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Pharmacogenetics in drug discovery and development: a translational perspective

Abstract

The ability to predict a patient's drug response on the basis of their genetic information is expected to decrease attrition during the development of new, innovative drugs, and reduce adverse events by being able to predict individual patients at risk. Most pharmacogenetic investigations have focused on drug-metabolism genes or candidate genes that are thought to be involved in specific diseases. However, robust new genetic tools now enable researchers to carry out multi-candidate gene-association and genome-wide studies for target discovery and drug development. Despite the expanding role of pharmacogenetics in industry, however, there is a paucity of published data. New forms of effective and efficient collaboration between industry and academia that may enhance the systematic collection of pharmacogenetic data are necessary to establish genetic profiles related to drug response, confirm pharmacogenetic associations and expedite the development of new drugs and diagnostic tests.

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Figure 1: Drug discovery and development pipeline and the contribution of PGx.
Figure 2: Reducing attrition through the application of pharmacogenetics.
Figure 3: Growth of HLA-B*5701 testing between August 2007 to November 2007.

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References

  1. Roses, A. D. Pharmacogenetics and the practice of medicine. Nature 405, 857–865 (2000).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  3. Spraggs, C. F. et al. Pharmacogenetics and obesity: common gene variants influence weight loss response of the norepinephrine/dopamine transporter inhibitor GW320659 in obese subjects. Pharmacogenet. Genomics 15, 883–889 (2005).

    Article  CAS  PubMed  Google Scholar 

  4. Risner, M. E. et al. Efficacy of rosiglitazone in a genetically defined population with mild-to-moderate Alzheimer's disease. Pharmacogenomics J. 6, 246–254 (2006).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  Google Scholar 

  6. Holden, A. L. The innovative use of a large-scale industry biomedical consortia to research the genetic basis of drug induced serious adverse events. Drug Discov. Today Technol. 2, 75–87 (2007).

    Article  Google Scholar 

  7. Vizirianakis, I. S. Clinical translation of genotyping and haplotyping data: implementation of in vivo pharmacology experience leading drug prescription to pharmacotyping. Clin. Pharmacokinet. 46, 807–824 (2007).

    Article  CAS  PubMed  Google Scholar 

  8. Hammond, I. W., Gibbs, T. G., Seifert, H. A. & Rich, D. S. Database size and power to detect safety signals in pharmacovigilance. Expert Opin. Drug Saf. 6, 713–721 (2007).

    Article  CAS  PubMed  Google Scholar 

  9. Bennett, C. L. et al. Evaluation of serious adverse drug reactions: a proactive pharmacovigilance program (RADAR) vs safety activities conducted by the Food and Drug Administration and pharmaceutical manufacturers. Arch. Int. Med. 167, 1041–1049 (2007).

    Article  Google Scholar 

  10. Hughes A. R. et al. Pharmacogenetics of hypersensitivity to abacavir: PGx hypothesis to confirmation to clinical utility? Pharmacogenomics J. 11 Mar 2008 (doi:10.1038/tpj.2008.3).

    Article  CAS  PubMed  Google Scholar 

  11. Johnson, J. R., Williams, G. & Pazdur, R. End points and United States Food and Drug Administration approval of oncology drugs. J. Clin. Oncol. 21, 1404–1411 (2003).

    Article  PubMed  Google Scholar 

  12. Lesko, L. J. Personalized medicine: elusive dream or imminent reality? Clin. Pharmacol. Ther. 81, 807–816 (2007).

    Article  CAS  PubMed  Google Scholar 

  13. Salerno, R. A. & Lesko, L. J. Three years of promise, proposals, and progress on optimizing the benefit/risk of medicines: a commentary on the 3rd FDA-DIA-PWG-PhRMA-BIO pharmacogenomics workshop. Pharmacogenomics J. 6, 78–81 (2006).

