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Clinical and epidemiological research
Extended report
BANK1 functional variants are associated with susceptibility to diffuse systemic sclerosis in Caucasians
  1. B Rueda1,
  2. P Gourh2,
  3. J Broen3,
  4. S K Agarwal2,
  5. C Simeon4,
  6. N Ortego-Centeno5,
  7. M C Vonk3,
  8. M Coenen6,
  9. G Riemekasten7,
  10. N Hunzelmann8,
  11. R Hesselstrand9,
  12. F K Tan2,
  13. J D Reveille2,
  14. S Assassi2,
  15. F J Garcia-Hernandez10,
  16. P Carreira11,
  17. M Camps12,
  18. A Fernandez-Nebro13,
  19. P Garcia de la Peña14,
  20. T Nearney15,
  21. D Hilda16,
  22. M A Gónzalez-Gay17,
  23. P Airo18,
  24. L Beretta19,
  25. R Scorza19,
  26. T R D J Radstake3,
  27. M D Mayes2,
  28. F C Arnett2,
  29. J Martin1
  1. 1Instituto de Parasitologia y Biomedicina ‘Lopez-Neyra’ (CSIC), Granada, Spain
  2. 2The University of Texas Health Science Center at Houston Medical School, Department of Internal Medicine, Division of Rheumatology and Clinical Immunology, Houston, Texas, USA
  3. 3Department of Rheumatology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
  4. 4Servicio de Medinina Interna, Hospital Valle de Hebron, Barcelona, Spain
  5. 5Servicio de Medicina Interna, Hospital Clinico Universitario, Granada, Spain
  6. 6Department of Human Genetics, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
  7. 7Department of Rheumatology and Clinical Immunology, Charité University Hospital, Berlin, Germany
  8. 8Department of Dermatology, University of Cologne, Cologne, Germany
  9. 9Department of Rheumatology, Lund University Hospital, Lund, Sweden
  10. 10Servicio de Medicina Interna, Hospital Virgen del Rocio, Sevilla, Spain
  11. 11Servicio de Reumatología, Hospital 12 de Octubre, Madrid, Spain
  12. 12Servicio de Medicina Interna, Hospital Carlos Haya, Málaga, Spain
  13. 13Servicio de Reumatología, Hospital Carlos Haya, Málaga, Spain
  14. 14Servicio de Reumatología, Hospital Ramon y Cajal, Madrid, Spain
  15. 15University of Texas Medical Branch at Galveston, Galveston, Texas, USA
  16. 16The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
  17. 17Servicio de Reumatología, Hospital Xeral-Calde, Lugo, Spain
  18. 18Servizio di Reumatologia ed Immunologia Clinica Spedali Civili, Brescia, Italy
  19. 19Referral Centre for Systemic Autoimmune Diseases, University of Milan, Milan, Italy
  1. Correspondence to Dr Blanca Rueda, Instituto de Parasitología y Biomedicina López-Neyra, Consejo Superior de Investigaciones Científicas, Parque Tecnológico de Ciencias de la Salud, Avenida del Conocimiento s/n 18100-Armilla (Granada), Spain; blarume{at}ipb.csic.es

Abstract

Objective To investigate the possible association of the BANK1 gene with genetic susceptibility to systemic sclerosis (SSc) and its subphenotypes.

Methods A large multicentre case–control association study including 2380 patients with SSc and 3270 healthy controls from six independent case–control sets of Caucasian ancestry (American, Spanish, Dutch, German, Swedish and Italian) was conducted. Three putative functional BANK1 polymorphisms (rs17266594 T/C, rs10516487 G/A, rs3733197 G/A) were selected as genetic markers and genotyped by Taqman 5´ allelic discrimination assay.

