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Overview of pharmacogenomics

Overview of pharmacogenomics
Literature review current through: Jan 2024.
This topic last updated: Dec 20, 2023.

INTRODUCTION — There is tremendous interindividual variability in the response to pharmacologic agents [1]. Plasma drug levels can vary more than 1000-fold when the same drug dose is administered to two individuals having approximately the same weight [2]. Drug-drug interactions, drug-food interactions, sex, age, disease state (ie, renal and hepatic function) and pregnancy can all influence variability in drug responses between patients. However, genetic factors are also likely to play a major role, since the individual response to a given pharmacologic agent is highly reproducible [3,4].

In theory, the identification of genetic factors that influence drug absorption, metabolism, and action at the receptor level should allow for individualized therapy; this could optimize drug efficacy and minimize toxicity profiles in a given population [1,5-8]. The potential for cost savings (through increased drug efficacy) and for decreased morbidity and mortality (through increased drug safety and fewer adverse drug reactions [ADRs]) is immense [9-13]. Although many ADRs are preventable and attributed in many cases to human error, others appear idiosyncratic, and potentially influenced by genetic factors. In one study of 2227 ADRs identified in a large teaching hospital, fewer than 50 percent had readily identified causes, and thus, might have been due to pharmacogenetic variability [14].

This topic provides a practical overview of the field of pharmacogenomics, including the historical context, the different ways in which pharmacogenomic differences can affect the response to drug therapy, an overview of US Food and Drug Administration (FDA) approved labeling of medications for which genetic testing is recommended, and the challenges that must be overcome before routine pharmacogenetic testing (genotyping) is fully integrated into mainstream clinical medicine.

TERMINOLOGY — The following terminology is used to describe factors that contribute to the effect of a specific drug on a specific individual:

Pharmacogenomics – Pharmacogenomics refers to the role of various components of the genome on response to a drug. Among the most commonly studied are genetic sequence variants, structural changes in chromosomes (eg, translocations), epigenetic variants (eg, changes in gene methylation), and variation in the expression profile of genes (changes in messenger RNA [mRNA] levels) or noncoding RNA (eg, changes in microRNA). The genetic variation can be inherited through the germline or acquired (eg, somatic mutation in a tumor). The availability of high-throughput techniques to interrogate the entire genome has facilitated many pharmacogenomic studies. (See "Next-generation DNA sequencing (NGS): Principles and clinical applications".)

Pharmacogenetics – Pharmacogenetics is a subcategory of pharmacogenomics that refers to the role of genetic variation on response to a drug. Pharmacogenetics generally is used to refer to a specific DNA polymorphism or coding variant rather than epigenetic or transcriptomic changes across the genome. In practice, pharmacogenetics and pharmacogenomics are often used interchangeably.

Pharmacokinetics – Pharmacokinetics (PK) refers to how a drug moves through an individual's body [15]. A drug's PK includes its absorption, distribution, metabolism, and elimination, all of which affect the drug's effect by altering the drug's concentration at its site of action.

Pharmacodynamics – Pharmacodynamics (PD) refers to an individual's body's therapeutic response to a drug [15]. This generally is determined by the drug's affinity and activity at its site of action, which is often a receptor.

Genotyping – Genotyping refers to determining the combination of alleles (variants) at a specific location in the genome. The alleles can be single base changes, insertions, deletions, or tandem repeats.

Genetic variation – Genetic variation refers to differences in genetic sequences among individuals in a population. Single nucleotide polymorphisms (SNPs) refer to variation at a single base pair, typically with a population frequency of at least 1 percent. Other forms of variation include insertions, deletions, copy number variants, and short tandem repeats. Variants that are seen at much lower prevalence than 1 percent of the population are often referred to as mutations, although this term may also be used to distinguish between variation that is inherited versus variation that arises de novo (see "Genetics: Glossary of terms"). All forms of variation have the potential to impact phenotype, regardless of their frequency, but the impact depends on a number of factors including the location of the variation within the genome and the functional consequences of the variation.

