistic regression: The top associated SNPs from stage 2 (P<0.005) were further tested for independence by logistic regression analysis conditioning on all the SNPs analyzed across the xMHC region.

Stratified analyses were then carried out according to anti-CCP status, and statistical analyses as listed above (1–3) were repeated for both subgroups.

All statistical analyses were performed using PLINK.43 Haplotypes were estimated using Haploview.44

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Conflict of interest

The authors declare no conflict of interest.

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Acknowledgements

This work was supported by the Arthritis Research UK (Grant reference number 17552). We are grateful to the NIHR Manchester Biomedical Research Centre and the WTCCC. GO is funded by the European Union (Marie Curie IEF Fellowship PIEF-GA-2009-235662).

Supplementary Information accompanies the paper on Genes and Immunity website