Pharmacogenomics: Increasing the safety and effectiveness ...

Pharmacogenomics:Increasing the safety and effectiveness of drug therapy

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Introduction to personalized medicine

The goal of personalized medicine is to individualize health care by using knowledge of patients’ health history, behaviors, environments, and, most importantly, genetic variation when making clinical decisions. Research on genetics has provided advances that can be used to more accurately predict the risk of developing certain diseases, personalize screening and surveillance protocols and, in some cases, prevent the onset of disease. In certain cases, genetics can also be used to diagnose diseases and tailor therapies and disease management strategies. These advancements in personalized medicine rely on knowledge of how a patient’s genotype (genetic makeup) influences his or her phenotype (observable traits or characteristics). Using the principles of personalized medicine, health care providers may be better equipped to move beyond the “one-size-fits-all” approach that defined much of patient care in the past, to care that is appropriate for unique patient subgroups.1

Pharmacogenomics

One of the most important components of personalized medicine is pharmacogenomics, the study of genetic variations that influence individual response to drugs. Enzymes responsible for drug metabolism and proteins that determine the cellular response to drugs (receptors) are encoded by genes, and can therefore be variable in expression, activity level and function when genetic variations are present. Knowing whether a patient carries any of these variations may help health care professionals individualize drug therapy, decrease the number of adverse drug reactions and increase the effectiveness of drugs. Pharmacogenomics has been characterized as “getting the right dose of the right drug to the right patient at the right time.”2 This brochure is intended to introduce the concept of pharmacogenomics to physicians and other health care providers using a case-based approach. Note that the terms “pharmacogenomics” and “pharmacogenetics” are often used interchangeably; for this brochure, “pharmacogenomics” will be used.

Genes commonly involved in pharmacogenomic drug metabolism and response

There are several genes responsible for differences in drug metabolism and response. Among the most common are the Cytochrome P450 (CYP) genes, encoding enzymes that control the metabolism of more than 70 percent of prescription drugs. People who carry variations in certain CYP genes often do not metabolize drugs at the same rate or extent as in most people, and this can influence response in many ways. Other genes known to affect drug response encode the receptors for regulatory molecules such as neurotransmitters, hormones, cytokines and growth factors, and cellular proteins such as enzymes, transporters, carriers, ion channels, structural proteins and transcription factors. Variations in these genes can lead to poor response and adverse drug reactions by disabling, inactivating, interfering with, or inaccurately inducing the signaling mechanisms or cellular machinery that must function for the body to respond properly to the drug; or by causing side effects that prevent continued use of the drug.

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Selected drugs whose safety and efficacy are affected by gene variations

The table below is a partial list of drugs that exhibit reduced therapeutic effectiveness and/or safety concerns in patients carrying certain genetic variations. These variations often make the drug unsafe or unsuitable for patients who carry the variations. This list contains examples of drugs that are affected by inherited genetic variations and by variations that are acquired and present in tumor tissue.

Drug Gene(s) Drug Gene(s)

Clopidogrel (Plavix®) CYP2C19 Azathiopurine (Imuran®) TPMT

Atomoxetine (Strattera®) CYP2D6 Irinotecan (Camptosar®) UGT1A1

Codeine CYP2D6 Cetuximab (Erbitux®)* EGFR

Tamoxifen (Nolvadex®) CYP2D6 Erlotinib (Tarceva®)* EGFR

Warfarin (Coumadin®) CYP2C9, VKORC1 Imatinib mesylate (Gleevec®)* C-KIT

Abacavir (Ziagen®) HLA-B*5701 Panitumumab (Vectibix®)* KRAS

Carbamazepine (Tegretol®) HLA-B*1502 Trastuzumab (Herceptin®)* Her2/neu

* Response to these drugs is dependent on genetic variations that are present in tumor tissue.

Adapted from U.S. Food and Drug Administration website (www.fda.gov/Drugs/ScienceResearch/ResearchAreas/Pharmacogenetics/ucm083378.htm). Accessed February 7, 2011.

Metabolizer phenotype

The metabolizer phenotype describes the patient’s ability to metabolize certain drugs and is based on the number and type of functional alleles of certain genes that a patient carries. These genes most commonly encode the CYP enzymes, which are the focus of much of this brochure. The metabolizer phenotype can range from “poor,” used to describe patients with little or no functional activity of a selected CYP enzyme, to “ultra-rapid,” used to describe patients with substantially increased activity of a selected CYP enzyme. Depending on the type of CYP variation present, the patient’s metabolizer phenotype and the type of drug (active pharmacologic agent or inactive prodrug precursor), therapeutic drug response is often suboptimal. The table on the following page summarizes the effects of CYP variation on therapeutic efficacy.3 For example, poor metabolizers are unable to metabolize certain drugs efficiently, resulting in a potentially toxic build-up of an active drug or the lack of conversion of a prodrug into an active metabolite. In contrast, in ultra-rapid metabolizers, an active drug is inactivated quickly, leading to a subtherapeutic response, while a prodrug is quickly metabolized, leading to rapid onset of therapeutic effect.

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Effects of CYP variants on therapeutic efficacy:

Metabolizer phenotype

Active drug (inactivated by metabolism)

Drug Inactive Metabolite

Prodrug (needs metabolism to produce active metabolite)

Prodrug Active Metabolite

Poor Increased efficacy; active metabolite may accumulate;usually require lower dose to avoid toxic accumulation

Decreased efficacy; prodrug may accumulate; may require lower dose to avoid toxic accumulation, or may require alternate drug

Ultra-rapid Decreased efficacy; active metabolite rapidly inactivated; usually require higher dose to offset inactivation

Increased efficacy;rapid onset of effect; may require lower dose to prevent excessive accumulation of active metabolite

Some drugs and foods cause altered metabolizer phenotype

Certain drugs mimic the effect of genetic variations, effectively causing changes in metabolizer phenotype. For example, quinidine is an inhibitor of CYP2D6 activity. A patient taking quinidine is therefore a CYP2D6 poor metabolizer, similar to someone who carries a loss-of function variation in CYP2D6. In those patients, drugs that require the activity of CYP2D6, such as atomoxetine, will not be metabolized at the same rate as in most people.4 Certain foods can also mimic the effects of genetic variations. One of the most common examples is grapefruit juice, which is an inhibitor of CYP3A4. In people regularly drinking grapefruit juice, drugs that require the activity of CYP3A4, such as diazepam, will not be metabolized at the same rate as in most people.4

Pharmacogenomics in the clinical setting

Awareness of the influence of gene variations on patient response to certain drugs can help physicians decide which type of drug therapy may be appropriate, and identify cases in which a patient isn’t responding as anticipated to a drug. The examples that follow illustrate three categories for which pharmacogenomic knowledge can help inform therapeutic decisions: predicting and preventing adverse reactions, determining the efficacy of a drug for a particular patient, and predicting the optimal drug dose.

Using pharmacogenomics to predict and prevent adverse drug reactions

Several drugs can cause severe or life-threatening reactions in patients with variations in genes that encode proteins that metabolize or are targets of the drugs. Knowing about patients’ genetic variations can help physicians avoid drugs that may cause adverse reactions. On the following two pages are examples of drugs in this category.

enzyme

enzyme

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Abacavir

Abacavir (Ziagen®) is a nucleoside reverse transcriptase inhibitor used in combination with other antiretrovirals to treat HIV infection.5 An immunologically-mediated hypersensitivity reaction occurs in 5–8 percent of patients taking abacavir, usually during the first six weeks after initiation of therapy. The hypersensitivity symptoms include a combination of fever, rash, gastrointestinal tract symptoms and respiratory symptoms that become more severe with continued dosing.6 Discontinuation of abacavir therapy results in reversal of symptoms. The abacavir hypersensitivity described above is associated with a variant allele of the major histocompatibility complex, HLA-B*5701. Patients who carry the HLA-B*5701 allele have an increased risk for developing a hypersensitivity reaction.6 HLA-B*5701 screening before abacavir treatment results in a significantly reduced number of hypersensitivity cases.6

The abacavir product labeling recommends genetic testing to detect the presence of HLA-B*5701.5 In the “Warnings and Precautions” section, the labeling states:

Serious and sometimes fatal hypersensitivity reactions have been associated with ZIAGEN and other abacavir-containing products. Patients who carry the HLA-B*5701 allele are at high risk for experiencing a hypersensitivity reaction to abacavir. Prior to initiating therapy with abacavir, screening for the HLA-B*5701 allele is recommended; this approach has been found to decrease the risk of a hypersensitivity reaction. Screening is also recommended prior to reinitiation of abacavir in patients of unknown HLA-B*5701 status who have previously tolerated abacavir. For HLA-B*5701-positive patients, treatment with an abacavir-containing regimen is not recommended and should be considered only with close medical supervision and under exceptional circumstances when the potential benefit outweighs the risk. (Label updated September 2010)

Case study

JS is a 35 year-old man who has recently been diagnosed as HIV positive. Before initiating abacavir anti-retroviral therapy, his physician orders genetic testing to determine whether he carries the HLA-B*5701 allele, knowing that JS would develop fever, rash, nausea and fatigue if he carried the variant allele. The test confirmed that JS carries the HLA-B*5701 allele.