Epigenetic changes – Epigenetic changes are those that affect genes without altering the gene sequence. This may occur via changes in gene methylation or histone modification (methylation, acetylation), either of which can influence the rate of transcription or silencing of gene expression. Other epigenetic changes include the alterations in noncoding RNAs and telomere length. These epigenetic changes can be passed on from parents to offspring but can also result from environmental influences on the epigenome.

An example of an epigenetic change that affects drug metabolism is reduced sensitivity of a tumor to a chemotherapeutic drug due to gene methylation [16]. Additional information about epigenetic regulation is discussed separately. (See "Principles of epigenetics".)

HISTORICAL CONTEXT — The roots of pharmacogenomics may date back as early as the 6th century BC, when Pythagoras was said to have recognized that eating fava beans caused illness in some, but not all, individuals [17]. In the 1940s, the immunochemist William Boyd noted that in contrast to Mediterranean populations, native Britons almost never developed hemolytic anemia after ingestion of fava beans; he suggested a genetic difference as the probable explanation [17]. It is now known that the hemolytic anemia associated with ingestion of fava beans, which may also occur with a variety of pharmacologic agents, is due to X-linked glucose-6-phosphate dehydrogenase deficiency (G6PD) [17]. (See "Diagnosis and management of glucose-6-phosphate dehydrogenase (G6PD) deficiency", section on 'Inciting drugs, chemicals, foods, illnesses'.)

The following pioneering discoveries ushered in the modern field of pharmacogenetics:

In 1932, Snyder attributed the 'phenylthiourea non-taster' phenotype to an autosomal recessive trait whose inheritance varied according to ethnicity [18].

In the 1950s, patients with an inherited deficiency of plasma cholinesterase were noted to have a prolonged paralytic response to suxamethonium [19].

In 1957, Motulsky first suggested that interindividual differences in drug efficacy as well as adverse drug reactions (ADRs) were at least partially attributable to genetic differences [20]. The term "pharmacogenetics" was first coined by Frederich Vogel, a German geneticist, in 1959 [21].

The role of genetics in the interindividual variation in drug response was reinforced by a series of twin studies conducted in the early 1960s [22-26]. Plasma half-lives of many drugs, including warfarin, were found to be similar in monozygotic twins, but varied significantly among dizygotic twins, siblings, and the general population.

In the late 1970s, two independent groups associated a deficiency in drug metabolism that was inherited in an autosomal recessive pattern with a markedly higher frequency of side effects in certain volunteers taking the antihypertensive debrisoquine [27] and the antiarrhythmic sparteine [28]. Approximately ten years later, the metabolism of both drugs was shown to result from allelic variation at the cytochrome P450 2D6 (CYP2D6) locus [29]. This was the first example of applied genotyping in the field of pharmacogenetics.

Since then, advances in human genetic technology and an increased understanding of the molecular basis of drug metabolism, transport, and action at the level of its target (often a receptor) has led to the characterization of dozens of genetic variants that influence the response to drug therapy. Adverse drug reactions remain a leading cause of death worldwide, as noted in a 2022 review [30].

WAYS IN WHICH GENETIC FACTORS INFLUENCE DRUG RESPONSE — The heritability of some drug responses was formally established via genetic studies, including the twin studies of Vessel and Page described above (see 'Historical context' above) [22-26]. However, most drugs have not been formally studied to assess the potential for response variability based upon hereditary characteristics, primarily because it is neither safe nor ethical to administer most medications to individuals in whom they are not indicated. Barring formal genetic studies, the distribution of responses to a certain drug in populations can strongly suggest a genetic component.

The interindividual response distribution to a drug may be either multimodal or unimodal. A multimodal distribution suggests distinct population subgroups of responders, and therefore plausibility of a pharmacogenetic basis for response heterogeneity [3]. A unimodal drug response distribution also supports the possibility of pharmacogenetic variation in response, with subjects demonstrating either a "good" or a "poor" response.

In particular, the combination of significant interindividual variability in level and/or response to a drug plus high repeatability within individual patients (the likelihood of a subsequent beneficial/poor response to a drug given a prior response) strongly suggests the potential for pharmacogenetic effects [3].

