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Priorities and standards in pharmacogenetic research

Abstract

The current enthusiasm for pharmacogenetics draws much of its inspiration from the relatively few examples of polymorphisms that have marked and seemingly clinically relevant effects on drug response. In this regard, pharmacogenetic research has paralleled the study of human disease, which has enjoyed success in identifying mutations underlying mendelian conditions. Progress in deciphering the genetics of complex diseases, involving the interaction of multiple genes with each other and with the environment has been considerably less successful. In most instances, drug responses will probably also prove to be complex, influenced by both the environment and multiple genetic factors. For pharmacogenetics to deliver on its potential, this complexity will need to be recognized and accommodated, both in basic research and in clinical application of pharmacogenetics. As the attention of researchers begins to shift toward more systematic pharmacogenetic investigations, we suggest some priorities and standards for pharmacogenetic research.

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References

  1. Goldstein, D.B., Tate, S.K. & Sisodiya, S.M. Pharmacogenetics goes genomic. Nat. Rev. Genet. 4, 937–947 (2003).

    Article  CAS  Google Scholar 

  2. Strittmatter, W.J. et al. Apolipoprotein E: high-avidity binding to beta-amyloid and increased frequency of type 4 allele in late-onset familial Alzheimer disease. Proc. Natl. Acad. Sci. USA 90, 1977–1981 (1993).

    Article  CAS  Google Scholar 

  3. Conley, R.R. & Kelly, D.L. Management of treatment resistance in schizophrenia. Biol. Psychiatry 50, 898–911 (2001).

    Article  CAS  Google Scholar 

  4. Meltzer, H.Y. & Okayli, G. Reduction of suicidality during clozapine treatment of neuroleptic-resistant schizophrenia: impact on risk-benefit assessment. Am. J. Psychiatry 152, 183–190 (1995).

    Article  CAS  Google Scholar 

  5. Honigfeld, G., Arellano, F., Sethi, J., Bianchini, A. & Schein, J. Reducing clozapine-related morbidity and mortality: 5 years of experience with the Clozaril National Registry. J. Clin. Psychiatry 59 Suppl., 3–7 (1998).

    Google Scholar 

  6. Duggan, A., Warner, J., Knapp, M. & Kerwin, R. Modelling the impact of clozapine on suicide in patients with treatment-resistant schizophrenia in the UK. Br. J. Psychiatry 182, 505–508 (2003).

    Article  Google Scholar 

  7. Shah, R.R. Pharmacogenetic aspects of drug-induced torsade de pointes: potential tool for improving clinical drug development and prescribing. Drug Saf. 27, 145–172 (2004).

    Article  CAS  Google Scholar 

  8. Wolbrette, D.L. Drugs that cause torsades de pointes and increase the risk of sudden cardiac death. Curr. Cardiol. Rep. 6, 379–384 (2004).

    Article  Google Scholar 

  9. Roses, A.D. Pharmacogenetics and drug development: the path to safer and more effective drugs. Nat. Rev. Genet. 5, 645–656 (2004).

    Article  CAS  Google Scholar 

  10. Parker, S.L., Tong, T., Bolden, S. & Wingo, P.A. Cancer statistics, 1997. CA Cancer J. Clin. 47, 5–27 (1997).

    Article  CAS  Google Scholar 

  11. Lynch, T.J. et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N. Engl. J. Med. 350, 2129–2139 (2004).

    Article  CAS  Google Scholar 

  12. Paez, J.G. et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 304, 1497–1500 (2004).

    Article  CAS  Google Scholar 

  13. Fischer, O.M., Streit, S., Hart, S. & Ullrich, A. Beyond Herceptin and Gleevec. Curr. Opin. Chem. Biol. 7, 490–495 (2003).

    Article  CAS  Google Scholar 

  14. Weinshilboum, R. Inheritance and drug response. N. Engl. J. Med. 348, 529–537 (2003).

    Article  Google Scholar 

  15. Schaeffeler, E. et al. Comprehensive analysis of thiopurine S-methyltransferase phenotype-genotype correlation in a large population of German-Caucasians and identification of novel TPMT variants. Pharmacogenetics 14, 407–417 (2004).

    Article  CAS  Google Scholar 

  16. Flowers, C.R. & Veenstra, D. The role of cost-effectiveness analysis in the era of pharmacogenomics. Pharmacoeconomics 22, 481–493 (2004).

    Article  Google Scholar 

  17. Strauss, J.F. III & Kafrissen, M. Waiting for the second coming. Nature 432, 43–45 (2004).

    Article  CAS  Google Scholar 

  18. Roses, A.D., Burns, D.K., Chissoe, S., Middleton, L. & St Jean, P. Disease-specific target selection: a critical first step down the right road. Drug Discov. Today 10, 177–189 (2005).

