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Global genetic variation of select opiate metabolism genes in self-reported healthy individuals

Abstract

CYP2D6 is a key pharmacogene encoding an enzyme impacting poor, intermediate, extensive and ultrarapid phase I metabolism of many marketed drugs. The pharmacogenetics of opiate drug metabolism is particularly interesting due to the relatively high incidence of addiction and overdose. Recently, trans-acting opiate metabolism and analgesic response enzymes (UGT2B7, ABCB1, OPRM1 and COMT) have been incorporated into pharmacogenetic studies to generate more comprehensive metabolic profiles of patients. With use of massively parallel sequencing, it is possible to identify additional polymorphisms that fine tune, or redefine, previous pharmacogenetic findings, which typically rely on targeted approaches. The 1000 Genomes Project data were analyzed to describe population genetic variation and statistics for these five genes in self-reported healthy individuals in five global super- and 26 sub-populations. Findings on the variation of these genes in various populations expand baseline understanding of pharmacogenetically relevant polymorphisms for future studies of affected cohorts.

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References

  1. Ingelman-Sundberg M, Sim SC, Gomez A, Rodriguez-Antona C . Influence of cytochrome P450 polymorphisms on drug therapies: pharmacogenetic, pharmacoepigenetic and clinical aspects. Pharmacol Ther 2007; 116: 496–526.

    Article  CAS  PubMed  Google Scholar 

  2. Ingelman-Sundberg M . Genetic polymorphisms of cytochrome P450 2D6 (CYP2D6): clinical consequences, evolutionary aspects and functional diversity. Pharmacogenomics J 2005; 5: 6–13.

    Article  CAS  PubMed  Google Scholar 

  3. Leppert W . CYP2D6 in the metabolism of opioids for mild to moderate pain. Pharmacology 2011; 87: 274–85.

    Article  CAS  PubMed  Google Scholar 

  4. Frost J, Helland A, Nordrum IS, Slørdal L . Investigation of morphine and morphine glucuronide levels and cytochrome P450 isoenzyme 2D6 genotype in codeine-related deaths. Forensic Sci Int 2012; 220: 6–11.

    Article  CAS  PubMed  Google Scholar 

  5. Frost J, Løkken TN, Helland A, Nordrum IS, Slørdal L . Post-mortem levels and tissue distribution of codeine, codeine-6-glucuronide, norcodeine, morphine and morphine glucuronides in a series of codeine-related deaths. Forensic Sci Int 2016; 262: 128–137.

    Article  CAS  PubMed  Google Scholar 

  6. Zhou SF, Di YM, Chan E, Du YM, Chow VD, Xue CC et al. Clinical pharmacogenetics and potential application in personalized medicine. Curr Drug Metab 2008; 9: 738–784.

    Article  CAS  PubMed  Google Scholar 

  7. Sistonen J, Madadi P, Ross CJ, Yazdanpanah M, Lee JW, Landsmeer ML et al. Prediction of codeine toxicity in infants and their mothers using a novel combination of maternal genetic markers. Clin Pharmacol Ther 2012; 91: 692–699.

    Article  CAS  PubMed  Google Scholar 

  8. Weber A, Szalai R, Sipeky C, Magyari L, Melegh M, Jaromi L et al. Increased prevalence of functional minor allele variants of drug metabolizing CYP2B6 and CYP2D6 genes in Roma population samples. Pharmacol Rep 2015; 67: 460–464.

    Article  CAS  PubMed  Google Scholar 

  9. The Human Cytochrome p450 Allele Nomenclature Database. Accessed on May 2016. Available at http://www.cypalleles.ki.se/cyp2d6.htm.

  10. Diatchenko L, Slade GD, Nackley AG, Bhalang K, Sigurdsson A, Belfer I et al. Genetic basis for individual variations in pain perception and the development of a chronic pain condition. Hum Mol Genet 2005; 14: 135–143.