Pharmacogenomic influences on drug response have traditionally been divided into four categories based upon the impact of genetic variability on the pharmacologic properties of a drug [31]:

Effect on drug pharmacokinetics; an example is a genetic variant that alters drug metabolism, affecting plasma concentration.

Effects on pharmacodynamics; an example is a genetic variation that reduces binding of the drug to its receptor, thereby decreasing therapeutic efficacy.

Effects on idiosyncratic reactions, such as the likelihood of a hypersensitivity reaction to a certain drug.

Effects on disease pathogenesis or severity and response to specific therapies; these include specific molecular defects related to the pathogenesis of certain malignancies for which specific targeted therapies have been developed.

Specific examples of medications and specific genetic variants relevant to their metabolism or targeting, along with indications for when pharmacogenetic testing is indicated, are discussed in more detail below. (See 'Use of genomic biomarkers to guide therapy' below.)

The following sections will expand upon these four categories and provide clinically relevant examples illustrating how pharmacogenetic variability might potentially influence drug response.

Altered pharmacokinetics — Pharmacokinetics refers to the transport and metabolism of administered drugs, including absorption, distribution, tissue localization, biotransformation, and excretion [32]. The vast majority of pharmacogenetic investigations reported in the literature have been in this area, with the major areas of study being genetic differences in drug metabolizing enzymes and drug transporters.

In humans, there are two phases of xenobiotic (ie, substances foreign to the body) metabolism that are controlled by several hundred drug metabolizing enzymes (figure 1), and their corresponding genes:

Phase I metabolism (modification) – During phase I metabolism, polar groups (charged to permit electrostatic interactions) are added to lipophilic molecules by oxidation, reduction, or hydrolysis to facilitate water-solubility. This group of reactions is catalyzed predominantly by the cytochrome P450 superfamily of mixed function oxidases (CYPs), which represent a classic example of polymorphic (ie, occurring in different types) drug metabolizing enzymes. (See "Drugs and the liver: Metabolism and mechanisms of injury", section on 'Phase I reactions'.)

Phase II metabolism (conjugation) – Following phase I metabolism, most compounds are still insufficiently hydrophilic for excretion, and require further processing (phase II reactions result) to form readily excretable, nontoxic substances. An example of a polymorphic phase II drug metabolizing enzyme is thiopurine-S-methyltransferase (TPMT), which is involved in the metabolism of azathioprine and 6-mercaptopurine (6-MP) [33]. (See "Drugs and the liver: Metabolism and mechanisms of injury", section on 'Phase II reactions'.)

CYP isoenzymes and drug metabolism — The cytochrome P450s (CYPs) are members of a superfamily of oxidative enzymes, which represent the major system for oxidative metabolism of therapeutic substances. Sequencing of the human genome has revealed 58 different human CYP genes, which encode various CYP isoenzymes. Information on human CYP P450 genes is available online at http://drnelson.uthsc.edu/cytochromeP450.html [34].

CYP enzyme activity can be affected by genetic and environmental factors. One of the more common environmental influences occurs through drug-drug interactions. A common example is induction or inhibition of CYP3A4 caused by administration of a drug, which in turn alters the metabolism of a second drug. This subject is discussed in detail separately. (See "Drugs and the liver: Metabolism and mechanisms of injury".)

More applicable to the field of pharmacogenomics is the fact that the majority of the CYP genes encoding for enzymes that are active in xenobiotic metabolism are polymorphic, and polymorphisms that affect drug metabolism are seen in a significant portion of the population [27,35-37]. In many cases, the prevalence varies according to ancestry. As an example, expression of CYP2D6 is functionally absent in 7 percent of individuals with ancestry from Europe and Africa, while deficiency is rare among individuals with ancestry from Asia [38]. Due to the importance of these genes, a website (http://drnelson.uthsc.edu/cytochromeP450.html) [34] has been created that is continuously updated for newly identified CYP polymorphisms at https://www.pharmvar.org/.

Polymorphisms in CYP genes may contribute to either diminished or absent metabolism, or excessive metabolism of a compound [39]. In general, genotypic CYP variations result in three metabolic phenotypes: ultra-rapid metabolizers, extensive (normal) metabolizers, and poor metabolizers.

