Nothing Special   »   [go: up one dir, main page]
Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Genetic association analyses implicate aberrant regulation of innate and adaptive immunity genes in the pathogenesis of systemic lupus erythematosus

Nature Genetics volume 47, pages 1457–1464 (2015)Cite this article

Subjects

Abstract

Systemic lupus erythematosus (SLE) is a genetically complex autoimmune disease characterized by loss of immune tolerance to nuclear and cell surface antigens. Previous genome-wide association studies (GWAS) had modest sample sizes, reducing their scope and reliability. Our study comprised 7,219 cases and 15,991 controls of European ancestry, constituting a new GWAS, a meta-analysis with a published GWAS and a replication study. We have mapped 43 susceptibility loci, including ten new associations. Assisted by dense genome coverage, imputation provided evidence for missense variants underpinning associations in eight genes. Other likely causal genes were established by examining associated alleles for cis-acting eQTL effects in a range of ex vivo immune cells. We found an over-representation (n = 16) of transcription factors among SLE susceptibility genes. This finding supports the view that aberrantly regulated gene expression networks in multiple cell types in both the innate and adaptive immune response contribute to the risk of developing SLE.

Access through your institution
Buy or subscribe

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Heat map of RTC scores for cis-acting gene expression in ex vivo cells.
Figure 2: Summary of the functional roles of likely causal genes in SLE and other autoimmune diseases.

Similar content being viewed by others

Accession codes

Accessions

Gene Expression Omnibus

References

  1. Deapen, D. et al. A revised estimate of twin concordance in systemic lupus erythematosus. Arthritis Rheum. 35, 311–318 (1992).

    Article  CAS  PubMed  Google Scholar 

  2. Alarcón-Segovia, D. et al. Familial aggregation of systemic lupus erythematosus, rheumatoid arthritis, and other autoimmune diseases in 1,177 lupus patients from the GLADEL cohort. Arthritis Rheum. 52, 1138–1147 (2005).

    Article  PubMed  Google Scholar 

  3. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  5. Yang, W. et al. Genome-wide association study in Asian populations identifies variants in ETS1 and WDFY4 associated with systemic lupus erythematosus. PLoS Genet. 6, e1000841 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Han, J.-W. et al. Genome-wide association study in a Chinese Han population identifies nine new susceptibility loci for systemic lupus erythematosus. Nat. Genet. 41, 1234–1237 (2009).

    Article  CAS  PubMed  Google Scholar 

  7. Graham, R.R. et al. Genetic variants near TNFAIP3 on 6q23 are associated with systemic lupus erythematosus. Nat. Genet. 40, 1059–1061 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Okada, Y. et al. A genome-wide association study identified AFF1 as a susceptibility locus for systemic lupus eyrthematosus in Japanese. PLoS Genet. 8, e1002455 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Cunninghame Graham, D.S. et al. Association of NCF2, IKZF1, IRF8, IFIH1, and TYK2 with systemic lupus erythematosus. PLoS Genet. 7, e1002341 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Hirschhorn, J.N. & Daly, M.J. Genome-wide association studies for common diseases and complex traits. Nat. Rev. Genet. 6, 95–108 (2005).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  13. Devlin, B. & Roeder, K. Genomic control for association studies. Biometrics 55, 997–1004 (1999).

    Article  CAS  PubMed  Google Scholar 

  14. Price, A.L., Zaitlen, N.A., Reich, D. & Patterson, N. New approaches to population stratification in genome-wide association studies. Nat. Rev. Genet. 11, 459–463 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. de Bakker, P.I.W. et al. Practical aspects of imputation-driven meta-analysis of genome-wide association studies. Hum. Mol. Genet. 17, R122–R128 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Lawrence, J.S., Martins, C.L. & Drake, G.L. A family survey of lupus erythematosus. 1. Heritability. J. Rheumatol. 14, 913–921 (1987).

    CAS  PubMed  Google Scholar 

  17. So, H.-C., Gui, A.H.S., Cherny, S.S. & Sham, P.C. Evaluating the heritability explained by known susceptibility variants: a survey of ten complex diseases. Genet. Epidemiol. 35, 310–317 (2011).

    Article  PubMed  Google Scholar 

  18. 1000 Genomes Project Consortium. An integrated map of genetic variation from 1,092 human genomes. Nature 491, 56–65 (2012).

