A Genome-Wide Association Study of a Biomarker of Nicotine Metabolism
Nicotine metabolism rate significantly varies between individuals and affects smoking behavior. Individuals with fast nicotine metabolism typically smoke more and thus have a greater risk for smoking-induced diseases. Further, the efficacy of smoking cessation pharmacotherapy is dependent on nicotine metabolism rate. Twin and family studies have shown that genes influence nicotine metabolism; however, only a minor fraction of variance in inter-individual differences in nicotine metabolism is accounted for by known reduced activity variants in CYP2A6, the main metabolic enzyme for nicotine. Here we utilized a biomarker of nicotine metabolism (nicotine metabolite ratio, NMR) in a genome-wide association study of three Finnish cohorts to identify novel genetic variants influencing nicotine metabolism rate. Our results enclose three independent novel signals in CYP2A6. The detected variants explain a strikingly large fraction of variance (up to 31%) in NMR in the study samples. A genetic risk score constructed using the independent signals predicts smoking quantity in two independent Finnish samples. Further, we enclose evidence for plausible epigenetic mechanisms influencing NMR. With the advent of other nicotine delivery devices than tobacco, such as e-cigarettes, the need to understand the long-term consequences and action mechanisms of nicotine and its metabolism are of high public health relevance.
Vyšlo v časopise:
A Genome-Wide Association Study of a Biomarker of Nicotine Metabolism. PLoS Genet 11(9): e32767. doi:10.1371/journal.pgen.1005498
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pgen.1005498
Souhrn
Nicotine metabolism rate significantly varies between individuals and affects smoking behavior. Individuals with fast nicotine metabolism typically smoke more and thus have a greater risk for smoking-induced diseases. Further, the efficacy of smoking cessation pharmacotherapy is dependent on nicotine metabolism rate. Twin and family studies have shown that genes influence nicotine metabolism; however, only a minor fraction of variance in inter-individual differences in nicotine metabolism is accounted for by known reduced activity variants in CYP2A6, the main metabolic enzyme for nicotine. Here we utilized a biomarker of nicotine metabolism (nicotine metabolite ratio, NMR) in a genome-wide association study of three Finnish cohorts to identify novel genetic variants influencing nicotine metabolism rate. Our results enclose three independent novel signals in CYP2A6. The detected variants explain a strikingly large fraction of variance (up to 31%) in NMR in the study samples. A genetic risk score constructed using the independent signals predicts smoking quantity in two independent Finnish samples. Further, we enclose evidence for plausible epigenetic mechanisms influencing NMR. With the advent of other nicotine delivery devices than tobacco, such as e-cigarettes, the need to understand the long-term consequences and action mechanisms of nicotine and its metabolism are of high public health relevance.
Zdroje
1. Moss HB, Chen CM, Yi HY. Measures of substance consumption among substance users, DSM-IV abusers, and those with DSM-IV dependence disorders in a nationally representative sample. J Stud Alcohol Drugs. 2012;73(5): 820–28. 22846246
2. Ross S, Peselow E. The neurobiology of addictive disorders. Clin Neuropharmacol. 2009;32(5): 269–76. 19834992
3. Dempsey D, Tutka P, Jacob P 3rd, Allen F, Schoedel K, Tyndale RF, et al. Nicotine metabolite ratio as an index of cytochrome P450 2A6 metabolic activity. Clin Pharmacol Ther. 2004;76(1): 64–72. 15229465