The clinically most important polymorphic variations in hepatic CYPs are seen in the CYP2C9, CYP2C19, CYP2D6, and CYP3A4 genes, which code for enzymes that are responsible for the phase I metabolism of approximately 60 to 70 percent of all therapeutic medications used in humans.

Clopidogrel and CYP2C19 variants — Although guidelines for CYP2C19 genotype-directed antiplatelet therapy are available from the Clinical Pharmacogenetics Implementation Consortium, many experts do not recommend routine testing of patients for "clopidogrel resistance" by genetic testing for CYP2C19 poor metabolizers [40].

This subject is discussed in detail separately. (See "Clopidogrel resistance and clopidogrel treatment failure", section on 'Variation in clopidogrel metabolism'.)

CYP2D6 variants — Given the evolving knowledge of pharmacogenomics and its impact on pharmacokinetics, preliminary dosing recommendations for several drugs have been made based upon known genetic variations in drug-metabolizing enzymes (figure 2) [41,42]. However, these have not been validated by prospective studies. Although guidelines for dosing of codeine and selective serotonin reuptake inhibitors based upon CYP2D6 phenotype are available from the Clinical Pharmacogenetics Implementation Consortium [43,44], routine assay to identify specific CYP2D6 genotypes as a means of choosing a dose for any of these compounds is not yet considered standard practice. (See "Selective serotonin reuptake inhibitors: Pharmacology, administration, and side effects", section on 'Dose'.)

Genetic polymorphisms have been particularly well studied in the CYP2D6 subfamily, which is responsible for the metabolism of a wide variety of drugs such as codeine, nortriptyline, metoprolol, the selective serotonin reuptake inhibitors (SSRIs), and tamoxifen [45,46]. CYP2D6 inhibitors are listed in the table (table 1). (See "Serotonin-norepinephrine reuptake inhibitors: Pharmacology, administration, and side effects" and "Mechanisms of action of selective estrogen receptor modulators and down-regulators", section on 'Altered tamoxifen metabolism'.)

CYP2D6 is highly polymorphic, with over 90 known allelic variants [47]. The following example illustrates the markedly different impact that the same genetic variant in CYP2D6 can have on the pharmacokinetic profile of two drugs, codeine and nortriptyline.

Both codeine and nortriptyline are metabolized by CYP2D6; however, codeine is a prodrug and its analgesic properties are not manifest until it is metabolized by CYP2D6, primarily to morphine and codeine-6-glucuronide. In contrast, nortriptyline is the active moiety and its metabolism results in inactivation of the drug to its primary metabolite.

At conventional doses, subjects who are poor metabolizers based upon CYP2D6 genotype will derive no therapeutic benefit from codeine (because it will not be converted to its active moiety), but they may be "overdosed" with nortriptyline, and at increased risk of side effects (figure 3).

Conversely, at conventional doses of codeine, subjects who are ultra-rapid metabolizers based upon CYP2D6 genotype have higher than expected morphine levels (an initial "overdose"), with more side effects and a shorter than expected duration of pain control [48]. On the other hand, these patients may derive no significant therapeutic benefit from nortriptyline because of excessive metabolism of the drug.

Thiopurines and polymorphisms in TPMT and NUDT15 — Polymorphisms in the CYP isoenzymes represent the most common genetic variant affecting pharmacokinetics, but there are others. As an example, thiopurine S-methyltransferase (TPMT, OMIM 187680) is responsible for the metabolism of the class of therapeutic compounds called thiopurines (eg, azathioprine, 6-mercaptopurine [6-MP], thioguanine).

Polymorphisms in the TPMT gene can result in functional inactivation or markedly decreased activity of the enzyme, and an increased risk of treatment-related leukopenia [49-52]. Over 24 low-functioning genetic variants have been identified, but the two most common (TPMT*2 and *3) account for more than 95 percent of defective TPMT activity in patients [33,53-55]. Approximately 10 percent of people have reduced TPMT activity and 0.3 percent (1 in 300) have no detectable levels [56,57].