    Article  CAS  PubMed  Google Scholar 

  14. Lesko, L. J. & Woodcock, J. Pharmacogenomic-guided drug development: regulatory perspective. Pharmacogenomics J. 2, 20–24 (2002).

    Article  CAS  PubMed  Google Scholar 

  15. Goodsaid, F, & Frueh, F. W. Implementing the U. S. FDA guidance on pharmacogenomic data submissions. Environ. Mol. Mutagen. 48, 354–358 (2007).

    Article  CAS  PubMed  Google Scholar 

  16. Orr, M. S., Goodsaid, F., Amur, S., Rudman, A. & Frueh, F. W. The experience with voluntary genomic data submissions at the FDA and a vision for the future of the voluntary data submission program. Clin. Pharmacol. Ther. 81, 294–297 (2007).

    Article  CAS  PubMed  Google Scholar 

  17. Roses, A. D. Genome-wide screening for drug discovery and companion diagnostics. Expert Opin. Drug Discov. 2, 489–501 (2007).

    Article  CAS  PubMed  Google Scholar 

  18. Roses, A. D. Genome-based pharmacogenetics and the pharmaceutical industry. Nature Rev. Drug Discov. 1, 541–549 (2002).

    Article  CAS  Google Scholar 

  19. Thorisson, G. A. & Stein, L. D. The SNP Consortium website: past, present and future. Nucleic Acids Res. 31, 124–127 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Ferguson, L. R., Philpott, M. & Dryland, P. Nutrigenomics in the whole-genome scanning era: Crohn's disease as example. Cell. Mol. Life Sci. 64, 3105–3118 (2007).

    Article  CAS  PubMed  Google Scholar 

  21. Florez, J. C. The new type 2 diabetes gene TCF7L2. Curr. Opin. Clin. Nutr. Metab. Care 10, 391–396 (2007).

    Article  CAS  PubMed  Google Scholar 

  22. Frayling, T. M. Genome-wide association studies provide new insights into type 2 diabetes aetiology. Nature Rev. Genet. 8, 657–662 (2007).

    Article  CAS  PubMed  Google Scholar 

  23. Grant, S. F. & Hakonarson, H. Recent development in pharmacogenomics: from candidate genes to genome-wide association studies. Expert Rev. Mol. Diagn. 7, 371–393 (2007).

    Article  CAS  PubMed  Google Scholar 

  24. Hamet, P. & Seda, O. Current status of genome-wide scanning for hypertension. Curr. Opin. Cardiol. 22, 292–297 (2007).

    Article  PubMed  Google Scholar 

  25. Ikegawa, S. New gene associations in osteoarthritis: what do they provide, and where are we going? Curr. Opin. Rheumatol. 19, 429–434 (2007).

    Article  PubMed  Google Scholar 

  26. Ioannidis, J. P. Non-replication and inconsistency in the genome-wide association setting. Hum. Hered. 64, 203–213 (2007).

    Article  CAS  PubMed  Google Scholar 

  27. Kruglyak, L. The road to genome-wide association studies. Nature Rev. Genet. 9, 314–318 (2008).

    Article  CAS  PubMed  Google Scholar 

  28. Mathew, C. G. New links to the pathogenesis of Crohn disease provided by genome-wide association scans. Nature Rev. Genet. 9, 9–14 (2008).

    Article  CAS  PubMed  Google Scholar 

  29. Molfino, N. A. Genetic predisposition to accelerated decline of lung function in COPD. Int. J. Chron. Obstruct. Pulmon. Disord. 2, 117–119 (2007).

    Google Scholar 

  30. Owen, K. R. & McCarthy, M. I. Genetics of type 2 diabetes. Curr. Opin. Genet. Dev. 17, 239–244 (2007).

    Article  CAS  PubMed  Google Scholar 

  31. Seifart, C. & Plagens, A. Genetics of chronic obstructive pulmonary disease. Int. J. Chron. Obstruct. Pulmon. Disord. 2, 541–550 (2007).