  19. Knight, J., Barnes, M.R., Breen, G. & Weale, M.E. Using functional annotation for the empirical determination of Bayes Factors for genome-wide association study analysis. PLoS ONE 6, e14808 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Morris, D.L. et al. Unraveling multiple MHC gene associations with systemic lupus erythematosus: model choice indicates a role for HLA alleles and non-HLA genes in Europeans. Am. J. Hum. Genet. 91, 778–793 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Dilthey, A.T., Moutsianas, L., Leslie, S. & McVean, G. HLA*IMP—an integrated framework for imputing classical HLA alleles from SNP genotypes. Bioinformatics 27, 968–972 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Fairfax, B.P. et al. Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression. Science 343, 1246949 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Fairfax, B.P. et al. Genetics of gene expression in primary immune cells identifies cell type–specific master regulators and roles of HLA alleles. Nat. Genet. 44, 502–510 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Raj, T. et al. Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes. Science 344, 519–523 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Nica, A.C. et al. Candidate causal regulatory effects by integration of expression QTLs with complex trait genetic associations. PLoS Genet. 6, e1000895 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Lewis, M.J. et al. UBE2L3 polymorphism amplifies NF-κB activation and promotes plasma cell development, linking linear ubiquitination to multiple autoimmune diseases. Am. J. Hum. Genet. 96, 221–234 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Noble, J.A. et al. A polymorphism in the TCF7 gene, C883A, is associated with type 1 diabetes. Diabetes 52, 1579–1582 (2003).

    Article  CAS  PubMed  Google Scholar 

  28. International Multiple Sclerosis Genetics Consortium (IMSGC). The expanding genetic overlap between multiple sclerosis and type I diabetes. Genes Immun. 10, 11–14 (2009).

  29. Zhang, Y. et al. Genes that escape X-inactivation in humans have high intraspecific variability in expression, are associated with mental impairment but are not slow evolving. Mol. Biol. Evol. 30, 2588–2601 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Scofield, R.H. et al. Klinefelter's syndrome (47,XXY) in male systemic lupus erythematosus patients: support for the notion of a gene-dose effect from the X chromosome. Arthritis Rheum. 58, 2511–2517 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Lanfranco, F., Kamischke, A., Zitzmann, M. & Nieschlag, E. Klinefelter's syndrome. Lancet 364, 273–283 (2004).

    Article  CAS  PubMed  Google Scholar 

  32. Namjou, B. et al. PTPN22 association in systemic lupus erythematosus (SLE) with respect to individual ancestry and clinical sub-phenotypes. PLoS ONE 8, e69404 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Karassa, F.B., Trikalinos, T.A. & Ioannidis, J.P.A. Role of the Fcγ receptor IIa polymorphism in susceptibility to systemic lupus erythematosus and lupus nephritis: a meta-analysis. Arthritis Rheum. 46, 1563–1571 (2002).

    Article  CAS  PubMed  Google Scholar 

  34. Floto, R.A. et al. Loss of function of a lupus-associated FcγRIIb polymorphism through exclusion from lipid rafts. Nat. Med. 11, 1056–1058 (2005).

    Article  CAS  PubMed  Google Scholar 

  35. Fanciulli, M. et al. FCGR3B copy number variation is associated with susceptibility to systemic, but not organ-specific, autoimmunity. Nat. Genet. 39, 721–723 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Manku, H. et al. Trans-ancestral studies fine map the SLE-susceptibility locus TNFSF4. PLoS Genet. 9, e1003554 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Jacob, C.O. et al. Lupus-associated causal mutation in neutrophil cytosolic factor 2 (NCF2) brings unique insights to the structure and function of NADPH oxidase. Proc. Natl. Acad. Sci. USA 109, E59–E67 (2012).

    Article  PubMed  Google Scholar 

  38. Sakurai, D. et al. Preferential binding to Elk-1 by SLE-associated IL10 risk allele upregulates IL10 expression. PLoS Genet. 9, e1003870 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Tchernev, V.T. et al. The Chediak-Higashi protein interacts with SNARE complex and signal transduction proteins. Mol. Med. 8, 56–64 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Molineros, J.E. et al. Admixture mapping in lupus identifies multiple functional variants within IFIH1 associated with apoptosis, inflammation, and autoantibody production. PLoS Genet. 9, e1003222 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Namjou, B. et al. High-density genotyping of STAT4 reveals multiple haplotypic associations with systemic lupus erythematosus in different racial groups. Arthritis Rheum. 60, 1085–1095 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Alexander, T. et al. Foxp3+ Helios+ regulatory T cells are expanded in active systemic lupus erythematosus. Ann. Rheum. Dis. 72, 1549–1558 (2013).