    Article  Google Scholar 

  19. Nebert, D.W., Jorge-Nebert, L. & Vesell, E.S. Pharmacogenomics and “individualized drug therapy”: high expectations and disappointing achievements. Am. J. Pharmacogenomics 3, 361–370 (2003).

    Article  Google Scholar 

  20. Nebert, D.W. & Vesell, E.S. Advances in pharmacogenomics and individualized drug therapy: exciting challenges that lie ahead. Eur. J. Pharmacol. 500, 267–280 (2004).

    Article  CAS  Google Scholar 

  21. Shorvon, S., Perucca, E., Fish, S. & Dodson, E. The Treatment of Epilepsy (Blackwell Science, Oxford, 2004).

    Book  Google Scholar 

  22. Tate, S.K. et al. Genetic predictors of the maximum doses patients receive during clinical use of the anti-epileptic drugs carbamazepine and phenytoin. Proc. Natl. Acad. Sci. USA 102, 5507–5512 (2005).

    Article  CAS  Google Scholar 

  23. Rajput, A.H. et al. Clinical-pathological study of levodopa complications. Mov. Disord. 17, 289–296 (2002).

    Article  Google Scholar 

  24. Krajinovic, M. et al. Role of polymorphisms in MTHFR and MTHFD1 genes in the outcome of childhood acute lymphoblastic leukemia. Pharmacogenomics J. 4, 66–72 (2004).

    Article  CAS  Google Scholar 

  25. Dervieux, T. et al. Polyglutamation of methotrexate with common polymorphisms in reduced folate carrier, aminoimidazole carboxamide ribonucleotide transformylase, and thymidylate synthase are associated with methotrexate effects in rheumatoid arthritis. Arthritis Rheum. 50, 2766–2774 (2004).

    Article  CAS  Google Scholar 

  26. Holleman, A. et al. Gene-expression patterns in drug-resistant acute lymphoblastic leukemia cells and response to treatment. N. Engl. J. Med. 351, 533–542 (2004).

    Article  CAS  Google Scholar 

  27. Kager, L. et al. Folate pathway gene expression differs in subtypes of acute lymphoblastic leukemia and influences methotrexate pharmacodynamics. J. Clin. Invest. 115, 110–117 (2005).

    Article  CAS  Google Scholar 

  28. Zembutsu, H. et al. Genome-wide cDNA microarray screening to correlate gene expression profiles with sensitivity of 85 human cancer xenografts to anticancer drugs. Cancer Res. 62, 518–527 (2002).

    CAS  Google Scholar 

  29. Watters, J.W., Kraja, A., Meucci, M.A., Province, M.A. & McLeod, H.L. Genome-wide discovery of loci influencing chemotherapy cytotoxicity. Proc. Natl. Acad. Sci. USA 101, 11809–11814 (2004).

    Article  CAS  Google Scholar 

  30. Xiao, Z. et al. Serum proteomic profiles suggest celecoxib-modulated targets and response predictors. Cancer Res. 64, 2904–2909 (2004).

    Article  CAS  Google Scholar 

  31. Botstein, D. & Risch, N. Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease. Nat. Genet. 33 Suppl. 228–237 (2003).

    Article  CAS  Google Scholar 

  32. Johnson, G.C. et al. Haplotype tagging for the identification of common disease genes. Nat. Genet. 29, 233–237 (2001).

    Article  CAS  Google Scholar 

  33. Ke, X. et al. Efficiency and consistency of haplotype tagging of dense SNP maps in multiple samples. Hum. Mol. Genet. 13, 2557–2565 (2004).

    Article  CAS  Google Scholar 

  34. Liu, N. et al. Haplotype block structures show significant variation among populations. Genet. Epidemiol. 27, 385–400 (2004).

    Article  Google Scholar 

  35. Ahmadi, K.R. et al. A single-nucleotide polymorphism tagging set for human drug metabolism and transport. Nat. Genet. 37, 84–89 (2005).

    Article  CAS  Google Scholar 

  36. Reich, D.E. et al. Linkage disequilibrium in the human genome. Nature 411, 199–204 (2001).

    Article  CAS  Google Scholar 

  37. Goldstein, D.B., Ahmadi, K.R., Weale, M.E. & Wood, N.W. Genome scans and candidate gene approaches in the study of common diseases and variable drug responses. Trends Genet. 19, 615–622 (2003).

    Article  CAS  Google Scholar 

  38. Stumpf, M.P. & Goldstein, D.B. Demography, recombination hotspot intensity, and the block structure of linkage disequilibrium. Curr. Biol. 13, 1–8 (2003).