    CAS  Google Scholar 

  32. Smoller, J. W. & Gardner-Schuster, E. Genetics of bipolar disorder. Curr. Psychiatry Rep. 9, 504–511 (2007).

    Article  PubMed  Google Scholar 

  33. Swaroop, A., Branham, K. E., Chen, W. & Abecasis, G. Genetic susceptibility to age-related macular degeneration: a paradigm for dissecting complex disease traits. Hum. Mol. Genet. 16, R174–R182 (2007).

    Article  CAS  PubMed  Google Scholar 

  34. Tremelling, M. & Parkes, M. Genome-wide association scans identify multiple confirmed susceptibility loci for Crohn's disease: lessons for study design. Inflamm. Bowel Dis. 13, 1554–1560 (2007).

    Article  PubMed  Google Scholar 

  35. Van Limbergen, J., Russell, R. K., Nimmo, E. R. & Satsangi, J. The genetics of inflammatory bowel disease. Am. J. Gastroenterol. 102, 2820–2831 (2007).

    Article  CAS  PubMed  Google Scholar 

  36. Jorgenson, E. & Witte, J. S. Genome-wide association studies of cancer. Future Oncol. 3, 419–427 (2007).

    Article  CAS  PubMed  Google Scholar 

  37. Eeles, R. A. et al. Multiple newly identified loci associated with prostate cancer susceptibility. Nature Genet. 40, 316–321 (2008).

    Article  CAS  PubMed  Google Scholar 

  38. Thomas, G. et al. Multiple loci identified in a genome-wide association study of prostate cancer. Nature Genet. 40, 310–315 (2008).

    Article  CAS  PubMed  Google Scholar 

  39. McCarthy, M. I. et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nature Rev. Genet. 9, 356–369 (2008).

    Article  CAS  PubMed  Google Scholar 

  40. Taylor, K. D., Norris, J. M. & Rotter, J. I. Genome-wide association: which do you want first: the good news, the bad news, or the good news? Diabetes 56, 2844–2848 (2007).

    Article  CAS  PubMed  Google Scholar 

  41. Curtis, D., Vine, A. E. & Knight, J. A pragmatic suggestion for dealing with results for candidate genes obtained from genome wide association studies. BMC Genet. 8, 20 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Vollenweider, P. et al. Health examination survey of the Lausanne population: first results of the CoLaus study. Rev. Med. Suisse 2, 2528–2530 (2006) (in French).

    CAS  PubMed  Google Scholar 

  43. Hurrell, C. et al. High prevalence of major cardiovascular risk factors in first-degree relatives of individuals with familial premature coronary artery disease — the GENECARD project. Atherosclerosis 194, 253–264 (2007).

    Article  CAS  PubMed  Google Scholar 

  44. Hauser, E. R. et al. Design of the genetics of early onset cardiovascular disease (GENECARD) study. Am. Heart J. 145, 602–613 (2003).

    Article  PubMed  Google Scholar 

  45. Zanke, B. W. et al. Genome-wide association scan identifies a colorectal cancer susceptibility locus on chromosome 8q24. Nature Genet. 39, 989–994 (2007).

    Article  CAS  PubMed  Google Scholar 

  46. Warren, L. L. et al. Use of pairwise marker combination and recursive partitioning in a pharmacogenetic genome-wide scan. Pharmacogenomics J. 7, 180–189 (2007).

    Article  CAS  PubMed  Google Scholar 

  47. Zeggini, E. et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science 316, 1336–1341 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Sladek, R. et al. A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 445, 881–885 (2007).

    Article  CAS  PubMed  Google Scholar 

  49. North, B. V. et al. Further investigation of linkage disequilibrium SNPs and their ability to identify associated susceptibility loci. Ann. Hum. Genet. 68, 240–248 (2004).