4. Strasser AA, Benowitz NL, Pinto AG, Tang KZ, Hecht SS, Carmella SG, et al. Nicotine metabolite ratio predicts smoking topography and carcinogen biomarker level. Cancer Epidemiol Biomarkers Prev. 2011;20(2): 234–38. doi: 10.1158/1055-9965.EPI-10-0674 21212060
5. Ray R, Tyndale RF, Lerman C. Nicotine dependence pharmacogenetics: role of genetic variation in nicotine-metabolizing enzymes. J Neurogenet. 2009;23(3): 252–61. doi: 10.1080/01677060802572887 19169923
6. Ho MK, Tyndale RF. Overview of the pharmacogenomics of cigarette smoking. Pharmacogenomics J. 2007;7(2): 81–98. 17224913
7. Benowitz NL. Pharmacology of nicotine: addiction, smoking-induced disease, and therapeutics. Annu Rev Pharmacol Toxicol. 2009;49: 57–71. doi: 10.1146/annurev.pharmtox.48.113006.094742 18834313
8. Grando SA. Connections of nicotine to cancer. Nat Rev Cancer. 2014;14(6): 419–29. doi: 10.1038/nrc3725 24827506
9. Hukkanen J, Jacob P 3rd, Benowitz NL. Metabolism and disposition kinetics of nicotine. Pharmacol Rev. 2005;57(1): 79–115. 15734728
10. Yamazaki H, Inoue K, Hashimoto M, Shimada T. Roles of CYP2A6 and CYP2B6 in nicotine C-oxidation by human liver microsomes. Arch Toxicol. 1999;73(2): 65–70. 10350185
11. Miksys S, Lerman C, Shields PG, Mash DC, Tyndale RF. Smoking, alcoholism and genetic polymorphisms alter CYP2B6 levels in human brain. Neuropharmacology. 2003;45(1): 122–32. 12814665
12. Garcia KL, Coen K, Miksys S, Lê AD, Tyndale RF. Effect of Brain CYP2B Inhibition on Brain Nicotine Levels and Nicotine Self-Administration. Neuropsychopharmacology. 2015;40(8):1910–8. doi: 10.1038/npp.2015.40 25652250
13. Mwenifumbo JC, Tyndale RF. Molecular genetics of nicotine metabolism. Handb Exp Pharmacol. 2009;192: 235–59. doi: 10.1007/978-3-540-69248-5_9 19184652
14. Thorgeirsson TE, Gudbjartsson DF, Surakka I, Vink JM, Amin N, Geller F, et al. Sequence variants at CHRNB3-CHRNA6 and CYP2A6 affect smoking behavior. Nat Genet. 2010;42(5): 448–53. doi: 10.1038/ng.573 20418888
15. Benowitz NL, Hukkanen J, Jacob P 3rd. Nicotine chemistry, metabolism, kinetics and biomarkers. Handb Exp Pharmacol. 2009;192: 29–60. doi: 10.1007/978-3-540-69248-5_2 19184645
16. Swan GE, Lessov-Schlaggar CN, Bergen AW, He Y, Tyndale RF, Benowitz NL. Genetic and environmental influences on the ratio of 3'hydroxycotinine to cotinine in plasma and urine. Pharmacogenet Genomics. 2009;19(5): 388–98. doi: 10.1097/FPC.0b013e32832a404f 19300303
17. Chenoweth MJ, Novalen M, Hawk LW Jr, Schnoll RA, George TP, Cinciripini PM, et al. Known and novel sources of variability in the nicotine metabolite ratio in a large sample of treatment-seeking smokers. Cancer Epidemiol Biomarkers Prev. 2014;23(9): 1773–82. doi: 10.1158/1055-9965.EPI-14-0427 25012994
18. Higashi E, Fukami T, Itoh M, Kyo S, Inoue M, Yokoi T, et al. Human CYP2A6 is induced by estrogen via estrogen receptor. Drug Metab Dispos. 2007;35(10): 1935–41. 17646279
19. Lerman C, Tyndale R, Patterson F, Wileyto EP, Shields PG, Pinto A, et al. Nicotine metabolite ratio predicts efficacy of transdermal nicotine for smoking cessation. Clin Pharmacol Ther. 2006;79(6):600–8. 16765148
20. Patterson F, Schnoll RA, Wileyto EP, Pinto A, Epstein LH, Shields PG, et al. Toward personalized therapy for smoking cessation: a randomized placebo-controlled trial of bupropion. Clin Pharmacol Ther. 2008;84(3): 320–25. doi: 10.1038/clpt.2008.57 18388868
21. Schnoll RA, Patterson F, Wileyto EP, Tyndale RF, Benowitz N, Lerman C. Nicotine metabolic rate predicts successful smoking cessation with transdermal nicotine: a validation study. Pharmacol Biochem Behav. 2009;92(1): 6–11. doi: 10.1016/j.pbb.2008.10.016 19000709
22. Lerman C, Schnoll RA, Hawk LW Jr, Cinciripini P, George TP, Wileyto EP, et al. Use of the nicotine metabolite ratio as a genetically informed biomarker of response to nicotine patch or varenicline for smoking cessation: a randomised, double-blind placebo-controlled trial. Lancet Respir Med. 2015;3(2): 131–38. doi: 10.1016/S2213-2600(14)70294-2 25588294