    Article  CAS  Google Scholar 

  39. Kruglyak, L. Prospects for whole-genome linkage disequilibrium mapping of common disease genes. Nat. Genet. 22, 139–144 (1999).

    Article  CAS  Google Scholar 

  40. Li, H. A permutation procedure for the haplotype method for identification of disease-predisposing variants. Ann. Hum. Genet. 65, 189–196 (2001).

    Article  CAS  Google Scholar 

  41. Reich, D.E. & Goldstein, D.B. Detecting association in a case-control study while correcting for population stratification. Genet. Epidemiol. 20, 4–16 (2001).

    Article  CAS  Google Scholar 

  42. Devlin, B. & Roeder, K. Genomic control for association studies. Biometrics 55, 997–1004 (1999).

    Article  CAS  Google Scholar 

  43. Bacanu, S.A., Devlin, B. & Roeder, K. Association studies for quantitative traits in structured populations. Genet. Epidemiol. 22, 78–93 (2002).

    Article  Google Scholar 

  44. Goldstein, D.B. Pharmacogenetics in the laboratory and the clinic. N. Engl. J. Med. 348, 553–556 (2003).

    Article  Google Scholar 

  45. Soranzo, N. et al. Identifying candidate causal variants responsible for altered activity of the ABCB1 multidrug resistance gene. Genome Res. 14, 1333–1344 (2004).

    Article  CAS  Google Scholar 

  46. Boffelli, D. et al. Phylogenetic shadowing of primate sequences to find functional regions of the human genome. Science 299, 1391–1394 (2003).

    Article  CAS  Google Scholar 

  47. Ovcharenko, I., Boffelli, D. & Loots, G.G. eShadow: a tool for comparing closely related sequences. Genome Res. 14, 1191–1198 (2004).

    Article  CAS  Google Scholar 

  48. Jiang, Z. et al. Toward the evaluation of function in genetic variability: characterizing human SNP frequencies and establishing BAC-transgenic mice carrying the human CYP1A1_CYP1A2 locus. Hum. Mutat. 25, 196–206 (2005).

    Article  Google Scholar 

  49. Shah, R.R. Pharmacogenetics in drug regulation; strengths and limitations. Proc. R. Soc. Lond. B Biol. Sci. (in the press).

  50. Lesko, L.J. & Woodcock, J. Translation of pharmacogenomics and pharmacogenetics: a regulatory perspective. Nat. Rev. Drug Discov. 3, 763–769 (2004).

    Article  CAS  Google Scholar 

  51. Kirchheiner, J. et al. Pharmacogenetics of antidepressants and antipsychotics: the contribution of allelic variations to the phenotype of drug response. Mol. Psychiatry 9, 442–473 (2004).

    Article  CAS  Google Scholar 

  52. Tate, S.K. & Goldstein, D.B. Will tomorrow's medicines work for everyone? Nat. Genet. 36, S34–S42 (2004).

    Article  CAS  Google Scholar 

  53. McGough, J.J. et al. Pharmacokinetics of SLI381 (ADDERALL XR), an extended-release formulation of Adderall. J. Am. Acad. Child Adolesc. Psychiatry 42, 684–691 (2003).

    Article  Google Scholar 

  54. Camilleri, M. et al. Serotonin-transporter polymorphism pharmacogenetics in diarrhea-predominant irritable bowel syndrome. Gastroenterology 123, 425–432 (2002).

    Article  CAS  Google Scholar 

  55. Berson, A. et al. Toxicity of alpidem, a peripheral benzodiazepine receptor ligand, but not zolpidem, in rat hepatocytes: role of mitochondrial permeability transition and metabolic activation. J. Pharmacol. Exp. Ther. 299, 793–800 (2001).

    CAS  Google Scholar 

  56. Ishikawa, C. et al. A frameshift variant of CYP2C8 was identified in a patient who suffered from rhabdomyolysis after administration of cerivastatin. J. Hum. Genet. 49, 582–585 (2004).

    Article  Google Scholar 

  57. Michalski, C. et al. A naturally occurring mutation in the SLC21A6 gene causing impaired membrane localization of the hepatocyte uptake transporter. J. Biol. Chem. 277, 43058–43063 (2002).

    Article  CAS  Google Scholar 

  58. Chung, W.H. et al. Medical genetics: a marker for Stevens-Johnson syndrome. Nature 428, 486 (2004).

    Article  CAS  Google Scholar 

  59. Napolitano, C. et al. Evidence for a cardiac ion channel mutation underlying drug-induced QT prolongation and life-threatening arrhythmias. J. Cardiovasc. Electrophysiol. 11, 691–696 (2000).

