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Special Focus on the 4th Biologie Prospective Santorini Conference: Functional Genomics Towards Personalized Healthcare - Perspective

Pharmacogenomics of adverse drug reactions: practical applications and perspectives

    Laurent Becquemont

    Université Paris Sud, Clinical Pharmacology Department, APHP, Hô pital Bicêtre, 78 rue du Général leclerc, 94275 Le Kremlin Bicêtre, France.

    Published Online:https://doi.org/10.2217/pgs.09.37

    Serious adverse drug reactions represent the sixth major cause of death in the USA, are the main reason for postmarketing drug withdrawal and represent billions of US dollars in costs every year in all developed countries. Some of these serious adverse drug reactions might be avoided by systematically screening for pharmacogenomic risk factors. During the last few years, regulatory agencies introduced pharmacogenomics labels for several drugs, but although a priori genetic testing remains advised or recommended, it is seldom compulsory due to poor evidence-based medicine knowledge. Recently published pharmacogenomic randomized, controlled and ongoing trials will progressively make genotyping tests, such as those for HLA-B*5701 (abacavir), TPMT (6-mercaptopurine), CYP2C9 plus VKORC1 (warfarin) and CYP3A5 (tacrolimus), mandatory. Parallel development of pharmacogenomic bed tests will certainly establish genetically-based prescriptions in routine medical practice.

    Papers of special note have been highlighted as: ▪ of interest ▪▪ of considerable interest

