Variants at multiple loci implicated in both innate and adaptive immune responses are associated with Sjögren's syndrome

Abstract

Sjögren's syndrome is a common autoimmune disease (affecting 0.7% of European Americans) that typically presents as keratoconjunctivitis sicca and xerostomia. Here we report results of a large-scale association study of Sjögren's syndrome. In addition to strong association within the human leukocyte antigen (HLA) region at 6p21 (Pmeta = 7.65 × 10−114), we establish associations with IRF5-TNPO3 (Pmeta = 2.73 × 10−19), STAT4 (Pmeta = 6.80 × 10−15), IL12A (Pmeta = 1.17 × 10−10), FAM167A-BLK (Pmeta = 4.97 × 10−10), DDX6-CXCR5 (Pmeta = 1.10 × 10−8) and TNIP1 (Pmeta = 3.30 × 10−8). We also observed suggestive associations (Pmeta < 5 × 10−5) with variants in 29 other regions, including TNFAIP3, PTTG1, PRDM1, DGKQ, FCGR2A, IRAK1BP1, ITSN2 and PHIP, among others. These results highlight the importance of genes that are involved in both innate and adaptive immunity in Sjögren's syndrome.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Summary of genome-wide association results for 27,501 variants overlapping between DS1 and DS2 after imputation and meta-analysis.
Figure 2: Regional plots of the meta-analysis results for the seven regions with Pmeta < 5 × 10−8.
Figure 3: Identification of cis-eQTLs in Sjögren's syndrome–associated regions.

Accession codes

Primary accessions

Gene Expression Omnibus

References

  1. 1

    Helmick, C.G. et al. Estimates of the prevalence of arthritis and other rheumatic conditions in the United States. Part I. Arthritis Rheum. 58, 15–25 (2008).

    PubMed  PubMed Central  Article  Google Scholar 

  2. 2

    Pillemer, S.R. et al. Incidence of physician-diagnosed primary Sjögren syndrome in residents of Olmsted County, Minnesota. Mayo Clin. Proc. 76, 593–599 (2001).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  3. 3

    Plesivcnik Novljan, M. et al. Incidence of primary Sjögren's syndrome in Slovenia. Ann. Rheum. Dis. 63, 874–876 (2004).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  4. 4

    Jonsson, R. et al. The complexity of Sjögren's syndrome: novel aspects on pathogenesis. Immunol. Lett. 141, 1–9 (2011).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  5. 5

    Vitali, C. et al. Classification criteria for Sjögren's syndrome: a revised version of the European criteria proposed by the American-European Consensus Group. Ann. Rheum. Dis. 61, 554–558 (2002).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  6. 6

    Thanou-Stavraki, A. & James, J.A. Primary Sjögren's syndrome: current and prospective therapies. Semin. Arthritis Rheum. 37, 273–292 (2008).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  7. 7

    Cobb, B.L., Lessard, C.J., Harley, J.B. & Moser, K.L. Genes and Sjögren's syndrome. Rheum. Dis. Clin. North Am. 34, 847–868 (2008).

    PubMed  PubMed Central  Article  Google Scholar 

  8. 8

    Hjelmervik, T.O., Petersen, K., Jonassen, I., Jonsson, R. & Bolstad, A.I. Gene expression profiling of minor salivary glands clearly distinguishes primary Sjögren's syndrome patients from healthy control subjects. Arthritis Rheum. 52, 1534–1544 (2005).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  9. 9

    Emamian, E.S. et al. Peripheral blood gene expression profiling in Sjögren's syndrome. Genes Immun. 10, 285–296 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  10. 10

    Ice, J.A. et al. Genetics of Sjögren's syndrome in the genome-wide association era. J. Autoimmun. 39, 57–63 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  11. 11

    Cruz-Tapias, P., Rojas-Villarraga, A., Maier-Moore, S. & Anaya, J.M. HLA and Sjögren's syndrome susceptibility. A meta-analysis of worldwide studies. Autoimmun. Rev. 11, 281–287 (2012).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  12. 12