23. Kettunen J, Tukiainen T, Sarin AP, Ortega-Alonso A, Tikkanen E, Lyytikäinen LP, et al. Genome-wide association study identifies multiple loci influencing human serum metabolite levels. Nat Genet. 2012;44(3): 269–76. doi: 10.1038/ng.1073 22286219
24. Demirkan A, Henneman P, Verhoeven A, Dharuri H, Amin N, van Klinken JB, et al. Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses. PLoS Genet. 2015;11(1): e1004835. doi: 10.1371/journal.pgen.1004835 25569235
25. Kaprio J. Twin studies in Finland 2006. Twin Res Hum Genet. 2006;9(6): 772–77. 17254406
26. Kaprio J. The Finnish Twin Cohort Study: an update. Twin Res Hum Genet. 2013;16(1): 157–62. doi: 10.1017/thg.2012.142 23298696
27. Latvala A, Tuulio-Henriksson A, Dick DM, Vuoksimaa E, Viken RJ, Suvisaari J, et al. Genetic origins of the association between verbal ability and alcohol dependence symptoms in young adulthood. Psychol Med. 2011;41(3): 641–51. doi: 10.1017/S0033291710001194 20529418
28. Dick DM, Aliev F, Viken R, Kaprio J, Rose RJ. Rutgers alcohol problem index scores at age 18 predict alcohol dependence diagnoses 7 years later. Alcohol Clin Exp Res. 2011;35(5): 1011–4. doi: 10.1111/j.1530-0277.2010.01432.x 21323682
29. Raitakari OT, Juonala M, Rönnemaa T, Keltikangas-Järvinen L, Räsänen L, Pietikäinen M, et al. Cohort profile: the cardiovascular risk in Young Finns Study. Int J Epidemiol. 2008;37(6): 1220–6. doi: 10.1093/ije/dym225 18263651
30. Lea RA, Dickson S, Benowitz NL. Within-subject variation of the salivary 3HC/COT ratio in regular daily smokers: prospects for estimating CYP2A6 enzyme activity in large-scale surveys of nicotine metabolic rate. J Anal Toxicol. 2006;30(6): 386–89. 16872570
31. Borodulin K, Vartiainen E, Peltonen M, Jousilahti P, Juolevi A, Laatikainen T, et al. Forty-year trends in cardiovascular risk factors in Finland. Eur J Public Health. 2015;25(3):539–46. doi: 10.1093/eurpub/cku174 25422363
32. Loukola A, Wedenoja J, Keskitalo-Vuokko K, Broms U, Korhonen T, Ripatti S, et al. Genome-wide association study on detailed profiles of smoking behavior and nicotine dependence in a twin sample. Mol Psychiatry. 2014;19(5): 615–24. doi: 10.1038/mp.2013.72 23752247
33. St Helen G, Novalen M, Heitjan DF, Dempsey D, Jacob P 3rd, Aziziyeh A, et al. Reproducibility of the nicotine metabolite ratio in cigarette smokers. Cancer Epidemiol Biomarkers Prev. 2012;21(7): 1105–14. doi: 10.1158/1055-9965.EPI-12-0236 22552800
34. Broms U, Pennanen M, Patja K, Ollila H, Korhonen T, Kankaanpää A, et al. Diurnal Evening Type is Associated with Current Smoking, Nicotine Dependence and Nicotine Intake in the Population Based National FINRISK 2007 Study. J Addict Res Ther. 2012 Jan 25;S2. pii: 002. 22905332
35. Tanner J-A, Novalen M, Jatlow P, Huestis MA, Murphy SE, Kaprio J, et al. Agreement and association between measures of the nicotine metabolite ratio by different analytical approaches in plasma and urine: Implications for clinical implementation. Cancer Epidemiology, Biomarkers & Prevention, in press
36. Delaneau O, Howie B, Cox AJ, Zagury JF, Marchini J. Haplotype estimation using sequencing reads. Am J Hum Genet. 2013;93(4): 687–96. doi: 10.1016/j.ajhg.2013.09.002 24094745
37. Howie BN, Donnelly P, Marchini J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 2009;5(6): e1000529. doi: 10.1371/journal.pgen.1000529 19543373
38. Genomes Project Consortium, Abecasis GR, Auton A Brooks LD, DePristo MA, Durbin RM, et al. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491(7422): 56–65. doi: 10.1038/nature11632 23128226
39. Neale MC, Boker SM, Xie G, Maes HH (2006). Mx: Statistical Modeling. VCU Box 900126, Richmond, VA 23298: Department of Psychiatry. 7th Edition.