    Article  CAS  Google Scholar 

  60. Makita, N. et al. Drug-induced long-QT syndrome associated with a subclinical SCN5A mutation. Circulation 106, 1269–1274 (2002).

    Article  Google Scholar 

  61. Ni, W., Li, M.W., Thakali, K., Fink, G.D. & Watts, S.W. The fenfluramine metabolite (+)-norfenfluramine is vasoactive. J. Pharmacol. Exp. Ther. 309, 845–852 (2004).

    Article  CAS  Google Scholar 

  62. Gross, A.S., Phillips, A.C., Rieutord, A. & Shenfield, G.M. The influence of the sparteine/debrisoquine genetic polymorphism on the disposition of dexfenfluramine. Br. J. Clin. Pharmacol. 41, 311–317 (1996).

    Article  CAS  Google Scholar 

  63. Belohlavkova, S., Simak, J., Kokesova, A., Hnilickova, O. & Hampl, V. Fenfluramine-induced pulmonary vasoconstriction: role of serotonin receptors and potassium channels. J. Appl. Physiol. 91, 755–761 (2001).

    Article  CAS  Google Scholar 

  64. Blanpain, C. et al. Serotonin 5-HT(2B) receptor loss of function mutation in a patient with fenfluramine-associated primary pulmonary hypertension. Cardiovasc. Res. 60, 518–528 (2003).

    Article  CAS  Google Scholar 

  65. Humbert, M. et al. BMPR2 germline mutations in pulmonary hypertension associated with fenfluramine derivatives. Eur. Respir. J. 20, 518–523 (2002).

    Article  CAS  Google Scholar 

  66. Zhang, J.Y., Zhan, J., Cook, C.S., Ings, R.M. & Breau, A.P. Involvement of human UGT2B7 and 2B15 in rofecoxib metabolism. Drug Metab. Dispos. 31, 652–658 (2003).

    Article  Google Scholar 

  67. Donger, C. et al. KVLQT1 C-terminal missense mutation causes a forme fruste long-QT syndrome. Circulation 96, 2778–2781 (1997).

    Article  CAS  Google Scholar 

  68. Ford, G.A., Wood, S.M. & Daly, A.K. CYP2D6 and CYP2C19 genotypes of patients with terodiline cardiotoxicity identified through the yellow card system. Br. J. Clin. Pharmacol. 50, 77–80 (2000).

    Article  CAS  Google Scholar 

  69. Acuna, G. et al. Pharmacogenetic analysis of adverse drug effect reveals genetic variant for susceptibility to liver toxicity. Pharmacogenomics J. 2, 327–334 (2002).

    Article  CAS  Google Scholar 

  70. Kumashiro, R. et al. Association of troglitazone-induced liver injury with mutation of the cytochrome P450 2C19 gene. Hepatol. Res. 26, 337–342 (2003).

    Article  CAS  Google Scholar 

  71. Watanabe, I. et al. A study to survey susceptible genetic factors responsible for troglitazone-associated hepatotoxicity in Japanese patients with type 2 diabetes mellitus. Clin. Pharmacol. Ther. 73, 435–455 (2003).

    Article  CAS  Google Scholar 

  72. Liguori, M.J. et al. Microarray analysis in human hepatocytes suggests a mechanism for hepatotoxicity induced by trovafloxacin. Hepatology 41, 177–186 (2005).

    Article  CAS  Google Scholar 

  73. Wong, D., Wang, M., Cheng, Y. & Fitzgerald, G.A. Cardiovascular hazard and non-steroidal anti-inflammatory drugs. Curr. Opin. Pharmacol. 5, 204–210 (2005).

    Article  CAS  Google Scholar 

  74. Cipollone, F. et al. A polymorphism in the cyclooxygenase 2 gene as an inherited protective factor against myocardial infarction and stroke. J. Am. Med. Assoc. 291, 2221–2228 (2004).

    Article  CAS  Google Scholar 

  75. Shah, R.R. Mechanistic basis of adverse drug reactions: the perils of inappropriate dose schedules. Expert Opinion on Drug Safety 4, 103–128 (2005).

    Article  CAS  Google Scholar 

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Acknowledgements

We thank S. Sisodiya, R. Shah, S. Tate, S. Huang and H. Willard for suggestions and critical reading of the manuscript. A.G.M.'s work is supported by NIEHS Ecogenetics Center Grant P30ES07033.

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Need, A., Motulsky, A. & Goldstein, D. Priorities and standards in pharmacogenetic research. Nat Genet 37, 671–681 (2005). https://doi.org/10.1038/ng1593

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