Pharmacogenomics

Genetic Variations

There is a vast similarity in the DNA sequence among the 6 billion bases that make up the human genome. In fact, 99.5% of the DNA sequence is believed to be identical across the human race. At the scale of billions of bases, the 0.5% difference still accounts for millions of bases and is sufficient for meaningful differences in the genetic predisposition to diseases and variable drug response. Differences occur at the rate of one change in every 1,000 bases. Various types of genetic variations have been identified (Figure 3-2). Among the most important types of sequence variations or mutations are the single nucleotide polymorphisms or SNPs (pronounced as “snips”). SNPs refer to variations in a sequence at a single position in a DNA sequence. For example, rather than a stretch of sequence such as AATGCTAG, an individual may have AAAGCTAG. The T in the third position, in this case, is changed to an A. A population frequency of >1% is used as a threshold to define variations at a single nucleotide position as a polymorphism. When population frequency is <1%, the variations are classified as mutations. Approximately 12 million SNPs have been identified to date. Importantly, a vast number of these SNPs are “silent”—that is, they do not alter or affect the function or expression of genes. However, in certain cases, these SNPs can have a profound effect on the expression or activity of the specific protein coded by the gene harboring the SNP.

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Types of genetic variations illustrated using an example wild-type sequence. SNP = single nucleotide polymorphisms; Leu = leucine; Ile = isoleucine.

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The SNPs are of different types, broadly classified as:

1. Synonymous—these SNPs do not result in a change in the encoded amino acid. For example, an AÆG substitution in AGA to AGG still results in the Arg amino acid in the polypeptide chain.

2. Nonsynonymous: These SNPs alter the amino acid encoded by the codon. For example, a CÆA substitution in CCG to CAG results in a change in the amino acid encoded from proline to glutamine. This type of SNP is also sometimes called a missense substitution. Another type of nonsynonymous SNP is a nonsense substitution wherein a single nucleotide change in the DNA sequence results in the generation of a stop codon, which causes the termination of the transcription process.

SNPs can also be in noncoding parts of the DNA, such as in the promoter regions of the genes. The promoter region of a gene is the DNA sequence that flanks the gene and to which critical proteins called transcription factors and RNA polymerase bind, ultimately resulting in the expression of the gene. So, while variants in these regions do not alter the sequence of the encoded protein, they have the potential to affect the expression levels of the proteins by affecting the normal transcriptional rate of a gene. It is important to note that based on the presence or absence of variant(s) at a particular site, a gene can be present in one of the two or more alternate forms. Each of these forms of a gene is called an allele. An allele can be a wild-type allele, which refers to the most common version of the gene sequence in a population, or it can be a variant allele. A copy of a gene inherited from a parent can be in wild-type or variant form. Each pair of alleles represents the genotype of a specific gene. Genotypes are described as homozygous if there are two identical alleles at a particular genetic location and as heterozygous if the two alleles differ. The genotype that an individual has for a specific gene (wild type/wild type; wild type/variant; variant/variant) eventually determines the phenotype that the patient exhibits for that gene function.

Because of the existence of millions of SNPs, a naming system is in place to ensure that individual SNPs are accurately referred to in the scientific literature and clinical practice. A few different nomenclature conventions have been used for designating SNPs. The two most common ones are—a star-allele-based convention and a RefSNP-based naming convention (Table 3-2).

While SNPs are the most common types of genetic variations, another type of genetic variation are the copy number variations (CNVs). The CNVs in genes result in an individual carrying multiple copies of a gene on a chromosome. A significant example of CNV is observed in the CYP2D6 gene, with multiple functional copies of the CYP2D6 gene reported in certain individuals. The typical annotation of gene duplication or multiplication is, for example, *1xN or *2xN where xN is the number of copies. These multiple copies can be of a normal function allele, an increased function allele, or a decreased function allele.