40. Silverberg MS, Cho JH, Rioux JD, McGovern DP, Wu J, Annese V, et al. Ulcerative colitis-risk loci on chromosomes 1p36 and 12q15 found by genome-wide association study. Nat Genet. 2009;41(2): 216–20. doi: 10.1038/ng.275 19122664
41. Purcell S, Cherny SS, Sham PC. Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits. Bioinformatics 2003;19(1): 149–50. 12499305
42. Aulchenko YS, Ripke S, Isaacs A, van Duijn CM. GenABEL: an R library for genome-wide association analysis. Bioinformatics. 2007;23(10): 1294–96. 17384015
43. Zhou X, Stephens M. Genome-wide efficient mixed-model analysis for association studies. Nat Genet. 2012;44(7): 821–24. doi: 10.1038/ng.2310 22706312
44. Liu JZ, Tozzi F, Waterworth DM, Pillai SG, Muglia P, Middleton L, et al. Meta-analysis and imputation refines the association of 15q25 with smoking quantity. Nat Genet. 2010;42(5): 436–40. doi: 10.1038/ng.572 20418889
45. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21(2): 263–65. 15297300
46. Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD, et al. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics. 2014;30(10): 1363–69. doi: 10.1093/bioinformatics/btu049 24478339
47. Naeem H, Wong NC, Chatterton Z, Hong MK, Pedersen JS, Corcoran NM, et al. Reducing the risk of false discovery enabling identification of biologically significant genome-wide methylation status using the HumanMethylation450 array. BMC Genomics. 2014;15: 51. doi: 10.1186/1471-2164-15-51 24447442
48. Bell JT, Pai AA, Pickrell JK, Gaffney DJ, Pique-Regi R, Degner JF, et al. DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol. 2011;12(1): R10. doi: 10.1186/gb-2011-12-1-r10 21251332
49. Almli LM, Stevens JS, Smith AK, Kilaru V, Meng Q, Flory J, et al. A genome-wide identified risk variant for PTSD is a methylation quantitative trait locus and confers decreased cortical activation to fearful faces. Am J Med Genet B Neuropsychiatr Genet. 2015;168B(5): 327–36. doi: 10.1002/ajmg.b.32315 25988933
50. Benjamini Y, Hochberg Y. Controlling the false discovery rate—A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, Series B (Metallurgy) 1995;57(1): 289–300.
51. Millstein J, Zhang B, Zhu J, Schadt EE. Disentangling molecular relationships with a causal inference test. BMC Genet. 2009;10: 23. doi: 10.1186/1471-2156-10-23 19473544
52. Cuellar-Partida G, Renteria ME, MacGregor S. LocusTrack: Integrated visualization of GWAS results and genomic annotation. Source Code Biol Med. 2015;10: 1. doi: 10.1186/s13029-015-0032-8 25750659
53. Dawood N, Vaccarino V, Reid KJ, Spertus JA, Hamid N, Parashar S, et al. Predictors of smoking cessation after a myocardial infarction: the role of institutional smoking cessation programs in improving success. Arch Intern Med. 2008;168(18): 1961–67. doi: 10.1001/archinte.168.18.1961 18852396
54. Hartmann-Boyce J, Stead LF, Cahill K, Lancaster T. Efficacy of interventions to combat tobacco addiction: Cochrane update of 2012 reviews. Addiction. 2013;108(10): 1711–21. doi: 10.1111/add.12291 23834141
55. Oscarson M, McLellan RA, Asp V, Ledesma M, Bernal Ruiz ML, Sinues B, et al. Characterization of a novel CYP2A7/CYP2A6 hybrid allele (CYP2A6*12) that causes reduced CYP2A6 activity. Hum Mutat. 2002;20(4): 275–83. 12325023
56. Benowitz NL, Swan GE, Jacob P 3rd, Lessov-Schlaggar CN, Tyndale RF. CYP2A6 genotype and the metabolism and disposition kinetics of nicotine. Clin Pharmacol Ther. 2006;80(5): 457–67. 17112802
57. Nakajima M, Fukami T, Yamanaka H, Higashi E, Sakai H, Yoshida R, et al. Comprehensive evaluation of variability in nicotine metabolism and CYP2A6 polymorphic alleles in four ethnic populations. Clin Pharmacol Ther. 2006;80(3): 282–97. 16952495
