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A genome-wide association meta-analysis of self-reported allergy identifies shared and allergy-specific susceptibility loci

Nature Genetics volume 45, pages 907–911 (2013)Cite this article

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Abstract

Allergic disease is very common and carries substantial public-health burdens. We conducted a meta-analysis of genome-wide associations with self-reported cat, dust-mite and pollen allergies in 53,862 individuals. We used generalized estimating equations to model shared and allergy-specific genetic effects. We identified 16 shared susceptibility loci with association P < 5 × 10−8, including 8 loci previously associated with asthma, as well as 4p14 near TLR1, TLR6 and TLR10 (rs2101521, P = 5.3 × 10−21); 6p21.33 near HLA-C and MICA (rs9266772, P = 3.2 × 10−12); 5p13.1 near PTGER4 (rs7720838, P = 8.2 × 10−11); 2q33.1 in PLCL1 (rs10497813, P = 6.1 × 10−10), 3q28 in LPP (rs9860547, P = 1.2 × 10−9); 20q13.2 in NFATC2 (rs6021270, P = 6.9 × 10−9), 4q27 in ADAD1 (rs17388568, P = 3.9 × 10−8); and 14q21.1 near FOXA1 and TTC6 (rs1998359, P = 4.8 × 10−8). We identified one locus with substantial evidence of differences in effects across allergies at 6p21.32 in the class II human leukocyte antigen (HLA) region (rs17533090, P = 1.7 × 10−12), which was strongly associated with cat allergy. Our study sheds new light on the shared etiology of immune and autoimmune disease.

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Figure 1: Manhattan plot of meta-analysis results for shared effects.
Figure 2: Manhattan plot of meta-analysis results for interactions with allergen.
Figure 3: Marginal effect sizes and 95% confidence intervals for rs17533090 for cat, pollen and dust-mite allergy in the 23andMe and ALSPAC cohorts.

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References

  1. Arbes, S.J. Jr., Gergen, P.J., Elliott, L. & Zeldin, D.C. Prevalences of positive skin test responses to 10 common allergens in the US population: results from the third National Health and Nutrition Examination Survey. J. Allergy Clin. Immunol. 116, 377–383 (2005).

    Article  PubMed  Google Scholar 

  2. Strachan, D.P. Family size, infection, and atopy: the first decade of the hygiene hypthesis. Thorax 55 (suppl. 1), S2–S10 (2000).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Fagnani, C. et al. Heritability and shared genetic effects of asthma and hay fever: an Italian study of young twins. Twin Res. Hum. Genet. 11, 121–131 (2008).

    Article  PubMed  Google Scholar 

  4. Willemsen, G., van Beijsterveldt, T.C.E.M., van Baal, C.G.C.M., Postma, D. & Boomsma, D.I. Heritability of self-reported asthma and allergy: a study in adult Dutch twins, siblings and parents. Twin Res. Hum. Genet. 11, 132–142 (2008).

    Article  PubMed  Google Scholar 

  5. Vercelli, D. Discovering susceptibility genes for asthma and allergy. Nat. Rev. Immunol. 8, 169–182 (2008).

    Article  CAS  PubMed  Google Scholar 

  6. Himes, B.E. et al. Genome-wide association analysis identifies PDE4D as an asthma-susceptibility gene. Am. J. Hum. Genet. 84, 581–593 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Sleiman, P.M.A. et al. Variants of DENND1B associated with asthma in children. N. Engl. J. Med. 362, 36–44 (2010).

    Article  CAS  PubMed  Google Scholar 

  8. Moffatt, M.F. et al. A large-scale, consortium-based genomewide association study of asthma. N. Engl. J. Med. 363, 1211–1221 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Hirota, T. et al. Genome-wide association study identifies three new susceptibility loci for adult asthma in the Japanese population. Nat. Genet. 43, 893–896 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Torgerson, D.G. et al. Meta-analysis of genome-wide association studies of asthma in ethnically diverse North American populations. Nat. Genet. 43, 887–892 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Ferreira, M.A.R. et al. Identification of IL6R and chromosome 11q13.5 as risk loci for asthma. Lancet 378, 1006–1014 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Esparza-Gordillo, J. et al. A common variant on chromosome 11q13 is associated with atopic dermatitis. Nat. Genet. 41, 596–601 (2009).

    Article  CAS  PubMed  Google Scholar 

  13. Sun, L.D. et al. Genome-wide association study identifies two new susceptibility loci for atopic dermatitis in the Chinese Han population. Nat. Genet. 43, 690–694 (2011).