Results A significant association of the rs10516487 G and rs17266594 T alleles with SSc susceptibility was observed (pooled OR=1.12, 95% CI 1.03 to 1.22; p=0.01 and pooled OR=1.14, 95% CI 1.05 to 1.25; p=0.003, respectively), whereas the rs3733197 genetic variant showed no statistically significant deviation. Stratification for cutaneous SSc phenotype showed that the BANK1 rs10516487 G, rs17266594 T and rs3733197 G alleles were strongly associated with susceptibility to diffuse SSc (dcSSc) (pooled OR=1.20, 95% CI 1.05 to 1.37, p=0.005; pooled OR=1.23, 95% CI 1.08 to 1.41, p=0.001; pooled OR=1.15, 95% CI 1.02 to 1.31, p=0.02, respectively). Similarly, stratification for specific SSc autoantibodies showed that the association of BANK1 rs10516487, rs17266594 and rs3733197 polymorphisms was restricted to the subgroup of patients carrying anti-topoisomerase I antibodies (pooled OR=1.20, 95% CI 1.02 to 1.41, p=0.03; pooled OR=1.24, 95% CI 1.05 to 1.46, p=0.01; pooled OR=1.26, 95% CI 1.07 to 1.47, p=0.004, respectively).

Conclusion The results suggest that the BANK1 gene confers susceptibility to SSc in general, and specifically to the dcSSc and anti-topoisomerase I antibody subsets.

https://doi.org/10.1136/ard.2009.118174

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    Introduction

    B cells are important regulators of immune homoeostasis and have an essential role in humoral and cellular immunity.1 Alteration of the mechanisms that control B-cell activation and function can lead to pathogenic autoantibody production and autoimmunity as occurs in different autoimmune diseases such as systemic lupus erythematosus (SLE) or rheumatoid arthritis (RA).2

    Recent results have shown that the B-cell scaffold protein with ankyrin repeats gene (BANK1), which encodes a signalling molecule expressed exclusively in B cells, is implicated in genetic predisposition to SLE and RA.3 4 Three functional polymorphisms affecting BANK1 regulatory sites and key functional domains (rs17266594 T/C, rs10516487 G/A and rs3733197 G/A) were strongly associated with susceptibility to SLE and RA.3 4

    Systemic sclerosis (SSc) is another autoimmune disease of unknown aetiology in which genetic factors are thought to have an important role.5 In the pathogenesis of SSc the dysregulation of the immune response is a central event shown by the presence of lymphocyte infiltrates in affected tissues, increased levels of inflammatory mediators and the presence of specific SSc autoantibodies. B cells seem to be one of the key players of this response.6 7 Analysis of gene expression patterns in patients with SSc discloses a strong expression of genes associated with B lymphocytes.7 In addition, in SSc there are indicators of increased B-cell activation such as hypergammaglobulinaemia, enhanced expression of activation markers and autoantibody production.6 8

    Thus, taking into consideration both the relevance of B cells in SSc pathogenesis and the hypothesis that different autoimmune conditions share common genetic markers,9 we selected BANK1 as an interesting functional candidate gene and investigated its implications in susceptibility to SSc, and its clinical and autoantibody subsets.

    Materials and methods

    Patients

    We conducted a large multicentre case–control association study including a total of 2380 patients with SSc and 3270 healthy controls. Six independent case–control sets with Caucasian ancestry were analysed (USA cohort: 1053 patients with SSc and 696 controls; Spanish cohort: 588 patients with SSc and 1051 controls; Dutch cohort: 142 patients with SSc and 256 controls; Swedish cohort: 89 patients with SSc; German cohort: 183 patients with SSc; and Italian cohort: 325 patients with SSc and 340 controls). As control populations for the Swedish and German cohorts genotype and allelic frequencies of 565 and 362 controls, respectively, were derived from a literature report.3

    All patients with SSc fulfilled the 1980 American College of Rheumatology classification criteria for SSc.10 Patients were classified as having limited (lcSSc) or diffuse SSc (dcSSc). Patients with SSc with cutaneous involvement distal from the elbows and knees fulfilled definitions for lcSSc.11 Those patients with SSc with cutaneous changes proximal to elbows and knees were classified as having dcSSc.12

    For patients with SSc, main clinical data, age, gender, disease duration and presence of SSc-specific autoantibodies anti-topoisomerase (ATA; anti-Scl-70) and anticentromere (ACA) have been described previously.13 14 Data for SSc-specific autoantibody status was available for 1038 USA, 353 Spanish, 133 Dutch, 74 Swedish, 168 German and 272 Italian patients with SSc.