58. Dempsey DA, St Helen G, Jacob P 3rd, Tyndale RF, Benowitz NL. Genetic and pharmacokinetic determinants of response to transdermal nicotine in white, black, and Asian nonsmokers. Clin Pharmacol Ther. 2013;94(6): 687–94. doi: 10.1038/clpt.2013.159 23933970
59. Fukami T, Nakajima M, Higashi E, Yamanaka H, Sakai H, McLeod HL, et al. Characterization of novel CYP2A6 polymorphic alleles (CYP2A6*18 and CYP2A6*19) that affect enzymatic activity. Drug Metab Dispos. 2005;33(8): 1202–10. 15900015
60. Al Koudsi N, Mwenifumbo JC, Sellers EM, Benowitz NL, Swan GE, Tyndale RF. Characterization of the novel CYP2A6*21 allele using in vivo nicotine kinetics. Eur J Clin Pharmacol. 2006;62(6): 481–84. 16758265
61. Hofmann MH, Blievernicht JK, Klein K, Saussele T, Schaeffeler E, Schwab M, et al. Aberrant splicing caused by single nucleotide polymorphism c.516G>T [Q172H], a marker of CYP2B6*6, is responsible for decreased expression and activity of CYP2B6 in liver. J Pharmacol Exp Ther. 2008;325(1): 284–92. doi: 10.1124/jpet.107.133306 18171905
62. Bloom AJ, Baker TB, Chen LS, Breslau N, Hatsukami D, Bierut LJ, et al. Variants in two adjacent genes, EGLN2 and CYP2A6, influence smoking behavior related to disease risk via different mechanisms. Hum Mol Genet. 2014;23(2): 555–61. doi: 10.1093/hmg/ddt432 24045616
63. Zhong W, Jiang MM, Weinmaster G, Jan LY, Jan YN. Differential expression of mammalian Numb, Numblike and Notch1 suggests distinct roles during mouse cortical neurogenesis. Development. 1997;124(10): 1887–97. 9169836
64. Yingjie L, Jian T, Changhai Y, Jingbo L. Numblike regulates proliferation, apoptosis, and invasion of lung cancer cell. Tumour Biol. 2013;34(5): 2773–80. doi: 10.1007/s13277-013-0835-7 23681800
65. Vaira V, Faversani A, Martin NM, Garlick DS, Ferrero S, Nosotti M, et al. Regulation of lung cancer metastasis by Klf4-Numb-like signaling. Cancer Res. 2013;73(8): 2695–2705. doi: 10.1158/0008-5472.CAN-12-4232 23440423
66. Benowitz NL. Nicotine addiction. N Engl J Med. 2010;362(24): 2295–2303. doi: 10.1056/NEJMra0809890 20554984
67. Chenoweth MJ, O'Loughlin J, Sylvestre MP, Tyndale RF. CYP2A6 slow nicotine metabolism is associated with increased quitting by adolescent smokers. Pharmacogenet Genomics. 2013;23(4): 232–35. doi: 10.1097/FPC.0b013e32835f834d 23462429
68. Chen LS, Bloom AJ, Baker TB, Smith SS, Piper ME, Martinez M, et al. Pharmacotherapy effects on smoking cessation vary with nicotine metabolism gene (CYP2A6). Addiction. 2014;109(1): 128–37. doi: 10.1111/add.12353 24033696
69. Lee KW, Pausova Z. Cigarette smoking and DNA methylation. Front Genet. 2013;4: 132. doi: 10.3389/fgene.2013.00132 23882278
70. Nasarre P, Potiron V, Drabkin H, Roche J. Guidance molecules in lung cancer. Cell Adh Migr. 2010;4(1): 130–45. 20139699
71. Maemura K, Yoshikawa H, Yokoyama K, Ueno T, Kurose H, Uchiyama K, et al. Delta-like 3 is silenced by methylation and induces apoptosis in human hepatocellular carcinoma. Int J Oncol. 2013;42(3): 817–22. doi: 10.3892/ijo.2013.1778 23337976
72. Fragkiadaki P, Soulitzis N, Sifakis S, Koutroulakis D, Gourvas V, Vrachnis N, et al. Downregulation of notch signaling pathway in late preterm and term placentas from pregnancies complicated by preeclampsia. PLoS One. 2015;10(5): e0126163. doi: 10.1371/journal.pone.0126163 25962154
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Genetika Reprodukčná medicínaČlánok vyšiel v časopise
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