    Article  CAS  PubMed  Google Scholar 

  11. Koren G, Cairns J, Chitayat D, Gaedigk A, Leeder SJ . Pharmacogenetics of morphine poisoning in a breastfed neonate of a codeine-prescribed mother. Lancet 2006; 368: 704.

    Article  PubMed  Google Scholar 

  12. Sallee FR, DeVane CL, Ferrell RE . Fluoxetine-related death in a child with cytochrome P-450 2D6 genetic deficiency. J Child Adolesc Psychopharmacol 2000 Spring; 10: 27–34.

    Article  CAS  PubMed  Google Scholar 

  13. Altar CA, Carhart JM, Allen JD, Hall-Flavin DK, Dechairo BM, Winner JG . Clinical validity: combinatorial pharmacogenomics predicts antidepressant responses and healthcare utilizations better than single gene phenotypes. Pharmacogenomics J 2015; 15: 443–451.

    Article  CAS  PubMed  Google Scholar 

  14. Lam J, Woodall KL, Solbeck P, Ross CJ, Carleton BC, Hayden MR et al. Codeine-related deaths: The role of pharmacogenetics and drug interactions. Forensic Sci Int 2014; 239: 50–56.

    Article  CAS  PubMed  Google Scholar 

  15. Baber M, Chaudhry S, Kelly L, Ross C, Carleton B, Berger H et al. The pharmacogenetics of codeine pain relief in the postpartum period. Pharmacogenomics J 2015; 15: 430–435.

    Article  CAS  PubMed  Google Scholar 

  16. Bastami S, Gupta A, Zackrisson AL, Ahlner J, Osman A, Uppugunduri S . Influence of UGT2B7, OPRM1 and ABCB1 gene polymorphisms on postoperative morphine consumption. Basic Clin Pharmacol Toxicol 2014; 115: 423–431.

    Article  CAS  PubMed  Google Scholar 

  17. Yuferov V, Levran O, Proudnikov D, Nielsen DA, Kreek MJ . Search for genetic markers and functional variants involved in the development of opiate and cocaine addiction and treatment. Ann N Y Acad Sci 2010; 1187: 184–207.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Brion M, Sobrino B, Martinez M, Blanco-Verea A, Carracedo A . Massive parallel sequencing applied to the molecular autopsy in sudden cardiac death in the young. Forensic Sci Int Genet 2015; 18: 160–170.

    Article  CAS  PubMed  Google Scholar 

  19. Narula N, Tester DJ, Paulmichl A, Maleszewski JJ, Ackerman MJ . Post-mortem Whole exome sequencing with gene-specific analysis for autopsy-negative sudden unexplained death in the young: a case series. Pediatr Cardiol 2015; 36: 768–778.

    Article  PubMed  Google Scholar 

  20. Koch WH . Technology platforms for pharmacogenomic diagnostic assays. Nat Rev Drug Discov 2004; 3: 749–761.

    Article  CAS  PubMed  Google Scholar 

  21. Brandl EJ, Tiwari AK, Zhou X, Deluce J, Kennedy JL, Müller DJ et al. Influence of CYP2D6 and CYP2C19 gene variants on antidepressant response in obsessive-compulsive disorder. Pharmacogenomics J 2014; 14: 176–181.

    Article  CAS  PubMed  Google Scholar 

  22. Levo A, Koski A, Ojanperä I, Vuori E, Sajantila A, Post-mortem SNP . analysis of CYP2D6 gene reveals correlation between genotype and opioid drug (tramadol) metabolite ratios in blood. Forensic Sci Int 2003; 135: 9–15.

