Genome-Wide Joint Meta-Analysis of SNP and SNP-by-Smoking Interaction Identifies Novel Loci for Pulmonary Function

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Genome-wide association studies have identified numerous genetic loci for spirometic measures of pulmonary function, forced expiratory volume in one second (FEV₁), and its ratio to forced vital capacity (FEV₁/FVC). Given that cigarette smoking adversely affects pulmonary function, we conducted genome-wide joint meta-analyses (JMA) of single nucleotide polymorphism (SNP) and SNP-by-smoking (ever-smoking or pack-years) associations on FEV₁ and FEV₁/FVC across 19 studies (total N = 50,047). We identified three novel loci not previously associated with pulmonary function. SNPs in or near DNER (smallest P_JMA =5.00×10⁻¹¹), HLA-DQB1 and HLA-DQA2 (smallest P_JMA =4.35×10⁻⁹), and KCNJ2 and SOX9 (smallest P_JMA =1.28×10⁻⁸) were associated with FEV₁/FVC or FEV₁ in meta-analysis models including SNP main effects, smoking main effects, and SNP-by-smoking (ever-smoking or pack-years) interaction. The HLA region has been widely implicated for autoimmune and lung phenotypes, unlike the other novel loci, which have not been widely implicated. We evaluated DNER, KCNJ2, and SOX9 and found them to be expressed in human lung tissue. DNER and SOX9 further showed evidence of differential expression in human airway epithelium in smokers compared to non-smokers. Our findings demonstrated that joint testing of SNP and SNP-by-environment interaction identified novel loci associated with complex traits that are missed when considering only the genetic main effects.

Vyšlo v časopise: Genome-Wide Joint Meta-Analysis of SNP and SNP-by-Smoking Interaction Identifies Novel Loci for Pulmonary Function. PLoS Genet 8(12): e32767. doi:10.1371/journal.pgen.1003098
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1003098

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1. HoleDJ, WattGC, Davey-SmithG, HartCL, GillisCR, et al. (1996) Impaired lung function and mortality risk in men and women: findings from the Renfrew and Paisley prospective population study. BMJ 313: 711–716.

2. SchunemannHJ, DornJ, GrantBJ, WinkelsteinWJr, TrevisanM (2000) Pulmonary function is a long-term predictor of mortality in the general population: 29-year follow-up of the Buffalo Health Study. Chest 118: 656–664.

3. MyintPK, LubenRN, SurteesPG, WainwrightNW, WelchAA, et al. (2005) Respiratory function and self-reported functional health: EPIC-Norfolk population study. Eur Respir J 26: 494–502.

4. RedlineS, TishlerPV, LewitterFI, TagerIB, MunozA, et al. (1987) Assessment of genetic and nongenetic influences on pulmonary function. A twin study. Am Rev Respir Dis 135: 217–222.

5. HubertHB, FabsitzRR, FeinleibM, GwinnC (1982) Genetic and environmental influences on pulmonary function in adult twins. Am Rev Respir Dis 125: 409–415.

6. WilkJB, ChenTH, GottliebDJ, WalterRE, NagleMW, et al. (2009) A genome-wide association study of pulmonary function measures in the Framingham Heart Study. PLoS Genet 5: e1000429 doi:10.1371/journal.pgen.1000429.

7. PillaiSG, GeD, ZhuG, KongX, ShiannaKV, et al. (2009) A genome-wide association study in chronic obstructive pulmonary disease (COPD): identification of two major susceptibility loci. PLoS Genet 5: e1000421 doi:10.1371/journal.pgen.1000421.

8. HancockDB, EijgelsheimM, WilkJB, GharibSA, LoehrLR, et al. (2010) Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function. Nat Genet 42: 45–52.

9. RepapiE, SayersI, WainLV, BurtonPR, JohnsonT, et al. (2010) Genome-wide association study identifies five loci associated with lung function. Nat Genet 42: 36–44.

10. Soler ArtigasM, LothDW, WainLV, GharibSA, ObeidatM, et al. (2011) Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function. Nat Genet 43: 1082–1090.