Phase I Metabolism

The phase I reaction is an enzymatic reaction that often occurs in the liver wherein polar modifications are introduced to the molecules of the drug by the processes of oxidation, reduction, or hydrolysis. Phase I reactions facilitate the conversion of lipophilic (dissolving in lipids or fats) drug molecules to hydrophilic (dissolving in water). This group of reactions is catalyzed predominantly by the cytochrome P450 superfamily of mixed-function oxidases (CYPs).

The sequencing of the human genome has identified 57 CYP genes. Together, they account for the metabolism of >75% of prescription pharmaceuticals. The majority of CYP genes are polymorphic (exist in variant forms) and these polymorphisms are found at significant levels in the population. These polymorphisms result in either a decrease or increase in enzymatic activity leading to an increase or decrease in the levels of the drugs that are metabolized by these enzymes. Among the numerous CYP enzymes, the most important polymorphisms are seen in CYP2C9, CYP2C19, and CYP2D6. Collectively, the genes that code for these enzymes are responsible for the way biotransformation of 60% to 70% of all medications occurs. The following discussion will cover the relevant genetic variants found in each of these phase I metabolizing enzymes (Figure 3-3).

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Important gene variants found in drug-metabolizing enzymes.

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Phase II Metabolism

Among the phase II metabolizing enzymes, important pharmacogenetic associations have been shown for thiopurine S-methyltransferase (TPMT) and uridine diphosphate (UDP) glucuronosyltransferases 1A1 (UGT1A1).

UGT1A1

UGT enzymes attach a glucuronic acid moiety to the drugs and endogenous substances (like bilirubin) that enhances their solubility in water, thereby allowing them to be excreted in bile or urine. The variants of UGT1A1 known to be clinically relevant include *28 and *6.

• UGT1A1*28: This variant has significant expression in Caucasians, with approximately 10% being homozygous and about 40% heterozygous. Also, it is present at 42% to 56% population frequency in African and 9% to 16% in Asian populations.

• UGT1A1*6: This variant is common in populations with East Asian ancestry (˜20%).

This background in drug-metabolizing enzymes is useful to understand the functional consequences of the presence of genetic variants in these enzymes. Individuals can be classified into the following standard phenotypes of metabolizer status for each metabolizing enzyme gene.

• Ultra-rapid metabolizer (UM): markedly increased metabolic activity.

• Normal metabolizer (NM): previously referred to as extensive metabolic (EM) activity.

• Intermediate metabolizer (IM): patients with reduced metabolic activity.

• Poor metabolizer (PM): markedly lower metabolic activity.

Importantly, the metabolizer phenotypes are determined by genotype for a particular enzyme that an individual may have. As mentioned earlier, this is dependent on the different combinations of allele pairs (wild type and variant) that an individual has for a specific gene. An increase in metabolic activity or UM phenotype is usually a result of gain-of-function variants. In contrast, the decrease in metabolic activity of an enzyme or PM is usually a result of loss-of-function variants. The amplitude of gain or loss of function is dependent on whether an individual is homozygous or heterozygous for the gain- or loss-of-function variants. Individuals homozygous for gain-of-function variants are usually UM and those homozygous for loss-of-function are usually PM. The exact genotype-phenotype relationship may vary for different genes (Table 3-4).

TABLE 3-4.

The Assignment of Metabolizer Phenotype for the CYP Enzymes Based on Genotype

Gene	Phenotype	Genotype
CYP2C9	NM	*1/*1
	IM	*1/*2, *1/*3, *2/*2
	PM	*2/*3, *3/*3
CYP2C19	UM	*1/*17, *17/*17
	NM	*1/*1
	IM	*1/*2, *1/*3, *2/*17
	PM	*2/*2, *2/*3, *3/*3
CYP2D6 a	UM	*1/*1xN, *1/*2xN, *2/*2xN
	NM	*1/*1, *1/*2, *1/*9, *1/*41, *2/*2
	IM	*4/*10, *4/*41, *5/*9
	PM	*3/*4, *4/*4, *5/*5, *5/*6

CYP, cytochrome P450; NM, normal metabolizer; IM, intermediate metabolizers; PM, poor metabolizers; UM, ultra-rapid metabolizers.

a

xN denotes the number of copies of the CYP2D6 gene.

