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Genetic loci associated with chronic obstructive pulmonary disease overlap with loci for lung function and pulmonary fibrosis

Abstract

Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide1. We performed a genetic association study in 15,256 cases and 47,936 controls, with replication of select top results (P < 5 × 10−6) in 9,498 cases and 9,748 controls. In the combined meta-analysis, we identified 22 loci associated at genome-wide significance, including 13 new associations with COPD. Nine of these 13 loci have been associated with lung function in general population samples2,3,4,5,6,7, while 4 (EEFSEC, DSP, MTCL1, and SFTPD) are new. We noted two loci shared with pulmonary fibrosis8,9 (FAM13A and DSP) but that had opposite risk alleles for COPD. None of our loci overlapped with genome-wide associations for asthma, although one locus has been implicated in joint susceptibility to asthma and obesity10. We also identified genetic correlation between COPD and asthma. Our findings highlight new loci associated with COPD, demonstrate the importance of specific loci associated with lung function to COPD, and identify potential regions of genetic overlap between COPD and other respiratory diseases.

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Figure 1: Study design showing the cohorts used in each stage of the analysis.
Figure 2: Manhattan plot.
Figure 3: Regional association plots for newly associated loci.
Figure 4: Genetic correlation (from LD score regression) between COPD and other traits.

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References

  1. Vestbo, J. et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am. J. Respir. Crit. Care Med. 187, 347–365 (2013).

    Article  CAS  PubMed  Google Scholar 

  2. Hancock, D.B. et al. Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function. Nat. Genet. 42, 45–52 (2010).

    Article  CAS  PubMed  Google Scholar 

  3. Repapi, E. et al. Genome-wide association study identifies five loci associated with lung function. Nat. Genet. 42, 36–44 (2010).

    Article  CAS  PubMed  Google Scholar 

  4. Soler Artigas, M. et al. Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function. Nat. Genet. 43, 1082–1090 (2011).

    Article  CAS  PubMed  Google Scholar 

  5. Hancock, D.B. et al. Genome-wide joint meta-analysis of SNP and SNP-by-smoking interaction identifies novel loci for pulmonary function. PLoS Genet. 8, e1003098 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Soler Artigas, M. et al. Sixteen new lung function signals identified through 1000 Genomes Project reference panel imputation. Nat. Commun. 6, 8658 (2015).

    Article  CAS  PubMed  Google Scholar 

  7. Wain, L.V. et al. Novel insights into the genetics of smoking behaviour, lung function, and chronic obstructive pulmonary disease (UK BiLEVE): a genetic association study in UK Biobank. Lancet Respir. Med. 3, 769–781 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Fingerlin, T.E. et al. Genome-wide association study identifies multiple susceptibility loci for pulmonary fibrosis. Nat. Genet. 45, 613–620 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Fingerlin, T.E. et al. Genome-wide imputation study identifies novel HLA locus for pulmonary fibrosis and potential role for auto-immunity in fibrotic idiopathic interstitial pneumonia. BMC Genet. 17, 74 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. González, J.R. et al. A common 16p11.2 inversion underlies the joint susceptibility to asthma and obesity. Am. J. Hum. Genet. 94, 361–372 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Laurell, C.-B. & Eriksson, S. The electrophoretic α-1-globulin pattern of serum in α-1-antitrypsin deficiency. Scand. J. Clin. Lab. Invest. 15, 132–140 (1963).

    Article  CAS  Google Scholar 

  12. Silverman, E.K. et al. Genome-wide linkage analysis of severe, early-onset chronic obstructive pulmonary disease: airflow obstruction and chronic bronchitis phenotypes. Hum. Mol. Genet. 11, 623–632 (2002).

    Article  CAS  PubMed  Google Scholar 

  13. Cho, M.H. et al. Risk loci for chronic obstructive pulmonary disease: a genome-wide association study and meta-analysis. Lancet Respir. Med. 2, 214–225 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Silverman, E.K. et al. Opportunities and challenges in the genetics of COPD 2010: an International COPD Genetics Conference report. COPD 8, 121–135 (2011).