    Korman, B.D. et al. Variant form of STAT4 is associated with primary Sjögren's syndrome. Genes Immun. 9, 267–270 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  13. 13

    Miceli-Richard, C. et al. Association of an IRF5 gene functional polymorphism with Sjögren's syndrome. Arthritis Rheum. 56, 3989–3994 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  14. 14

    Nordmark, G. et al. Association of EBF1, FAM167A(C8orf13)-BLK and TNFSF4 gene variants with primary Sjögren's syndrome. Genes Immun. 12, 100–109 (2011).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  15. 15

    Nordmark, G. et al. Additive effects of the major risk alleles of IRF5 and STAT4 in primary Sjögren's syndrome. Genes Immun. 10, 68–76 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  16. 16

    Kang, H.I. et al. Comparison of HLA class II genes in Caucasoid, Chinese, and Japanese patients with primary Sjögren's syndrome. J. Immunol. 150, 3615–3623 (1993).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. 17

    ENCODE Project Consortium. A user's guide to the encyclopedia of DNA elements (ENCODE). PLoS Biol. 9, e1001046 (2011).

  18. 18

    Rossin, E.J. et al. Proteins encoded in genomic regions associated with immune-mediated disease physically interact and suggest underlying biology. PLoS Genet. 7, e1001273 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  19. 19

    Frisch, M., Klocke, B., Haltmeier, M. & Frech, K. LitInspector: literature and signal transduction pathway mining in PubMed abstracts. Nucleic Acids Res. 37, W135–W140 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  20. 20

    Nekrep, N. et al. Mutation in a winged-helix DNA-binding motif causes atypical bare lymphocyte syndrome. Nat. Immunol. 3, 1075–1081 (2002).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  21. 21

    Meissner, T.B. et al. NLRC5 cooperates with the RFX transcription factor complex to induce MHC class I gene expression. J. Immunol. 188, 4951–4958 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  22. 22

    Loiseau, P. et al. HLA class I and class II are both associated with the genetic predisposition to primary Sjögren syndrome. Hum. Immunol. 62, 725–731 (2001).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  23. 23

    Raychaudhuri, S. et al. Five amino acids in three HLA proteins explain most of the association between MHC and seropositive rheumatoid arthritis. Nat. Genet. 44, 291–296 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  24. 24

    Savitsky, D., Tamura, T., Yanai, H. & Taniguchi, T. Regulation of immunity and oncogenesis by the IRF transcription factor family. Cancer Immunol. Immunother. 59, 489–510 (2010).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  25. 25

    Takaoka, A. et al. Integral role of IRF-5 in the gene induction programme activated by Toll-like receptors. Nature 434, 243–249 (2005).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  26. 26

    Sigurdsson, S. et al. Polymorphisms in the tyrosine kinase 2 and interferon regulatory factor 5 genes are associated with systemic lupus erythematosus. Am. J. Hum. Genet. 76, 528–537 (2005).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  27. 27

    Sigurdsson, S. et al. Association of a haplotype in the promoter region of the interferon regulatory factor 5 gene with rheumatoid arthritis. Arthritis Rheum. 56, 2202–2210 (2007).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  28. 28

    Stahl, E.A. et al. Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci. Nat. Genet. 42, 508–514 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  29. 29

    Dideberg, V. et al. An insertion-deletion polymorphism in the interferon regulatory Factor 5 (IRF5) gene confers risk of inflammatory bowel diseases. Hum. Mol. Genet. 16, 3008–3016 (2007).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  30. 30

    Liu, X. et al. Genome-wide meta-analyses identify three loci associated with primary biliary cirrhosis. Nat. Genet. 42, 658–660 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  31. 31

    Dieudé, P. et al. Association between the IRF5 rs2004640 functional polymorphism and systemic sclerosis: a new perspective for pulmonary fibrosis. Arthritis Rheum. 60, 225–233 (2009).