    Bibliography

    • Lazarou J, Pomeranz BH, Corey PN: Incidence of adverse drug reactions in hospitalized patients: a meta-analysis of prospective studies. JAMA279,1200–1205 (1998).▪ Excellent meta-analysis of 39 prospective studies from US hospitals assessing the incidence of serious adverse drug reactions, which can be evaluated as the sixth leading cause of mortaility in the USA.
    • Moore T, Cohen M, Furberg C: Serious adverse drug events reported to the food and drug administration, 1998–2005. Arch. Intern. Med.167,1752–1759 (2008).
    • Pirmohamed M, James S, Meakin S et al.: Adverse drug reactions as cause of admission to hospital: prospective analysis of 18,820 patients. BMJ329,15–19 (2004).▪ Excellent observational study including 18,820 patients admitted over 6 months in two large English hospitals. Provides prevalence of admissions due to adverse drug reactions and the incurred cost.
    • DiMasi J: Risks in new drug development: approval success rates for investigational drugs. Clin. Pharmacol. Ther.69,297–307 (2001).
    • Wysowski D, Swartz L: Adverse drug event surveillance and drug withdrawals in the United States, 1969–2002. Arch. Intern. Med.165,1363–1369 (2005).
    • Meyer UA: Pharmacogenetics – five decades of therapeutic lessons from genetic diversity. Nat. Rev. Genet.5,669–675 (2004).
    • Frueh F, Amur S, Mummaneni P et al.: Pharmacogenomic biomarker information in drug labels approved by the United States food and drug administration: prevalence of related drug use. Pharmacotherapy28,992–998 (2008).
    • Wilke R, Lin D, Roden D et al.: Identifying genetic risk factors for serious adverse drug reactions: current progress and challenges. Nat. Rev. Drug Discov.6,904–916 (2007).
    • Colhoun HM, McKeigue PM, Davey Smith G: Problems of reporting genetic associations with complex outcomes. Lancet361,865–872 (2003).▪▪ Review discussing the methodologic pitfalls of pharmacogenomic association studies leading to poor reproducibility of the results of numerous studies
    • 10  Anderson J, Horne B, Stevens S et al.: Randomized trial of genotype-guided versus standard warfarin dosing in patients initiating oral anticoagulation. Circulation116,2563–2570 (2007).
    • 11  Behre H, Greb R, Mempel A et al.: Significance of a common single nucleotide polymorphism in exon 10 of the follicle-stimulating hormone (FSH) receptor gene for the ovarian response to FSH: a pharmacogenetic approach to controlled ovarian hyperstimulation. Pharmacogenet. Genomics15,451–456 (2005).
    • 12  Caraco Y, Blotnick S, Muszkat M: CYP2C9 genotype-guided warfarin prescribing enhances the efficacy and safety of anticoagulation: a prospective randomized controlled study. Clin. Pharmacol. Ther.83,460–470 (2008).
    • 13  Furuta T, Shirai N, Kodaira M et al.: Pharmacogenomics-based tailored versus standard therapeutic regimen for eradication of H. pylori. Clin. Pharmacol. Ther.81,521–528 (2007).
    • 14  Hillman MA, Wilke RA, Yale SH et al.: A prospective, randomized pilot trial of model-based warfarin dose initiation using CYP2C9 genotype and clinical data. Clin. Med. Res.3,137–145 (2005).
    • 15  Mallal S, Phillips E, Carosi G et al.: HLA-B*5701 screening for hypersensitivity to abacavir. N. Engl. J. Med.358,568–579 (2008).▪▪ Largest randomized, controlled trial in pharmacogenomics demonstrating the usefulness of HLA-B*5701 screening to prevent hypersensitivity reactions to abacavir. Reports a 100% predictive positive value.
    • 16  Quteineh L, Verstuyft C, Furlan V et al.: Influence of CYP3A5 genetic polymorphism on tacrolimus daily requirements, acute rejection and nephrotoxicity in renal graft recipients. Basic Clin. Pharmacol. Toxicol.103,546–552 (2008).
    • 17  Macphee I, Fredericks S, Tai T et al.: Tacrolimus pharmacogenetics: polymorphisms associated with expression of cytochrome p4503A5 and P-glycoprotein correlate with dose requirement. Transplantation74,1486–1489 (2002).
    • 18  Anglicheau D, Legendre C, Beaune P, Thervet E: Cytochrome P450 3A polymorphisms and immunosuppressive drugs: an update. Pharmacogenomics8,835–849 (2007).