    Article  CAS  PubMed  Google Scholar 

  50. Libioulle, C. et al. Novel Crohn disease locus identified by genome-wide association maps to a gene desert on 5p13.1 and modulates expression of PTGER4. PLoS Genet. 3, e58 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661–678 (2007).

  52. Raelson, J. V. et al. Genome-wide association study for Crohn's disease in the Quebec Founder Population identifies multiple validated disease loci. Proc. Natl Acad. Sci. USA 104, 14747–14752 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Coon, K. D. et al. A high-density whole-genome association study reveals that APOE is the major susceptibility gene for sporadic late-onset Alzheimer's disease. J. Clin. Psychiatry 68, 613–618 (2007).

    Article  CAS  PubMed  Google Scholar 

  54. Scott, L. J. et al. A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 316, 1341–1345 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Hunter, D. J. et al. A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer. Nature Genet. 39, 870–874 (2007).

    Article  CAS  PubMed  Google Scholar 

  56. Schymick, J. C. et al. Genome-wide genotyping in amyotrophic lateral sclerosis and neurologically normal controls: first stage analysis and public release of data. Lancet Neurol. 6, 322–328 (2007).

    Article  CAS  PubMed  Google Scholar 

  57. Li, H. et al. Candidate single-nucleotide polymorphisms from a genomewide association study of Alzheimer disease. Arch. Neurol. 65, 45–53 (2008).

    Article  PubMed  Google Scholar 

  58. Roses, A. D., St Jean, P. L. & Ehm, M. G. Use of whole-genome association scans in disease gene identification, drug discovery and development. IDrugs 10, 797–804 (2007).

    CAS  PubMed  Google Scholar 

  59. Meng, Y. et al. Association between SORL1 and Alzheimer's disease in a genome-wide study. Neuroreport 18, 1761–1764 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Dreses-Werringloer, U. et al. A polymorphism in CALHM1 influences Ca2+ homeostasis, Ab levels, and Alzheimer's disease risk. Cell 133, 1149–1161 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Editorial. Freely associating. Nature Genet. 22, 1–2 (1999).

  62. Rebbeck, T. R., Khoury, M. J. & Potter, J. D. Genetic association studies of cancer: where do we go from here? Cancer Epidemiol. Biomarkers Prev. 16, 864–865 (2007).

    Article  PubMed  Google Scholar 

  63. Rebbeck, T. R. et al. Genetic variation and cancer: improving the environment for publication of association studies. Cancer Epidemiol. Biomarkers Prev. 13, 1985–1986 (2004).

    PubMed  Google Scholar 

  64. Sakharkar, M. K., Sakharkar, K. R. & Pervaiz, S. Druggability of human disease genes. Int. J. Biochem. Cell Biol. 39, 1156–1164 (2007).

    Article  CAS  PubMed  Google Scholar 

  65. Saunders, A. M. et al. The role of apolipoprotein E in Alzheimer's disease: pharmacogenomic target selection. Biochim. Biophys. Acta 1502, 85–94 (2000).

    Article  CAS  PubMed  Google Scholar 

  66. Roses, A. D. et al. Complex disease-associated pharmacogenetics: drug efficacy, drug safety, and confirmation of a pathogenetic hypothesis (Alzheimer's disease). Pharmacogenomics J. 7, 10–28 (2007).

    Article  CAS  PubMed  Google Scholar 

  67. Mallal, S. et al. Association between presence of HLA-B*5701, HLA-DR7, and HLA-DQ3 and hypersensitivity to HIV-1 reverse-transcriptase inhibitor abacavir. Lancet 359, 727–732 (2002).

    Article  CAS  PubMed  Google Scholar 

  68. Hetherington, S. et al. Genetic variations in HLA-B region and hypersensitivity reactions to abacavir. Lancet 359, 1121–1122 (2002).

    Article  CAS  PubMed  Google Scholar 

  69. Hammond, E. et al. External quality assessment of HLA-B*5701 reporting: an international multicentre survey. Antiv. Ther. 12, 1027–1032 (2007).