    Article  CAS  PubMed  Google Scholar 

  23. Rosenberg NA, Huang L, Jewett EM, Szpiech ZA, Jankovic I, Boehnke M . Genome-wide association studies in diverse populations. Nat Rev Genet 2010; 11: 356–366.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Gaedigk A, Sangkuhl K, Whirl-Carrillo M, Klein T, Leeder JS . Prediction of CYP2D6 phenotype from genotype across world populations. Genet Med 2016; 19: 69–76.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Stelzer G, Dalah I, Stein TI, Satanower Y, Rosen N, Nativ N et al. In silico human genomics with GeneCards. Hum Genomics 2011; 5: 709–717.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. 1000 Genomes Project Consortium 1000 Genomes Project Consortium Auton A Brooks LD Durbin RM Garrison EP Kang HM et al. A global reference for human genetic variation. Nature 2015; 526: 68–74.

    Article  Google Scholar 

  27. Karolchik D, Hinrichs AS, Kent WJ . The UCSC Genome Browser. Curr Protoc Bioinformatics 2012; Chapter 1: Unit 1.4.

    Google Scholar 

  28. Weir BS . 1 Genetic Data Analysis. 2nd edn. Sinauer Associates: Sunderland, MA, 1996, pp 376.

    Google Scholar 

  29. Wang J, Shete S . Testing departure from Hardy-Weinberg proportions. Methods Mol Biol 2012; 850: 77–102.

    Article  PubMed  Google Scholar 

  30. Teo YY, Fry AE, Clark TG, Tai ES, Seielstad M . On the usage of HWE for identifying genotyping errors. Ann Hum Genet 2007; 71: 701–703.

    Article  CAS  PubMed  Google Scholar 

  31. McLaren W, Pritchard B, Rios D, Chen Y, Flicek P, Cunningham F . Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor. Bioinformatics 2010; 26: 2069–2070.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Kumar P, Henikoff S, Ng PC . Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc 2009; 4: 1073–1081.

    Article  CAS  PubMed  Google Scholar 

  33. Ng PC, Henikoff S . Predicting the effects of amino acid substitutions on protein function. Annu Rev Genomics Hum Genet 2006; 7: 61–80.

    Article  CAS  PubMed  Google Scholar 

  34. Ng PC, Henikoff S . SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res 2003; 31: 3812–3814.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Ng PC, Henikoff S . Accounting for human polymorphisms predicted to affect protein function. Genome Res 2002; 12: 436–446.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Ng PC, Henikoff S . Predicting deleterious amino acid substitutions. Genome Res 2001; 11: 863–874.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P et al. A method and server for predicting damaging missense mutations. Nat Methods 2010; 7: 248–249.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Adzhubei I, Jordan DM, Sunyaev SR . Predicting functional effect of human missense mutations using PolyPhen-2. Curr Protoc Hum Genet 2013; Chapter 7: Unit 7.20.

    Google Scholar 

  39. Choi Y, Sims GE, Murphy S, Miller JR, Chan AP . Predicting the functional effect of amino acid substitutions and indels. PLoS ONE 2012; 7: e46688.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Choi Y, Chan AP . PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics 2015; 31: 2745–2747.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Choi Y (2012). A Fast Computation of Pairwise Sequence Alignment Scores Between a Protein and a Set of Single-Locus Variants of Another Protein. In Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine (BCB '12). ACM, New York, NY, USA, 414–417.

  42. Desmet FO, Hamroun D, Lalande M, Collod-Béroud G, Claustres M, Béroud C . Human Splicing Finder: an online bioinformatics tool to predict splicing signals. Nucleic Acids Res 2009; 37: e67.

    Article  PubMed  PubMed Central  Google Scholar 

  43. RStudio Team (2015). RStudio: Integrated Development for R. RStudio, Inc., Boston, MA, USA. doi: http://www.rstudio.com/.

  44. Gaedigk A, Simon SD, Pearce RE, Bradford LD, Kennedy MJ, Leeder JS . The CYP2D6 activity score: translating genotype information into a qualitative measure of phenotype. Clin Pharmacol Ther 2008; 83: 234–242.