    Article  PubMed  Google Scholar 

  15. Mannino, D.M. & Buist, A.S. Global burden of COPD: risk factors, prevalence, and future trends. Lancet 370, 765–773 (2007).

    Article  PubMed  Google Scholar 

  16. Pillai, S.G. et al. A genome-wide association study in chronic obstructive pulmonary disease (COPD): identification of two major susceptibility loci. PLoS Genet. 5, e1000421 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Cho, M.H. et al. Variants in FAM13A are associated with chronic obstructive pulmonary disease. Nat. Genet. 42, 200–202 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Cho, M.H. et al. A genome-wide association study of COPD identifies a susceptibility locus on chromosome 19q13. Hum. Mol. Genet. 21, 947–957 (2012).

    Article  CAS  PubMed  Google Scholar 

  19. Hobbs, B.D. et al. Exome array analysis identifies a common variant in IL27 associated with chronic obstructive pulmonary disease. Am. J. Respir. Crit. Care Med. 194, 48–57 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Wilk, J.B. et al. A genome-wide association study of pulmonary function measures in the Framingham Heart Study. PLoS Genet. 5, e1000429 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Wilk, J.B. et al. Genome-wide association studies identify CHRNA5/3 and HTR4 in the development of airflow obstruction. Am. J. Respir. Crit. Care Med. 186, 622–632 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Hao, K. et al. Lung eQTLs to help reveal the molecular underpinnings of asthma. PLoS Genet. 8, e1003029 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Giambartolomei, C. et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet. 10, e1004383 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Vasioukhin, V., Bowers, E., Bauer, C., Degenstein, L. & Fuchs, E. Desmoplakin is essential in epidermal sheet formation. Nat. Cell Biol. 3, 1076–1085 (2001).

    Article  CAS  PubMed  Google Scholar 

  25. Sato, Y. et al. The novel PAR-1-binding protein MTCL1 has crucial roles in organizing microtubules in polarizing epithelial cells. J. Cell Sci. 126, 4671–4683 (2013).

    Article  CAS  PubMed  Google Scholar 

  26. Sato, Y. et al. MTCL1 crosslinks and stabilizes non-centrosomal microtubules on the Golgi membrane. Nat. Commun. 5, 5266 (2014).

    Article  CAS  PubMed  Google Scholar 

  27. Uhlén, M. et al. Tissue-based map of the human proteome. Science 347, 1260419 (2015).

    Article  CAS  PubMed  Google Scholar 

  28. 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).

    CAS  PubMed  Google Scholar 

  29. Ward, L.D. & Kellis, M. HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease. Nucleic Acids Res. 44, D877–D881 (2016).

    Article  CAS  PubMed  Google Scholar 

  30. Lei, Y. et al. The mitochondrial proteins NLRX1 and TUFM form a complex that regulates type I interferon and autophagy. Immunity 36, 933–946 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Lei, Y., Wen, H. & Ting, J.P. The NLR protein, NLRX1, and its partner, TUFM, reduce type I interferon, and enhance autophagy. Autophagy 9, 432–433 2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Kang, M.J. et al. Suppression of NLRX1 in chronic obstructive pulmonary disease. J. Clin. Invest. 125, 2458–2462 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Wert, S.E. et al. Increased metalloproteinase activity, oxidant production, and emphysema in surfactant protein D gene-inactivated mice. Proc. Natl. Acad. Sci. USA 97, 5972–5977 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Lomas, D.A. et al. Serum surfactant protein D is steroid sensitive and associated with exacerbations of COPD. Eur. Respir. J. 34, 95–102 (2009).

    Article  CAS  PubMed  Google Scholar 

  35. Foreman, M.G. et al. Polymorphisms in surfactant protein-D are associated with chronic obstructive pulmonary disease. Am. J. Respir. Cell Mol. Biol. 44, 316–322 (2011).