    Article  CAS  Google Scholar 

  70. Faruki, H., Heine, U., Brown, T., Koester, R. & Lai-Goldman M. HLA-B*5701 clinical testing: early experience in the United States. Pharmacogenet. Genomics 17, 857–860 (2007).

    Article  CAS  PubMed  Google Scholar 

  71. Jordan, J. et al. Stimulation of cholecystokinin-A receptors with GI181771X does not cause weight loss in overweight or obese patients. Clin. Pharmacol. Ther. 83, 281–287 (2008).

    Article  CAS  PubMed  Google Scholar 

  72. Roses, A. Stimulation of cholecystokinin-A receptors with Gl181771X: a failed clinical trial that did not test the proposed mechanism of action. Clin. Pharmacol. Ther. (in the press).

  73. Watson, G. S. et al. Preserved cognition in patients with early Alzheimer disease and amnestic mild cognitive impairment during treatment with rosiglitazone: a preliminary study. Am. J. Geriat. Psychiatry 13, 950–958 (2005).

    Google Scholar 

  74. Pedersen, W. A. et al. Rosiglitazone attenuates learning and memory deficits in Tg2576 Alzheimer mice. Exp. Neurol. 199, 265–273 (2006).

    Article  CAS  PubMed  Google Scholar 

  75. 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  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  77. Haber, D. A. et al. Molecular targeted therapy of lung cancer: EGFR mutations and response to EGFR inhibitors. Cold Spring Harb. Symp. Quant. Biol. 70, 419–426 (2005).

    Article  CAS  PubMed  Google Scholar 

  78. Welsch, T., Kleeff, J. & Friess, H. Molecular pathogenesis of pancreatic cancer: advances and challenges. Curr. Mol. Med. 7, 504–521 (2007).

    Article  CAS  PubMed  Google Scholar 

  79. Kato, S. et al. PIK3CA mutation is predictive of poor survival in patients with colorectal cancer. Int. J. Cancer 121, 1771–1778 (2007).

    Article  CAS  PubMed  Google Scholar 

  80. Amado, R. G. et al. Wild-type KRAS is required for panitumumab efficacy in patients with metastatic colorectal cancer. J. Clin. Oncol. 26, 1626–1634 (2008).

    Article  CAS  PubMed  Google Scholar 

  81. US Food and Drug Administration (FDA)/Center for Drug Evaluation and Research. FDA approves Vectibix (panitumumab) to treat metastatic colorectal carcinoma. FDA web site [online], (2006).

  82. Bilancia, D. et al. Lapatinib in breast cancer. Ann. Oncol. 18 (Suppl. 6), vi26–vi30 (2007).

    Article  PubMed  Google Scholar 

  83. Moy, B. & Goss, P. E. Lapatinib-associated toxicity and practical management recommendations. Oncologist 12, 756–765 (2007).

    Article  CAS  PubMed  Google Scholar 

  84. Geyer, C. E. et al. Lapatinib plus capecitabine for HER2-positive advanced breast cancer. N. Engl. J. Med. 355, 2733–2743 (2006).

    Article  CAS  PubMed  Google Scholar 

  85. Zaks, T. Z. et al. Role of pharmacogenetic studies in early clinical development: Phase I studies with lapatinib. J. Clin. Oncol. 24 (Suppl. 18), 3029 (2006).

    Article  Google Scholar 

  86. Wang, L. & Weinshilboum, R. Thiopurine S-methyltransferase pharmacogenetics: insights, challenges and future directions. Oncogene 25, 1629–1638 (2006).

    Article  CAS  PubMed  Google Scholar 

  87. Dervieux, T. et al. Differing contribution of thiopurine methyltransferase to mercaptopurine versus thioguanine effects in human leukemic cells. Cancer Res. 61, 5810–5816 (2001).