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  32. 32

    Radstake, T.R. et al. Genome-wide association study of systemic sclerosis identifies CD247 as a new susceptibility locus. Nat. Genet. 42, 426–429 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  33. 33

    Harley, J.B. et al. Genome-wide association scan in women with systemic lupus erythematosus identifies susceptibility variants in ITGAM, PXK, KIAA1542 and other loci. Nat. Genet. 40, 204–210 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  34. 34

    Graham, R.R. et al. Three functional variants of IFN regulatory factor 5 (IRF5) define risk and protective haplotypes for human lupus. Proc. Natl. Acad. Sci. USA 104, 6758–6763 (2007).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  35. 35

    Miceli-Richard, C. et al. The CGGGG insertion/deletion polymorphism of the IRF5 promoter is a strong risk factor for primary Sjögren's syndrome. Arthritis Rheum. 60, 1991–1997 (2009).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  36. 36

    Sigurdsson, S. et al. Comprehensive evaluation of the genetic variants of interferon regulatory factor 5 (IRF5) reveals a novel 5 bp length polymorphism as strong risk factor for systemic lupus erythematosus. Hum. Mol. Genet. 17, 872–881 (2008).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  37. 37

    Dawidowicz, K. et al. The interferon regulatory factor 5 gene confers susceptibility to rheumatoid arthritis and influences its erosive phenotype. Ann. Rheum. Dis. 70, 117–121 (2011).

    PubMed  Article  PubMed Central  Google Scholar 

  38. 38

    Kristjansdottir, G. et al. Interferon regulatory factor 5 (IRF5) gene variants are associated with multiple sclerosis in three distinct populations. J. Med. Genet. 45, 362–369 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  39. 39

    Kaplan, M.H. STAT4: a critical regulator of inflammation in vivo. Immunol. Res. 31, 231–242 (2005).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  40. 40

    Remmers, E.F. et al. STAT4 and the risk of rheumatoid arthritis and systemic lupus erythematosus. N. Engl. J. Med. 357, 977–986 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  41. 41

    Rueda, B. et al. The STAT4 gene influences the genetic predisposition to systemic sclerosis phenotype. Hum. Mol. Genet. 18, 2071–2077 (2009).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  42. 42

    Mells, G.F. et al. Genome-wide association study identifies 12 new susceptibility loci for primary biliary cirrhosis. Nat. Genet. 43, 329–332 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  43. 43

    Gestermann, N. et al. STAT4 is a confirmed genetic risk factor for Sjogren's syndrome and could be involved in type 1 interferon pathway signaling. Genes Immun. 11, 432–438 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  44. 44

    Watford, W.T. et al. Signaling by IL-12 and IL-23 and the immunoregulatory roles of STAT4. Immunol. Rev. 202, 139–156 (2004).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  45. 45

    Xu, M. et al. Regulation of antitumor immune responses by the IL-12 family cytokines, IL-12, IL-23, and IL-27. Clin. Dev. Immunol. 2010, 832454 (2010).

    PubMed  PubMed Central  Google Scholar 

  46. 46

    Hirschfield, G.M. et al. Primary biliary cirrhosis associated with HLA, IL12A, and IL12RB2 variants. N. Engl. J. Med. 360, 2544–2555 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  47. 47

    Hunt, K.A. et al. Newly identified genetic risk variants for celiac disease related to the immune response. Nat. Genet. 40, 395–402 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  48. 48

    Lessard, C.J. et al. Identification of IRF8, TMEM39A, and IKZF3-ZPBP2 as susceptibility loci for systemic lupus erythematosus in a large-scale multiracial replication study. Am. J. Hum. Genet. 90, 648–660 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  49. 49

    Gottenberg, J.E. et al. Activation of IFN pathways and plasmacytoid dendritic cell recruitment in target organs of primary Sjögren's syndrome. Proc. Natl. Acad. Sci. USA 103, 2770–2775 (2006).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  50. 50

    Pérez, P. et al. Gene expression and chromosomal location for susceptibility to Sjögren's syndrome. J. Autoimmun. 33, 99–108 (2009).

