The genetic background of primary Sjögren’s syndrome (pSS) is partly shared with systemic lupus erythematosus (SLE). Immunoglobulin G Fc receptors are important for clearance of immune complexes. Fcγ receptor variants and gene deletion have been found to confer SLE risk. In this study, four Fcγ receptor single-nucleotide polymorphisms (SNPs) and one copy number variation (CNV) were studied. Swedish and Norwegian pSS patients (N=527) and controls (N=528) were genotyped for the Fcγ receptor gene variant FCGR2A H131R (rs1801274) by the Illumina GoldenGate assay. FCGR3A F158V (rs396991) was analysed in 488 patients and 485 controls, FCGR3B rs447536 was analysed in 471 patients and 467 controls, and FCGR3B rs448740 was analysed in 478 cases and 455 controls, using TaqMan SNP genotyping assays. FCGR3B CNV was analysed in 124 patients and 139 controls using a TaqMan copy number assay. None of the SNPs showed any association with pSS. Also, no FCGR3B CNV association was detected. The lack of association of pSS with Fcγ receptor gene variants indicates that defective immune complex clearance may not be as important in pSS pathogenesis as in SLE, and may point to important differences between SLE and pSS.
Primary Sjögren’s syndrome (pSS) is a chronic systemic autoimmune disease mainly affecting the salivary and lacrimal glands. Population-based family studies have not yet been undertaken to ascertain the heritability of this disease. Based on multiplex families, twin case reports, candidate gene studies and clinical considerations, the disease is regarded as a complex genetic trait.1 pSS shares several genetic susceptibility factors and phenotypic features with rheumatoid arthritis and systemic lupus erythematosus (SLE) and twin concordance in pSS is assumed by some investigators to be between that of rheumatoid arthritis, 15%, and SLE, 25%.1 Candidate genes showing associations with pSS and other rheumatic diseases include the interferon-related genes IRF5 and STAT4, as well as HLA-DR and HLA-DQ variants.2, 3 Moreover, a recent study has shown association of pSS with EBF1, BLK and TNFSF4.4
Immunoglobulin G (IgG) Fc-receptors (FcγR) are immune cell membrane glycoproteins that bind to the Fc portion of IgG. They have different effects depending on their expression on immune cells. FcγR are important links between the adaptive and innate immune system, and are crucial for phagocytic function (reviewed in reference 5). Low-affinity single-nucleotide polymorphisms (SNPs) in FCGR2A and FCGR3A, and low copy number of FCGR3B, have been found to confer risk of SLE or lupus nephritis, probably because of defective clearance of immune complexes, contributing to inflammation.5, 6
Defective clearance of immune complexes has not been much studied in pSS. The few studies that are available were based on small samples, and showed inconsistent results concerning phagocytosis in pSS patients.7, 8, 9 A preliminary report showed genotyping results for the low-affinity SNPs FCGR2A rs1801274 and FCGR3A rs396991, in 228 pSS patients and 206 controls.10 No associations were found in patients versus controls, or related to patient anti-Sjögren’s syndrome A and/or anti-Sjögren’s syndrome B status. Regarding FcγRIIIB, the human neutrophil antigen (HNA)-1a and HNA-1b receptor forms differ by four amino acids and the corresponding encoding FCGR3B gene by five nucleotides, leading to differences in phagocytic activity.11, 12 PCR analyses of rs447536 and rs448740 have shown good accordance with serotype.13, 14 Regarding FCGR3B copy number, pSS was associated with deletion in a recent study on 174 pSS patients and 162 controls,15 and both deletion and duplication were associated with the disease in a study with a small pSS cohort.16 The aim of this study was to explore whether any of the mentioned FcγR gene SNPs were associated with pSS in a larger case–control association study, and to possibly replicate previous findings concerning FCGR3B copy number variation (CNV).
The studied SNPs and genotyping results are shown in Table 1. Genotyping success rates were 90–96% for the studied SNPs. All markers were in Hardy–Weinberg equilibrium with P>0.012. None of the SNPs showed any association with pSS at the allelic or at the genotypic level assuming an additive genetic model and correcting for age, gender and nationality. In addition, anti-Sjögren’s syndrome A and/or anti-Sjögren’s syndrome B status among patients showed no association with any SNP. Also, no FCGR3B CNV association was detected (Figure 1). In a previous study, we obtained HNA-1a/HNA-1b typing on 282 individuals using an allele-specific amplification as described by Bux et al.13 (data not shown). In this study, we genotyped rs447536 and rs448740, which discriminate more efficiently between the HNA-1a/HNA-1b and other allelotypes. Indeed, by comparing rs447536 and rs448740 with the previous HNA-1a/HNA-1b obtained by PCR, >20% of the individuals showed other allelotypes. Therefore, we chose to keep the rs447536 and rs448740 genotypes rather than the HNA-1a/HNA-1b classical description.