    CAS  PubMed  Google Scholar 

  88. Evans, W. E. et al. Preponderance of thiopurine S-methyltransferase deficiency and heterozygosity among patients intolerant to mercaptopurine or azathioprine. J. Clin. Oncol. 19, 2293–2301 (2001).

    Article  CAS  PubMed  Google Scholar 

  89. Coulthard, S. & Hogarth, L. The thiopurines: an update. Invest. New Drugs 23, 523–532 (2005).

    Article  CAS  PubMed  Google Scholar 

  90. Lennard, L. & Lilleyman, J. S. Individualizing therapy with 6-mercaptopurine and 6-thioguanine related to the thiopurine methyltransferase genetic polymorphism. Ther. Drug Monit. 18, 328–334 (1996).

    Article  CAS  PubMed  Google Scholar 

  91. Oldenburg, J. et al. Current pharmacogenetic developments in oral anticoagulation therapy: the influence of variant VKORC1 and CYP2C9 alleles. Thromb. Haemost. 98, 570–578 (2007).

    Article  CAS  PubMed  Google Scholar 

  92. Harrington, D. J. et al. Pharmacodynamic resistance to warfarin associated with a Val66Met substitution in vitamin K epoxide reductase complex subunit 1. Thromb. Haemost. 93, 23–26 (2005).

    Article  CAS  PubMed  Google Scholar 

  93. Rost, S. et al. Mutations in VKORC1 cause warfarin resistance and multiple coagulation factor deficiency type 2. Nature 427, 537–541 (2004).

    Article  CAS  PubMed  Google Scholar 

  94. Roses, A. “Personalized medicine: elusive dream or imminent reality?”: A commentary. Clin. Pharmacol. Ther. 81, 801–805 (2007).

    Article  CAS  PubMed  Google Scholar 

  95. Mallal, S. et al. HLA-B*5701 screening for hypersensititvy to abacivar. N. Engl. J. Med. 358, 568–579 (2008).

    Article  PubMed  Google Scholar 

  96. Hetherington, S. et al. Hypersensitivity reactions during therapy with the nucleoside reverse transcriptase inhibitor abacavir. Clin. Ther. 23, 1603–1614 (2001).

    Article  CAS  PubMed  Google Scholar 

  97. [No authors listed]. New drug, antibiotic, and biological drug product regulations; accelerated approval — FDA. Final rule. Fed. Regist. 57, 58942–58960 (1992).

  98. Shapiro, M., Ward, K. M. & Stern, J. J. A near-fatal hypersensitivity reaction to abacavir: case report and literature review. AIDS Read. 11, 222–226 (2001).

    CAS  PubMed  Google Scholar 

  99. Mallal, S. et al. PREDICT-1 study: a randomized, double-blind trial to determine the clinical utility of HLA-B*5701 pharmacogenetic screening for abacavir hypersensitivity in HIV-infected patients (Study CNA106030). IAS2007 web site [online] (2007).

  100. Phillips, E. J. & Mallal, S. A. Pharmacogenetics and the potential for the individualization of antiretroviral therapy. Curr. Opin. Infect. Dis. 21, 16–24 (2008).

    Article  CAS  PubMed  Google Scholar 

  101. Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the use of antiretroviral agents in HIV-1-infected adults and adolescents. Department of Health and Human Services. AIDSinfo web site [online], (2008).

  102. Home, P. D. et al. Rosiglitazone evaluated for cardiovascular outcomes — an interim analysis. N. Engl. J. Med. 357, 28–38 (2007).

    Article  CAS  PubMed  Google Scholar 

  103. Nissen, S. E,. Wolski, K,. Nissen, S. E. & Wolski, K. Effect of rosiglitazone on the risk of myocardial infarction and death from cardiovascular causes. N. Engl. J. Med. 356, 2457–2471 (2007).

    Article  CAS  PubMed  Google Scholar 

  104. McAdams, M., Staffa, J. & Dal Pan, G. Estimating the extent of reporting to FDA: a case study of statin-associated rhabdomyolysis. Pharmacoepidemiol. Drug Saf. 17, 229–239 (2008).