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  51. 51

    Cornall, R.J. & Goodnow, C.C. B cell antigen receptor signalling in the balance of tolerance and immunity. Novartis Found. Symp. 215, 21–30 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. 52

    Nemazee, D. & Weigert, M. Revising B cell receptors. J. Exp. Med. 191, 1813–1817 (2000).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  53. 53

    Hom, G. et al. Association of systemic lupus erythematosus with C8orf13-BLK and ITGAM-ITGAX. N. Engl. J. Med. 358, 900–909 (2008).

    CAS  Article  Google Scholar 

  54. 54

    Simpfendorfer, K.R. et al. The autoimmunity-associated BLK haplotype exhibits cis-regulatory effects on mRNA and protein expression that are prominently observed in B cells early in development. Hum. Mol. Genet. 21, 3918–3925 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  55. 55

    Sawcer, S. et al. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis. Nature 476, 214–219 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  56. 56

    Hansen, A., Lipsky, P.E. & Dorner, T. B cells in Sjögren's syndrome: indications for disturbed selection and differentiation in ectopic lymphoid tissue. Arthritis Res. Ther. 9, 218 (2007).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  57. 57

    Ma, C.S. et al. Early commitment of naive human CD4+ T cells to the T follicular helper (TFH) cell lineage is induced by IL-12. Immunol. Cell Biol. 87, 590–600 (2009).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  58. 58

    Adrianto, I. et al. Association of a functional variant downstream of TNFAIP3 with systemic lupus erythematosus. Nat. Genet. 43, 253–258 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  59. 59

    Uddin, M., Sturge, M., Rahman, P. & Woods, M.O. Autosome-wide copy number variation association analysis for rheumatoid arthritis using the WTCCC high-density SNP genotype data. J. Rheumatol. 38, 797–801 (2011).

    PubMed  Article  PubMed Central  Google Scholar 

  60. 60

    Allanore, Y. et al. Genome-wide scan identifies TNIP1, PSORS1C1, and RHOB as novel risk loci for systemic sclerosis. PLoS Genet. 7, e1002091 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  61. 61

    Nair, R.P. et al. Genome-wide scan reveals association of psoriasis with IL-23 and NF-κB pathways. Nat. Genet. 41, 199–204 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  62. 62

    Adrianto, I. et al. Two independent functional risk haplotypes in TNIP1 are associated with systemic lupus erythematosus. Arthritis Rheum. 64, 3695–3705 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  63. 63

    Gateva, V. et al. A large-scale replication study identifies TNIP1, PRDM1, JAZF1, UHRF1BP1 and IL10 as risk loci for systemic lupus erythematosus. Nat. Genet. 41, 1228–1233 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  64. 64

    Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. 65

    Cortes, A. & Brown, M.A. Promise and pitfalls of the Immunochip. Arthritis Res. Ther. 13, 101 (2011).

    PubMed  PubMed Central  Article  Google Scholar 

  66. 66

    Price, A.L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  67. 67

    McKeigue, P.M., Carpenter, J.R., Parra, E.J. & Shriver, M.D. Estimation of admixture and detection of linkage in admixed populations by a Bayesian approach: application to African-American populations. Ann. Hum. Genet. 64, 171–186 (2000).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  68. 68

    Halder, I., Shriver, M., Thomas, M., Fernandez, J.R. & Frudakis, T. A panel of ancestry informative markers for estimating individual biogeographical ancestry and admixture from four continents: utility and applications. Hum. Mutat. 29, 648–658 (2008).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  69. 69

    Willer, C.J., Li, Y. & Abecasis, G.R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  70. 70

    Cochran, W.G. The combination of estimates from different experiments. Biometrics 10, 101–129 (1954).

    Article  Google Scholar 

  71. 71

    Higgins, J.P., Thompson, S.G., Deeks, J.J. & Altman, D.G. Measuring inconsistency in meta-analyses. Br. Med. J. 327, 557–560 (2003).