    Article  CAS  PubMed  Google Scholar 

  43. Oparina, N.Y. et al. PXK locus in systemic lupus erythematosus: fine mapping and functional analysis reveals novel susceptibility gene ABHD6. Ann. Rheum. Dis. 74, e14 (2015).

    Article  CAS  PubMed  Google Scholar 

  44. Vaughn, S.E. et al. Lupus risk variants in the PXK locus alter B-cell receptor internalization. Front. Genet. 5, 450 (2014).

    PubMed  Google Scholar 

  45. Castillejo-López, C. et al. Genetic and physical interaction of the B-cell systemic lupus erythematosus–associated genes BANK1 and BLK. Ann. Rheum. Dis. 71, 136–142 (2012).

    Article  CAS  PubMed  Google Scholar 

  46. Caster, D.J. et al. ABIN1 dysfunction as a genetic basis for lupus nephritis. J. Am. Soc. Nephrol. 24, 1743–1754 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Luo, X. et al. A functional variant in MicroRNA-146a promoter modulates its expression and confers disease risk for systemic lupus erythematosus. PLoS Genet. 7, e1002128 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Zhang, Y. et al. Two missense variants in UHRF1BP1 are independently associated with systemic lupus erythematosus in Hong Kong Chinese. Genes Immun. 12, 231–234 (2011).

    Article  CAS  PubMed  Google Scholar 

  49. Kim, S.J., Gregersen, P.K. & Diamond, B. Regulation of dendritic cell activation by microRNA let-7c and BLIMP1. J. Clin. Invest. 123, 823–833 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Zhou, X.J. et al. Genetic association of PRDM1-ATG5 intergenic region and autophagy with systemic lupus erythematosus in a Chinese population. Ann. Rheum. Dis. 70, 1330–1337 (2011).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Westra, H.-J. et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat. Genet. 45, 1238–1243 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Kottyan, L.C. et al. The IRF5-TNPO3 association with systemic lupus erythematosus (SLE) has two components that other autoimmune disorders variably share. Hum. Mol. Genet. 24, 582–596 (2015).

    Article  CAS  PubMed  Google Scholar 

  54. Guthridge, J.M. et al. Two functional lupus-associated BLK promoter variants control cell-type- and developmental-stage-specific transcription. Am. J. Hum. Genet. 94, 586–598 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Zhao, H. et al. An intronic variant associated with systemic lupus erythematosus changes the binding affinity of Yinyang1 to downregulate WDFY4. Genes Immun. 13, 536–542 (2012).

    Article  CAS  PubMed  Google Scholar 

  56. Heinig, M. et al. A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk. Nature 467, 460–464 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Crispín, J.C. et al. Expression of CD44 variant isoforms CD44v3 and CD44v6 is increased on T cells from patients with systemic lupus erythematosus and is correlated with disease activity. Arthritis Rheum. 62, 1431–1437 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Zhang, J. et al. Epistatic interaction between genetic variants in susceptibility gene ETS1 correlates with IL-17 levels in SLE patients. Ann. Hum. Genet. 77, 344–350 (2013).

    Article  CAS  PubMed  Google Scholar 

  59. Morris, E.E. et al. A GA microsatellite in the Fli1 promoter modulates gene expression and is associated with systemic lupus erythematosus patients without nephritis. Arthritis Res. Ther. 12, R212 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Mori, T. et al. Lnk/Sh2b3 controls the production and function of dendritic cells and regulates the induction of IFN-γ–producing T cells. J. Immunol. 193, 1728–1736 (2014).

    Article  CAS  PubMed  Google Scholar 

  61. Manjarrez-Orduño, N. et al. CSK regulatory polymorphism is associated with systemic lupus erythematosus and influences B-cell signaling and activation. Nat. Genet. 44, 1227–1230 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Bronson, P.G. et al. The rs4774 CIITA missense variant is associated with risk of systemic lupus erythematosus. Genes Immun. 12, 667–671 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Fujimoto, M. et al. Inadequate induction of suppressor of cytokine signaling-1 causes systemic autoimmune diseases. Int. Immunol. 16, 303–314 (2004).

    Article  CAS  PubMed  Google Scholar 

  64. Rhodes, B. et al. The rs1143679 (R77H) lupus associated variant of ITGAM (CD11b) impairs complement receptor 3 mediated functions in human monocytes. Ann. Rheum. Dis. 71, 2028–2034 (2012).