    • 19  Llerena A, Michel G, Jeannesson E et al.: Third Santorini conference pharmacogenomics workshop report: ‘Pharmacogenomics at the crossroads: what else than good science will be needed for the field to become part of Personalized Medicine?’ Clin. Chem. Lab. Med.45,843–850 (2007).
    • 20  Owen R, Klein T, Altman R: The education potential of the pharmacogenetics and pharmacogenomics knowledge base (PharmGKB). Clin. Pharmacol. Ther.82,472–475 (2007).
    • 21  Patel K, Babyatsky M: Medical education: a key partner in realizing personalized medicine in gastroenterology. Gastroenterology134,656–661 (2008).
    • 22  Shields A, Lerman C: Anticipating clinical integration of pharmacogenetic treatment strategies for addiction: are primary care physicians ready? Clin. Pharmacol. Ther.83,635–639 (2008).
    • 23  Deverka P, McLeod H: Harnessing economic drivers for successful clinical implementation of pharmacogenetic testing. Clin. Pharmacol. Ther.84,191–193 (2008).
    • 24  Vegter S, Boersma C, Rozenbaum M, Wilffert B, Navis G, Postma M: Pharmacoeconomic evaluations of pharmacogenetic and genomic screening programmes: a systematic review on content and adherence to guidelines. Pharmacoeconomics26,569–587 (2008).
    • 25  Criswell LA, Lum RF, Turner KN et al.: The influence of genetic variation in the HLA-DRB1 and LTA-TNF regions on the response to treatment of early rheumatoid arthritis with methotrexate or etanercept. Arthritis Rheum.50,2750–2756 (2004).
    • 26  Ferrell P, McLeod H: Carbamazepine, HLA-B*1502 and risk of Stevens–Johnson syndrome and toxic epidermal necrolysis: US FDA recommendations. Pharmacogenomics9,1543–1546 (2008).
    • 27  Hung S, Chung W, Liou L et al.: HLA-B*5801 allele as a genetic marker for severe cutaneous adverse reactions caused by allopurinol. Proc. Natl Acad. Sci. USA102,4134–4139 (2005).
    • 28  Gatanaga H, Honda H, Oka S: Pharmacogenetic information derived from analysis of HLA alleles. Pharmacogenomics9,207–214 (2008).▪▪ Review on the different HLA alleles predictive of drug response.
    • 29  Young B, Squires K, Patel P et al.: First large, multicenter, open-label study utilizing HLA-B*5701 screening for abacavir hypersensitivity in North America. AIDS22,1673–1675 (2008).
    • 30  Rauch A, Nolan D, Martin A, McKinnon E, Almeida C, Mallal S: Prospective genetic screening decreases the incidence of abacavir hypersensitivity reactions in the Western Australian HIV cohort study. Clin. Infect. Dis.43,99–102 (2006).
    • 31  Zucman D, Truchis P, Majerholc C, Stegman S, Caillat-Zucman S: Prospective screening for human leukocyte antigen-B*5701 avoids abacavir hypersensitivity reaction in the ethnically mixed French HIV population. J. Acquir. Immune Defic. Syndr.45,1–3 (2007).
    • 32  Schackman B, Scott C, Walensky R, Losina E, Reedberg K, Sax P: The cost-effectiveness of HLA-B*5701 genetic screening to guide initial antiretroviral therapy for HIV. AIDS22,2025–2033 (2008).
    • 33  Horton R, Wilming L, Rand V et al.: Gene map of the extended major histocompatibility complex. Nat. Rev. Genet.5,889–899 (2004).
    • 34  Ingelman -Sundberg M: Pharmacogenomic biomarkers for prediction of severe adverse dreug reactions. N. Engl. J. Med.358,637–639 (2008).
    • 35  Klein R: Power analysis for genome-wide association studies. BMC Genet.8,58 (2007).
    • 36  Li Q, Zheng G, Li Z, Yu KS: Efficient approximation of p-value of the maximum of correlated tests, with applications to genome-wide association studies. Ann. Hum. Genet.72,397–406 (2008).
    • 37  Nelson M, Bacanu S-A, Mosteller M et al.: Genome-wide approaches to identify pharmacogenetic contributions to adverse drug reactions. Pharmacogenomics J.9,23–33 (2008).▪▪ Excellent review on the methodological aspects of genome-wide association studies and study power, providing the major determinants of the number of patients to include.
    • 38  Link E, Parish S, Armitage J et al.: SLCO1B1 variants and statin-induced myopathy – a genomewide study. N. Engl. J. Med.359,789–799 (2008).▪ Genome-wide association study that clearly demonstrates that SLC01B1 is related to statin myopathy.