An important concept to understand regarding drug metabolism is the effect it has on the biological activity of the drug molecules. Typically, the drugs are bioactive molecules capable of producing the desired therapeutic effect in their native unmodified forms. The modifications of the chemical structure of the parent drug molecule in the process of metabolism often result in a reduction in the activity of the drug. However, this is not always true. For certain drugs, the process of undergoing metabolism in the body results in the activation of the drug molecule. These drugs are called prodrugs—they are administered in their inactive precursor forms and get converted to active moieties by virtue of the chemical modification that occurs in the body. Therefore, the effect of pharmacogenetic variants in the drug-metabolizing enzyme is dependent on the type of drug molecule being examined (Figure 3-4).

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The effect of functional status of metabolizing enzymes on the drug levels, efficacy, and toxicity of prodrugs and active drugs. GoF, gain of function; NF, normal function; LoF, loss of function.

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For a standard drug (eg, warfarin) with a bioactive parent moiety, a loss-of-function variant results in decreased conversion to the inactive form and an increase in the levels of the active drug molecule that can exceed the intended therapeutic range. This situation can result in increased toxicity of the drug directly related to increased levels of the drug in the circulation. On the other hand, a gain-of-function variant for an enzyme metabolizing the bioactive parent moiety will result in increased metabolism of the drug to inactive forms and as a result, there is a risk of loss of therapeutic efficacy.

For a prodrug (eg, clopidogrel), wherein the drug metabolite is the active form, a loss-of-function variant results in decreased conversion to the active form and as a result, a loss of efficacy. On the other hand, a gain-of-function variant for an enzyme metabolizing the prodrug will result in increased metabolism of the drug to active forms and as a result, an increased risk of causing a toxic drug response.

Both scenarios are observed in clinical practice. Therefore, a knowledge of the basic pharmacological characteristics of the drug is critical to understanding the potential pharmacogenetic interactions.

It is important to consider the information about genetic variants in drug-metabolizing enzymes in the context of the specific role that the enzyme plays in the metabolism of a given drug. Often, drug molecules may have multiple metabolic pathways, each contributing to the breakdown of a specific fraction of the drug. If the variant is found in an enzyme that does not contribute significantly to the breakdown of the drug, then having genetic variants in that enzyme will not have a measurable clinical impact on the pharmacological effect of the drug. A variation of this rule is when the minor metabolic pathway may be more important for the pharmacological effect of the drug. For example, the antiplatelet drug clopidogrel is broken down by enzymes called esterases (accounting for 85% of clopidogrel metabolism) and by CYP2C19 (accounting for 15% of clopidogrel metabolism). In this case, although CYP2C19 is responsible for a much smaller fraction of clopidogrel metabolism, this metabolic pathway converts the prodrug clopidogrel to its active moiety responsible for antiplatelet action; esterases convert clopidogrel to inactive metabolites. Therefore, in this case, loss-of-function variants in CYP2C19 are clinically important although the contribution of CYP2C19 to the metabolic fate of clopidogrel is relatively minor.

While metabolizing enzymes are a major focus of pharmacogenetic interactions, variants in other types of proteins such as transporters and the proteins of the immune system are also clinically relevant.

Transporters are proteins that allow the uptake of drugs and other molecules into cells. Genetic variants that affect the functional activity of transporters can prevent a drug from accumulating in the target tissue and lead to greater off-target adverse effects of drugs. Among transporters, organic anion transporting polypeptide 1B1 (OATP1B1), the protein product of a gene called SLCO1B1, is especially important in the context of pharmacogenetics. OATP1B1 is found in the liver cells and is responsible for the transport of widely used drugs such as statins, angiotensin-converting enzyme (ACE) inhibitors, and angiotensin II (AT II) receptor blockers into the liver cells (Figure 3-5). The two known variants of SLCO1B1 that are associated with reduced OATP1B1 transport function are *5 and *15.