For individuals with low or absent TPMT activity, thiopurine dose reductions of up to 90 percent may be needed, based upon experience in pediatric acute lymphocytic leukemia (ALL) [58-60]. Prospective testing of TPMT genotype for dose adjustments has also been shown to be effective at reducing toxicity of 6-MP without compromising efficacy [61].

Clinical assessment of neutrophil counts following thiopurines is complicated by a common variant in another gene, ACKR1, which affects baseline neutrophil counts. Determination of ACKR1 genotype may have a role in evaluating thiopurine toxicity. (See 'Potential benefits of genotyping' below.)

Variants in a second metabolizing enzyme, NUDT15 (nucleoside diphosphate-linked moiety X motif 15, NUDIX 15), have been identified that strongly influence thiopurine tolerance in patients with ALL or inflammatory bowel disease [62,63]. The first identified single nucleotide polymorphism (SNP) linked to thiopurine toxicity was a cytosine for thymidine change that resulted in a substitution of cysteine for arginine at amino acid position 139 (R139C) [64]. Individuals with this variant are extremely sensitive to 6-MP and tolerated only 8 percent of the standard dose. Since then, several variant alleles have been identified with varying prevalences among different populations and varying degrees of functional effects [65,66]. The NUDT15 poor metabolizer phenotype is observed at a frequency of approximately one in 50 people with ancestry from countries in East Asia, which is more common than the TPMT poor metabolizer phenotype in people with ancestry from European countries [66].

Specific dosing recommendations for thiopurines according to TPMT and NUDT15 genotype were updated by the Clinical Pharmacogenetics Implementation Consortium in 2018 [67].

However, genotyping for TPMT and NUDT15 polymorphisms has not been universally adopted, and the optimal clinical circumstances in which to perform routine testing are not well defined. The available data on cost-effectiveness are conflicting [68-70]. Furthermore, a systematic review of the use of TPMT genotyping concluded that compared with intermediate or normal activity, low TPMT enzymatic activity was significantly associated with myelotoxicity and leucopenia, but for patients with chronic inflammatory disease, there was imprecision in estimates of genotyping sensitivity and insufficient evidence of outcomes effectiveness [71].

The US Food and Drug Administration (FDA) maintains an updated Table of Pharmacogenetic Associations online [72]. While no specific pharmacogenomic recommendations are made (aside from companion diagnostics), included in the updates is a specific table for "Pharmacogenetic associations for which the data support therapeutic management recommendations"; this table includes suggestive language for pharmacogenetic guidance related to treatment with any thiopurine (azathioprine, mercaptopurine, thioguanine).

In the case of azathioprine, they recommend that clinicians consider alternative therapy in poor metabolizers. Dose reduction is recommended in intermediate metabolizers with pathogenic variants in NUDT15 or TPMT, and intermediate metabolizers for both genes may require more substantial dose reductions.

For 6-MP and thioguanine, they recommend consideration of decreasing doses for poor metabolizers and consideration of decreases in intermediate metabolizers.

Expert opinions continue to differ regarding the role of TPMT and NUDT15 genotyping prior to the administration of thiopurines for treatment of cancer and immune or inflammatory disorders. Some experts advocate routine testing, while others, citing the low frequency of homozygous TPMT variants among some individuals (only approximately 1 in 300 in people with European ancestry) and the fact that the majority of patients who develop myelosuppression while taking azathioprine do not have detectable TPMT gene mutations, disagree with this approach. Some clinicians, in particular those treating acute leukemia with 6-MP, only perform TPMT and NUDT15 genotyping if there is unexpectedly severe or prolonged myelosuppression. In the absence of a family history of poor metabolism or a known variant found incidentally on genetic testing, we advocate this approach, acknowledging that this is an evolving area.

Details of dosing in specific disorders are presented separately. (See "Pharmacology and side effects of azathioprine when used in rheumatic diseases", section on 'Pharmacogenetics and azathioprine toxicity' and "Chronic immunotherapy for myasthenia gravis", section on 'Administration of specific drugs' and "Post-remission therapy for Philadelphia chromosome negative acute lymphoblastic leukemia in adults" and "Thiopurines: Pretreatment testing and approach to therapeutic drug monitoring for adults with inflammatory bowel disease".)