    Article  CAS  PubMed  Google Scholar 

  36. Mathai, S.K. et al. Desmoplakin variants are associated with idiopathic pulmonary fibrosis. Am. J. Respir. Crit. Care Med. 193, 1151–1160 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Pickrell, J.K. et al. Detection and interpretation of shared genetic influences on 42 human traits. Nat. Genet. 48, 709–717 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Washko, G.R. et al. Lung volumes and emphysema in smokers with interstitial lung abnormalities. N. Engl. J. Med. 364, 897–906 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Chilosi, M., Poletti, V. & Rossi, A. The pathogenesis of COPD and IPF: distinct horns of the same devil? Respir. Res. 13, 3 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Stanley, S.E. et al. Telomerase mutations in smokers with severe emphysema. J. Clin. Invest. 125, 563–570 (2015).

    Article  PubMed  Google Scholar 

  41. Soriano, J.B. et al. The proportional Venn diagram of obstructive lung disease: two approximations from the United States and the United Kingdom. Chest 124, 474–481 (2003).

    Article  PubMed  Google Scholar 

  42. Welter, D. et al. The NHGRI GWAS Catalog, a curated resource of SNP–trait associations. Nucleic Acids Res. 42, D1001–D1006 (2014).

    Article  CAS  PubMed  Google Scholar 

  43. 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 

  44. Thorgeirsson, T.E. et al. Sequence variants at CHRNB3CHRNA6 and CYP2A6 affect smoking behavior. Nat. Genet. 42, 448–453 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Tobacco and Genetics Consortium. Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nat. Genet. 42, 441–447 (2010).

  46. Finucane, H.K. et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet. 47, 1228–1235 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236–1241 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Stanley, S.E. et al. Loss-of-function mutations in the RNA biogenesis factor NAF1 predispose to pulmonary fibrosis–emphysema. Sci. Transl. Med. 8, 351ra107 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Coram, M.A. et al. Leveraging multi-ethnic evidence for mapping complex traits in minority populations: an empirical Bayes approach. Am. J. Hum. Genet. 96, 740–752 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Deloukas, P. et al. Large-scale association analysis identifies new risk loci for coronary artery disease. Nat. Genet. 45, 25–33 (2013).

    Article  CAS  PubMed  Google Scholar 

  51. Wood, A.R. et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat. Genet. 46, 1173–1186 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Locke, A.E. et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197–206 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Zheng, H.F. et al. Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture. Nature 526, 112–117 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Castaldi, P.J. et al. The association of genome-wide significant spirometric loci with chronic obstructive pulmonary disease susceptibility. Am. J. Respir. Cell Mol. Biol. 45, 1147–1153 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Winkler, T.W. et al. Quality control and conduct of genome-wide association meta-analyses. Nat. Protoc. 9, 1192–1212 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  56. 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 

  57. Yang, J., Lee, S.H., Goddard, M.E. & Visscher, P.M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76–82 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Yang, J. et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat. Genet. 44, 369–375 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Lamontagne, M. et al. Refining susceptibility loci of chronic obstructive pulmonary disease with lung eqtls. PLoS One 8, e70220 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Bossé, Y. et al. Molecular signature of smoking in human lung tissues. Cancer Res. 72, 3753–3763 (2012).

    Article  CAS  PubMed  Google Scholar 

  61. Lamontagne, M. et al. Genetic regulation of gene expression in the lung identifies CST3 and CD22 as potential causal genes for airflow obstruction. Thorax 69, 997–1004 (2014).