11. BeatyTH, RuczinskiI, MurrayJC, MarazitaML, MungerRG, et al. (2011) Evidence for gene-environment interaction in a genome wide study of nonsyndromic cleft palate. Genet Epidemiol 35: 469–478.

12. LiuY, XuH, ChenS, ChenX, ZhangZ, et al. (2011) Genome-wide interaction-based association analysis identified multiple new susceptibility Loci for common diseases. PLoS Genet 7: e1001338 doi:10.1371/journal.pgen.1001338.

13. EgeMJ, StrachanDP, CooksonWO, MoffattMF, GutI, et al. (2011) Gene-environment interaction for childhood asthma and exposure to farming in Central Europe. J Allergy Clin Immunol 127: 138–144, 144 e131–134.

14. ManningAK, HivertMF, ScottRA, GrimsbyJL, Bouatia-NajiN, et al. (2012) A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nat Genet 44: 659–669.

15. ManningAK, LaValleyM, LiuC-T, RiceK, AnP, et al. (2011) Meta-analysis of gene-environment interaction: joint estimation of SNP and SNPxEnvironment regression coefficients. Genet Epidemiol 35: 11–18.

16. AschardH, HancockDB, LondonSJ, KraftP (2010) Genome-wide meta-analysis of joint tests for genetic and gene-environment interaction effects. Hum Hered 70: 292–300.

17. HamzaTH, ChenH, Hill-BurnsEM, RhodesSL, MontimurroJ, et al. (2011) Genome-wide gene-environment study identifies glutamate receptor gene GRIN2A as a Parkinson's disease modifier gene via interaction with coffee. PLoS Genet 7: e1002237 doi:10.1371/journal.pgen.1002237.

18. (2010). How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease: A Report of the Surgeon General. Atlanta (GA).

19. Lango AllenH, EstradaK, LettreG, BerndtSI, WeedonMN, et al. (2010) Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature 467: 832–838.

20. WenW, ChoYS, ZhengW, DorajooR, KatoN, et al. (2012) Meta-analysis identifies common variants associated with body mass index in east Asians. Nat Genet 44: 307–311.

21. CornelisMC, Tchetgen TchetgenEJ, LiangL, QiL, ChatterjeeN, et al. (2012) Gene-environment interactions in genome-wide association studies: a comparative study of tests applied to empirical studies of type 2 diabetes. Am J Epidemiol 175: 191–202.

22. ElksCE, PerryJR, SulemP, ChasmanDI, FranceschiniN, et al. (2010) Thirty new loci for age at menarche identified by a meta-analysis of genome-wide association studies. Nat Genet 42: 1077–1085.

23. LindgrenCM, HeidIM, RandallJC, LaminaC, SteinthorsdottirV, et al. (2009) Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution. PLoS Genet 5: e1000508 doi:10.1371/journal.pgen.1000508.

24. MoffattMF, GutIG, DemenaisF, StrachanDP, BouzigonE, et al. (2010) A large-scale, consortium-based genomewide association study of asthma. N Engl J Med 363: 1211–1221.

25. KohansalR, Martinez-CamblorP, AgustiA, BuistAS, ManninoDM, et al. (2009) The natural history of chronic airflow obstruction revisited: an analysis of the Framingham offspring cohort. Am J Respir Crit Care Med 180: 3–10.

26. LiuJZ, TozziF, WaterworthDM, PillaiSG, MugliaP, et al. (2010) Meta-analysis and imputation refines the association of 15q25 with smoking quantity. Nat Genet 42: 436–440.

27. EdgarR, DomrachevM, LashAE (2002) Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 30: 207–210.

28. BarrettT, TroupDB, WilhiteSE, LedouxP, EvangelistaC, et al. (2011) NCBI GEO: archive for functional genomics data sets–10 years on. Nucleic Acids Res 39: D1005–1010.

29. HarveyBG, HeguyA, LeopoldPL, CarolanBJ, FerrisB, et al. (2007) Modification of gene expression of the small airway epithelium in response to cigarette smoking. J Mol Med (Berl) 85: 39–53.