In this case–control study, the genotyped FcγR gene polymorphisms showed no association with pSS. To our knowledge, the sample sizes in this study are larger than those in other reports on rs1801274 and rs396991.10 We did not replicate the findings of an association with FCGR3B CNV previously reported in two studies.15, 16 The lack of association with pSS versus control status indicates that defective immune complex clearance may not be as important in pSS pathogenesis as in SLE. These two diseases may be looked on, not as discrete entities, but as partially overlapping phenotypes, with a gradual transition from one to the other, or with both diseases present simultaneously (SLE-SS overlap).17 The FcγR variants studied here may be among the genetic factors determining such a transition. Our findings therefore may point to crucial differences between SLE and pSS pathogenesis, and may give directions for future research.
The lack of association regarding FCGR3B CNV differs from findings in two other studies in pSS.15, 16 One possible explanation might be the different methods used to analyse CNV, and the different stringency for the inclusion of data and selection of controls (we only accepted s.d.<0.15 between replicates while the study by Nossent et al. used s.d.<0.2, and their control group was not gender matched). However, more analyses are needed in different cohorts to ascertain or disprove any true relationship. Other mechanisms for a possible reduced immune complex clearance in pSS should be studied, especially the role of complement factors and receptors,18 and possible roles of genetic variants in these. Also, replication studies should be performed with a large sample size for all SNPs studied, and could preferentially include other potentially interacting variants. FcγRIIB is an inhibitory Fc receptor important in balancing immune activation, and polymorphisms both in the promoter and in the exon of this receptor’s gene have been implicated in SLE.19 In addition, CNV is found to affect both the FCGR3A and FCGR3B genes,20 and CNV can falsely skew the SNP genotyping results, blurring any true association of the studied SNPs.21
The FcγR IIA-H131R polymorphism, rs1801274, confers reduced IgG2 binding by the R131 variant.22 In a meta-analysis, homozygotes were found to have an increased SLE risk (odds ratio of 1.3), and the population-attributable fraction of SLE cases because of FcγR IIA-R131 variant was estimated to be 13%.5 In FcγR IIIA, the V158F polymorphism (rs396991) causes reduced binding of most IgG subclasses by the F158 variant.22 This low-affinity allele is associated with SLE nephritis; the proportion of nephritis cases in SLE that could be attributed to the F158 allele has been estimated to be 10–14%.5 Low copy number of FCGR3B correlates with reduced receptor expression and immune complex uptake, and an association has been found in SLE as well as in other diseases.6, 23
Using TaqMan probes with specificity for rs447536 and rs448740, corresponding to a PCR-based method that reportedly showed good agreement with serological HNA-1a/HNA-1b assessment,13 a relatively high frequency of samples could not be assigned to any of the two FCGR3B forms. A possible reason could be inaccuracies of the TaqMan assay, and/or the original PCR method, which showed 100 and 15% accuracy with two different serological phenotyping methods.13 Another possibility is inherent characteristics in the gene region. According to the literature, the number of SNPs and haplotypes in this area does not seem to have been clarified. Also, sequencing results have shown a confusing picture,24 all of which can affect genotyping efficiency of these regions.
To conclude, FcγR IIA, IIIA and IIIB SNPs and FcγR IIIB CNV were not associated with pSS. The lack of association indicates that defective immune complex clearance may not be as important in pSS pathogenesis as in SLE, indicating differences between SLE and pSS pathogenesis.