    Article  CAS  PubMed  Google Scholar 

  45. Bernard S, Neville KA, Nguyen AT, Flockhart DA . Interethnic differences in genetic polymorphisms of CYP2D6 in the U.S. population: clinical implications. Oncologist 2006; 11: 126–135.

    Article  CAS  PubMed  Google Scholar 

  46. Wilson JF, Weale ME, Smith AC, Gratrix F, Fletcher B, Thomas MG et al. Population genetic structure of variable drug response. Nat Genet 2001; 29: 265–269.

    Article  CAS  PubMed  Google Scholar 

  47. Li J, Zhang L, Zhou H, Stoneking M, Tang K . Global patterns of genetic diversity and signals of natural selection for human ADME genes. Hum Mol Genet 2011; 20: 528–540.

    Article  CAS  PubMed  Google Scholar 

  48. Mizzi C, Dalabira E, Kumuthini J, Dzimiri N, Balogh I, BaÅŸak N et al. A European Spectrum of Pharmacogenomic Biomarkers: Implications for Clinical Pharmacogenomics. PLoS ONE 2016; 11: e0162866.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Murray T, Beaty TH, Mathias RA, Rafaels N, Grant AV, Faruque MU et al. African and non-African admixture components in African Americans and an African Caribbean population. Genet Epidemiol 2010; 34: 561–568.

    Article  PubMed  Google Scholar 

  50. Benn-Torres J, Bonilla C, Robbins CM, Waterman L, Moses TY, Hernandez W et al. Admixture and population stratification in African Caribbean populations. Ann Hum Genet 2008; 72: 90–98.

    CAS  PubMed  Google Scholar 

  51. Xu S, Yin X, Li S, Jin W, Lou H, Yang L et al. Genomic dissection of population substructure of Han Chinese and its implication in association studies. Am J Hum Genet 2009; 85: 762–774.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Yasuda SU, Zhang L, Huang SM . The role of ethnicity in variability in response to drugs: focus on clinical pharmacology studies. Clin Pharmacol Ther 2008; 84: 417–423.

    Article  CAS  PubMed  Google Scholar 

  53. Sistonen J, Sajantila A, Lao O, Corander J, Barbujani G, Fuselli S . CYP2D6 worldwide genetic variation shows high frequency of altered activity variants and no continental structure. Pharmacogenet Genomics 2007; 17: 93–101.

    CAS  PubMed  Google Scholar 

  54. Qin S, Shen L, Zhang A, Xie J, Shen W, Chen L et al. Systematic polymorphism analysis of the CYP2D6 gene in four different geographical Han populations in mainland China. Genomics 2008; 92: 152–158.

    Article  CAS  PubMed  Google Scholar 

  55. Sulovari A, Chen YH, Hudziak JJ, Li D . Atlas of human diseases influenced by genetic variants with extreme allele frequency differences. Hum Genet 2017; 136: 39–54.

    Article  PubMed  Google Scholar 

  56. Bartošová O, Polanecký O, Perlík F, Adámek S, Slanař O . OPRM1 and ABCB1 polymorphisms and their effect on postoperative pain relief with piritramide. Physiol Res 2015; 64: S521–S527.

    PubMed  Google Scholar 

  57. Barratt DT, Coller JK, Hallinan R, Byrne A, White JM, Foster DJ, Somogyi AA . ABCB1 haplotype and OPRM1 118 A > G genotype interaction in methadone maintenance treatment pharmacogenetics. Pharmgenomics Pers Med 2012; 5: 53–62.

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We would like to thank Emily Perry from the 1000 Genomes Helpdesk for assistance with extracting information from the Table Browser.

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Correspondence to F R Wendt.

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Wendt, F., Pathak, G., Sajantila, A. et al. Global genetic variation of select opiate metabolism genes in self-reported healthy individuals. Pharmacogenomics J 18, 281–294 (2018). https://doi.org/10.1038/tpj.2017.13

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