30. CaulfieldJJ, FernandezMH, SousaAR, LaneSJ, LeeTH, et al. (1999) Regulation of major histocompatibility complex class II antigens on human alveolar macrophages by granulocyte-macrophage colony-stimulating factor in the presence of glucocorticoids. Immunology 98: 104–110.

31. GlanvilleAR, TazelaarHD, TheodoreJ, ImotoE, RouseRV, et al. (1989) The distribution of MHC class I and II antigens on bronchial epithelium. Am Rev Respir Dis 139: 330–334.

32. DixonAL, LiangL, MoffattMF, ChenW, HeathS, et al. (2007) A genome-wide association study of global gene expression. Nat Genet 39: 1202–1207.

33. KraftP, YenYC, StramDO, MorrisonJ, GaudermanWJ (2007) Exploiting gene-environment interaction to detect genetic associations. Hum Hered 63: 111–119.

34. Gauderman WJ, Morrison JM (2006) QUANTO 1.1: A computer program for power and sample size calculations for genetic-epidemiology studies.

35. TohgoA, EirakuM, MiyazakiT, MiuraE, KawaguchiSY, et al. (2006) Impaired cerebellar functions in mutant mice lacking DNER. Mol Cell Neurosci 31: 326–333.

36. FukazawaN, YokoyamaS, EirakuM, KengakuM, MaedaN (2008) Receptor type protein tyrosine phosphatase zeta-pleiotrophin signaling controls endocytic trafficking of DNER that regulates neuritogenesis. Mol Cell Biol 28: 4494–4506.

37. ParkJR, JungJW, SeoMS, KangSK, LeeYS, et al. (2010) DNER modulates adipogenesis of human adipose tissue-derived mesenchymal stem cells via regulation of cell proliferation. Cell Prolif 43: 19–28.

38. KowalikL, HudspethAJ (2011) A search for factors specifying tonotopy implicates DNER in hair-cell development in the chick's cochlea. Dev Biol 354: 221–231.

39. GusehJS, BoresSA, StangerBZ, ZhouQ, AndersonWJ, et al. (2009) Notch signaling promotes airway mucous metaplasia and inhibits alveolar development. Development 136: 1751–1759.

40. TsaoPN, VasconcelosM, IzvolskyKI, QianJ, LuJ, et al. (2009) Notch signaling controls the balance of ciliated and secretory cell fates in developing airways. Development 136: 2297–2307.

41. TilleyAE, HarveyBG, HeguyA, HackettNR, WangR, et al. (2009) Down-regulation of the notch pathway in human airway epithelium in association with smoking and chronic obstructive pulmonary disease. Am J Respir Crit Care Med 179: 457–466.

42. RaychaudhuriS, SandorC, StahlEA, FreudenbergJ, LeeHS, et al. (2012) Five amino acids in three HLA proteins explain most of the association between MHC and seropositive rheumatoid arthritis. Nat Genet 44: 291–296.

43. ZhernakovaA, van DiemenCC, WijmengaC (2009) Detecting shared pathogenesis from the shared genetics of immune-related diseases. Nat Rev Genet 10: 43–55.

44. HirotaT, TakahashiA, KuboM, TsunodaT, TomitaK, et al. (2011) Genome-wide association study identifies three new susceptibility loci for adult asthma in the Japanese population. Nat Genet 43: 893–896.

45. TorgersonDG, AmplefordEJ, ChiuGY, GaudermanWJ, GignouxCR, et al. (2011) Meta-analysis of genome-wide association studies of asthma in ethnically diverse North American populations. Nat Genet 43: 887–892.

46. MahdiH, FisherBA, KallbergH, PlantD, MalmstromV, et al. (2009) Specific interaction between genotype, smoking and autoimmunity to citrullinated alpha-enolase in the etiology of rheumatoid arthritis. Nat Genet 41: 1319–1324.

47. GordonCT, TanTY, BenkoS, FitzpatrickD, LyonnetS, et al. (2009) Long-range regulation at the SOX9 locus in development and disease. J Med Genet 46: 649–656.