    Article  CAS  PubMed  Google Scholar 

  105. Aagaard, L., Soendergaard, B., Stenver, D. I. & Hansen, E. H. Knowledge creation about ADRs — turning the perspective from the rear mirror to the projector? Br. J. Clin. Pharmacol. 65, 364–376 (2008).

    Article  PubMed  Google Scholar 

  106. Gibson, B. R., Suh, R. & Tilson, H. The US drug safety system: role of the pharmaceutical industry. Pharmacoepidemiol. Drug Saf. 17, 110–114 (2008).

    Article  PubMed  Google Scholar 

  107. Drazen, J. M., Morrissey, S. & Curfman, G. D. Rosiglitazone — continued uncertainty about safety. N. Engl. J. Med. 357, 63–64 (2007).

    Article  CAS  PubMed  Google Scholar 

  108. Holden, A. L. The SNP consortium: summary of a private consortium effort to develop an applied map of the human genome. Biotechniques (Suppl.), 22–24 (2002).

  109. International HapMap Consortium et al. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851–861 (2007).

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

  111. Drews, J. Drug discovery: a historical perspective. Science 287, 1960–1964 (2000).

    Article  CAS  PubMed  Google Scholar 

  112. Hauser, E. R. et al. A genomewide scan for early-onset coronary artery disease in 438 families: the GENECARD Study. Am. J. Hum. Genet. 75, 436–447 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Grupe, A. et al. Evidence for novel susceptibility genes for late-onset Alzheimer's disease from a genome-wide association study of putative functional variants. Hum. Mol. Genet. 16, 865–873 (2007).

    Article  CAS  PubMed  Google Scholar 

  114. Bierut, L. J. et al. Novel genes identified in a high-density genome wide association study for nicotine dependence. Hum. Mol. Genet. 16, 24–35 (2007).

    Article  CAS  PubMed  Google Scholar 

  115. Hampe, J. et al. A genome-wide association scan of nonsynonymous SNPs identifies a susceptibility variant for Crohn disease in ATG16L1. Nature Genet. 39, 207–211 (2007).

    Article  CAS  PubMed  Google Scholar 

  116. Seshadri, S. et al. Genetic correlates of brain aging on MRI and cognitive test measures: a genome-wide association and linkage analysis in the Framingham Study. BMC Med. Genet. 8, (Suppl. 1), S15 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  117. Lai, E., Riley, J., Purvis, I. & Roses, A. A 4-Mb high-density single nucleotide polymorphism-based map around human APOE. Genomics 54, 31–38 (1998).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  119. Pericak-Vance, M. A. et al. Linkage studies in familial Alzheimer disease: evidence for chromosome 19 linkage. Am. J. Hum. Genet. 48, 1034–1050 (1991).

    CAS  PubMed  PubMed Central  Google Scholar 

  120. Saunders, A. M. & Roses, A. D. Apolipoprotein E4 allele frequency, ischemic cerebrovascular disease, and Alzheimer's disease. Stroke 24, 1416–1417 (1993).

    Article  CAS  PubMed  Google Scholar 

  121. Corder, E. H. et al. Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer's disease in late onset families. Science 261, 921–923 (1993).

    Article  CAS  PubMed  Google Scholar 

  122. Roses, A. D. Genetic testing for Alzheimer disease. Practical and ethical issues. Arch. Neurol. 54, 1226–1229 (1997).