    Article  CAS  PubMed  Google Scholar 

  14. Paternoster, L. et al. Meta-analysis of genome-wide association studies identifies three new risk loci for atopic dermatitis. Nat. Genet. 44, 187–192 (2012).

    Article  CAS  Google Scholar 

  15. Andiappan, A.K. et al. Genome-wide association study for atopy and allergic rhinitis in a Singapore Chinese population. PLoS ONE 6, e19719 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Wan, Y.I. et al. A genome-wide association study to identify genetic determinants of atopy in subjects from the United Kingdom. J. Allergy Clin. Immunol. 127, 223–231 (2011).

    Article  CAS  PubMed  Google Scholar 

  17. Ramasamy, A. et al. A genome-wide meta-analysis of genetic variants associated with allergic rhinitis and grass sensitization and their interaction with birth order. J. Allergy Clin. Immunol. 128, 996–1005 (2011).

    Article  CAS  PubMed  Google Scholar 

  18. Eriksson, N. et al. Web-based, participant-driven studies yield novel genetic associations for common traits. PLoS Genet. 6, e1000993 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Fraser, A. et al. Cohort profile: the Avon Longitudinal Study of Parents and Children: ALSPAC mothers cohort. Int. J. Epidemiol. 42, 97–110 (2013).

    Article  PubMed  Google Scholar 

  20. Bønnelykke, K. et al. Meta-analysis of genome-wide association studies identifies ten loci influencing allergic sensitization. Nat. Genet. published online; doi:10.1038/ng.2694 (30 June 2013).10.1038/ng.2694

    PubMed  PubMed Central  Google Scholar 

  21. Zeller, T. et al. Genetics and beyond—the transcriptome of human monocytes and disease susceptibility. PLoS ONE 5, e10693 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Eder, W. et al. Toll-like receptor 2 as a major gene for asthma in children of European farmers. J. Allergy Clin. Immunol. 113, 482–488 (2004).

    Article  CAS  PubMed  Google Scholar 

  23. Tantisira, K. et al. Toll-like receptor 6 gene (TLR6): single-nucleotide polymorphism frequencies and preliminary association with the diagnosis of asthma. Genes Immun. 5, 343–346 (2004).

    Article  CAS  PubMed  Google Scholar 

  24. Kormann, M.S. et al. Toll-like receptor heterodimer variants protect from childhood asthma. J. Allergy Clin. Immunol. 122, 86–92 (2008).

    Article  CAS  PubMed  Google Scholar 

  25. Kurz, T. et al. Fine mapping and positional candidate studies on chromosome 5p13 identify multiple asthma susceptibility loci. J. Allergy Clin. Immunol. 118, 396–402 (2006).

    Article  CAS  PubMed  Google Scholar 

  26. Evans, D.M. et al. Interaction between ERAP1 and HLA-B27 in ankylosing spondylitis implicates peptide handling in the mechanism for HLA-B27 in disease susceptibility. Nat. Genet. 43, 761–767 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Libioulle, C. et al. Novel Crohn disease locus identified by genome-wide association maps to a gene desert on 5p13.1 and modulates expression of PTGER4. PLoS Genet. 3, e58 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Kabashima, K. et al. Prostaglandin E2–EP4 signaling initiates skin immune responses by promoting migration and maturation of Langerhans cells. Nat. Med. 9, 744–749 (2003).

    Article  CAS  PubMed  Google Scholar 

  29. Yao, C. et al. Prostaglandin E2–EP4 signaling promotes immune inflammation through Th1 cell differentiation and Th17 cell expansion. Nat. Med. 15, 633–640 (2009).

    Article  CAS  PubMed  Google Scholar 

  30. Lin, X. et al. Control of calcium signal propagation to the mitochondria by inositol 1,4,5-trisphosphate–binding proteins. J. Biol. Chem. 280, 12820–12832 (2005).

    Article  CAS  PubMed  Google Scholar 

  31. Franke, A. et al. Genome-wide meta-analysis increases to 71 the number of confirmed Crohn's disease susceptibility loci. Nat. Genet. 42, 1118–1125 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Dubois, P.C. et al. Multiple common variants for celiac disease influencing immune gene expression. Nat. Genet. 42, 295–302 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Jin, Y. et al. Variant of TYR and autoimmunity susceptibility loci in generalized vitiligo. N. Engl. J. Med. 362, 1686–1697 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Harris, M.B. et al. Transcriptional repression of Stat6-dependent interleukin-4–induced genes by BCL-6: specific regulation of Iɛ transcription and immunoglobulin E switching. Mol. Cell Biol. 19, 7264–7275 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Kusam, S., Toney, L.M., Sato, H. & Dent, A.L. Inhibition of Th2 differentiation and GATA-3 expression by BCL-6. J. Immunol. 170, 2435–2441 (2003).