48. OonumaH, IwasawaK, IidaH, NagataT, ImutaH, et al. (2002) Inward rectifier K(+) current in human bronchial smooth muscle cells: inhibition with antisense oligonucleotides targeted to Kir2.1 mRNA. Am J Respir Cell Mol Biol 26: 371–379.

49. AndelfingerG, TapperAR, WelchRC, VanoyeCG, GeorgeALJr, et al. (2002) KCNJ2 mutation results in Andersen syndrome with sex-specific cardiac and skeletal muscle phenotypes. Am J Hum Genet 71: 663–668.

50. BiW, DengJM, ZhangZ, BehringerRR, de CrombruggheB (1999) Sox9 is required for cartilage formation. Nat Genet 22: 85–89.

51. LiuY, HoganBL (2002) Differential gene expression in the distal tip endoderm of the embryonic mouse lung. Gene Expr Patterns 2: 229–233.

52. BiW, HuangW, WhitworthDJ, DengJM, ZhangZ, et al. (2001) Haploinsufficiency of Sox9 results in defective cartilage primordia and premature skeletal mineralization. Proc Natl Acad Sci U S A 98: 6698–6703.

53. FosterJW, Dominguez-SteglichMA, GuioliS, KwokC, WellerPA, et al. (1994) Campomelic dysplasia and autosomal sex reversal caused by mutations in an SRY-related gene. Nature 372: 525–530.

54. HoustonCS, OpitzJM, SprangerJW, MacphersonRI, ReedMH, et al. (1983) The campomelic syndrome: review, report of 17 cases, and follow-up on the currently 17-year-old boy first reported by Maroteaux et al in 1971. Am J Med Genet 15: 3–28.

55. PsatyBM, O'DonnellCJ, GudnasonV, LunettaKL, FolsomAR, et al. (2009) Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium: Design of prospective meta-analyses of genome-wide association studies from 5 cohorts. Circ Cardiovasc Genet 2: 73–80.

56. HarrisTB, LaunerLJ, EiriksdottirG, KjartanssonO, JonssonPV, et al. (2007) Age, Gene/Environment Susceptibility-Reykjavik Study: multidisciplinary applied phenomics. Am J Epidemiol 165: 1076–1087.

57. The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC investigators. Am J Epidemiol 129: 687–702.

58. StrachanDP, RudnickaAR, PowerC, ShepherdP, FullerE, et al. (2007) Lifecourse influences on health among British adults: effects of region of residence in childhood and adulthood. Int J Epidemiol 36: 522–531.

59. HughesGH, CutterG, DonahueR, FriedmanGD, HulleyS, et al. (1987) Recruitment in the Coronary Artery Disease Risk Development in Young Adults (Cardia) Study. Control Clin Trials 8: 68S–73S.

60. FriedmanGD, CutterGR, DonahueRP, HughesGH, HulleySB, et al. (1988) CARDIA: study design, recruitment, and some characteristics of the examined subjects. J Clin Epidemiol 41: 1105–1116.

61. FriedLP, BorhaniNO, EnrightP, FurbergCD, GardinJM, et al. (1991) The Cardiovascular Health Study: design and rationale. Ann Epidemiol 1: 263–276.

62. BurneyPG, LuczynskaC, ChinnS, JarvisD (1994) The European Community Respiratory Health Survey. Eur Respir J 7: 954–960.

63. DayN, OakesS, LubenR, KhawKT, BinghamS, et al. (1999) EPIC-Norfolk: study design and characteristics of the cohort. European Prospective Investigation of Cancer. Br J Cancer 80 (Suppl 1) 95–103.

64. DawberTR, KannelWB (1966) The Framingham study. An epidemiological approach to coronary heart disease. Circulation 34: 553–555.

65. FeinleibM, KannelWB, GarrisonRJ, McNamaraPM, CastelliWP (1975) The Framingham Offspring Study. Design and preliminary data. Prev Med 4: 518–525.