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Organic anion transporting polypeptide 1B1 (OATP1B1) transporter-mediated uptake of medications in the liver. A, Normal or wild-type OATP1B1 allows medications such as statins, angiotensin-converting enzyme inhibitors, and angiotensin receptor blockers to be taken up into the liver cells. B, OATP1B1 with certain sequence variations (designated OATP1B1*) is unable to allow the entry of medications into the liver cells. The blood levels of the medications increase, resulting in an increased likelihood of adverse effects.

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The immune response to drug therapy can have significant implications. Drug-induced hypersensitivity reactions or drug allergies account for 10% of all adverse drug reactions. For a given drug, these reactions would occur only in a small fraction of patients. Predicting which patients would show a hypersensitivity reaction is not easy but certain genetic markers can be useful in this determination. The human leukocyte antigen B (HLA-B) protein is a component of the immune system that has been implicated in drug-induced hypersensitivity. Normally, HLA-B is expressed on the surface of cells and presents cellular peptides to T cells, a major type of immune cell. Certain HLA-B alleles are associated with susceptibility to severe skin reactions (Stevens-Johnson syndrome [SJS] or toxic epidermal necrolysis [TEN]) to drugs such as abacavir or carbamazepine. These include variants *57:01 and *15:02. The *15:02 variant is reported at a higher allelic frequency in those with Han Chinese ancestry.

Clopidogrel-CYP2C19

Clopidogrel is a widely prescribed antiplatelet drug that functions as an irreversible inhibitor of a receptor found on the surface of platelets. Clopidogrel binding to this receptor prevents adenosine diphosphate (ADP) from binding to it and activating the platelets. The key feature of clopidogrel pharmacology is that it is administered as an inactive prodrug that must be metabolized to its active form by the action of the enzyme CYP2C19. This process is affected by genetic polymorphisms in CYP2C19, as indicated in an earlier section. Variants that decrease the CYP2C19 activity decrease the formation of the active metabolite of clopidogrel and thereby decrease its antiplatelet effect. Increased variability in clopidogrel response is observed in such individuals and therapy modifications may be required.

Carriers of CYP2C19 loss-of-function alleles are at risk of more cardiovascular events (myocardial infarction [MI], stroke, stent thrombosis, etc.) due to inadequate antiplatelet effect with clopidogrel usage. Based on their genotypes, they can be classified as EM (*1/*1), UM (*1/*17, *17/*17), IM (*1/*2, *1/*3, *2/*17), and/or PM (*2/*2, *3/*3, *2/*3). Current guidelines suggest using standard clopidogrel dosing in UM and EM but considering an alternative antiplatelet agent such as ticagrelor or prasugrel for IM and PM patients. These recommendations are most beneficial and applicable for patients with acute coronary syndrome (ACS) and those undergoing percutaneous coronary intervention (PCI). Patients with stable ischemic heart disease are less likely to derive benefit from these recommendations.

Codeine-CYP2D6

Codeine is an analgesic that belongs to the opioid class of drugs. It is indicated for mild to moderately severe pain and also finds use as an antitussive medication. Codeine is a prodrug that is metabolized by CYP2D6 leading to its bioactivation to morphine in the liver. The analgesic effect of codeine is almost entirely dependent on the generation of morphine in this reaction. As indicated earlier, CYP2D6 is a polymorphic phase I enzyme, with known fully functional (*1 and *2), partially functional (*10, *17, and *41), and nonfunctional (*3, *4, *5, and *6) variants. Based on the inherited alleles, the possible phenotypes of CYP2D6 activity include UM, EM, IM, and PM.