    Article  CAS  PubMed  Google Scholar 

  37. Hermann-Kleiter, N. & Baier, G. NFAT pulls the strings during CD4+ T helper cell effector functions. Blood 115, 2989–2997 (2010).

    Article  CAS  PubMed  Google Scholar 

  38. Karwot, R. et al. Protective role of nuclear factor of activated T cells 2 in CD8+ long-lived memory T cells in an allergy model. J. Allergy Clin. Immunol. 121, 992–999 (2008).

    Article  CAS  PubMed  Google Scholar 

  39. Karwot, R., Ubel, C., Bopp, T., Schmitt, E. & Finotto, S. Increased immunosuppressive function of CD4+CD25+Foxp3+GITR+ T regulatory cells from NFATc2−/− mice controls allergen-induced experimental asthma. Immunobiology 217, 905–911 (2012).

    Article  CAS  PubMed  Google Scholar 

  40. Plagnol, V. et al. Genome-wide association analysis of autoantibody positivity in type 1 diabetes cases. PLoS Genet. 7, e1002216 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Anderson, C.A. et al. Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47. Nat. Genet. 43, 246–252 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Liao, W., Lin, J.-X., Wang, L., Li, P. & Leonard, W.J. Modulation of cytokine receptors by IL-2 broadly regulates differentiation into helper T cell lineages. Nat. Immunol. 12, 551–559 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Park, S.-W. et al. Distinct roles of FOXA2 and FOXA3 in allergic airway disease and asthma. Am. J. Respir. Crit. Care Med. 180, 603–610 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Wan, H. et al. Compensatory roles of Foxa1 and Foxa2 during lung morphogenesis. J. Biol. Chem. 280, 13809–13816 (2005).

    Article  CAS  PubMed  Google Scholar 

  45. Bauer, S. et al. Activation of NK cells and T cells by NKG2D, a receptor for stress-inducible MICA. Science 285, 727–729 (1999).

    Article  CAS  PubMed  Google Scholar 

  46. Martin, A.M. et al. Predisposition to abacavir hypersensitivity conferred by HLA-B*5701 and a haplotypic Hsp70-Hom variant. Proc. Natl. Acad. Sci. USA 101, 4180–4185 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Ferrell, P.B. Jr. & McLeod, H.L. Carbamazepine, HLA-B*1502 and risk of Stevens-Johnson syndrome and doxic epidermal necrolysis: US FDA recommendations. Pharmacogenomics 9, 1543–1546 (2008).

    Article  CAS  PubMed  Google Scholar 

  48. Strange, A. et al. A genome-wide association study identifies new psoriasis susceptibility loci and an interaction between HLA-C and ERAP1. Nat. Genet. 42, 985–990 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Pereyra, F. et al. The major genetic determinants of HIV-1 control affect HLA class I peptide presentation. Science 330, 1551–1557 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Young, R.P. et al. HLA-DR and HLA-DP genotypes and immunoglobulin E responses to common major allergens. Clin. Exp. Allergy 24, 431–439 (1994).

    Article  CAS  PubMed  Google Scholar 

  51. Howell, W.M. & Holgate, S.T. HLA genetics and allergic disease. Thorax 50, 815–818 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Romagnani, S. The Th1/Th2 paradigm. Immunol. Today 18, 263–266 (1997).

    Article  CAS  PubMed  Google Scholar 

  53. Smith, H.E. et al. Is structured allergy history sufficient when assessing patients with asthma and rhinitis in general practice? J. Allergy Clin. Immunol. 123, 646–650 (2009).

    Article  PubMed  Google Scholar 

  54. Schatz, M. & Zeiger, R.S. Asthma and allergy in pregnancy. Clin. Perinatol. 24, 407–432 (1997).

    Article  CAS  PubMed  Google Scholar 

  55. Falush, D., Stephens, M. & Pritchard, J. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164, 1567–1587 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Henn, B.M. et al. Cryptic distant relatives are common in both isolated and cosmopolitan genetic samples. PLoS ONE 7, e34267 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. 1000 Genomes Project Consortium. R.M. A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010).