Drug transport — Inherited variations in drug transport proteins make up the second major area of pharmacogenetic investigation in the area of pharmacokinetics. The potential clinical relevance of inherited differences in membrane drug transport proteins can be illustrated by the following examples.

Efficacy of non-nucleoside reverse transcriptase inhibitors – Members of the adenosine triphosphate (ATP)-binding cassette (ABC) family of membrane transporters are among the most extensively studied in terms of drug disposition and modulating drug action at the cellular level [4]. One member, the P-glycoprotein, is encoded by the human ABCB1 gene (also called the multidrug resistant 1 or MDR1 gene, MIM *171050). P-glycoprotein enhances the energy-dependent cellular efflux of many substrates, such as bilirubin, and several medications, including many antiretroviral agents [4]. Several studies have examined whether certain SNPs within the ABCB1 gene may predict either plasma concentrations of drug, virologic efficacy, or drug toxicity in subsets of HIV-infected patients [73-76]. While each of these studies has demonstrated differences related to one particular variant (MDR1 3435C to T), the mechanistic basis for these associations remains to be clarified.

Some data also suggest that genotypic differences in drug transport across membranes may influence the ability to achieve high cerebrospinal fluid (CSF) drug levels, although the clinical significance of this finding (ie, whether rates of HIV-related dementia are lower in patients with these genetic variants) is unclear [73]. (See "Overview of antiretroviral agents used to treat HIV", section on 'Non-nucleoside reverse transcriptase inhibitors (NNRTIs)'.)

Sunitinib-related toxicity – In a study of 219 patients treated with sunitinib, a multitargeted tyrosine kinase inhibitor used for the treatment of advanced renal cell cancer, the prevalence and severity of several side effects, including mucosal inflammation and hand-foot syndrome, were significantly higher in patients who had inherited specific haplotypes of the ABCB1 and ABCB2 efflux transporter genes [77].

Solute carrier organic anion transporter family (SLCOB1) polymorphisms and high-dose methotrexate – Plasma concentrations are quite variable following administration of high-dose methotrexate for treatment of leukemia, lymphoma, and osteosarcoma. A variety of inherited genetic polymorphisms affect methotrexate pharmacokinetics, toxicity, and efficacy [78]. As an example, the SLCO1B1 (solute carrier organic anion transporter family, member 1B1, MIM *604843) gene encodes organic anion transporting polypeptide 1B1 (OATP1B1). This peptide is localized at the membrane of hepatocytes and mediates uptake of substrates from sinusoidal blood, resulting in their net excretion from the blood, likely via biliary excretion. Inherited polymorphisms in the SLCO1B1 gene and OATP1B1 levels appear to be important determinants of plasma methotrexate levels and toxicity following administration of high-dose methotrexate [78-81]. (See "Therapeutic use and toxicity of high-dose methotrexate".)

Variants in SLCO2B1 have also been associated with simvastatin-induced myopathy [82]. SLCO2B1 variants have also affected in montelukast levels and asthmatic response to montelukast [83]. These associations are discussed in detail separately. (See "Statin muscle-related adverse events", section on 'Patient characteristics' and "Antileukotriene agents in the management of asthma", section on 'Future directions'.)

Altered pharmacodynamics — Pharmacodynamics is the study of the biochemical and physiologic consequences of drug administration (ie, the effect of a drug at its therapeutic target and at other nontarget sites) [32]. Genetic variation may lead to interindividual differences in therapeutic response despite the presence of appropriate concentrations of the drug at its intended target. These variations can modulate drug response by affecting the drug target itself or one of the downstream components in the target's mechanistic pathway.

While studies of pharmacogenetic predictors of efficacy at therapeutic target sites may eventually become the primary basis for "individualized therapy," there are relatively few clinical examples of replicable pharmacogenomic associations related to pharmacodynamics, compared with pharmacokinetics [84]. There are at least three reasons for the prominence of pharmacokinetic over pharmacodynamic pharmacogenetic studies:

The biology of drug metabolism and drug transport is relatively straightforward, and each compound typically has one principal enzyme responsible for its metabolism. In contrast, the physiology of most drug target pathways is fairly complex, providing multiple venues that may require investigation prior to the discovery of an interaction between the drug and genetic differences within the target pathway.