    Article  PubMed  Google Scholar 

  62. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S.L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. 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 

  64. Chang, C.C. et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2016).

  66. Hardin, M. et al. The clinical and genetic features of COPD–asthma overlap syndrome. Eur. Respir. J. 44, 341–350 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  Google Scholar 

  68. Morris, A.P. Transethnic meta-analysis of genomewide association studies. Genet. Epidemiol. 35, 809–822 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Kichaev, G. & Pasaniuc, B. Leveraging functional-annotation data in trans-ethnic fine-mapping studies. Am. J. Hum. Genet. 97, 260–271 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Lu, Q., Powles, R.L., Wang, Q., He, B.J. & Zhao, H. Integrative tissue-specific functional annotations in the human genome provide novel insights on many complex traits and improve signal prioritization in genome wide association studies. PLoS Genet. 12, e1005947 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Trynka, G. et al. Disentangling the effects of colocalizing genomic annotations to functionally prioritize non-coding variants within complex-trait loci. Am. J. Hum. Genet. 97, 139–152 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Slowikowski, K., Hu, X. & Raychaudhuri, S. SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci. Bioinformatics 30, 2496–2497 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Tasş an, M. et al. Selecting causal genes from genome-wide association studies via functionally coherent subnetworks. Nat. Methods 12, 154–159 (2015).

    Article  CAS  Google Scholar 

  74. International HapMap Consortium. The International HapMap Project. Nature 426, 789–796 (2003).

  75. Cho, M.H. et al. A genome-wide association study of emphysema and airway quantitative imaging phenotypes. Am. J. Respir. Crit. Care Med. 192, 559–569 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Zhang, K., Cui, S., Chang, S., Zhang, L. & Wang, J. i-GSEA4GWAS: a web server for identification of pathways/gene sets associated with traits by applying an improved gene set enrichment analysis to genome-wide association study. Nucleic Acids Res. 38, W90–W95 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Kanehisa, M. & Goto, S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27–30 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Gene Ontology Consortium. Gene ontology: tool for the unification of biology. Nat. Genet. 25, 25–29 (2000).

  79. Gene Ontology Consortium. Gene Ontology Consortium: going forward. Nucleic Acids Res. 43, D1049–D1056 (2015).

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Acknowledgements

Please refer to the Supplementary Note for full acknowledgments.

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Contributions

B.D.H. and M.H.C. contributed to the study concept and design, data analysis, statistical support, and manuscript writing. K.d.J., A.B.W., S.J.L., and D.P.S. contributed to the study concept and design and to data analysis. N.S. and M.S.A. contributed to the data analysis and statistical support. T.H.B. and J.E.H. contributed to the study concept and design and to statistical support. L.L. contributed to the data collection, data analysis, and statistical support. K.E.N. contributed to data collection and data analysis. J.D.C., B.M.P., N.L., R.T.-S., G.T.O., Y.T., R.G.B., S.I.R., P.B., A.G., P.G.W., D.A.M., D.A.S., and E.K.S. contributed to the study concept and design and to data collection. D.Q., T.A.F., M.L., Y.B., N.S., N.F., P.J.C., R.P.C., T.M.B., S.A.G., J.C.L., J.D., J.B.W., M.K.L., S.L., A.M., X.-Q.W., and E.J.A. contributed to the data analysis. L.V.W., I.P.H., P.D.P., D.S.P., W.M., M.D.T., and H.M.B. contributed to the study concept and design. S.R.H., M.O., J.V., P.A.D., W.J.K., Y.-M.O., S.S.R., D.S., A.A.L., G.G.B., B.H.S., A.G.U., E.R.B., D.A.L., J.-J.Y., D.K.K., I.H., P.S., and M.H. contributed to the data collection. All authors, including those whose initials are not listed above, contributed to the critical review and editing of the manuscript and approved the final version of the manuscript.

Corresponding author

Correspondence to Michael H Cho.