How did genetic testing help JS and his physician?

Knowing that JS carried the HLA-B*5701 variation indicated that he would likely experience a hypersensitivity reaction. JS’s physician will probably not include abacavir in his antiretroviral regimen.

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Codeine

Codeine is a prodrug with analgesic properties due primarily to its conversion into morphine.7,8 Conversion to morphine is mediated by the cytochrome P450 enzyme CYP2D6. Variations that decrease the metabolic activity of CYP2D6 result in a poor analgesic response due to the reduced conversion of codeine into morphine,3 and patients carrying such a variation are considered poor metabolizers and receive little therapeutic benefit from codeine. It is estimated that 5–10 percent of Caucasians are CYP2D6 poor metabolizers; the percentage is approximately 2–3 percent in other racial and ethnic groups.7,9,10

Variations (such as gene duplications) can also result in increased metabolic activity of CYP2D6; these result in an enhanced analgesic response due to the rapid conversion of codeine into morphine. Patients who carry such variations are at risk for opioid toxicity, which includes moderate to severe central nervous system depression. The prevalence of the CYP2D6 ultra-rapid metabolizer phenotype has been estimated at 1–10 percent in Caucasians, 3–5 percent in African Americans, 16–28 percent in North Africans, Ethiopians and Arabs, and up to 21 percent in Asians.3,11

The product labeling (updated in July 2009) of drugs containing codeine include warnings that CYP2D6 ultra-rapid metabolizers “may experience overdose symptoms such as extreme sleepiness, confusion or shallow breathing, even at labeled dosage regimens,” and encourages physicians to “choose the lowest effective dose for the shortest period of time and inform their patients about the risks and the signs of morphine overdose.”11 Of additional concern is the use of codeine in nursing mothers. Product labeling includes the statement that women who are CYP2D6 ultra-rapid metabolizers achieve “higher-than-expected levels of morphine in breast milk and potentially dangerously high serum morphine levels in their breastfed infants.” A 2007 U.S. Food and Drug Administration (FDA) Public Health Advisory warns about the dangers to neonates of codeine use in breast-feeding mothers and states that the only way to determine prior to drug administration whether a patient is an ultra-rapid metabolizer is by the use of a genetic test.12 Canadian guidelines also state that genetic testing is available.13

Case study

DS is a 30 year-old woman who gave birth by caesarian section 10 days ago. Her physician prescribed codeine for post-caesarian pain. Despite taking no more than the prescribed dose, DS experienced nausea and dizziness while she was taking codeine. She also noticed that her breastfed infant was lethargic and feeding poorly. When DS mentioned these symptoms to her physician, he recommended that she discontinue codeine use. Within a few days, both DS’s and her infant’s symptoms were no longer present.

How would genetic testing help DS and her physician?

Genotyping of DS’s CYP2D6 gene may have revealed a duplication of CYP2D6 genes, placing her in the ultra-rapid metabolizer category. Armed with this knowledge, DS’s physician would likely have prescribed a different analgesic that would have spared DS and her infant the symptoms of opioid toxicity.

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Using pharmacogenomics to predict effectiveness

Several drugs are subtherapeutic or ineffective in patients with variations in genes that encode drug-metabolizing proteins or targets of the drugs. Knowing about patients’ genetic variations can help physicians select drug therapies that will be most effective for individual patients. Below is an example of a drug in this category.

Clopidogrel

Clopidogrel (Plavix®) is a platelet inhibitor used in the treatment of a number of cardiovascular diseases. It is often prescribed for secondary prevention following acute coronary syndromes and for those undergoing percutaneous coronary intervention. However, despite clopidogrel treatment, up to one-quarter of patients experience a subtherapeutic antiplatelet response, resulting in a higher risk for ischemic events.14,15

Clopidogrel is a prodrug; its antiplatelet properties are exerted once it is converted to an active metabolite.16 A cytochrome P450 enzyme, CYP2C19, mediates the conversion of clopidogrel into the active metabolite. Patients who carry certain variations in CYP2C19 are considered poor metabolizers and show reduced ability to convert clopidogrel into its active metabolite, resulting in a diminished antiplatelet effect.16,17 Further, these patients are more likely to have an ischemic event following clopidogrel therapy.17 Approximately 2–20 percent of patients (depending on ethnicity) are likely to carry CYP2C19 variations.3,18

A Boxed Warning is included in the product labeling to alert health care providers about its reduced effectiveness in patients who are CYP2C19 poor metabolizers, and to inform health care providers that genetic tests are available to detect genetic variations in CYP2C1918:

WARNING: DIMINISHED EFFECTIVENESS IN POOR METABOLIZERS

The effectiveness of Plavix is dependent on its activation to an active metabolite by the cytochrome P450 (CYP) system, principally CYP2C19. Plavix at recommended doses forms less of that metabolite and has a smaller effect on platelet function in patients who are CYP2C19 poor metabolizers. Poor metabolizers with acute coronary syndrome or undergoing percutaneous coronary intervention treated with Plavix at recommended doses exhibit higher cardiovascular event rates than do patients with normal CYP2C19 function. Tests are available to identify a patient’s CYP2C19 genotype; these tests can be used as an aid in determining therapeutic strategy. Consider alternative treatment or treatment strategies in patients identified as CYP2C19 poor metabolizers. (Label updated February 2011).

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Case study

JM is a 58 year-old man who recently had an acute myocardial infarction. To prevent subsequent ischemic events, JM’s physician recommends antiplatelet therapy and prescribes clopidogrel. Six months later, JM suffered another acute MI, and his physician suspects that the patient has been non-adherent, or alternatively, that clopidogrel therapy may have been ineffective.

How would genetic testing help JM and his physician?

Determining JM’s CYP2C19 genotype may reveal that he carries a variant that diminishes the antiplatelet effect of clopidogrel. If this were the case, alternative anti-platelet therapies may have been considered, reducing the chance that JM would suffer a second cardiac event.

In patients taking both clopidogrel and the proton pump inhibitors omeprazole or esomeprazole, diminished antiplatelet activity and adverse cardiac outcomes have been observed.19 It is thought that omeprazole and esomeprazole inhibit the activity of CYP2C19, making patients who take these drugs de facto CYP2C19 poor metabolizers, similar to someone who carries a loss-of function variation in CYP2C19. In these patients, drugs that require the activity of CYPC19, such as clopidogrel, will not be metabolized at the same rate as in most people.

Using pharmacogenomics to predict optimal dose

Genetic variations can lead to an altered dosage regimen. Knowing whether a patient carries these genetic variations can assist physicians in determining optimal therapeutic dose. An example of a drug with an altered dosage regimen in patients with certain genetic variations is warfarin.

Warfarin

Warfarin (Coumadin®) is the most widely-prescribed anticoagulant used to treat and prevent thromboembolic diseases. It is metabolized by the CYP2C9 enzyme, and its anticoagulant effect is mediated by the enzyme VKORC1. Variation in the CYP2C9 gene causes some patients to have slow metabolism of warfarin and a longer half-life of the drug, resulting in higher than usual blood concentrations of warfarin and greater anticoagulant effect. Certain variations in the VKORC1 gene result in reduced activity of the enzyme and subsequently reduced synthesis of coagulation factors. The combination of slow warfarin metabolism caused by CYP2C9 gene variations and reduced coagulation caused by VKORC1 gene variations increases the risk of bleeding during warfarin therapy.

Warfarin has a narrow therapeutic index; variations in CYP2C9 and VKORC1, in addition to several other patient characteristics, make it difficult to predict the effective dose. Those carrying certain CYP2C9 and VKORC1 variations are likely to require altered doses and may require prolonged time to reach a stable maintenance dose. The prevalence of these CYP2C9 and VKORC1 variations is variable among racial and ethnic groups: up to 17 percent of Caucasians, 4 percent of African-Americans and less than 2 percent of Asians carry at least one variant of CYP2C9;20 while 37 percent of Caucasians, 14 percent of African-Americans, and 89 percent of Asians carry at least one variant in VKORC1.21

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The warfarin product labeling (updated January 2010) states “The patient’s CYP2C9 and VKORC1 genotype information, when available, can assist in selection of the starting dose,” and includes the following table of expected therapeutic doses for patients with different combinations of CYP2C9 and VKORC1 variations:22

Range of Expected Therapeutic Warfarin Doses (in mg) for CYP2C9 and VKORC1 Genotypes†

VKORC1 genotype

CYP2C9 genotype

*1/*1 *1/*2 *1/*3 *2/*2 *2/*3 *3/*3

GG 5–7 5–7 3–4 3–4 3–4 0.5–2

AG 5–7 3–4 3–4 3–4 0.5–2 0.5–2

AA 3–4 3–4 0.5–2 0.5–2 0.5–2 0.5–2

† Ranges are derived from multiple published clinical studies. Other clinical factors (e.g., age, race, body weight, sex, concomitant medications, and comorbidities) are generally accounted for, along with genotype, in the ranges expressed in the table.