    The study was approved by all local ethic committees and all participants were included after written informed consent.

    BANK1 single nucleotide polymorphisms (SNPs) genotyping

    Three putative functional BANK1 polymorphisms (rs17266594 T/C, rs10516487 G/A, rs3733197 G/A) were selected as genetic markers and genotyped by Taqman 5′ allelic discrimination assay (see online supplementary material).

    Statistical analysis

    We tested Hardy–Weinberg equilibrium for each case–control set by using the program FINETI (http://ihg.gsf.de/cgi-bin/hw/hwa2.pl, accessed 31 December 2009). Significance was calculated by χ2 test using Statcalc software (Epi Info 2002; Centers for Disease Control and Prevention, Atlanta, Georgia, USA). p Values <0.05 were considered as statistically significant. Analysis of the combined data from all populations was performed using the Stats Direct software. First, homogeneity of OR among cohorts was calculated using Breslow–Day and Woolf Q methods. We then performed a calculation of the pooled OR under a fixed-effects model (Mantel–Haenszel meta-analysis) or random effects (DerSimonian–Laird) when necessary.

    The estimation of the power of the study was performed using the Quanto v 0.5 software (Department of Preventive Medicine University of Southern California, California, USA). For the pooled analysis of SSc (n=2380) and considering a medium minor allele frequency of 0.30 our study reached a 99% power to detect the effect of a polymorphism at an OR of 1.3, similar to that observed for the analysed BANK1 polymorphisms in previous studies.3 4 Under the same conditions, estimation of the power for the pooled analysis of SSc clinical analysis was 93% for lcSSc (n=1394), 73% for dcSSc (n=770), 71% for ACA (n=749) and 51% for ATA (n=435). Since the BANK1-analysed SNPs are in strong linkage disequilibrium, the Bonferroni correction for multiple testing was not applied.15

    Results

    The distribution of the BANK1-analysed polymorphisms was found to be in Hardy–Weinberg equilibrium in all the patients with SSc and control groups.

    First, we investigated the possible implication of BANK1 rs17266594, rs10516487 and rs3733197 SNPs in SSc susceptibility. In the independent analysis, an increased frequency of the rs10516487 G and the rs17266594 T alleles among patients with SSc compared with controls was observed, although these differences were not statistically significant except for the rs17266594 T allele in the Italian population (p=0.001, OR=1.54, 95% CI 1.20 to 2.0) (table 1). In spite of the different geographical origin of study case–control sets, the combinability test according to the Breslow–Day method showed no significant differences among them. Therefore, we performed a pooled OR analysis using the Mantel–Haenszel test under fixed effects that showed a significant association of the rs10516487 G and the rs17266594 T alleles with SSc susceptibility (pooled OR=1.12, 95% CI 1.03 to 1.22, p=0.01 and pooled OR=1.14, 95% CI 1.05 to 1.25, p = 0.003, respectively) (table 1). The analysis of the rs3733197 genetic variant did not show any statistically significant deviation in the independent and pooled analyses (table 1).

    View this table:
    Table 1

    Distribution of BANK1 single nucleotide polymorphisms (SNPs) genotypic and allelic frequencies in patients with systemic sclerosis (SSc) and controls

    To further characterise the role of the BANK1 gene in SSc susceptibility we investigated its possible implication in SSc subtype or clinical manifestations. In the stratification accordingly to SSc subtype, we found that the general trend was an increased frequency of the major alleles of BANK1 rs10516487, rs17266594 and rs3733197 genetic variants in patients with dcSSc compared with healthy subjects (table 2). Only in the Spanish and Swedish populations the frequency of these alleles in patients with dcSSc was very similar to that observed in the control population (table 2). A meta-analysis of the six study populations showed that the BANK1 rs10516487 G, rs17266594 T and rs3733197 G alleles were strongly associated with dcSSc susceptibility (pooled OR=1.20, 95% CI 1.05 to 1.37, p=0.005; pooled OR=1.23, 95% CI 1.08 to 1.41, p=0.001; and pooled OR=1.15, 95% CI 1.02 to 1.31, p=0.02, respectively) (table 2). In contrast, for limited SSc no significant association of the BANK1 rs10516487, rs17266594 or rs3733197 polymorphisms was observed in the independent and pooled analysis (table 2).