    Article  Google Scholar 

  72. 72

    Barrett, J.C., Fry, B., Maller, J. & Daly, M.J. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263–265 (2005).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  73. 73

    Pruim, R.J. et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics 26, 2336–2337 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  74. 74

    Frazer, K.A. et al. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851–861 (2007).

    CAS  Article  Google Scholar 

  75. 75

    Howie, B.N., Donnelly, P. & Marchini, J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 5, e1000529 (2009).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  76. 76

    Via, M., Gignoux, C. & Burchard, E.G. The 1000 Genomes Project: new opportunities for research and social challenges. Genome Med. 2, 3 (2010).

    PubMed  PubMed Central  Article  Google Scholar 

  77. 77

    Zheng, X. et al. HIBAG-HLA genotype imputation with attribute bagging. Pharmacogenomics J. published online, doi:10.1038/tpj.2013.18 (28 May 2013).10.1038/tpj.2013.18

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  78. 78

    Barbosa-Morais, N.L. et al. A re-annotation pipeline for Illumina BeadArrays: improving the interpretation of gene expression data. Nucleic Acids Res. 38, e17 (2010).

    Article  CAS  Google Scholar 

  79. 79

    Irizarry, R.A. et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4, 249–264 (2003).

    PubMed  PubMed Central  Article  Google Scholar 

  80. 80

    Johnson, W.E., Li, C. & Rabinovic, A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8, 118–127 (2007).

    Article  Google Scholar 

  81. 81

    Shabalin, A.A. Matrix eQTL: ultra fast eQTL analysis via large matrix operations. Bioinformatics 28, 1353–1358 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  82. 82

    Dozmorov, M.G., Cara, L.R., Giles, C.B. & Wren, J.D. GenomeRunner: automating genome exploration. Bioinformatics 28, 419–420 (2012).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  83. 83

    Fujita, P.A. et al. The UCSC Genome Browser database: update 2011. Nucleic Acids Res. 39, D876–D882 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  84. 84

    Quinlan, A.R. & Hall, I.M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

Download references

Acknowledgements

We are grateful to all the individuals with Sjögren's syndrome and those serving as healthy controls who participated in this study. We thank the following individuals for their help in the collection and ascertainment of the samples used in this study: E. Rothrock, J. Harris, S. Johnson, S. Cioli, N. Weber, D. Williams, W. Daniels, C. Pritchett-Frazee, K. Crouch, L. Battiest, J. Rodgers, J. Robertson, T. Nguyen, A. Crosbie, E. James, C. Meyer, A. McElroy, E. Emamian, J. Ermer, K. Rohlf, J. Leon, A. Petersen, D. Hartle, J. Novizke, W. Ortman, C. Espy, B. Cobb, G. Kristjansdottir, M. Eidsheim, J. Benessiano, Centre de Ressources Biologiques, Hôpital Bichat, Paris, and the SNP&SEQ Technology Platform, Uppsala, Sweden. We also thank S. Glenn and J. Ning for their ongoing assistance in developing and maintaining the computational infrastructure used to perform this study.