Adapted from Warfarin drug labeling, 2010.22

The product labeling suggests that this table of expected therapeutic doses can be used to assist prescribers in choosing initial warfarin dose for patients whose CYP2C9 and VKORC1 genotypes are known. For example, if genetic testing reveals that a patient carries the *1/*3 variation of CYP2C9 and the AG variation of VKORC1, his or her expected therapeutic warfarin dose is likely to be in the 3–4 mg range.

Dosing algorithms that rely on clinical features such as age, sex and weight, along with genotype, can also assist in the determination of optimal dose (visit www.warfarindosing.org, where one such algorithm can be found). Genotype is one factor of many that contribute to variation in a patient’s response to warfarin. Careful monitoring of INR is still required during titration to steady state and monitoring of long-term therapy.

Case study

ML is a 65 year-old woman who has recently been diagnosed with atrial fibrillation. To reduce the risk of stroke and other thrombotic events, ML’s physician recommends warfarin therapy. To estimate the initial dose, ML’s clinical characteristics (age, sex, weight, diet) were considered. However, ML will need to return to the clinic every day for INR monitoring until a stable dose is determined, and then every few weeks thereafter for maintenance monitoring.

How would genetic testing help ML and her physician?

Determination of ML’s CYP2C9 and VKORC1 genotype would reveal whether she carries any variations that alter her ability to metabolize and respond to warfarin. Knowing about any gene variations before initiating therapy allows for more accurate initial dosing and faster INR stabilization, and can reduce the risk for bleeding or clotting events.

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Pharmacogenomics and genetic testing

Genetic tests that detect variations in the genes that control metabolism and response to certain drugs are commercially available. Costs and insurance coverage are variable, depending on the type of test ordered. Your hospital and reference laboratories as well as clinical geneticists are valuable sources of information on the best test to order and interpretation of results.

It is important to note that the field of pharmacogenomics is still developing, with new findings being rapidly reported. Clinical trials and other studies focusing on the benefits, risks and cost-effectiveness of using genetic information to inform drug therapy are underway. In the meantime, physicians and health care providers should be familiar with the concept that genetic variations can cause their patients to respond unexpectedly to drug therapy, and that in some cases, it may be appropriate to use genetic testing to guide therapeutic decisions. For more information on pharmacogenomics, visit the following websites:

• UC San Diego Skaggs School of Pharmacy and Pharmaceutical Sciences Pharmacogenomics Education Program (http://pharmacogenomics.ucsd.edu/home.aspx)

• American College of Clinical Pharmacology The Future of Medicine: Pharmacogenomics (http://user.accp1.org/Sample_Home.htm)

• Indiana University School of Medicine, Division of Clinical Pharmacology Defining Genetic Influences on Pharmacologic Responses (www.drug-interactions.com)

• U.S. Food and Drug AdministrationGenomics (www.fda.gov/Drugs/ScienceResearch/ResearchAreas/Pharmacogenetics/default.htm)

• Pharmacogenomics Research Network (www.nigms.nih.gov/initatives/pgrn)

Acknowledgements

The American Medical Association, the Arizona Center for Education and Research on Therapeutics (AzCERT), and the Critical Path Institute thank the American Academy of Family Physicians, the American College of Clinical Pharmacy, the American Society for Clinical Pharmacology and Therapeutics, Medco Research Institute, the Personalized Medicine Coalition, and several individuals with expertise in pharmacogenomics for their helpful review comments. This brochure was partially funded by a grant from the Agency for Healthcare Research and Quality to AzCERT. The authors of this document declare no conflicts of interest. The information contained in this document is not intended to be a treatment recommendation or an endorsement of any particular product.

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References

1. Collins FS. 2010. The Future of Personalized Medicine. NIH Medline Plus 5(1):2–3.

2. Lesko L. Regulatory Perspective on Warfarin Relabeling with Genetic Information. May 2007. Presentation at the 9th National Conference on Anti-Coagulation Therapy. www.fda.gov/downloads/Drugs/ScienceResearch/ResearchAreas/Pharmacogenetics/ucm085563.pdf. Accessed June 23, 2010.

3. Belle DJ, Singh H. (2008). Genetic Factors in Drug Metabolism. Am Fam Physician 77(11):1553–1560.

4. Indiana University Division of Clinical Pharmacology. P450 Drug interaction Table. 2010. http://medicine.iupui.edu/clinpharm/ddis/table.asp. Accessed June 23, 2010.

5. GlaxoSmithKline. Ziagen® (abacavir sulfate) product labeling. 2010. http://us.gsk.com/products/assets/us_ziagen.pdf. Accessed February 8, 2011.

6. Mallal S, Phillips E, Carosi G, Molina JM, Workman C, Tomazic J et al. (2008). HLA-B*5701 screening for hypersensitivity to abacavir. N Engl J Med 358(6):568–579.

7. Madadi P, Ross CJD, Hayden MR, Carleton BC, Gaedigk A, Leeder JS, Koren G. (2009). Pharmacogenomics of Neonatal Opioid Toxicity Following Maternal Use of Codeine During Breastfeeding: A Case-Control Study. Clin Pharmacol Ther 85(1):31–35.

8. Willmann S, Edginton AN, Coboeken K, Ahr A, Lippert J. (2009). Risk to the Breast-Fed Neonate From Codeine Treatment to the Mother: A Quantitative Mechanistic Modeling Study. Clin Pharmacol Ther 86(6):634–643.

9. Rollason V, Samer C, Piguet V, Dayer P, Desmeules J. (2008). Pharmacogenomics of analgesics: Toward the individualization or prescription. Pharmacogenomics 9(7):905–933.

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

11. Roxane Laboratories Inc. Codeine sulfate product labeling. 2009. www.accessdata.fda.gov/drugsatfda_docs/label/2009/022402s000lbl.pdf. Accessed March 3, 2010.

12. US Food and Drug Administration. (2007). Public Health Advisory: Use of Codeine By Some Breastfeeding Mothers May Lead To Life-Threatening Side Effects In Nursing Babies. http://www.fda.gov/Drugs/DrugSafety/ PostmarketDrugSafetyInformationfor Patientsand Providers/default.htm. Accessed February 8, 2011.

13. Madadi P, Moretti M, Djokanovic N, Bozzo P, Nulman I, Ito S, Koren G. (2009). Guidelines for maternal codeine use during breastfeeding. Can Fam Physician 55(11):1077–1078.

14. Ellis KJ, Stouffer GA, McLeod HL, Lee CR. Clopidogrel pharmacogenomics and risk of inadequate platelet inhibition: U.S. FDA recommendations. (2009). Pharmacogenomics 10(11):1799–1817.

15. Simon T, Verstuyft C, Mary-Krause M, Quteineh L, Drouet E, Meneveau N et al. (2009). Genetic determinants of response to clopidogrel and cardiovascular events. N Engl J Med 360(4): 363–375.

16. Shuldiner AR, O’Connell JR, Bliden KP, Gandhi A, Ryan K, Horenstein RB et al. (2009) Association of cytochrome P450 2C19 genotype with the antiplatelet effect and clinical efficacy of clopidogrel therapy. JAMA 302(8):849–857.

17. Mega JL, Close SL, Wiviott SD, Shen L, Hockett RD, Brandt JT et al. Cytochrome p-450 polymorphisms and response to clopidogrel. N Engl J Med 2009; 360(4):354–362.

18. Bristol Meyers Squibb/Sanofi Pharmaceuticals Partnership. Plavix® (clopidogrel bisulfate) product labeling. 2011. www.accessdata.fda.gov/drugsatfda_docs/label/2011/020839s052lbl.pdf. Accessed February 8, 2011.

19. Ho PM, Maddox TM, Wang L, Fihn SD, Jesse RL, Peterson ED, Rumsfeld JS. (2009). Risk of Adverse Outcomes Associated With Concomitant Use of Clopidogrel and Proton Pump Inhibitors Following Acute Coronary Syndrome. JAMA 301(9):937–944.

20. Gage, BF. (2006). Pharmacogenetics-Based Coumarin Therapy. Hematology ASH Educ Prog Book. 467–473.

21. Reider MJ, Reiner AP, Gage BF, Nickerson DA, Eby CS, McLeod HL et al. (2005). Effect of VKORC1 Haplotypes on Transcriptional Regulation and Warfarin Dose. N Engl J Med 352(22):2285–2293.

22. Bristol Meyers Squibb Company. Coumadin® (warfarin sodium) product labeling. 2010. www.accessdata.fda.gov/drugsatfda_docs/label/2010/009218s108lbl.pdf. Accessed February 8, 2011.

For more information contact:

American Medical Associationwww.ama-assn.org/go/geneticsThe American Medical Association, with its mission to promote the art and science of medicine and the betterment of public health, is a non-profit organization that unites physicians nationwide to work on the most important professional and public health issues.

Arizona Center for Education and Research on Therapeuticswww.azcert.orgThe Arizona Center for Education and Research on Therapeutics is an independent, collaborative program of the Critical Path Institute and the University of Arizona College of Pharmacy. Its mission is to improve therapeutic outcomes and reduce adverse events caused by drug interactions.

Critical Path Institutewww.c-path.orgThe Critical Path Institute is an independent, non-profit organization dedicated to bringing scientists from the FDA, industry and academia together to improve the path for innovative new drugs, diagnostic tests and devices to reach patients in need.

© 2011 American Medical Association. All rights reserved.

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EDUCATIONAL OBJECTIVE: Readers will discern the implications of pharmacogenomic testing as it emerges

Pharmacogenomic testing: Relevance in medical practiceWhy drugs work in some patients but not in others

■■ ABSTRACT

Genetics may account for much of the variability in our patients’ responses to drug therapies. This article offers the clinician an up-to-date overview of pharmacoge-nomic testing, discussing implications and limitations of emerging validated tests relevant to the use of warfa-rin (Coumadin), clopidogrel (Plavix), statins, tamoxifen (Nolvadex), codeine, and psychotropic drugs. It also discusses the future role of pharmacogenomic testing in medicine.

■■ KEY POINTS

Polymorphisms that affect the pharmacokinetics and pharmacodynamics of specific drugs are common.

Testing for certain polymorphisms before prescribing certain drugs could help avoid adverse drug effects and improve efficacy.

Pharmacogenomic testing has only recently begun to enter clinical practice, and routine testing is currently limited to a few clinical scenarios. However, additional applications may be just around the corner.

Many pharmacogenomic tests are available, but testing has not yet been recommended for most drugs. Needed are large-scale trials to show that routine testing im-proves patient outcomes.

CLEVELAND CLINIC JOURNAL OF MEDICINE VOLUME 78 • NUMBER 4 APRIL 2011 243

I n many patients, certain drugs do not work as well as expected, whereas in other

patients they cause toxic effects, even at lower doses. For some patients, the reason may be genetic. Sizeable minorities of the population carry genetic variants—polymorphisms —that affect their response to various drugs. Thanks to ge-netic research, our understanding of the vari-ability of drug response has advanced markedly in the last decade. Many relevant polymor-phisms have been identified, and tests for some of them are available.

See related editorial, page 241

Armed with the knowledge of their pa-tients’ genetic status, physicians could predict their response to certain drugs, leading to bet-ter efficacy, fewer adverse drug reactions, and a better cost-benefit ratio. The possible impact is substantial, since more than half of the drugs most commonly involved in adverse drug reactions are metabo-lized by polymorphic enzymes.1 Adverse drug reactions remain a significant detriment to public health, having a substantial impact on rates of morbidity and death and on health-care costs.2–8 In the United States, adverse drug reactions are a leading cause of death in hospitalized patients4 and are annually re-sponsible for hundreds of thousands of deaths and hundreds of billions of dollars in added costs.2,4,6–8

But the era of truly individualized medicine is not here yet. For most drugs, pharmacoge-nomic testing has not been endorsed by expert committees (and insurance companies will not

REVIEW

doi:10.3949/ccjm.78a.10145

CREDITCME

JOSEPH P. KITZMILLER, MD, PhDDepartment of Pharmacology, Division of Clinical Trials, College of Medicine, The Ohio State University, Columbus, OH

DAVID K. GROEN, MDDepartment of Pharmacology, Division of Clinical Trials, College of Medicine, The Ohio State University, Columbus, OH

MITCH A. PHELPS, PhDDivision of Pharmaceutics Resources, College of Pharmacy, The Ohio State University, Columbus, OH

WOLFGANG SADEE, Dr rer natChairman, Department of Pharmacology; Director, Program in Pharmacogenomics, College of Medicine, The Ohio State University, Columbus, OH

244 CLEVELAND CLINIC JOURNAL OF MEDICINE VOLUME 78 • NUMBER 4 APRIL 2011

PHARMACOGENOMIC TESTING

pay for it), since we still lack evidence that clinical outcomes improve. This, we hope, will change as ongoing clinical trials are com-pleted. FIGURE 1 describes the various stages involved in translational pharmacogenomic research.11

In the meantime, physicians can educate their patients and promote efforts to incorpo-rate genomic information into standard clini-cal decision-making. This article offers an overview of pharma-cogenomic testing, discussing implications and limitations of a few validated tests. Spe-cifically, we will discuss testing that is relevant when using warfarin (Coumadin), clopidogrel (Plavix), statins, tamoxifen (Nolvadex), co-deine, and psychotropic medications, as well as the future role of pharmacogenomic testing in medicine.

■ WHAT IS PHARMACOGENOMICS?

Pharmacogenomics is the study of how genet-ic factors relate to interindividual variability of drug response. Many clinicians may not be familiar with the background and terminology used in the pharmacogenomic literature. Below, a brief re-view of the terminology is followed by a sche-matic describing the various stages of research involved in pharmacogenomics and the ad-vancement of a test into standard practice. The review and schematic may be help-ful for evaluating the clinical significance of pharmacogenomics-related articles.

From genotype to phenotypeGenotype refers to the coding sequence of DNA base pairs for a particular gene, and phe-notype (eg, disease or drug response) refers to a trait resulting from the protein product encod-ed by the gene. The name of a gene often re-fers to its protein product and is italicized (eg, the CYP3A4 gene encodes for the CYP3A4 enzyme). Two alleles per autosomal gene (one pa-ternal and one maternal) form the genotype. Heterozygotes possess two different alleles, and homozygotes possess two of the same alleles. The most common allele in a population is referred to as the wild type, and allele frequen-cies can vary greatly in different populations.9

Most sequence variations are single nu-cleotide polymorphisms (SNPs, pronounced “snips”), a single DNA base pair substitution that may result in a different gene product. SNPs can be classified as structural RNA polymorphisms (srSNPs), regulatory polymor-phisms (rSNPs), or polymorphisms in coding regions (cSNPs)10: srSNPs alter mRNA pro-cessing and translation, rSNPs alter transcrip-tion, and cSNPs alter protein sequence and function. Recently, genetic associations with a phe-notype have been done on a large scale, with millions of SNPs measured in each of many subjects. This approach, called a genome-wide association study or GWAS, has revealed countless candidate genes for clinical traits, but only a few have resulted in a practical clinical application. SNPs may by themselves exert a pharmacokinetic effect (ie, how the body processes the drug), a pharmacodynamic effect (ie, how the drug affects the body), or both, or they may act in concert with other genetic factors. Pharmacodynamic effects can result from a pharmacokinetic effect or can re-sult from variations in a pharmacologic target. Establishing a genotype-phenotype associa-tion can involve clinical studies, animal trans-genic studies, or molecular and cellular func-tional assays.

Clinical applications are emergingAlthough pharmacogenomic testing is begin-ning to affect the way medicine is practiced, it is recommended, or at least strongly sug-gested, by labeling mandated by the US Food and Drug Administration (FDA) for only a few clinical scenarios, mostly in the treat-ment of cancer and human immunodeficiency virus (TABLE 1). However, applications are also being developed for a few widely prescribed drugs and drug classes in primary care. We will therefore focus our discussion on the ad-vantages and limitations of a few of these ex-amples for which clinical applications may be emerging.

■ WARFARIN: IMPORTANCE OF CYP2C9, VKORC1

Warfarin is used for the long-term treatment and prevention of thromboembolic events.

Pharmaco- genomic testing is beginning to affect the way medicine is practiced


KITZMILLER AND COLLEAGUES

How a genetic test becomes a standard of care: Typical advancement pathway

Identify candidate genetic variantThe US Food and Drug Administration (FDA) lists genetic tests validated for accuracy and reproduc-ibility at www.fda.gov/Drugs/ScienceResearch/ResearchAreas/Pharmacogenetics.

Determine penetrance of genetic variantAllele frequency is an important determinant of clinical significance; even genetic variants associated with large pharmacokinetic or pharmacodynamic effects may not have sufficient clinical utility if they occur only rarely.

Determine genotype-phenotype associationMeasured biologic or physiologic effects (associa-tions) are often viewed as surrogates for clinical response; however, clinical responses do not always correspond as predicted.

Determine clinical significanceClinical trials that compare implementation of genetic testing to the current standard of care should be used for determining clinical significance.

Determine cost-effectivenessThe cost-effectiveness of implementing a pharmacoge-nomic testing application should compare favorably with current standard practice. Cost-effectiveness assessments measure a variety of outcomes, including clinical events and quality-adjusted life-years.

Standard of careThe FDA can require genetic information to be added to a product label (eg, codeine), recommend the use of genetic testing data if available (eg, warfarin [Coumadin]), or even recommend genetic testing prior to prescribing a medication to specific patient populations—eg, HLA-B genotyping prior to prescrib-ing carbamazepine (Tegretol, Equetro) to genetically at-risk patients.11

FIGURE 1

This drug has a narrow therapeutic win-dow and shows substantial interpatient dose variability. The start of warfarin therapy is associated with one of the highest rates of adverse events and emergency room visits of any single drug.12 More than 2 million pa-tients start warfarin each year in the United States alone,13 and about 20% of them are hospitalized within the first 6 months because of bleeding due to overanticoagulation.14

The findings from a recent study suggest that pharmacogenomic testing may eventu-ally allow more patients to safely benefit from warfarin therapy. In this large, nationwide, prospective study, hospitalization rates were 30% lower when pharmacogenomic testing was used.14 However, no reduction was seen in the time needed to reach the target interna-tional normalized ratio (INR) or in the need for INR checks at 6 months. Furthermore,

About 20% of patients starting warfarin are hospitalized in the first 6 months because of bleeding



this study used historical control data, and some or all of the reduction in hospitalization rates may be attributed to more frequent INR checks in the patients who underwent testing than in the historical control group. A relationship between warfarin dose re-quirements and the genetic status of CYP2C9, which encodes a major drug-metabolizing en-zyme, has been demonstrated in retrospective and prospective studies.15–17

S-warfarin is metabolized by CYP2C9, which is polymorphicWarfarin contains equal amounts of two iso-mers, designated S and R. S-warfarin, which is more potent, is metabolized principally by CYP2C9, while R-warfarin is metabolized by CYP1A2, CYP2C19, and CYP3A4. People who possess two copies of the wild type CYP2C9 gene CYP2C9*1 metabolize warfarin very well and so are called “extensive warfarin metabolizers.” Carriers of the allelic variants CYP2C9*2 and CYP2C9*3 (which have point mutations in exons 3 and 7 of CY-P2C9, respectively), have less capacity. Com-pared with those who are homozygous for the wild-type gene, homozygous carriers of CY-P2C9*3 clear S-warfarin at a rate that is 90% lower, and those with the CYP2C9*1/*3, CY-P2C9*1/*2, CYP2C9*2/*2, or CYP2C9*2/*3 genotypes clear it at a rate 50% to 75% lower. A meta-analysis of 12 studies found that the CYP2C9 genotype accounted for 12% of the interindividual variability of warfarin dose re-quirements.18

About 8% of whites carry at least one copy of CYP2C9*2, as do 1% of African Americans; the allele is rare in Asian populations. The frequency of CYP2C9*3 is 6% in whites, 1% in African Americans, and 3% in Asians.19,20 People with CYP2C9*4 or CYP2C9*5 have a diminished capacity to clear warfarin; how-ever, these variants occur so infrequently that their clinical relevance may be minimal.

Warfarin’s target, VKOR, is also polymorphicGenetic variation in warfarin’s pharmaco-logic target, vitamin K 2,3-epoxide reductase (VKOR), also influences dose requirements. Warfarin decreases the synthesis of vitamin-K-dependent clotting factors by inhibiting

TABLE 1

FDA-mandated product labeling: Genetic biomarkers and their clinical context

C-KIT (cytokine receptor)Imatinib mesylate (Gleevec) is indicated for the treatment of pa-tients with Kit (CD117)-positive unresectable tumors or metastatic malignant gastrointestinal stromal tumors (GIST).

CCR5 (C-C chemokine receptor type 5)Maraviroc (Selzentry) is indicated for treatment-experienced adult patients infected with CCR5-tropic HIV-1 infection.

Chromosome 5qLenalidomide (Revlimid) is indicated for the treatment of patients with transfusion-dependent anemia due to low- or intermediate-risk myelodysplastic syndromes associated with a deletion 5q cytogenic abnormality with or without additional cytogenic abnormalities.

Familial hypercholesterolemia Atorvastatin (Lipitor) dosage adjustment is necessary for children who have homozygous or heterozygous familial hypercholesterol-emia.

G6PD (glucose-6-phosphate dehydrogenase)Testing for G6PD deficiency is recommended in high-risk popula-tions before starting treatment with rasburicase (Elitek).

HER2/neu (human epidermal growth factor receptor 2)HER2 testing is recommended before starting treatment with trastuzumab (Herceptin).

HLA-B*1502 (major histocompatibility complex, class I, B)HLA-B testing is recommended in high-risk populations before starting treatment with carbamazepine (Tegretol, Equetro).

HLA-B*5701 (major histocompatibility complex, class I, B)HLA-B testing is recommended before starting treatment with abacavir (Ziagen).

Philadelphia (Ph1) chromosome Dasatinib (Sprycel) is indicated for treatment of adults with Philadelphia-chromosome-positive acute lymphoblastic leukemia with resistance or intolerance to prior therapy.

TPMT (thiopurine methyltransferase) TPMT testing is recommended before starting treatment with azathioprine (Imuran).

ADAPtED FROM US FOOD AND DRUg ADMINIStRAtION (FDA). tABLE OF PhARMACOgENOMIC BIOMARkERS IN DRUg LABELS. www.FDA.gOV/DRUgS/SCIENCERESEARCh/RESEARChAREAS/

PhARMACOgENEtICS/UCM083378.htM. ACCESSED 2/3/2011.



VKOR. This inhibition depends on the pa-tient’s C1 subunit gene, VKORC1. Patients with a guanine-to-adenine SNP 1,639 bases upstream of VKORC1 (–1639G>A) need lower warfarin doses—an average of 25% low-er in those with the GA genotype (ie, one al-lele has guanine in the –1639 position and the other allele has adenine in that position) and 50% lower in those with the AA genotype compared with the wild-type genotype GG.21 This promoter SNP, positioned upstream (ie, before the gene-coding region), greatly influ-ences VKORC1 expression. A meta-analysis of 10 studies found that the VKORC1 polymorphism accounts for 25% of the interindividual variation in war-farin dose.18 In one study, the frequency of the AA genotype in a white population was 14%, AG 47%, and GG 39%; in a Chinese popula-tion the frequency of AA was 82%, AG 18%, and GG 0.35%.22

CYP4F2 and GGCX also affect warfarin’s dose requirementsGenetic variations in the enzymes CYP4F2 and gamma-glutamyl carboxylase (GGCX) also influence warfarin dose requirements. Al-though the data are limited and the effects are smaller than those of CYP2C9 and VKORC1, people with a SNP in CYP4F2 need 8% high-er doses of warfarin, while those with a SNP in GGCX need 6% lower doses.23

CYP2C9 and VKORC1 testing is availableCurrently, the clinical pharmacogenetic tests relevant for warfarin use are for CYP2C9 and VKORC1.10 The FDA has approved four warfarin phar-macogenetic test kits, but most third-party pay-ers are reluctant to reimburse for testing because it is not currently considered a standard of care. Testing typically costs a few hundred dollars, but it should become less expensive as it becomes more commonplace. The current FDA-ap-proved product label for warfarin does not rec-ommend routine pharmacogenomic testing for determining initial or maintenance doses, but it does acknowledge that dose requirements are influenced by CYP2C9 and VKORC1 and states that genotype information, when available, can assist in selecting the starting dose.24 The product label includes a table (TABLE 2) of expected therapeutic warfarin doses based on CYP2C9 and VKORC1 genotypes, which can be used when choosing the initial dose for patients whose genetic status is known. A well-developed warfarin-dosing model in-corporating traditional clinical factors and patient genetic status is available on the non-profit Web site www.warfarindosing.org.25

Clinical trials of warfarin pharmacogenomic testing are under wayAlthough genetic status can greatly influence an individual patient’s warfarin dosing re-

Patients with CYP2C9 variants or VKORC1 variants may need lower doses of warfarin

TABLE 2

Range of expected warfarin doses based on CYP2C9 and VKORC1 genotypes

VKORC1 GENOTYPE

CYP2C9 GENOTYPE

*1/*1 *1/*2 *1/*3 *2/*2 *2/*3 *3/*3

GG 5–7 mg 5–7 mg 3–4 mg 3–4 mg 3–4 mg 0.5–2 mg

AG 5–7 mg 3–4 mg 3–4 mg 3–4 mg 0.5–2 mg 0.5–2 mg

AA 3–4 mg 3–4 mg 0.5–2 mg 0.5–2 mg 0.5–2 mg 0.5–2 mg

This table and the following comments were taken directly from the warfarin prescribing information. Ranges are derived from multiple published clinical studies. Other factors (eg, age, race, body weight, sex, concomitant medications, and comorbidities) are generally accounted for along with genotype in the ranges expressed in the table. The VKORC1 –1639G>A (rs9923231) variant is used in this table. Other coinherited VKORC1 variants may also be important determinants of warfarin dose. Patients with CYP2C9 *1/*3, *2/*2, *2/*3, and *3/*3 may require a prolonged time (< 2 to 4 weeks) to achieve the maximum international normalized ratio effect for a given dosage regimen.24



FDA: Poor CYP2C19 metabolizers may not benefit from clopidogrel

quirement, routine prospective pharmacoge-nomic testing is not endorsed by the FDA or by other expert panels26 because there is cur-rently insufficient evidence to recommend for or against it. Several large prospective trials are under way. For example, the National Heart, Lung, and Blood Institute began a prospective trial in about 1,200 patients to evaluate the use of clinical plus genetic information to guide the initiation of warfarin therapy and to im-prove anticoagulation control for patients.27 The results, expected in September 2011, and those of other large prospective trials should provide adequate evidence for making recom-mendations about the clinical utility of rou-tine pharmacogenetic testing for guiding war-farin therapy. Several recent cost-utility and cost-effec-tiveness studies have attempted to quantify the value of pharmacogenomic testing for warfarin therapy,28–30 but their analyses are largely lim-ited because the benefit (clinical utility) is yet to be sufficiently characterized. The relevance of such analyses may soon be drastically diminished, as several non-vita-min-K-dependent blood thinners such as riva-roxaban (Xarelto), dabigatran (Pradaxa), and apixaban are poised to enter clinical practice.31

■ CLOPIDOGREL IS ACTIVATED BY CYP2C19

Clopidogrel, taken by about 40 million pa-tients worldwide, is used to prevent athero-thrombotic events and cardiac stent thrombo-sis when given along with aspirin. Clopidogrel is a prodrug, and to do its job it must be transformed to a more active me-tabolite (FIGURE 2). CYP2C19 is responsible for its metabolic activation, and CYP2C19 loss-of-function alleles appear to be associated with higher rates of recurrent cardiovascular events in patients receiving clopidogrel. At least one loss-of-function allele is carried by 24% of the white non-Hispanic population, 18% of Mexicans, 33% of African Americans, and 50% of Asians. Homozygous carriers, who are poor CYP2C19 metabolizers, make up 3% to 4% of the population.32

Studies of clopidogrel pharmacogenomicsA recent genome-wide association study

conducted in a cohort of 429 healthy Amish persons revealed a SNP in CYP2C19 to be as-sociated with a diminished response to clopi-dogrel and to account for 12% of the variation in drug response.33 Traditional factors (the pa-tient’s age, body-mass index, and cholesterol level) combined accounted for less than 10% of the variation. Findings were similar in a subsequent in-vestigation in 227 cardiac patients receiving clopidogrel: 21% of those with the variant had a cardiovascular ischemic event or died dur-ing a 1-year follow-up period compared with 10% of those without the variant (hazard ratio 2.42, P = .02).33 A 12-year prospective study investigat-ing clopidogrel efficacy in 300 cardiac patients under the age of 45 used cardiovascular death, nonfatal myocardial infarction, and urgent coro-nary revascularization as end points. It conclud-ed that the only independent predictor of these events was the patient’s CYP2C19 status.34

A study in 2,200 patients with recent myo-cardial infarction examined whether any of the known allelic variations that modulate clopidogrel’s absorption (ABCB1), metabolic activation (CYP3A4/5 and CYP2C19), or bio-logic activity (P2RY12 and ITGB3) was asso-ciated with a higher rate of the combined end point of all-cause mortality, nonfatal myocar-dial infarction, or stroke. None of the SNPs in CYP3A4/5, P2RY12, or ITGB3 that were evaluated was associated with a higher risk at 1 year. However, the allelic variations modu-lating clopidogrel’s absorption (ABCB1) and metabolism (CYP2C19) were associated with higher event rates. Patients with two variant ABCB1 alleles had a higher adjusted hazard ratio (95% confidence interval [CI] 1.2–2.47) than those with the wild-type allele. Patients who had one or two CYP2C19 loss-of-func-tion alleles had a higher event rate than those with two wild-type alleles (95% CI 1.10–3.58 and 1.71–7.51, respectively).35

Conversely, researchers from the Popula-tion Health Research Institute found no as-sociation between poor-metabolizer status and treatment outcomes when CYP2C19 analysis was retrospectively added to the find-ings of two large clinical trials (combined N > 5,000). However, patients with acute coro-nary syndrome benefited more from clopido-



M Why some drugs don’t work in some patients

Medical Illustrator: Beth Halasz CCF ©2011

FIGURE 2

The normal “wild-type” allele (CYP2C19*1) results in a normal-functioning CYP2C19 enzyme capable of converting the inactive prodrug clopidogrel (Plavix) to its active metabolite.

Pharmacogenomic research investigates how patients’ genetics influence their response to medication. Genetic vari-ability can influence how quickly a drug is metabolized, how well a drug works, or even the likelihood of side effects. The example below depicts how genetic variation can influence the conversion of a prodrug.

Clopidogrel is a prodrug

Active metabolite

Functional enzyme CYP2C19

Clopidogrel remains inactive

Variant alleles (mainly CYP2C19*2, CYP2C19*3, and CYP2C19*17) result in poor-metabolizer status (having little or no CYP2C19 function). For CYP2C19*2, the single-nucleotide polymorphism (SNP) is substitution of adenine for guanine at position 681 of CYP2C19 (681G > A). The resulting CYP2C19 protein is unable to convert clopidogrel to its active form, and drug efficacy is reduced.

CYP2C19*2 protein is enzymatically inactive

SNP



grel treatment if they were ultra-rapid metab-olizers (possessing the gain-of-function allele CYP2C19*17).36

Current status of clopidogrel testing: UncertainA current FDA boxed warning states that poor CYP2C19 metabolizers may not benefit from clopidogrel and recommends that prescribers consider alternative treatment for patients in this category.37 However, routine CYP2C19 testing is not recommended, and no firm rec-ommendations have been established regard-ing dose adjustments for CYP2C19 status. Clinicians should be aware that the low exposure seen in poor metabolizers also occurs in patients taking drugs that inhibit CYP2C19 (TABLE 3).38 In 2010, the American College of Cardi-ology Foundation Task Force on Clinical Ex-

pert Consensus Documents and the American Heart Association collectively pronounced the current evidence base insufficient for rec-ommending routine pharmacogenomic test-ing.39

Needed are large-scale studies examin-ing the cost-effectiveness and clinical util-ity of genotype-guided clopidogrel therapy compared with other therapy options such as prasugrel (Effient), an analogue not metabo-lized by CYP2C19. One such study, sponsored by Medco Health Solutions, plans to enroll 14,600 cardiac patients and has an estimated completion date in June 2011.40 The expec-tation that clopidogrel will be available in generic form in 2012 adds to the uncertainty regarding the cost-effectiveness of CYP2C19 testing for clopidogrel therapy.

■ STATINS: SLC01B1*5 INCREASES MYOPATHY RISK

Statins lower the concentration of low-den-sity lipoprotein cholesterol (LDL-C), result-ing in a relative-risk reduction of about 20% for each 1 mmol/L (39 mg/dL) decrement in LDL-C.41 They are one of the most commonly prescribed classes of drugs, but their side ef-fects can limit their appeal: statin-induced myopathy occurs in about 1:1,000 to 1:10,000 patients and is difficult to predict. SLC01B1. The Study of the Effectiveness of Additional Reductions in Cholesterol and Homocysteine (SEARCH), a genome-wide association study, recently found a SNP (SL-CO1B1*5) in the SLC01B1 gene to be associ-ated with a higher risk of statin-induced myop-athy in cardiac patients receiving simvastatin (Zocor) 40 or 80 mg daily.42 The SLC01B1 gene, located on chromosome 12, influences the extent of the drug’s hepatic uptake and its serum concentration. Only the SLC01B1*5 SNP emerged as a predictor of statin-induced myopathy across the entire genome.42 The authors believe the findings are likely to apply to other statins. The mechanisms leading to statin-induced myopathy and the impact of statin pharmacogenomics are still unclear.43

CYP3A4. Other genetic variants may play a vital role in determining response to statin therapy. Carriers of a newly identified CYP3A4

TABLE 3

Drugs that inhibit CYP2C19 (and therefore can reduce the effect of clopidogrel)

Chloramphenicol

Cimetidine (Tagamet)

Felbamate (Felbatol)

Fluoxetine (Prozac)

Fluvoxamine (Luvox)

Indomethacin (Indocin)

Ketoconazole (Nizoral)

Lansoprazole (Prevacid)

Modafinil (Provigil)

Omeprazole (Priloxec)

Oxcarbazepine (Trileptal)

Pantoprazole (Protonix)

Probenecid (Benemid)

Rabeprazole (AcipHex)

Ticlopidine (Ticlid)

Topiramate (Topamax)

BASED ON INFORMAtION IN FLOCkhARt DA. DRUg INtERACtIONS: CYtOChROME P450 DRUg INtERACtION tABLE.

INDIANA UNIVERSItY SChOOL OF MEDICINE (2007). httP://MEDICINE.IUPUI.EDU/CLINPhARM/DDIS/tABLE.ASP.



polymorphism (intron 6 SNP, rs35599367, C>T) required significantly lower statin doses (0.2–0.6 times less) for optimal lipid control. The analyses included atorvastatin (Lipitor), simvastatin, and lovastatin (Mevacor), and the association was robust (P = .019).44

Statin pharmacogenomic testing is not routinely recommendedRoutine pharmacogenomic testing for statin therapy is not recommended. Additional stud-ies are needed to determine the clinical utility and cost-effectiveness of pharmacogenomic testing (involving a combination of several polymorphisms) in various patient popula-tions delineated by type of statin, dose, and concomitant use of other drugs.

■ TAMOXIFEN IS ACTIVATED BY CYP2D6

Tamoxifen is prescribed to prevent the recur-rence of estrogen-receptor-positive breast can-cer, to treat metastatic breast cancer, to pre-vent cancer in high-risk populations, and to treat ductal carcinoma in situ. Tamoxifen is metabolized to form en-doxifen, which has much higher potency and higher systemic levels than tamoxifen.45 Both CYP2D6 and CYP3A4/5 are required to pro-duce endoxifen via two intermediates, but CYP2D6 catalyzes the critical step leading to metabolic activation. The CYP2D6 gene is highly polymorphic, with more than 75 allelic variants identi-fied. Extensive literature is available describ-ing the influence of CYP2D6 polymorphisms on tamoxifen metabolism and therapy out-comes.46–52 Several CYP2D6 variants result in reduced or no enzyme activity, and people who have more than two normally function-ing alleles have exaggerated enzyme activity (gene amplification).

Classification of CYP2D6 statusSeveral systems have been developed to cat-egorize the phenotypic activity of CYP2D6 based on genotype. A genetic basis for the observed diversity in the metabolism of cytochrome P450 sub-strates was recognized more than 30 years ago. People were categorized as either extensive or poor metabolizers, reflecting normal vs im-

paired ability to metabolize the CYP2D6 sub-strates sparteine and debrisoquine. Later work expanded this system to include categories for intermediate (between poor and extensive) and ultra-rapid (better than extensive) me-tabolizers. The genetic basis for these categories in-cludes homozygosity for dysfunctional vari-ants (the poor-metabolizer group) or extra copies of normal functioning variants (the ultra-rapid-metabolizer group). Newer systems have been described for characterizing the CYP2D6 activity pheno-type whereby CYP2D6 variants are assigned activity scores.53–56 The various scoring sys-tems have been reviewed by Kirchheiner.57 A recent version of the activity scoring system also takes into consideration the many drugs that inhibit CYP2D6, such as amioda-rone (Cordarone) and fluoxetine (Prozac) that can reduce the action of tamoxifen if given with it (TABLE 4).58 For example, the tamoxifen exposure (as predicted by the CYP2D6-activi-ty score) experienced by a CYP2D6 extensive metabolizer taking a CYP2D6-inhibiting drug may be similar to the exposure experienced by a CYP2D6 poor metabolizer receiving the same tamoxifen dose but not taking a CY-P2D6-inhibiting drug. Likewise, the activity score of a CYP2D6 intermediate metabolizer taking a CYP2D6-inducing drug may be similar to that of a CYP2D6 ultra-rapid metabolizer not taking a CYP2D6-inducing drug. Examples of CY-P2D6 inducers are dexamethasone, rifampin, and hyperforin (St. John’s wort). While the newer systems are reported to provide better correlations between genotype and phenotype scores, the older scoring sys-tems and the categorical names are still widely used (eg, in the FDA-approved AmpliChip CYP450 test from Roche,59 which includes genotype data for CYP2D6 and CYP2C19).

No firm recommendations for CYP2D6 testing in tamoxifen usersThe different genotypes and phenotypes vary in prevalence in different ethnic groups, and significantly different activ-ity levels for endoxifen formation are ob-served. Tamoxifen lacks efficacy in those who are poor CYP2D6 metabolizers—ie,

The pharmacogenomics of codeine has become a hot topic, especially in breastfeeding mothers



about 7% of the white population. However, the FDA has not made firm recommendations about CYP2D6 testing for prescribing tamoxifen because the evidence of benefit, although suggestive, has been consid-ered insufficient. Clinicians should be aware that tamoxi-fen’s efficacy is greatly reduced by concomi-tant therapy with CYP2D6-inhibiting drugs (TABLE 4).

Other genes affecting tamoxifen: CYP3A4/5, SULT1A1, and UGT2B15Some investigators propose that polymor-phisms in additional genes encoding enzymes in the tamoxifen metabolic and elimination pathways (eg, CYP3A4/5, SULT1A1, and UGT2B15) also need to be considered to ac-count adequately for interindividual variation in drug response. For example, CYP3A4 and CYP3A5 are also polymorphic, and large interindividual variation exists in their enzyme activities. These enzymes have overlapping substrate specificities, represent the most abundant drug-metabolizing enzymes in the human liv-er, and are involved in the biotransformation of a broad range of endogenous substrates and most drugs.60 Clinical studies evaluating the impact of CYP3A4/5 polymorphisms have been incon-sistent in their conclusions, which is gener-ally attributed to the relatively low functional impact or the low prevalence of the SNPs evaluated. Many of the nearly 100 CYP3A4/5 polymorphisms identified have not yet been characterized regarding their functional im-pact on enzyme expression or activity. CYP-3A4/5 enzyme activity is highly variable be-tween individuals and warrants further study of its role in outcomes of tamoxifen therapy. Ongoing and future prospective clinical trials evaluating CYP2D6, CYP3A4/5, and other relevant polymorphisms are necessary to de-fine their clinical relevance before routine ge-netic testing for tamoxifen can be justified.

■ CODEINE IS ALSO ACTIVATED BY CYP2D6

Codeine also depends on the CYP2D6 gene, as it must be activated to its more potent opioid metabolites, including morphine.

TABLE 4

Drugs that inhibit CYP2D6 (and therefore can reduce the effects of tamoxifen and codeine)

Amiodarone (Cordarone, Pacerone)Bupropion (Wellbutrin)Celecoxib (Celebrex)Chlorpheniramine Chlorpromazine (Thorazine)Cimetidine (Tagamet)Cinacalcet (Sensipar)Citalopram (Celexa)Clemastine (Tavist) Clomipramine (Anafranil)Cocaine Diphenhydramine (Benadryl)Doxepin (Sinequan)Doxorubicin (Adriamycin)Duloxetine (Cymbalta)Escitalopram (Lexapro)Fluoxetine (Prozac)Halofantrine (Halfan)Haloperidol (Haldol)Hydroxyzine (Vistaril)Levomepromazine Methadone Metoclopramide (Reglan)Mibefradil (Posicor)Midodrine (ProAmatine) MoclobemideParoxetine (Paxil)Perphenazine (Trilafon)Quinidine Ranitidine (Zantac)Ritonavir (Norvir)Sertraline (Zoloft)Terbinafine (Lamisil)Ticlopidine (Ticlid)

Tripelennamine (Pyribenzamine)

BASED ON INFORMAtION IN FLOCkhARt DA. DRUg INtERACtIONS: CYtOChROME P450 DRUg INtERACtION tABLE. INDIANA UNIVERSItY SChOOL OF MEDICINE

(2007). httP://MEDICINE.IUPUI.EDU/CLINPhARM/DDIS/tABLE.ASP.



Poor CYP2D6 metabolizers do not benefit from codeine therapy. The pharmacogenomics of codeine has be-come a hot topic, especially regarding breast-feeding mothers. The debate was ignited with the publication in 2006 of a case report of an infant’s death, apparently the result of meta-bolic polymorphisms.61 The evolution of this debate and the outcome of the case may be noteworthy to clinicians, as they illustrate the gravity of public and patient interest in phar-macogenomic testing. In this case, the breast-feeding mother had taken codeine regularly for about 14 days when her 13-day-old infant died from toxic levels of morphine. Unknown to her and the prescriber, both the mother and infant were ultra-rapid CYP2D6 metabolizers, resulting in a more rapid and extensive con-version of codeine to morphine. A logical strategy for preventing similar deaths would be routine CYP2D6 genotyp-ing when prescribing codeine to breast-feeding mothers. However, after several investigations examined the metabolic and excretion pathways of codeine in their en-tirety, the FDA did not recommend routine CYP2D6 testing when prescribing codeine to breastfeeding mothers because several other factors, including rare genetic variations of other enzymes, proved necessary for reach-ing the opioid toxicity leading to the infant’s death.62

■ PHARMACOGENOMICS OF PSYCHOTROPIC DRUGS

Pharmacogenomic testing has clinical utility for some psychotropic drugs.

HLA-B and carbamazepineConsidered a standard of care, HLA-B geno-typing is appropriate before prescribing carba-mazepine (Tegretol, Equetro) to patients in populations in which HLAB*1502 is likely to be present, such as Asians. Carriers of HLA-B*1502 are at higher risk of life-threatening skin reactions such as Stevens-Johnson syn-drome.11 Several other pharmacogenomic appli-cations for psychotropic medications have been suggested, but routine testing has not been recommended by the FDA or endorsed

by any expert panel because sufficient clini-cal utility and cost-effectiveness have not been demonstrated. A brief summary of study findings and a few practical sugges-tions follow. Polymorphisms in metabolizing enzymes have been investigated in patients receiving psychotropic drugs.

CYP2D6 and antidepressantsMany antidepressants show significant differ-ences in plasma drug levels with CYP2D6 poly-morphisms (in descending order of influence)55: • Imipramine (Tofranil)• Doxepin (Adapin, Silenor, Sinequan)• Maprotiline (Deprilept, Ludiomil,

Psymion)• Trimipramine (Surmontil)• Desipramine (Noraprim)• Nortriptyline (Aventyl, Pamelor)• Clomipramine (Anafranil)• Paroxetine (Paxil)• Venlafaxine (Effexor)• Amitriptyline (Elavil)• Mianserin• Trazadone (Desyrel)• Bupropion (Wellbutrin)• Nefazodone (Serzone)• Citalopram (Celexa)• Sertraline (Zoloft).

CYP2D6 and antipsychoticsSeveral antipsychotics are also influenced by CYP2D6 polymorphisms (also in descending order of influence)55:• Perphenazine (Trilafon)• Thioridazine (Mellaril)• Olanzapine (Zyprexa)• Zuclopenthixol (Cisordinol, Clopixol,

Acuphase)• Aripiprazole (Abilify)• Flupentixol (Depixol, Fluanxol)• Haloperidol (Haldol)• Perazine (Taxilan)• Risperidone (Risperdal)• Pimozide (Orap).

CYP2C19 and antidepressantsCYP2C19 polymorphisms are likewise associ-ated with differences in drug metabolism for many antidepressants, such as (in descending order of CYP2C19-mediated influence)55:

Consider non-SSRI antidepressants for patients with the SLC6A4 variant



• Trimipramine • Doxepin• Amitriptyline• Imipramine • Citalopram (Celexa)• Clomipramine • Moclobemide (Aurorix, Manerix)• Sertraline• Fluvoxamine (Luvox).

Clinical relevance of CYP2D6 and CYP2C19Several studies have demonstrated that poor and intermediate CYP2D6 metaboliz-ers have a higher incidence of adverse ef-fects when taking CYP2D6-dependent an-tidepressants63–68; however, an almost equal number of studies did not find statistically

significant associations.69–72 Likewise, several studies have found an association between ultra-rapid CYP2D6 metabolizer status and diminished response to antidepressants,65,73,74 but no association was found in a larger ret-rospective study.75

Routine CYP2D6 and CYP2C19 screening is not recommended when prescribing psycho-tropic drugs. However, reviews of the pharma-cokinetic data have suggested a few practical applications when genetic status is already known. In general, clinicians can consider re-ducing the dose of tricyclic antidepressants by about 50% when prescribing to CYP2D6-poor-metabolizers.55,76–78

TABLE 5 gives examples of specific dose ad-justments of antidepressants and antipsychot-

Knowing the frequency of pharmaco-genomic variants in a given population can be helpful in prescribing

TABLE 5

Suggested dose adjustments based on CYP2D6 phenotypePERCENT OF STANDARD DOSE

DRUG POOR METABOLIZERS

INTERMEDIATE METABOLIZERS

EXTENSIVE METABOLIZERS

ULTRA-RAPID METABOLIZERS

Imipramine (Tofranil) 30 80 130 180

Doxepin (Sinequan) 35 80 130 175

Trimipramine (Surmontil) 35 90 130 180

Despramine (Norpramin) 40 80 125 170

Nortriptyline (Pamelor) 55 95 120 150

Clomipramine (Anafranil) 60 90 110 145

Paroxetine (Paxil) 65 85 115 135

Venlafaxine (Effexor) 70 80 105 130

Amitriptyline (Elavil) 75 90 105 130

Bupropion (Wellbutrin) 90 95 105 110

Perphenazine (Trilafon) 30 80 125 175

Haloperidol (Haldol) 75 95 100 115

Olanzapine (Zyprexa) 60 105 120 150

Risperidone (Risperdal) 85 90 100 110

Dose-adjustment values were determined by comparing drug concentration, clearance, or exposure data across phenotypes. Values have been approximated to the nearest 5%.

ADAPtED FROM INFORMAtION IN kIRChhEINER J, NICkChEN k, BAUER M, Et AL. PhARMACOgENEtICS OF ANtIDEPRESSANtS AND ANtIPSYChOtICS: thE CONtRIBUtION OF ALLELIC VARIAtIONS tO thE PhENOtYPE OF DRUg RESPONSE. MOL PSYChIAtRY 2004; 9:442–473.



ics based on CYP2D6-mediated influence. Kirchheiner’s review article55 includes several similar tables and charts based on CYP2D6 status as well as several based on CYP2C9 status. Clinicians should consider using these types of pharmacokinetic-derived charts and tables when prescribing to patients whose ge-netic status is known.

Genes that affect serotonin metabolismSeveral genes in the serotonin pathway have been investigated to determine whether they influence patients’ susceptibility to depres-sion and adverse effects and response to psy-chotropic medications. SLC6A4. Polymorphisms in the promot-er region of the serotonin transporter gene SLC6A4 appear to influence the treatment response and side-effect profiles of selective serotonin reuptake inhibitors (SSRIs). Car-riers of the SLC6A4 5-HTTLPR L alleles have fewer side effects79 and better response to SSRI treatment, and carriers of the S allele have a higher incidence of antidepressant-induced mania80 and poorer response to SSRI treatment.81 5-HT. Polymorphisms in serotonin recep-tors (2A and 2C subtypes) appear to influ-ence SSRI response and side effects. Carriers of 5-HT 2A C alleles had more severe adverse effects from paroxetine,71 but another 5-HT 2A polymorphism common to Asians is asso-ciated with better response to antidepressant therapy.82 A 5-HT 2C polymorphism was as-sociated with a lower incidence of antipsy-chotic-induced weight gain.83 Although the understanding of these re-lationships is incomplete and routine phar-macogenomic testing is not currently recom-mended, reviews of the pharmacodynamic data have suggested a few practical applica-tions when a patient’s genetic status is already known. One should consider:• Selecting treatments other than SSRIs for

depressed patients known to possess the SLC6A4 variant

• Selecting citalopram for depressed pa-tients known to carry the 5-HT 2A poly-morphism

• Avoiding treatment with antipsychotic drugs for patients known to possess the 5-HT 2C polymorphism.

■ THE FUTURE OF PHARMACOGENOMIC TESTING

The examples discussed in this article provide some insight about how pharmacogenomic test-ing is maturing and slowly being integrated into the practice of medicine. They also illustrate the complexity of the multiple stages of research that pharmacogenomic applications must go through in order to be adopted as standard practice. In the future, pharmacogenomic data will continue to accumulate, and the clinical util-ity of many other pharmacogenomic tests may be uncovered. The FDA provides infor-mation on emerging pharmacogenomic tests at its Web site, www.fda.gov.11 Its up-to-date “Table of Valid Genomic Biomarkers in the Context of Approved Drug Labels” includes boxed warnings, recommendations, research outcomes, and relevant population genetics. If the FDA continues its current policy, pro-spective randomized trials that show improve-ment in patient outcomes will remain the gold standard for determining the clinical signifi-cance of a pharmacogenomic test. Furthermore, cost-benefit analyses are likely to continue dic-tating policy regarding pharmacogenomic test-ing, and cost-benefit profiles should improve as technology advances and as information gath-ered from a single test becomes applicable to multiple medications and clinical scenarios. In the meantime, physicians should be-come familiar with the terms used in medical genetics and pharmacogenomics and begin to understand genetic contributions to the outcomes of drug therapy. For example, un-derstanding the consequences of metabolizer status and the frequency of variants in a given population can be tremendously helpful when advising our patients about anticipating po-tential problems when taking specific medi-cations and about making informed decisions about pharmacogenomic testing. This exchange of information alone may go a long way in improving therapy outcomes even when prospective pharmacogenomic testing is not routinely performed. Furthermore, an in-creasing number of patients will already have ge-notyping information available when they come to us, and clinicians need to be aware of the many pharmacogenomic applications recommended by the FDA when genetic status is known.10 ■



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ADDRESS: Joseph P. Kitzmiller, MD, PhD, Department of Pharmacology, The Ohio State University, 5072C Graves Hall, 333 West 10th Avenue, Columbus, OH 43210; e-mail [email protected].

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