    Article  CAS  PubMed  Google Scholar 

  65. Chrabot, B.S. et al. Genetic variation near IRF8 is associated with serologic and cytokine profiles in systemic lupus erythematosus and multiple sclerosis. Genes Immun. 14, 471–478 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Sun, J., Matthias, G., Mihatsch, M.J., Georgopoulos, K. & Matthias, P. Lack of the transcriptional coactivator OBF-1 prevents the development of systemic lupus erythematosus–like phenotypes in Aiolos mutant mice. J. Immunol. 170, 1699–1706 (2003).

    Article  CAS  PubMed  Google Scholar 

  67. Shaw, M.H. et al. A natural mutation in the Tyk2 pseudokinase domain underlies altered susceptibility of B10.Q/J mice to infection and autoimmunity. Proc. Natl. Acad. Sci. USA 100, 11594–11599 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Kaufman, K.M. Fine mapping of Xq28: both MECP2 and IRAK1 contribute to risk for systemic lupus erythematosus in multiple ancestral groups. Ann. Rheum. Dis. 72, 437–444 (2013).

    Article  CAS  PubMed  Google Scholar 

  69. Freedman, M.L. et al. Assessing the impact of population stratification on genetic association studies. Nat. Genet. 36, 388–393 (2004).

    Article  CAS  PubMed  Google Scholar 

  70. Reich, D.E. & Goldstein, D.B. Detecting association in a case-control study while correcting for population stratification. Genet. Epidemiol. 20, 4–16 (2001).

    Article  CAS  PubMed  Google Scholar 

  71. Marchini, J., Howie, B., Myers, S., McVean, G. & Donnelly, P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat. Genet. 39, 906–913 (2007).

    Article  CAS  PubMed  Google Scholar 

  72. Marchini, J. & Howie, B. Genotype imputation for genome-wide association studies. Nat. Rev. Genet. 11, 499–511 (2010).

    Article  CAS  PubMed  Google Scholar 

  73. Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661–678 (2007).

  74. Delaneau, O., Howie, B., Cox, A.J., Zagury, J.-F. & Marchini, J. Haplotype estimation using sequencing reads. Am. J. Hum. Genet. 93, 687–696 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Gagliano, S.A., Barnes, M.R., Weale, M. & Knight, J. A Bayesian method to incorporate hundreds of functional characteristics with association evidence to improve variant prioritization. PLoS ONE 9, e98122 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Wakefield, J. Bayes factors for genome-wide association studies: comparison with P-values. Genet. Epidemiol. 33, 79–86 (2009).

    Article  PubMed  Google Scholar 

  77. Maller, J.B. et al. Bayesian refinement of association signals for 14 loci in 3 common diseases. Nat. Genet. 44, 1294–1301 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Jeffreys, H. Theory of Probability 3rd edn. (Oxford Univ. Press, 1961).

  79. Grundberg, E. et al. Mapping cis- and trans-regulatory effects across multiple tissues in twins. Nat. Genet. 44, 1084–1089 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

T.J.V., J.D.R. and M.E.A.-R. were awarded funding to carry out genotyping and analysis from the George Koukis Foundation and an Arthritis Research UK Special Strategic Award (19289). M.E.A.-R. received grants from the Instituto de Salud Carlos III (PS09/00129), co-financed by the FEDER funds of the European Union, the Consejería de Salud de Andalucía (PI0012) and the Swedish Research Council of Medicine, and from the European Science Foundation to the BIOLUPUS network. J.B. was funded by the George Koukis Foundation and the Arthritis Research UK Special Strategic Award. J.E.W. was funded by the Canadian Institutes of Health Research (94825). C.L.P. was funded by a Wellcome Trust grant (085492). P.T. is employed by the Biomedical Research Centre. L.C. was funded by the China Scholarship Council (201406380127). The research was funded and supported by the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy's and St. Thomas' National Health Service (NHS) Foundation Trust and King's College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the UK Department of Health.