CYP2D6 UM carriers possess multiple functional copies of the CYP2D6 gene, with reports of 2 to 13 copies present in some individuals. In patients with PM CYP2D6 phenotype, codeine is not activated to morphine. Such patients would experience inadequate pain relief from codeine and fewer uncomfortable gastrointestinal side effects although the sedation, nausea, and dry mouth are reported to be comparable between PM and EM patients. On the opposite end of the activity spectrum, the UM phenotype will result in an increased generation of morphine, making patients more susceptible to codeine’s analgesic effect as well as its serious adverse effects of drowsiness and respiratory depression, even at standard doses. The CPIC guidelines suggest avoiding codeine in both CYP2D6 UM and PM patients. The FDA label for codeine, while describing the pharmacogenetic influence on codeine pharmacology, does not recommend a specific course of action.

Simvastatin-SLCO1B1

Statins are prescribed to reduce serum cholesterol, specifically the low-density lipoprotein cholesterol (LDL-C). Due to their LDL-C-lowering property, statins have a significant effect of decreasing cardiovascular disease risk. The mechanism of action of statins involves inhibition of HMG-CoA reductase in the liver. HMG-CoA is the rate-limiting enzyme that catalyzes an early step in the synthesis of cholesterol. In response to the reduced free cholesterol content within the liver cells, the expression of the LDL receptor gene is increased. An increase in the number of LDL receptors on the surface of liver cells causes increased removal of LDL from the blood, thereby lowering LDL-C levels. While statins enjoy widespread usage, statin-associated muscle symptoms (SAMS) can limit their use, at least in certain groups of patients. The incidence of SAMS is reported to range between 7% and 29%. These muscle toxicities often lead to noncompliance with statin therapy, resulting in an increased risk of cardiovascular disease and mortality.

The LDL-C-lowering pharmacological effect of statins requires their uptake and concentration in the liver cells. The OATP1B1 transporter facilitates the liver uptake of statins in addition to several other medications (Figure 3.5). The OAT1B1 protein is encoded by the SLCO1B1 gene. The SCLO1B1*5 variant is associated with a decrease in the transport function of OATP1B1 attributed to a decrease in the expression of the transporter on the surface of liver cells. The heterozygous and homozygous carriers of the *5 variant have higher plasma concentrations of statins. This increased systemic exposure of statins is associated with an increase in the risk of development of myopathy. Among the statin drug class, this pharmacogenetic interaction is primarily ascribed to simvastatin. The risk of myopathy is higher with the 80 mg dose of simvastatin than for those on lower doses. Using a low dose of simvastatin or considering an alternative statin (such as pravastatin or rosuvastatin) is recommended by the CPIC guidelines in patients with intermediate or low function of OAT1B1. The availability of low-cost alternate statins as well as generally low incidence of adverse effects with statins has made the use of pharmacogenetic testing before statin initiation unnecessary. However, pharmacogenetic testing can help identify underlying reasons for the observation of muscle toxicity with simvastatin use and can help to guide statin switching in such patients.

Abacavir-HLA-B

Abacavir is a medication used in the treatment of acquired immunodeficiency syndrome (AIDS) caused by the human immunodeficiency virus (HIV). The use of abacavir is associated with skin hypersensitivity reactions, particularly SJS. A genetic mechanism for these reactions has been elucidated with the identification of the HLA-B gene variants. HLA-B belongs to the major histocompatibility complex (MHC) family of proteins that are expressed on the surface of almost all cells and participate in antigen presentation to the immune system. The protein breakdown products are attached to the MHC molecules for presentation on the cell surface. Physiologically, the presentation of “self” proteins or the body’s own proteins does not activate the immune system, whereas infection by pathogens results in the presentation of “non-self” proteins and elicitation of an immune response. Certain drug molecules also get processed in a manner similar to proteins and are presented on cell surfaces complexed with MHC molecules.