    View this table:
    Table 2

    Analysis of BANK1 polymorphisms according to systemic sclerosis (SSc) subtype

    Interestingly, the analysis of BANK1 genetic variants according to specific SSc autoantibody status confirmed the findings from the subtype analysis since the associations of BANK1 rs10516487, rs17266594 and rs3733197 polymorphisms were significant only in the subgroup of patients carrying anti-Scl-70 antibodies that are highly specific for dcSSc (pooled OR=1.20, 95% CI 1.02 to 1.41, p=0.03; pooled OR=1.24, 95% CI 1.05 to 1.46, p=0.01; pooled OR=1.26, 95% CI 1.07 to 1.47, p=0.004) (table 3). In contrast, in the ACA patient groups the distribution of BANK1 rs10516487, rs17266594 and rs3733197 genotypes and allelic frequencies did not reach any statistically significant skewing with ORs near 1.00 for the three SNPs (table 3). Additionally, this analysis showed the same trend in all six study populations even in the Spanish and Swedish groups, in which the subtype stratification showed no risk effect of BANK1 polymorphisms for the dcSSc form (table 3).

    View this table:
    Table 3

    Analysis of BANK1 polymorphisms according to systemic sclerosis (SSc)-specific autoantibodies

    The analysis of the BANK1 selected genetic markers considering SSc organ involvement (interstitial lung disease, pulmonary hypertension) did not show any statistically significant skewing (data not shown).

    Discussion

    In this study we analysed for the first time the possible association of the BANK1 gene in genetic predisposition to SSc susceptibility and subphenotypes. BANK1 is a functionally excellent a priori candidate gene since it is implicated in the regulation of B-cell receptor-mediated activation and B cells are thought to have a relevant role in SSc susceptibility.6 16 17

    We conducted a large association study which included six independent case–control sets of European Caucasian ancestry and observed that BANK1 functional polymorphisms are associated with genetic predisposition to SSc, specifically with the diffuse form of the disease and the presence of ATA. Although our results strongly suggest that the BANK1 gene confers susceptibility to dcSSc but not to lcSSc, it should be noted that owing to the lower prevalence of the diffuse form of the disease, the number of patients with dcSSc included in our study (n=770) has only 70% power to detect an association and therefore further independent replication studies are needed to confirm BANK1 as a genetic marker of dcSSc across populations.

    The hypothesis that genetic differences may influence the development of different SSc clinical subsets is supported by a number of well-powered SSc genetic studies that are being conducted. In this vain, recent evidence suggest that the STAT4 gene confers an increased risk for lcSSc susceptibility but not for dcSSc.13 Similarly, the BLK gene has been shown to confer increased risk for lcSSc (unpublished observation). Meanwhile, other genetic factors, such as PTPN22 or MIF genes, seem to predispose particularly to dcSSc/anti-Scl-70 positive subset.18 19

    Thus, the association of BANK1 with dcSSc reported in this work supports novel evidence for this hypothesis.

    All the BANK1 genetic markers analysed in this study have been found to exert functional relevance. The rs10516487 and rs17266594 SNPs associated with dcSSc susceptibility lead to a non-synonymous substitution (R61H) and to a branch point site, respectively.3 The rs10516487 polymorphism lies within a region essential for binding to the calcium channel IP3R, a downstream protein that mediates BANK1 activity.3 The functional relevance of the rs17266594 SNP resides in its ability to alter the expression of the two different BANK1 isoforms since in subjects with the rs17266594 G risk allele the expression of the full-length BANK1 protein is decreased while the Δ2 isoform is upregulated.3 Thus the presence of these risk alleles could lead to more efficient splicing of a more ‘active’ protein.