HRS genetic data were obtained from the database of Genotypes and Phenotypes (dbGaP) under accession phs000187.v1.p1; the study is sponsored by the National Institute on Aging (grants U01AG009740, RC2AG036495 and RC4AG039029) and was conducted by the University of Michigan. The melanoma study data were obtained from dbGaP under accession phs000187.v1.p1. Research support to collect data and develop an application to support this project was provided by US National Institutes of Health (NIH) grants 3P50CA093459, 5P50CA097007, 5R01ES011740 and 5R01CA133996. Funding support for the Genes and Blood Clotting Study was provided through the US NIH/National Heart, Lung, and Blood Institute (NHLBI) (R37HL039693). The Genes and Blood Clotting Study is one of the Phase 3 studies that are part of the Gene-Environment Association Studies (GENEVA) under the Genes, Environment and Health Initiative (GEI). Assistance with genotype cleaning was provided by the GENEVA Coordinating Center (U01HG004446, US NIH). Funding support for DNA extraction and genotyping, which were performed at the Broad Institute, was provided by the US NIH/NHLBI (R37HL039693). Additional support was provided by the Howard Hughes Medical Institute. The data sets used for the analyses described in this manuscript were obtained from dbGaP under accession phs000304.v2.p1. CGEMS prostate cancer study data were obtained from dbGaP under accession phs000207.v1.p1. We thank Genentech, Inc., for providing the genotype data from their GWAS. We thank V. Anand and S. Ragan for their help in coordinating data collection. We thank T. Axelsson, B. Fürnrohr, S. Ragan and J. Kelly for their help with the replication study.

A large number of people contributed samples or clinical data to the GWAS. The following samples were obtained via the BIOLUPUS network coordinated by M.E.A.-R.: Belgium: B. Lawerys and F. Houssiau (Université Catholique de Louvain). Denmark: S. Jacobsen (University of Copenhagen), P. Junker and H. Laustrup (Odense University Hospital). Germany: T. Witte (Medizinische Hochschule Hannover). Greece: H. Moutsopoulos and E.K. Kapsogeorgou (National University of Athens). Hungary: E. Endreffy and L. Kovacs (Albert Szent-Györgyi Medical University). Iceland: K. Steinsson (Landspitali National University Hospital). Italy: A. Doria (University of Padova), P.L. Meroni (IRCCS Istituto Auxologico Italiano), R. Scorza (University of Milan), S. D'Alfonso (providing samples from Rome, Naples and Siena; Università del Piemonte Orientale). The Netherlands: M. Bijl and C. Kallenberg (University of Groningen). Portugal: C. Vasconcelos (Hospital Santo António, Porto), B. Martins Silva (University of Porto). Spain: J. Martín and E. Martín Rodríguez (Instituto de Parasitología y Biomedicina Lopez Neyra), A. Suárez (Hospital Universitario Central de Asturias), I. Rua Figueroa (Hospital Dr. Negrín, Gran Canaria), G. Pons-Estel (Hospital Clinic, Barcelona). From the GENLES collaboration: Argentina: B. Pons-Estel (Hospital Provincial de Rosario). Other contributors: Canada: P. Fortin, J. Wither, D. Gladman and M. Urowitz (Toronto Western Hospital, University Health Network), A. Clarke, S. Bernatsky, C. Pineau and J. Rauch (McGill University), T. Hudson (Ontario Institute for Cancer Research), J. Pope (University of Western Ontario), C. Peschken and C. Hitchon (University of Manitoba), J. Hanly (Dalhousie University), C.D. Smith (Ottawa Hospital), E. Rich and J.-L. Senécal (Centre Hospitalier de l'Université de Montréal), M. Zummer (Maisonneuve-Rosemont Hospital), G. Boire (Université de Sherbrooke), S. Barr (University of Calgary). Germany: M.-A. Lee-Kirsch (Technische Universität Dresden). The Netherlands: T. Huizinga (Leiden University Medical Center; Dutch and Polish samples). Spain: J. Cortés Hernández, J. Ordi Ros and J. Castro Marrero (Vall d'Hebron Research Institute). Turkey: S. Yavuz (Istanbul Bilim University, Avrupa Florence Nightingale Hospital). UK: C. Gordon (University of Birmingham), K. Vinen (King's College London), D. Isenberg (University College Hospital), L. Erwig (University of Aberdeen), D. D'Cruz (St. Thomas' Hospital, London), A.J. Rees (Medical Research Council/Kidney Research UK Glomerulonephritis Biobank), I. Bruce (University of Manchester). United States: A. Sawalha (University of Michigan; Turkish samples), L. Criswell (University of California, San Francisco).