Variability in drug metabolism related to genetic factors (eg, the difference in drug levels seen in ultra-rapid versus slow metabolizers because of CYP variants) can be as high as a 10,000-fold difference, whereas differences in target binding related to genetics are generally less than 20-fold [85,86]. The resultant ability (power) to detect differences in drug metabolism is clearly far greater than the ability to detect variance in drug targets.

The pattern of inheritance permits easier identification of pharmacokinetic variants. Typically, the inheritance pattern underlying the pharmacogenetic effects related to differences in drug metabolism or transport is Mendelian (eg, X-linked inheritance underlying G6PD deficiency). (See "Inheritance patterns of monogenic disorders (Mendelian and non-Mendelian)".)

In contrast, the inheritance patterns of pharmacodynamic pharmacogenetic relationships usually demonstrate relationships consistent with the complex traits underlying the purpose of the drug. Thus, these target responses tend to be determined by polygenic or gene-environment interactions, both of which are much more difficult to identify.

Warfarin and VKORC1 polymorphisms — An example of a genetic variant that influences pharmacodynamics is the effect of polymorphisms in the gene encoding vitamin K epoxide reductase complex (VKORC1) on response to the anticoagulant warfarin, a drug with a narrow therapeutic index and a wide variability in individual dosing. VKORC1 variants account for approximately 25 percent of the phenotypic variability in warfarin dosing [87]. (See 'Lack of cost-effectiveness analyses' below.)

Genetic testing for detecting variants of the VKORC1 genes is available to help clinicians assess whether a patient may be especially sensitive to warfarin and require a lower starting dose; they also test for genetic variants in CYP2C9 that influence warfarin metabolism. However, routine genotyping of patients prior to starting warfarin is not widely accepted (or recommended in guidelines from the American College of Chest Physicians [88]). This position is supported by the results of three randomized trials, which found that pharmacogenetic-based as compared with clinically guided dosing had either no or at best marginal usefulness in improving clinical outcomes (time within a therapeutic range of the international normalized ratio [INR] or excess bleeding). (See "Warfarin and other VKAs: Dosing and adverse effects", section on 'Initial dosing' and "Warfarin and other VKAs: Dosing and adverse effects", section on 'Warfarin administration' and "Vitamin K-dependent clotting factors: Gamma carboxylation and functions of Gla".)

VKORC1 is responsible for the conversion of vitamin K-epoxide to vitamin K, which is the rate-limiting step in the physiological process of vitamin K recycling and the primary therapeutic target for warfarin. Common polymorphisms within the VKORC1 gene appear to modulate the mean daily dose of warfarin required to achieve the targeted intensity of anticoagulation. In a study on the effect of VKORC1 polymorphisms in 297 patients undergoing warfarin anticoagulation, a low-dose haplotype group (group A) and a high-dose haplotype group (non-A or group B) were identified, with the following mean warfarin maintenance doses [87]:

Group A/A – 2.7 ± 0.2 mg/day

Group A/B – 4.9 ± 0.2 mg/day

Group B/B – 6.2 ± 0.3 mg/day

Genotyping for polymorphisms in VKORC1 (and in CYP2C9, which is the primary enzyme involved in the metabolism of warfarin) has also been proposed as a means of determining whether to choose an alternative anticoagulant rather than warfarin in patients who might be especially sensitive to warfarin effect based on genotype [89]. However, this approach is unlikely to be practical due to the delay in receiving results and the relatively greater importance of other factors in the choice of anticoagulant (eg, overall efficacy, safety, cost). (See "Atrial fibrillation in adults: Use of oral anticoagulants", section on 'Choice of anticoagulant'.)

Effect on idiosyncratic reactions — An idiosyncratic reaction is an adverse drug reaction (ADR) that cannot be anticipated based upon the known drug target. Examples in which an idiosyncratic reaction to a drug varies according to genetic factors include abacavir hypersensitivity and HLA-B*5701, severe cutaneous adverse reactions to allopurinol and HLA-B*5801, TCL1A variants and musculoskeletal side effects from aromatase inhibitors, and HLA-A*3101 or B*1502 and carbamazepine hypersensitivity.