Patients and methods
For the rs1801274 genotyping, a total of 581 patients with pSS and 595 controls were included. After genotype quality control where individuals with a genotype success rate of <90% were removed, 527 cases and 528 controls remained for analysis. The patients were selected from the rheumatology clinics at the Stockholm (n=59), Malmö (n=149), Linköping (n=62) and Uppsala (n=63) University Hospitals in Sweden and the rheumatology clinics at Haukeland University Hospital (n=126) and Stavanger University Hospital (n=68) in Norway. For genotyping of rs396991, rs447536 and rs448740, 519 patient samples and 497 control samples were available. Data on gender, age and autoantibody profile were collected (Table 2). The patients were unrelated and Caucasians. They fulfilled the American-European consensus criteria.25 Patients with SLE, rheumatoid arthritis or other potentially associated diseases (secondary Sjögren’s syndrome) were excluded. All patients gave their informed consent and the study was approved by the relevant ethical committees.
The controls were healthy blood donors from Uppsala and Linköping (n=114) in Sweden, and Bergen and Stavanger (n=219) in Norway. Controls from Malmö and Stockholm (n=262) were from established population-based study cohorts. Controls from Stavanger (n=71) were volunteers recruited as healthy control subjects for participation in a controlled pSS study. FCGR3B CNV was analysed in a smaller pSS cohort of 141 patients from Haukeland University Hospital, Bergen, Norway, and 149 healthy blood donor controls.
Genotyping of rs1801274 was performed using the GoldenGate assay from Illumina Inc. (San Diego, CA, USA) as described previously.4 For genotyping of rs396991, a commercially available TaqMan SNP allelic discrimination assay was used. Genotyping of rs447536 and rs448740 was performed using custom TaqMan SNP genotyping assays. TaqMan genotyping was performed using 20 ng of genomic DNA in a total reaction volume of 2 μl. The assays were amplified on an ABI 7900 HT (Applied Biosystems, Foster City, CA, USA), and analysed with the Sequence Detection Systems (SDS) Software v2.3, according to the supplier’s protocol. The clusters were visually examined for each assay and manually corrected if necessary. Gene copy number of FCGR3B was estimated by performing a duplex quantitative real-time PCR using exon 3 of PMP22 as a reference gene. PMP22 was verified not to have CNV by comparing PMP22 to exon 25 of RB1. Data from 10 patients and 10 controls were removed because of an s.d. higher than 0.15 between triplicates, leaving 124 patients and 138 controls for further CNV analyses. For further details, see Supplementary method section.
An allelic logistic regression was used to evaluate the effect of pSS versus control status (where the affection status is the outcome predicted by the alleles). Unadjusted P-values, and odds ratios with 95% confidence interval were computed. To estimate any effect of a positive anti-Sjögren’s syndrome A and/or anti-Sjögren’s syndrome B, a corresponding logistic regression was performed with antibody status as the dependent variable. In addition, genotypes were encoded under an additive model: minor alleles ‘D’ and major alleles ‘d’, and DD=0, Dd=1 and dd=2. The numeric genotypes were then used, including age, gender and nationality as covariates in a linear regression. SNP genotyping results were analysed using the Helix Tree SNP Variation Suite software (Golden Helix: http://www.goldenhelix.com). CNV data were analysed using the Mann–Whitney rank sum test with the GraphPad Prism v. 5.0 (GraphPad Software Inc., San Diego, CA, USA) and Fisher’s exact test using PASW Statistics 18.0 (SPSS Inc, Chicago, IL, USA).
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We thank Marianne Eidsheim and Dagny Ann Sandnes from the Broegelmann Research Laboratory, University of Bergen, for excellent technical assistance. Genotyping of rs1801274 was performed by the SNP&SEQ Technology Platform in Uppsala, Sweden. Isolation and storage of some of the Swedish DNA samples were performed by Region Skåne’s Competence Centre for Clinical Research, RSKC. The Malmö Diet and Cancer Study/Malmö Preventive Medicine program provided the population-based cohort from which the Malmö controls originated. The Malmö controls consisted of a population-based cohort included in the Malmö Cost-Cancer registry. The controls from Stockholm were samples from the population-based Epidemiological Investigation of Rheumatoid Arthritis (EIRA) control cohort. This work was supported by the University of Bergen; the Strategic Research Program at Helse Bergen; the Western Norway Regional Health Authority (Helse Vest) and the Broegelmann Foundation, Bergen, Norway. Also, the Swedish Research Council, the Swedish Rheumatism Foundation, King Gustaf V’s 80-year Foundation, Ragnar Söderberg Foundation and COMBINE. The SNP Technology Platform in Uppsala, Sweden, was established by funding from the Knut and Alice Wallenberg Foundation.
The authors declare no conflict of interest.
Supplementary Information accompanies this paper on Genes and Immunity website
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