    BANK1 is primarily expressed in CD19 B cells that are significantly overexpressed in patients with SSc.3 20 Activation through the B-cell receptor leads to BANK1 phosphorylation and signalling.17 For subjects carrying BANK1 functional mutations, altered B-cell activation may occur that could contribute to the production of autoantibodies as well. This could be the case for SSc, in which disease-specific autoantibodies are produced. However, further functional studies are necessary to elucidate the exact molecular mechanisms by which BANK1 is implicated in the B-cell activation process and, more precisely, how it can lead to the development of dcSSc.

    In summary, our results suggest that the BANK1 gene is associated with dcSSc genetic susceptibility. This could in part provide an explanation for one of the best described pathogenic mechanisms of disease, the production of specific autoantibodies.

    Acknowledgments

    We thank Sofia Vargas for her invaluable contribution to the collection, isolation and storage of the DNA samples. This work was supported by grants SAF2009-11110, in part by Junta de Andalucía, grupo CTS-180 and by RETICS Program, RD08/0075 (RIER) from Instituto de Salud Carlos III (ISCIII). BR is supported by the I3P CSIC program funded by the ‘Fondo Social Europeo’. TR was funded by the VIDI laureate from the Dutch association of research (NWO) and Dutch Arthritis Foundation (reumafonds).