  58. Browning, S.R. & Browning, B.L. Rapid and accurate haplotype phasing and missing data inference for whole genome association studies using localized haplotype clustering. Am. J. Hum. Genet. 81, 1084–1097 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Howie, B., Fuchsberger, C., Stephens, M., Marchini, J. & Abecasis, G.R. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat. Genet. 44, 955–959 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  62. Li, Y., Willer, C.J., Ding, J., Scheet, P. & Abecasis, G.R. MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet. Epidemiol. 34, 816–834 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Hinrichs, A.S. et al. The UCSC Genome Browser Database: update 2006. Nucleic Acids Res. 34, D590–D598 (2006).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Liang, K.Y. & Zeger, S. Longitudinal data analysis using generalized linear models. Biometrika 73, 13–22 (1986).

    Article  Google Scholar 

  66. Voorman, A., Rice, K. & Lumley, T. Fast computation for genome-wide association studies using boosted one-step statistics. Bioinformatics 28, 1818–1822 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Halekoh, U., Højsgaard, S. & Yan, J. The R package geepack for generalized estimating equations. J. Stat. Softw. 15, 1–11 (2006).

    Article  Google Scholar 

  68. Fisher, R.A. Statistical Methods for Research Workers (Oliver and Boyd, Edinburgh, 1932).

  69. Higgins, J.P.T. & Thompson, S.G. Quantifying heterogeneity in a meta-analysis. Stat. Med. 21, 1539–1558 (2002).

    PubMed  Google Scholar 

  70. Ward, L.D. & Kellis, M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 40, D930–D934 (2012).

    Article  CAS  PubMed  Google Scholar 

  71. ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

  72. Hindorff, L.A. et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl. Acad. Sci. USA 106, 9362–9367 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank the customers of 23andMe who answered surveys, as well as the employees of 23andMe, who together made this research possible. We also thank K. Nadeau for assistance in survey development and S. Nelson and R. Altman for reviewing surveys. This work was supported in part by the National Heart, Lung, and Blood Institute of the US National Institutes of Health under grant 1R43HL115873-01.

We are extremely grateful to all the families who took part in ALSPAC, to the midwives for their help in recruiting them and to the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The UK MRC (grant 74882), the Wellcome Trust (grant 092731) and the University of Bristol provide core support for ALSPAC.

This publication is the work of the authors, and D.A.H., N.J.T. and J.Y.T. will serve as guarantors for the contents of this paper.

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  1. Nicholas J Timpson and Joyce Y Tung: These authors contributed equally to this work.

Authors and Affiliations

  1. 23andMe, Inc., Mountain View, California, USA

    David A Hinds, Amy K Kiefer, Chuong B Do, Nicholas Eriksson, Joanna L Mountain, Uta Francke & Joyce Y Tung

  2. Medical Research Council (MRC) Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol, UK

    George McMahon, David M Evans, George Davey-Smith & Nicholas J Timpson

  3. School of Social and Community Medicine, University of Bristol, Bristol, UK

    Beate St Pourcain & Susan M Ring

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Contributions

D.A.H. and G.M. analyzed the data. A.K.K. designed the survey for 23andMe. G.M., D.M.E. and B.S.P. were part of the ALSPAC GWAS preparation team. S.M.R. was responsible for ALSPAC sample collection and preparation. C.B.D. and N.E. developed analytical tools. J.L.M., U.F. and G.D.-S. supervised the project. D.A.H., G.M., N.J.T. and J.Y.T. designed the study and wrote the manuscript.

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Correspondence to David A Hinds.

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Competing interests

D.A.H., A.K.K., C.B.D., N.E., J.L.M., U.F. and J.Y.T. are current or former employees of and own stock or stock options in 23andMe, Inc.

Supplementary information

Supplementary Figures and Tables

Supplementary Figures 1 and 2, Supplementary Tables 2–4, 6–9 and 11–15, and Supplementary Note (PDF 6440 kb)

Supplementary Table 1

Association test results in the 23andMe cohort, the ALSPAC cohort, and the meta-analysis (XLS 2165 kb)

Supplementary Table 5

SNP-SNP interaction test results (XLS 80 kb)

Supplementary Table 10

ENCODE project annotations of allergy loci using HaploReg (XLS 164 kb)

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Hinds, D., McMahon, G., Kiefer, A. et al. A genome-wide association meta-analysis of self-reported allergy identifies shared and allergy-specific susceptibility loci. Nat Genet 45, 907–911 (2013). https://doi.org/10.1038/ng.2686

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