    • 39  Kameyama Y, Yamashita K, Kobayashi K, Hosokawa M, Chiba K: Functional characterization of SLCO1B1 (OATP-C) variants, SLCO1B1*5, SLCO1B1*15 and SLCO1B1*15+C1007G, by using transient expression systems of HeLa and HEK293 cells. Pharmacogenet. Genomics15,513–522 (2005).
    • 40  Neuvonen PJ, Backman JT, Niemi M: Pharmacokinetic comparison of the potential over-the-counter statins simvastatin, lovastatin, fluvastatin and pravastatin. Clin. Pharmacokinet.47,463–474 (2008).
    • 41  Pasanen MK, Neuvonen M, Neuvonen PJ, Niemi M: SLCO1B1 polymorphism markedly affects the pharmacokinetics of simvastatin acid. Pharmacogenet. Genomics16,873–879 (2006).
    • 42  Wolfberg A: Genes on the Web – direct-to-consumer marketing of genetic testing. N. Engl. J. Med.345,543–545 (2006).
    • 43  Mega J, Close S, Wiviott S et al.: Cytochrome p-450 polymorphisms and response to clopidogrel. N. Engl. J. Med.360,354–362 (2009).
    • 44  Simon T, Verstuyft C, Mary-Krause M et al.: Genetic determinants of response to clopidogrel and cardiovascular events. N. Engl. J. Med.360,363–375 (2009).
    • 45  Mardis E: The impact of next-generation sequencing technology on genetics. Trends Genet.24,133–141 (2008).
    • 46  Chung W, Hung S, Hong H et al.: Medical genetics: a marker for Stevens–Johnson syndrome. Nature428,486 (2004).
    • 47  Donaldson P, Bhatnagar P, Graham J et al.: Flucloxacillin-induced liver injury: the extended MHC 57.1 haplotype as a major risk factor. Hepatology48,396A–397A (2008).
    • 48  Hoskins J, Goldberg R, Qu P, Ibrahim J, McLeod H: UGT1A1*28 genotype and irinotecan-induced neutropenia: dose matters. J. Natl Cancer Inst.99,1290–1295 (2007).
    • 49  Côté J, Kirzin S, Kramar A et al.: UGT1A1 polymorphism can predict hematologic toxicity in patients treated with irinotecan. J. Clin. Oncol.13,3269–3275 (2007).
    • 50  Martin A, Nolan D, James I et al.: Predisposition to nevirapine hypersensitivity associated with HLA-DRB1*0101 and abrogated by low CD4 T-cell counts. AIDS19,97–99 (2005).
    • 51  Littera R, Carcassi C, Masala A et al.: HLA-dependent hypersensitivity to nevirapine in Sardinian HIV patients. AIDS20,1624–1626 (2006).
    • 52  Quteineh L, Verstuyft C, Descot C et al.: Vitamin K epoxide reductase (VKORC1) genetic polymorphism is associated to oral anticoagulant overdose. Thromb. Haemost.94,690–691 (2005).
    • 53  Lucena M, Andrade R, Martínez C et al.: Glutathione S-transferase m1 and t1 null genotypes increase susceptibility to idiosyncratic drug-induced liver injury. Hepatology48,588–596 (2009).
    • 54  Daly A, Aithal G, Leathart J, Swainsbury R, Dang T, Day C: Genetic susceptibility to diclofenac-induced hepatotoxicity: contribution of UGT2B7, CYP2C8, and ABCC2 genotypes. Gastroenterology132,272–281 (2007).
    • 55  Huang YS, Chern H, Su WJ et al.: Polymorphism of the N-acetyltransferase 2 gene as a susceptibility risk factor for antituberculosis drug-induced hepatitis. Hepatology35,883–889 (2002).
    • 56  Possuelo L, Castelan J, de Brito T et al.: Association of slow N-acetyltransferase 2 profile and anti-TB drug-induced hepatotoxicity in patients from Southern Brazil. Eur. J. Clin. Pharmacol.64,673–681 (2008).
    • 57  Kindmark A, Jawaid A, Harbron C et al.: Genome-wide pharmacogenetic investigation of a hepatic adverse event without clinical signs of immunopathology suggests an underlying immune pathogenesis. Pharmacogenomics J.8,186–195 (2008).
    • 58  Simon T, Becquemont L, Mary-Krause M et al.: Combined glutathione-S-transferase M1 and T1 genetic polymorphism and tacrine hepatotoxicity. Clin. Pharmacol. Ther.67,432–437 (2000).
    • 101  Tacrolimus in renal transplantation: individualization by pharmacogenetic www.clinicaltrials.gov/ct2/show/NCT00552201
    • 102  Registry of federally and privately supported clinical trials conducted in the USA and around the world www.clinicaltrials.gov
    • 103  International warfarin pharmacogenetics consortium. Provides an algorithm which predicts the warferin daily dose requirement based on pharmacogenetic and clinical factors www.warfarindosing.org
    • 104  US FDA Center of Drug Evaluation and Research where the drug product characteristics, including pharmacogenomics labels, are updated www.fda.gov/cder/genomics/
    • 105  European Medicines Agency www.emea.europa.eu/