For the replication study, samples were provided by J. Wither (Toronto Western Research Institute, University Health Network, Canada), E. Silverman (The Hospital for Sick Children and University of Toronto, Canada), P. Gaffney (Oklahoma Medical Research Foundation, USA), A.-C. Syvänen and L. Rönnblom and the Swedish SLE Network (Uppsala Universitet, Sweden), R. Voll, G. Schett and B. Fuernrohr (University of Erlangen-Nuremberg, Germany) and N. Costedoat-Chalumeau (AP-HP, Hôpital Cochin, Centre de Référence Maladies Auto-Immunes et Systémiques Rares, France; Université Paris Descartes–Sorbonne Paris Cité, France). Replication genotyping was performed by the SNP&SEQ Technology Platform in Uppsala, which is part of the Swedish National Genomics Infrastructure (NGI) hosted by the Science for Life Laboratory.

We thank T. Raj and P. De Jager for contributing gene expression data (CD4+ T cells and CD14+ or CD16+ monocytes). These gene expression data are deposited in the Gene Expression Omnibus under accession GSE56035.

Author information

Author notes

  1. James Bentham

    Present address: Present address: Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.,

  2. James Bentham and David L Morris: These authors contributed equally to this work.

Authors and Affiliations

  1. Division of Genetics and Molecular Medicine, King's College London, London, UK

    James Bentham, David L Morris, Deborah S Cunninghame Graham, Christopher L Pinder, Philip Tombleson, Lingyan Chen & Timothy J Vyse

  2. Genentech, Inc., South San Francisco, California, USA

    Timothy W Behrens & Robert R Graham

  3. Instituto de Parasitología y Biomedicina López Neyra, Consejo Superior de Investigaciones Científicas (CSIC), Granada, Spain

    Javier Martín

  4. Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK

    Benjamin P Fairfax & Julian C Knight

  5. Harvard Medical School, Boston, Massachusetts, USA

    Joseph Replogle

  6. Department of Medical Sciences, Science for Life Laboratory, Uppsala University, Uppsala, Sweden

    Ann-Christine Syvänen & Lars Rönnblom

  7. Toronto Western Research Institute (TWRI), University Health Network, Toronto, Ontario, Canada

    Joan E Wither

  8. Genetics and Genomic Medicine of Inflammation, Université de Montréal, Montreal, Quebec, Canada

    John D Rioux

  9. Montreal Heart Institute, Montreal, Quebec, Canada

    John D Rioux

  10. Centro de Genómica e Investigación Oncológica (GENYO), Pfizer–Universidad de Granada–Junta de Andalucía, Granada, Spain

    Marta E Alarcón-Riquelme

  11. Division of Immunology, Infection and Inflammatory Disease, King's College London, London, UK

    Timothy J Vyse

Authors
  1. James Bentham
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David L Morris
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Deborah S Cunninghame Graham
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Christopher L Pinder
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Philip Tombleson
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Timothy W Behrens
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Javier Martín
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Benjamin P Fairfax
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Julian C Knight
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Lingyan Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Joseph Replogle
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Ann-Christine Syvänen
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Lars Rönnblom
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Robert R Graham
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Joan E Wither
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. John D Rioux
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Marta E Alarcón-Riquelme
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Timothy J Vyse
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

T.J.V. supervised the study. M.E.A.-R., J.M., A.-C.S., L.R. and J.E.W. provided samples. J.B. preprocessed the genotype data and carried out quality control analysis for the GWAS data. D.L.M., P.T. and J.B. carried out statistical analysis of the GWAS data. D.L.M. and T.J.V. designed the replication chip. D.L.M., P.T. and J.B. carried out quality control analysis of the controls for the replication study. T.W.B. and R.R.G. provided data from an SLE GWAS that were used in the meta-analysis. D.L.M. carried out statistical analysis for the replication study. D.L.M. and J.B. carried out statistical analysis of the 1000 Genomes Project data. D.L.M., L.C., J.R., B.P.F. and J.C.K. carried out statistical analysis of the eQTL data. D.S.C.G. and C.L.P. coordinated sample collection and genotyping. D.L.M., J.B., D.S.C.G., J.D.R. and T.J.V. wrote the manuscript. All authors have read and contributed to the manuscript.

Corresponding author

Correspondence to Timothy J Vyse.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–16, Supplementary Tables 1–9 and Supplementary Note. (PDF 4208 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bentham, J., Morris, D., Cunninghame Graham, D. et al. Genetic association analyses implicate aberrant regulation of innate and adaptive immunity genes in the pathogenesis of systemic lupus erythematosus. Nat Genet 47, 1457–1464 (2015). https://doi.org/10.1038/ng.3434

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.3434

This article is cited by

Search

Advanced 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