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Competing interests

I.P.H. has received grant support from Pfizer. P.J.C. has received research funding from GlaxoSmithKline. B.P. serves on the data and safety monitoring board (DSMB) of a clinical trial funded by the manufacturer and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. N.L. and R.T.-S. are shareholders and employees of GlaxoSmithKline. S.I.R. is a current employee and shareholder at AstraZeneca. He has served as a consultant, participated on advisory boards, and received honoraria for speaking or grant support from the American Board of Internal Medicine, Advantage Healthcare, Almirall, the American Thoracic Society, AstraZeneca, Baxter, Boehringer Ingelheim, Chiesi, ClearView Healthcare, the Cleveland Clinic, Complete Medical Group, CSL, Dailchi Sankyo, Decision Resources, Forest, Gerson Lehman, Grifols, GroupH, Guidepoint Global, Haymarket, Huron Consulting, Inthought, Johnson & Johnson, Methodist Health System–Dallas, NCI Consulting, Novartis, Pearl, Penn Technology, Pfizer, PlanningShop, PSL FirstWord, Qwessential, Takeda, Theron, and WebMD. W.T. reports fees to the Department, all outside the submitted work, from Pfizer, GSK, Chiesi, Roche Diagnostics/Ventana, Biotest, Merck Sharp Dohme, Novartis, Lilly Oncology, Boehringer Ingelheim, and grants from Dutch Asthma Fund. J.C.L. is currently an employee of GNS Healthcare. J.B.W. was employed by Pfizer during the time this research was performed. P.B. has received consulting and lecture fees from AstraZeneca, Boehringer Ingelheim, Chiesi, Novartis, and Teva. L.L. has performed consultancy for Boehringer Ingelheim and has received an AstraZeneca Scientific Award and travel support from Novartis, the European Respiratory Society, and the Belgian Respiratory Society. P.G.W. has consulted for Amgen, Sanofi, Novartis, Genentech/Roche, Boehringer Ingelheim, and Neostem and has had research grants from Pfizer and Genentech. D.L. received grant support, honoraria, and consultancy fees from GlaxoSmithKline for work on the ICGN and ECLIPSE studies and was a member of and chaired the GSK Respiratory Therapy Area Board (2009–2015). M.H. is a current employee of AstraZeneca. D.A.S. is serving on the scientific advisory boards of Apellis Pharmaceuticals and Pliant Therapeutics, and is the founder and owner of Eleven P15. The University of Groningen has received money for D.S.P. with regard to a grant for research from AstraZeneca, Chiesi, Genentec, GlaxoSmithKline, and Roche. Fees for consultancies were given to the University of Groningen by AstraZeneca, Boehringer Ingelheim, Chiesi, GlaxoSmithKline, Takeda, and TEVA. E.K.S. has received honoraria and consulting fees from Merck, grant support and consulting fees from GlaxoSmithKline, and honoraria and travel support from Novartis. M.H.C. has received grant support from GlaxoSmithKline.

Additional information

A list of members and affiliations appears in the Supplementary Note.

A list of members and affiliations appears in the Supplementary Note.

A list of members and affiliations appears in the Supplementary Note.

A list of members and affiliations appears in the Supplementary Note.

A list of members and affiliations appears in the Supplementary Note.

A list of members and affiliations appears in the Supplementary Note.

A list of members and affiliations appears in the Supplementary Note.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6, Supplementary Tables 1, 2, 4–7, 9–13 and 15–20, and Supplementary Note (PDF 8454 kb)

Supplementary Table 3

Full results table for all 79 variants submitted for testing in UK BiLEVE stage 2 analysis. (XLSX 63 kb)

Supplementary Table 8

Full results (P < 0.05 in meta-analysis) for lung expression quantitative trait locus (eQTL) analysis. (XLSX 24 kb)

Supplementary Table 14

Lookup of NHGRI-EBI GWAS Catalog asthma-associated trait genome-wide significant GWAS loci in our COPD association stage 1 meta-analysis results. (XLSX 13 kb)

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Hobbs, B., de Jong, K., Lamontagne, M. et al. Genetic loci associated with chronic obstructive pulmonary disease overlap with loci for lung function and pulmonary fibrosis. Nat Genet 49, 426–432 (2017). https://doi.org/10.1038/ng.3752

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