    Article  CAS  PubMed  Google Scholar 

  123. Collins, F. & Galas, D. A new five-year plan for the U. S. Human Genome Project. Science 262, 43–46 (1993).

    Article  CAS  PubMed  Google Scholar 

  124. Chang, S. et al. Lipid- and receptor-binding regions of apolipoprotein E4 fragments act in concert to cause mitochondrial dysfunction and neurotoxicity. Proc. Natl Acad. Sci. USA 102, 18694–18699 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Huang, Y. et al. Apolipoprotein E fragments present in Alzheimer's disease brains induce neurofibrillary tangle-like intracellular inclusions in neurons. Proc. Natl Acad. Sci. USA 98, 8838–8843 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Roses, A. D. et al. Cis-acting human ApoE tissue expression element is associated with human pattern of intraneuronal ApoE in transgenic mice. Neurobiol. Aging 19 (Suppl. 1), S53–S58 (1999).

    Google Scholar 

  127. Hirschhorn, J. N., Lohmueller, K., Byrne, E. & Hirschhorn, K. A comprehensive review of genetic association studies. Genet. Med. 4, 45–61 (2002).

    Article  CAS  PubMed  Google Scholar 

  128. Yu, C. E. et al. Comprehensive analysis of APOE and selected proximate markers for late-onset Alzheimer's disease: patterns of linkage disequilibrium and disease/marker association. Genomics 89, 655–665 (2007).

    Article  CAS  PubMed  Google Scholar 

  129. Mahley, R. W., Weisgraber, K. H. & Huang, Y. Apolipoprotein E4: a causative factor and therapeutic target in neuropathology, including Alzheimer's disease. Proc. Natl Acad. Sci. USA 103, 5644–5651 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Xu, Q. et al. Profile and regulation of apolipoprotein E (ApoE) expression in the CNS in mice with targeting of green fluorescent protein gene to the ApoE locus. J. Neurosci. 26, 4985–4994 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Grant, S. F. et al. Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes. Nature Genet. 38, 320–323 (2006).

    Article  CAS  PubMed  Google Scholar 

  132. Helgason, A. et al. Refining the impact of TCF7L2 gene variants on type 2 diabetes and adaptive evolution. Nature Genet. 39, 218–225 (2007).

    Article  CAS  PubMed  Google Scholar 

  133. Chissoe, S. Genes associated with type II diabetes mellitus. WO2007027630 A2 (patent pending) (2007).

  134. 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  PubMed  Google Scholar 

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Acknowledgements

I thank T. Yamada and J. Niedel who supported a Genetics Research Directorate within a large pharmaceutical company, and the hundreds of scientists and physicians at GlaxoSmithKline in genetics research whose dedication and work provided the impetus for the data generated as examples of pharmacogenetics projects. The support of GlaxoSmithKline during a rapidly changing period of technology growth and change had a profound impact on the formation of the SNP Consortium and the Severe Adverse Event Consortium. I also thank the Duke University School of Medicine and the Fuqua School of Business for enabling the establishment of the Deane Drug Discovery Institute as part of the Institute for Genome Sciences and Policy. The Institute operates as a virtual pharmaceutical company owned by a not-for-profit institution with no public shareholders.

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Allen D. Roses retired from GlaxoSmithKline in October 2007 and has founded a private pharmacogenetic consultation and project management company, Cabernet Pharmaceuticals, Inc. Cabernet has multiple service contracts for pipeline PGx with several biotechnical and pharmaceutical companies. He holds stock options of GlaxoSmithKline until September 2009. He was a member of the FDA Science Board for 4 years and currently consults for the FDA.

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DATABASES

OMIM

Alzheimer's disease

Crohn's disease

non-small-cell lung cancer

type 2 diabetes mellitus

FURTHER INFORMATION

FDA Science and Mission at Risk

Guidance for Industry: E15 Definitions for Genomic Biomarkers, Pharmacogenomics, Pharmacogenetics, Genomic Data and Sample Coding Categories

Guidance for Industry and FDA. Staff Pharmacogenetic Tests and Genetic Tests for Heritable Markers

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Roses, A. Pharmacogenetics in drug discovery and development: a translational perspective. Nat Rev Drug Discov 7, 807–817 (2008). https://doi.org/10.1038/nrd2593

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