    References

    1. ↵
      1. LeBien TW,
      2. Tedder TF
      . B lymphocytes: how they develop and function. Blood 2008;112:1570–80.
      OpenUrlAbstract/FREE Full Text
    2. ↵
      1. Zouali M
      . B lymphocytes – chief players and therapeutic targets in autoimmune diseases. Front Biosci 2008;13:4852–61.
      OpenUrlPubMedWeb of Science
    3. ↵
      1. Kozyrev SV,
      2. Abelson AK,
      3. Wojcik J,
      4. et al
      . Functional variants in the B-cell gene BANK1 are associated with systemic lupus erythematosus. Nat Genet 2008;40:211–16.
      OpenUrlCrossRefPubMedWeb of Science
    4. ↵
      1. Orozco G,
      2. Abelson AK,
      3. González-Gay MA,
      4. et al
      . Study of functional variants of the BANK1 gene in rheumatoid arthritis. Arthritis Rheum 2009;60:372–9.
      OpenUrlCrossRefPubMedWeb of Science
    5. ↵
      1. Agarwal SK,
      2. Tan FK,
      3. Arnett FC
      . Genetics and genomic studies in scleroderma (systemic sclerosis). Rheum Dis Clin North Am 2008;34:17–40.
      OpenUrlCrossRefPubMedWeb of Science
    6. ↵
      1. Gu YS,
      2. Kong J,
      3. Cheema GS,
      4. et al
      . The immunobiology of systemic sclerosis. Semin Arthritis Rheum 2008;38:132–60.
      OpenUrlCrossRefPubMedWeb of Science
    7. ↵
      1. Whitfield ML,
      2. Finlay DR,
      3. Murray JI,
      4. et al
      . Systemic and cell type-specific gene expression patterns in scleroderma skin. Proc Natl Acad Sci USA 2003;100:12319–24.
      OpenUrlAbstract/FREE Full Text
    8. ↵
      1. Cepeda EJ,
      2. Reveille JD
      . Autoantibodies in systemic sclerosis and fibrosing syndromes: clinical indications and relevance. Curr Opin Rheumatol 2004;16:723–32.
      OpenUrlCrossRefPubMedWeb of Science
    9. ↵
      1. Zhernakova A,
      2. van Diemen CC,
      3. Wijmenga C
      . Detecting shared pathogenesis from the shared genetics of immune-related diseases. Nat Rev Genet 2009;10:43–55.
      OpenUrlCrossRefPubMedWeb of Science
    10. ↵
      Subcommittee for scleroderma criteria of the American Rheumatism Association Diagnostic and Therapeutic Criteria Committee. Preliminary criteria for the classification of systemic sclerosis (scleroderma). Arthritis Rheum 1980;23:581–90.
      OpenUrlCrossRefPubMedWeb of Science
    11. ↵
      1. LeRoy EC,
      2. Medsger TA Jr
      . Criteria for the classification of early systemic sclerosis. J Rheumatol 2001;28:1573–6.
      OpenUrlAbstract/FREE Full Text
    12. ↵
      1. LeRoy EC,
      2. Black C,
      3. Fleischmajer R,
      4. et al
      . Scleroderma (systemic sclerosis): classification, subsets and pathogenesis. J Rheumatol 1988;15:202–5.
      OpenUrlPubMedWeb of Science
    13. ↵
      1. Rueda B,
      2. Broen J,
      3. Simeon C,
      4. et al
      . The STAT4 gene influences the genetic predisposition to systemic sclerosis phenotype. Hum Mol Genet 2009;18:2071–7.
      OpenUrlAbstract/FREE Full Text
    14. ↵
      1. Gourh P,
      2. Tan FK,
      3. Assassi S,
      4. et al
      . Association of the PTPN22 R620W polymorphism with anti-topoisomerase I- and anticentromere antibody-positive systemic sclerosis. Arthritis Rheum 2006;54:3945–53.
      OpenUrlCrossRefPubMedWeb of Science
    15. ↵
      1. Balding DJ
      . A tutorial on statistical methods for population association studies. Nat Rev Genet 2006;7:781–91.
      OpenUrlCrossRefPubMedWeb of Science
    16. ↵
      1. Aiba Y,
      2. Yamazaki T,
      3. Okada T,
      4. et al
      . BANK negatively regulates Akt activation and subsequent B cell responses. Immunity 2006;24:259–68.
      OpenUrlCrossRefPubMedWeb of Science
    17. ↵
      1. Yokoyama K,
      2. Su Ih IH,
      3. Tezuka T,
      4. et al
      . BANK regulates BCR-induced calcium mobilization by promoting tyrosine phosphorylation of IP(3) receptor. EMBO J 2002;21:83–92.
      OpenUrlAbstract/FREE Full Text
    18. ↵
      1. Dieudé P,
      2. Guedj M,
      3. Wipff J,
      4. et al
      . The PTPN22 620W allele confers susceptibility to systemic sclerosis: findings of a large case-control study of European Caucasians and a meta-analysis. Arthritis Rheum 2008;58:2183–8.
      OpenUrlCrossRefPubMedWeb of Science
    19. ↵
      1. Wu SP,
      2. Leng L,
      3. Feng Z,
      4. et al
      . Macrophage migration inhibitory factor promoter polymorphisms and the clinical expression of scleroderma. Arthritis Rheum 2006;54:3661–9.
      OpenUrlCrossRefPubMedWeb of Science
    20. ↵
      1. Sato S,
      2. Fujimoto M,
      3. Hasegawa M,
      4. et al
      . Altered B lymphocyte function induces systemic autoimmunity in systemic sclerosis. Mol Immunol 2004;41:1123–33.
      OpenUrlCrossRefPubMedWeb of Science

    Supplementary materials

    • Web Only Data ard.2009.118174

      Files in this Data Supplement:

    Footnotes

    • BR, PG, JB, TRDJR, MDM, FCA and JM contributed equally to this manuscript.

    • Funding The US studies were supported by the NIH/NIAMS Center of Research Translation (CORT) in Scleroderma (P50AR054144) (FCA), the NIH/NIAMS Scleroderma Family Registry and DNA Repository (N01-AR-0-2251) (MDM), UTHSC-H Center for Clinical and Translational Sciences (Houston CTSA Program) (NIH/NCRR 3UL1RR024148) (FCA), NIH/NIAMS K08 Award (K08AR054404) (SKA), Scleroderma Foundation New Investigator Award (SKA).

    • Competing interests None.

    • Ethics approval This study was conducted with the approval of the ethics committees of each participating hospital.

    • Provenance and peer review Not commissioned; externally peer reviewed.

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      Corrections
      BMJ Publishing Group Ltd and European League Against Rheumatism
      Annals of the Rheumatic Diseases 2011; 70 880-880 Published Online First: 03 Apr 2011. doi: 10.1136/ard.2009.118174corr1