In the case of abacavir, such complexation with HLA protein occurs in patients with certain variants of HLA-B. In particular, the HLA-B*57:01 allele binds abacavir and presents the drug along with other peptide fragments on the surface of cells. This presentation results in the recognition of peptide fragments on the cell surface as non-self and causes the development of a hypersensitivity reaction due to immune system activation. This pharmacogenetic mechanism does not affect drug pharmacokinetics or pharmacodynamics; rather it affects only the risk of hypersensitivity reactions. The presence of even just one HLA-B*57:01 allele is associated with an increased risk of hypersensitivity reactions and there are no intermediate phenotypes. The evidence supporting the role of HLA-B*57:01 in abacavir-induced hypersensitivity reaction is quite strong; CPIC recommendations call for HLA-B*57:01 screening in all patients starting abacavir for the first time before the initiation of therapy. In patients lacking the HLA-B*57:01, abacavir can be used at standard doses. In patients carrying HLA-B*57:01, abacavir is not recommended.

Another HLA-B variant with known pharmacogenetic interaction is HLA-B*15:02 which is implicated in carbamazepine-associated SJS and TEN.

Warfarin-CYP2C9-VKORC1

Warfarin is an oral anticoagulant that has been in clinical usage for more than six decades and is frequently called by its former brand name Coumadin. The initiation of warfarin therapy for its anticoagulation effect is characterized by frequent dose adjustments needed to achieve target international normalized ratio (INR) values in each patient. If the dose of warfarin is too high, it increases the risk of bleeding, whereas if the dose is too low, there is an increased risk of thromboembolism. The dose of warfarin required to achieve the therapeutic INR can be highly variable between patients; up to 10- to 20-fold differences (0.5 to 7 mg) in the warfarin dose required have been observed. Genetic factors have been shown to account for a significant portion of warfarin’s dose variability.

Variants in three genes have been shown to influence warfarin response: CYP2C9, vitamin K epoxide reductase 1 (VKORC1), and CYP4F2. The role of these genes in warfarin response is evident in examining warfarin’s mechanism of action (Figure 3-6). The S enantiomer of warfarin (the active stereoisomer) is metabolized by the enzyme CYP2C9 to inactive metabolites. Warfarin’s molecular target protein is VKORC1, a protein that warfarin inhibits. VKORC1 is responsible for converting vitamin K (in its epoxide form) to reduced vitamin K, which functions as a cofactor in the activation of clotting factors. The reduced vitamin K is converted back to epoxide vitamin K by the action of the enzyme gamma-glutamyl carboxylase (GGCX). These conversion reactions between epoxide and reduced vitamin K catalyzed by VKORC1 and GGCX are termed the vitamin K cycle. The enzyme CYP4F2 removes reduced vitamin K from the vitamin K cycle by converting it to hydroxy-vitamin K1. Overall, warfarin inhibition of VKORC1 prevents the generation of reduced vitamin K, which leads to the inhibition of clotting factor activation. CYP2C9 prevents warfarin activity by converting it to inactive metabolites. The action of CYP4F2 is consistent with the warfarin effect as it limits the amount of reduced vitamin K available for clotting factor activation.

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The mechanism of action of warfarin. CYP = cytochrome P450; GGCX = gamma-glutamyl carboxylase; VKORC1 = vitamin K epoxide reductase 1.

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The CYP2C9 genetic variants have been indicated earlier. Especially important are the loss-of-function alleles—*2 and *3. Patients with these alleles have a higher sensitivity to warfarin due to decreased metabolism of warfarin to inactive metabolites. Such patients need lower doses of warfarin to achieve the therapeutic INR. With regard to VKORC1, the most common variant is seen in the promoter region of the gene. The SNP at the –1639 position causes a decrease in the transcription of the VKORC1 gene and hence, a decrease in the expression of the VKORC1 protein. Since the target protein of the warfarin effect is reduced, patients carrying the VKORC1 1639G>A SNP have a greater sensitivity to warfarin and thereby lower dose requirement. The allelic frequency of CYP2C9 and VKORC1 across different races shows important differences: CYP2C9 *2 and *3 are seen at higher levels in the white population (13% and 7%, respectively) as compared to Asian (0 and 4%) and Black populations (3% and 2%); VKORC1 –1639G>A is seen at a frequency of 40% in Whites, 91% in Asians, and 11% in Black populations. In patients with African ancestry, CYP2C9*5, *6, *8, and *11 are important in the determination of warfarin dose. A SNP in the CYP4F2 gene (rs2108622; designated as *3) has been shown to be associated with a higher warfarin dose requirement.