We thank the following funding agencies for their support: this publication was made possible by grants P50 AR0608040 (K.L.S., C.J.L., R.H.S. and A.D.F.), 5R01 DE015223 (K.L.S. and J.B.H.), 5RC2 AR058959 (P.M.G.), 5P01 AR049084-10 (J.B.H.), 5P30 AR053483 (J.A.J. and J.M.G.), 5U19 AI082714 (K.L.S., J.A.J. and C.J.L.), 1R01 DE018209-02 (K.L.S. and J.B.H.), 5R01 DE018209 (K.L.S.), 8P20 GM103456 (P.M.G., C.J.L., J.D.W. and I.A.), P20 GM103636 (M.G.D. and J.D.W.), 5R37 AI024717-25 (J.B.H.), 5P01 AI083194-03 (K.L.S. and J.B.H.), 7S10 RR027190-02 (J.B.H.), 1U01 AI101934 (J.A.J. and J.M.G.), 1RC1 AR058554 (J.A.J. and J.M.G.) and 5P30 GM103510 (J.A.J. and J.M.G.) from the NIH. The contents are the sole responsibility of the authors and do not necessarily represent the official views of the NIH. Additional funding was obtained from Intramural Research Program of the National Institute of Dental and Craniofacial Research (G.G.I.), US Department of Veterans Affairs IMMA 9 (J.B.H.), US Department of Defense PR094002 (J.B.H.), American College of Rheumatology Research and Education Foundation/Abbott Health Professional Graduate Student Preceptorship Award 2009 (C.J.L. and K.L.S.), Oklahoma Medical Research Foundation (C.J.L. and K.L.S.), Sjögren's Syndrome Foundation (K.L.S.), Phileona Foundation (K.L.S.), the French ministry of health (PHRC 2006-AOM06133) and the French ministry of research (ANR-2010-BLAN-1133) (X.M. and C.M.-R.), The Strategic Research Program at Helse Bergen, Western Norway Regional Health Authority (L.G.G., J.G.B. and R.J.), The Broegelmann Foundation (J.G.B. and R.J.), Norwegian Foundation for Health and Rehabilitation (E.H.), KFO 250 TP03, WI 1031/6-1 (T.W.), KFO 250, Z1 (T.W.), Medical Research Council, UK G0800629 (W.-F.N. and S.B.), Northumberland, Tyne and Wear Comprehensive Local Research Network (CLRN) (W.-F.N.), The Swedish Research Council (M.W.-H. and L. Rönnblom), The King Gustaf the V-th 80-year Foundation (M.W.-H.), Knut and Alice Wallenberg Foundation (L. Rönnblom) and The Swedish Rheumatism Association (M.W.-H., G.N., L. Rönnblom and P.E.). This study made use of genotypes available through dbGAP, with acknowledgments provided in the Supplementary Note.

Author information

Affiliations

Authors

Consortia

Contributions

C.J.L., K.M.G., J.A.K., C.G.M., J.B.H. and K.L.S. were responsible for the study design. C.J.L., J.A.I., A.R., K.M.G., C.M.-R., S.B., S.L., J.G.B., L.G.G., E.H., J.M.G., D.S.C.G., M.E.G., A.N.M.N.-H., K.P., J.S.M.-M., A.D.F., M.-L.E., J.A.L., J.C., R.G., K.S.H., G.D.H., M.T.B., A.J.W.H., P.J.H., D.M.L., L. Radfar, M.D.R., D.U.S., T.J.V., P.M.G., J.A.J., R.O., M.W.-H., M.K., H.J., G.G.I., T.W., R.J., M.R., G.N., P.E., W.-F.N., X.M., J.-M.A., L. Rönnblom, N.L.R., B.M.S., R.H.S., J.B.H. and K.L.S. assisted in the collection and characterization of the Sjögren's syndrome cases and healthy controls. K.M.K., A.J.A. and P.M.G. performed the genotyping. C.J.L., H.L., I.A. and J.A.I. performed all analyses and imputation under the guidance of C.G.M. and K.L.S. M.G.D. and J.D.W. performed the enrichment analysis. C.J.L., H.L., I.A., J.A.I., J.A.K., C.G.M. and K.L.S. prepared the manuscript, and all authors approved the final draft.

Corresponding author

Correspondence to Kathy L Sivils.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Further details appear in the Supplementary Note.

Supplementary information

Supplementary Text and Figures

Supplementary Note, Supplementary Figures 1–31 and Supplementary Tables 1–16 (PDF 15872 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Lessard, C., Li, H., Adrianto, I. et al. Variants at multiple loci implicated in both innate and adaptive immune responses are associated with Sjögren's syndrome. Nat Genet 45, 1284–1292 (2013). https://doi.org/10.1038/ng.2792

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing