The Application of Drug-Dosing Guidelines Based on Preemptive Genetic Testing

The application of genetic data to effectively influence health care outcomes is poised for rapid acceptance. Genetic testing can provide results that can be used to make the best therapeutic choices.

Specific genetic testing results related to drug therapy are gaining acceptance as decision support data in various clinical settings, including hospitals and community pharmacies.^1-4 Genetic testing is the basis for the clinical application of pharmacogenetics, relating the variability in response to a drug to variability in a specific gene. The genes of interest in pharmacotherapy are those that code for specific proteins, including drug receptors (eg, beta adrenergic), drug transporters (eg, organic anion), and drug metabolizing enzymes (eg, cytochrome P450; CYPs).

Currently, ready access to genetic testing for pharmacogenetics is limited, and is mostly available at larger research hospitals and academic medical centers which have the instrumentation to perform the genetic testing allowing rapid turnaround of test results, for example, within 24 hours and sooner.^1,3,5 Application of pharmacogenetics in the community pharmacy setting includes genetic testing through partnerships with clinical laboratories.² A limitation in the community pharmacy setting is the lack of rapid turnaround of genetic testing results, which may take approximately 6 to 14 days.^6,7

Clinical Application of Pharmacogenetics

In order for an individual to optimally benefit from the clinical application of pharmacogenetics, the results of genetic testing should be available at the time of therapeutic decision making. Point-of-care testing products which can facilitate decision making are currently in development and have undergone clinical evaluation; however, they are not widely available for clinical use.^8,9

Eventually, as costs continue to decrease, “preemptive” genetic testing in the form of whole-genome sequencing will become a standard. Here, once the testing is done, the data can be stored in a secure database and queried at the time of decision making, thus optimizing the use of genetic data in clinical therapeutics.^10,11

In the future, deoxyribonucleic acid (DNA) sampling and whole-genome sequencing will occur early in life, likely at the time of birth. The genetic data can then be utilized for medical decision making throughout an individual’s life. The cost of whole-genome testing has been decreasing rapidly and is likely to fall below $1000 in 2013.^12,13 Once the cost is established at an acceptable level, the use of whole-genome preemptive data will supplant the use of current testing approaches.

To address a second barrier to the clinical implementation of pharmacogenetics—the lack of peer-reviewed and vetted pharmacogenetic-based dosing guidelines—the Clinical Pharmacogenetics Implementation Consortium (CPIC) is providing guidelines for specific gene—drug pairs. Currently, guidelines are available for thiopurine methyltransferase (TPMT)- thiopurines,¹⁴ CYP2C19-clopidogrel,¹⁵ CYP2C9 and VKORC1-warfarin,¹⁶ CYP2D6-codeine,¹⁷ HLA-B-abacavir,¹⁸ SLCO1B1-simvastatin,¹⁹ and HLA-Ballopurinal.²⁰ A guideline for CYP2D6 and CYP2C19-tricyclic antidepressants has recently been published, and 8 other guidelines are being developed.^21,22

These guidelines are developed with the assumption that genetic testing data, such as whole-genome sequencing data, would be available for use at the time of therapeutic decision making.²³ The data provided by preemptive genetic testing would allow for optimal personalized medicine, as the point-of-care therapeutic decisions would be based on an individual’s geneticdata. The CPIC guidelines would then be used to show how the clinician should utilize the genetic test results.

Genetic information is in the form of DNA, which consists of a sequence of approximately 3 billion base pairs [adenine (A) coupled with thymine (T) and guanine (G) coupled with cytosine (C)], packaged in the 23 chromosomes that we receive from each of our parents (46 chromosomes total). Genes are sections of DNA sequences that code for the production of amino acids to make proteins. As we receive DNA from each parent, we are receiving a set of genes. A base at a specific location in a gene from each parent is referred to as the genotype. A single nucleotide polymorphism (SNP; pronounced “snip”) is a variation in the DNA sequence where an expected base (A, T, G, C) is replaced by another base at a single location in the sequence. This single base change can result in altered function of the protein that is formed. A reference SNP number (ie, rs number) is assigned to each specific SNP in the National Center for Biotechnology Information SNP database. The rs number is a specific and consistent identifier of a given SNP.

In order to have an idea of how preemptive genetic testing can be utilized in the context of pharmacogenetics, we provide 2 examples using the DNA data provided by preemptive genetic testing of 5 individuals. The testing was performed by a direct-to-consumer (DTC) genetics company and provided information on nearly 1 million SNPs for each individual. These “raw data” provided by the DTC company were stored in a secure database to be made available for query when clinical decision making is supported by the use of genetic data. We then apply the CPIC guidelines for the drug-gene pairs; simvastatin — SLCO1B1 and clopidogrel – CYP2C19.

Simvastatin — SLCO1B1

SLCO1B1 is a gene that codes for the influx (uptake) transporter protein OATP1B1 (organic anion transporter polypeptide 1B1). OATP1B1 is responsible for the transport of many different drugs from the blood into various tissues, including hepatic tissue.²⁴ In 1 study, there were more than 90 SNPs identified in the SLCO1B1 gene.²⁵ One common SNP, rs4149056, where C replaces T at a specific location in the SLCO1B1 gene DNA sequence, results in the transporter having decreased function. Decreased function of OATP1B1 means that less simvastatin is moved from the blood into hepatocytes, where it exerts its pharmacologic effect (inhibition of HMG-CoA reductase) and is also metabolized. This results in greater exposure and potentially toxicity to the drug, as evidenced by an increased area under the simvastatin plasma-concentration versus time curve. In patients taking simvastatin, the rs4149056 SNP is associated with an increased risk of myopathy.²⁶

Querying the database of preemptive genetic data for the 5 individuals, we see that 3 individuals have a TT genotype (1 T from each parent), while 2 individuals have the rs4149056 SNP with a CT genotype (Table). The C, received from 1 parent, imparts increased risk of myopathy. The CPIC guidelines point out that individuals with a TT genotype have normal risk of myopathy, those with a CT genotype have intermediate risk of myopathy, and a CC genotype is associated with a high risk of myopathy.¹⁹

With respect to dosing simvastatin in a CT genotype individual, the guidelinesstate the position of the FDA, recommending against the use of the 80-mg dose. A lower dose should be considered and, if efficacy is compromised, an alternative statin should be used. Additionally, a warning of increased risk of myopathy with simvastatin is noted for CT (and CC) genotype individuals with the use of a 40-mg dose. Here, a lower dose (20 mg) of simvastatin or alternative statin is recommended.¹⁹

Other considerations must be taken into account when dosing simvastatin, such as drug interactions. The CPIC guidelines should be referred to for a comprehensive presentation of the simvastatin-SLCO1B1 interaction.¹⁹

Clopidogrel — CYP2C19

Clopidogrel is an inhibitor of platelet aggregation that works by irreversibly binding to the platelet adenosine diphosphate (ADP) P2Y₁₂ receptor. Clopidogrel is a prodrug that requires bioactivation by the cytochrome P450 enzyme CYP2C19, drug metabolizing enzyme, to elicit its therapeutic benefits.^27,28

The CPIC dosing guidelines refer to 2 common SNPs in the CYP2C19 gene DNA sequence that results in altered enzyme function. The rs4244285 SNP encodes the CYP2C19*2 variant. The rs4244285 SNP describes the case where G is replaced with C or A and results in loss-of-function of the CYP2C19 enzyme. Loss-of-function in the CYP2C19 enzyme decreases the conversion of clopidogrel to its active metabolite.

Querying the database of preemptive genetic data for the 5 individuals, we see that 3 individuals have a GG genotype, one G from each parent, while 2 individuals have the rs4244285 SNP with the AG genotype. The CPIC dosing guidelines for clopidogrel recommend not using the drug in individuals who carry at least 1 variant allele (*1/*2 or *2/*2). These individuals should receive prasugrel or another therapeutic alternative. This is especially the case for individuals having undergone percutaneous coronary intervention (PCI) with stent placement(s). Data show that these individuals, when carrying 1 or 2 loss-of-function (eg, *1/*2 or *2/*2) forms of the CYP2C19 gene, are at significantly increased risk of cardiovascular events.²⁹ Genotyping is indicated in this setting and can help the clinician decide if clopidogrel is a therapeutic option (ie, for *1/*1 individuals), or if another therapeutic agent such as prasugrel is needed (eg, in *1/*2 or *2/*2 individuals).

The rs12248560 SNP encodes the CYP2C19*17 variant, describing the replacement of a C by either a T or an A at a specific location in the DNA sequence of the CYP2C19 gene. Two of the 5 individuals with preemptive genetic data have the CYP2C19*17 variant. One individual is homozygous (*17/*17), having received a T from each parent. The second individual is heterozygous, receiving 1 C and 1 variant T (*1/*17).

The other individuals have the common CC genotype. Individuals with 1 or 2 variant *17 forms of the CYP2C19 enzyme have increased activity and are considered to be ultrarapid metabolizers (UMs). These individuals are very efficient at bioactivating clopidogrel, resulting in increased formation of the active form of the drug. Individuals who are UMs demonstrate normal or potentiated inhibition of platelet aggregation in response to clopidogrel. The CPIC dosing guidelines recommend following the package label dosing instructions, noting however that these patients may be at increased risk of bleeding.¹⁵

Use of Pharmacogenetics

The simvastatin-SLCO1B1 and clopidogrel-CYP2C19 examples presented here address 3 major components of the use of pharmacogenetics. First, preemptive genetic data can be used to make a drug selection based on avoidance of a potential adverse event. With the simvastatin — SLCO1B1 example, an alternative treatment can be chosen that would greatly decrease or avoid the potential of myopathy. Second, the clopidogrel – CYP2C19 example points to the use of preemptive genetic data to choose the optimal therapeutic agent based on efficacy; here, optimally decreasing the potential for a stent thrombosis after PCI.

The third component is economics, and the clopidogrel — CYP2C19 example can be used to demonstrate this. Currently, with preemptive testing not being standard, individual 1-time genetic testing specifically for CYP2C19 may cost as much as $325. Clopidogrel, now available as a generic product, is relatively inexpensive, whereas prasugrel and ticagrelor as potential alternatives, notwithstanding health insurance, are considerably more expensive. Optimal antiplatelet therapy is critical in the PCI population, where the cost of treatment of a stent thrombosis can be in excess of $40,000.

Genetic testing can provide results that can be used to make the best therapeutic choice (eg, clopidogrel for the *1/*1 individual versus prasugrel for the *1/*2 or *2/*2 individual). The testing can facilitate therapeutic decision making that will help prevent stent thrombosis— induced myocardial infarction or death as well as positively impact health care economics. Here, CYP2C19 genotyping and either clopidogrel or an alternative drug is clearly less expensive that the cost of treating a patient with a stent thrombosis. In the future, with preemptive testing, the savings of health care dollars can be significant.^30,31

The application of genetic data to effectively influence health care outcomes is poised for rapid acceptance. The ability to identify an SNP in drug receptors, transporters, and drug metabolizing enzymes and have the data available at the time of clinical decision making is the ultimate goal. As demonstrated, the availability of preemptive genetic testing data and pharmacogenetic-based drug dosing guidelines can help optimize pharmacotherapy decision making.

References

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About the Authors

David F. Kisor, BSPharm, PharmD, RPh, is professor of pharmacokinetics in the department of pharmaceutical and biomedical sciences, focusing on pharmacogenetics and pharmacokinetics, at the Raabe College of Pharmacy at Ohio Northern University. Kisor received his bachelor of science degree in pharmacy from the University of Toledo and his PharmD from The Ohio State University. He has integrated pharmacogenetics into the pharmacokinetic subject matter since 1998. He is a member of the American Pharmacists Association, the American Association of Colleges of Pharmacy, the National Coalition for Healthcare Provider Education in Genetics, and the Personalized Medicine Coalition (PMC), and is the advisor for the ONU student chapter of the PMC. He has written numerous papers related to pharmacogenetics and is a co-author of a recently published book on the topic.

Jon E. Sprague, RPh, PhD, is professor of pharmacology and dean at the Raabe College of Pharmacy at Ohio Northern University. Before returning to ONU as dean in 2006, Dr. Sprague was chair and professor of pharmacology at the Virginia College of Osteopathic Medicine at Virginia Tech University. He received his PhD in pharmacology and toxicology from Purdue University and his pharmacy degree from Ferris State University. His research interests include studying the hyperthermic mechanisms of the substituted amphetamines, namely 3,4-methylenedioxymethamphetamine (MDMA, Ecstasy). One of Dr. Sprague’s major professional priorities is to assist in the implementation of personalized medicine to improve health outcomes. He recently coauthored a textbook entitled, “Pharmacogenetics, Kinetics, and Dynamics for Personalized Medicine.”