The recommendations from CPIC guidelines include using published and validated algorithms for warfarin dosing in the non-African carriers of VKORC1 –1639G>A and CYP2C9*2 and *3 variants. The carriers of either VKORC1 –1639G>A or CYP2C9*2 and *3 have lower dose requirements, whereas those with the loss-of-function CYP2C9 variants as well as VKORC1 –1639G>A have the lowest warfarin dose requirements. In contrast, wild-type CYP2C9 and VKORC1 carriers require higher warfarin doses. The incorporation of CYP4F2 genetic information has also been shown to improve the accuracy of warfarin dose prediction. The warfarindosing.org website contains the two major dosing algorithms developed for the determination of warfarin dose: the Gage algorithm and the International Warfarin Pharmacogenetics Consortium (IWPC) algorithm. These algorithms integrate genetic as well as nongenetic factors in the determination of warfarin dose. Warfarin dose determination shows that the pharmacogenetic factors, although important, are not always sufficient to explain the variability in drug response. Nongenetic factors such as the patient’s age, race, weight, height, and clinical factors such as the history of smoking, presence of liver disease, and use of other co-administered drugs (statins, amiodarone, antifungals, antibiotics, etc.) can have a significant effect on the warfarin dose required in each patient. This integrated approach that factors pharmacogenomic evidence into therapeutic decision making along with patient and clinical characteristics represents the spirit of precision medicine.

The pharmacogenetics of warfarin is unique in two different ways. First, it is one of the few examples showing how pharmacogenetic variants in pharmacodynamic proteins can influence drug response. The majority of the well-studied pharmacogenetic interactions are based on variants in pharmacokinetic proteins such as metabolizing enzymes and transporters. VKORC1 variants show that there likely are several more clinically meaningful variants in the pharmacodynamic proteins that have not been discovered yet. Second, the pharmacogenetics of warfarin illustrates the polygenic nature of warfarin response—ie, genetic variants in multiple genes influence response to warfarin. Frequently, how individual genes, in isolation, influence drug response has been the focus of attention. However, the drug response in the body is a composite of multiple proteins made by multiple genes, some affecting the active levels of the drugs and others affecting the pharmacological effect produced. These proteins/genes can be of the same functional class (e.g., metabolizing enzymes) or divergent protein classes (metabolizing enzymes vs. receptors). In a specific patient, the observed genetic influence on drug response is a net effect of all genes with which that drug interacts in the body to produce its pharmacological activity.

As illustrated by the above examples, pharmacogenomics-guided drug therapy has the potential to improve clinical outcomes of both efficacy and adverse effects. However, the application of this guidance is often dependent on the availability of a patient’s genetic sequence information. The genetic sequencing tests are available in different formats: single-gene tests, gene panels, and whole-genome sequencing. The cost of getting the genetic sequencing and the turnaround time for getting the genetic information to the prescribers often impede the full adoption of pharmacogenetic guidance. However, if this information were already available, then many of the pharmacogenomic recommendations could be readily applied in the selection of the right drug at the right dose. Such preemptive genetic testing would enable the application of pharmacogenomic-guided drug therapies over the lifetime of a patient. Unlike other diagnostic tests (blood sugar, lipid panels, etc.), genetic tests for each specific gene need to be performed only once and can provide immense value throughout a patient’s lifespan. The proliferation of such tests and services will expand the patient population who have their genetic information available to use in therapeutic decision making.