66. YendeS, WatererGW, TolleyEA, NewmanAB, BauerDC, et al. (2006) Inflammatory markers are associated with ventilatory limitation and muscle dysfunction in obstructive lung disease in well functioning elderly subjects. Thorax 61: 10–16.

67. JarvelinMR, Hartikainen-SorriAL, RantakallioP (1993) Labour induction policy in hospitals of different levels of specialisation. Br J Obstet Gynaecol 100: 310–315.

68. RantakallioP (1969) Groups at risk in low birth weight infants and perinatal mortality. Acta Paediatr Scand 193 (Suppl 193): 191+.

69. BildDE, BluemkeDA, BurkeGL, DetranoR, Diez RouxAV, et al. (2002) Multi-ethnic study of atherosclerosis: objectives and design. Am J Epidemiol 156: 871–881.

70. RodriguezJ, JiangR, JohnsonWC, MacKenzieBA, SmithLJ, et al. (2010) The association of pipe and cigar use with cotinine levels, lung function, and airflow obstruction: a cross-sectional study. Ann Intern Med 152: 201–210.

71. HofmanA, van DuijnCM, FrancoOH, IkramMA, JanssenHL, et al. (2011) The Rotterdam Study: 2012 objectives and design update. Eur J Epidemiol 26: 657–686.

72. MartinBW, Ackermann-LiebrichU, LeuenbergerP, KunzliN, StutzEZ, et al. (1997) SAPALDIA: methods and participation in the cross-sectional part of the Swiss Study on Air Pollution and Lung Diseases in Adults. Soz Praventivmed 42: 67–84.

73. VolzkeH, AlteD, SchmidtCO, RadkeD, LorbeerR, et al. (2011) Cohort profile: the study of health in Pomerania. Int J Epidemiol 40: 294–307.

74. AndrewT, HartDJ, SniederH, de LangeM, SpectorTD, et al. (2001) Are twins and singletons comparable? A study of disease-related and lifestyle characteristics in adult women. Twin Res 4: 464–477.

75. StolkRP, RosmalenJG, PostmaDS, de BoerRA, NavisG, et al. (2008) Universal risk factors for multifactorial diseases: LifeLines: a three-generation population-based study. Eur J Epidemiol 23: 67–74.

76. The International HapMap Project. Nature 426: 789–796.

77. ShahaniAK (1970) A Saturated Experiment in Sequential Determination of Operating Conditions. Journal of the Royal Statistical Society Series D (The Statistician) 19: 403–408.

78. KooperbergC, LeblancM (2008) Increasing the power of identifying gene x gene interactions in genome-wide association studies. Genet Epidemiol 32: 255–263.

79. MurcrayCE, LewingerJP, ContiDV, ThomasDC, GaudermanWJ (2011) Sample size requirements to detect gene-environment interactions in genome-wide association studies. Genet Epidemiol 35: 201–210.

80. MurcrayCE, LewingerJP, GaudermanWJ (2009) Gene-environment interaction in genome-wide association studies. Am J Epidemiol 169: 219–226.

81. GaudermanWJ, ThomasDC, MurcrayCE, ContiD, LiD, et al. (2010) Efficient genome-wide association testing of gene-environment interaction in case-parent trios. Am J Epidemiol 172: 116–122.

82. WillerCJ, LiY, AbecasisGR (2010) METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26: 2190–2191.

83. Pe'erI, YelenskyR, AltshulerD, DalyMJ (2008) Estimation of the multiple testing burden for genomewide association studies of nearly all common variants. Genet Epidemiol 32: 381–385.

84. JohnsonAD, HandsakerRE, PulitSL, NizzariMM, O'DonnellCJ, et al. (2008) SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics 24: 2938–2939.

85. WadsworthSJ, NijmehHS, HallIP (2006) Glucocorticoids increase repair potential in a novel in vitro human airway epithelial wounding model. J Clin Immunol 26: 376–387.

86. SayersI, SwanC, HallIP (2006) The effect of beta2-adrenoceptor agonists on phospholipase C (beta1) signalling in human airway smooth muscle cells. Eur J Pharmacol 531: 9–12.