Several trials have demonstrated the improved safety of drug administration with prior immunogenetic screening for HLA-B*5701, and guidelines from expert groups (including the Clinical Pharmacogenetics Implementation Consortium [CPIC] [90]) endorse the use of abacavir only in patients who have tested negative for HLA-B*5701. (See "Abacavir hypersensitivity reaction" and 'Online resources for clinicians' below.)

AbacavirAbacavir is a nucleoside analog with potent activity against HIV; however, a proportion of patients develop severe hypersensitivity reactions to this drug. Abacavir hypersensitivity is associated with carriage of the major histocompatibility complex (MHC) class I allele HLA-B*5701. It is theorized that abacavir is metabolized to an aldehyde-reactive metabolite, which undergoes classical MHC class I processing. Presentation of the peptide-HLA complex on an antigen-presenting cell to the receptor of an abacavir-specific CD8+ T-cell activates the release of inflammatory cytokines, resulting in the clinical syndrome of acute hypersensitivity syndrome.

Allopurinol – There is a strong association between inheritance of the HLA-B*5801 allele and severe cutaneous adverse events in patients treated with allopurinol, particularly in individuals with ancestry from certain countries in Asia, including Han Chinese and Thai patients, and in patients with kidney disease who are of Korean descent. Similar concerns apply to patients with a family history of severe cutaneous adverse reactions to allopurinol. Screening is advised by several expert groups in high-risk patients [91]. This subject and the role of HLA-B*5801 testing prior to allopurinol administration are discussed in detail elsewhere. (See "Pharmacologic urate-lowering therapy and treatment of tophi in patients with gout", section on 'Allopurinol' and "Tumor lysis syndrome: Prevention and treatment", section on 'Prevention'.)

Aromatase inhibitors – Inherited variants in the T-cell leukemia 1A (TCL1A) gene have been associated with the risk of musculoskeletal side effects in women receiving an aromatase inhibitor (AI) for treatment of breast cancer [92]. However, the magnitude of the excess risk is small, and only a small fraction (approximately 11 percent) of the clinically significant musculoskeletal adverse events from AIs may be attributable to this particular genetic variant [93]. Therefore, testing is not recommended. (See "Adjuvant endocrine and targeted therapy for postmenopausal women with hormone receptor-positive breast cancer".)

CarbamazepineCarbamazepine, an anticonvulsant and mood stabilizing drug, can cause Stevens-Johnson syndrome and the related toxic epidermal necrolysis, idiosyncratic reactions that may be reduced in frequency by avoiding the drug in patients carrying one of two HLA alleles, B*1502 (in people with ancestry from Asian countries) and A*3101 (in people with ancestry from European countries). Based on these observations, testing of people with Asian ancestry for the B*1502 allele before using the related drug oxcarbazepine has also been suggested by US FDA [72]. (See "Antiseizure medications: Mechanism of action, pharmacology, and adverse effects", section on 'Carbamazepine' and "Antiseizure medications: Mechanism of action, pharmacology, and adverse effects", section on 'Oxcarbazepine'.)

Disease pathogenesis — The final category of drug response that may be influenced by genetics is that certain genetic variations can influence disease pathogenesis, the underlying severity of a disease, and response to specific therapies. As examples:

Cystic fibrosis (CF) is a multisystem disorder that is caused by pathogenic variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene, which regulates chloride and water transport in the lungs, digestive tract, and elsewhere. CFTR modulator drugs target the abnormal CFTR protein, with the choice among these drugs guided by CFTR genotype, as discussed separately. (See "Cystic fibrosis: Treatment with CFTR modulators".)

Certain hereditary cancer syndromes are caused by pathogenic variants in genes affecting stability of the genome, and in some cases the type of germline variant can affect the risk reduction strategies used or the choice of therapy [94]. (See "Management of ovarian cancer associated with BRCA and other genetic mutations" and "Tissue-agnostic cancer therapy: DNA mismatch repair deficiency, tumor mutational burden, and response to immune checkpoint blockade in solid tumors".)

USE OF GENOMIC BIOMARKERS TO GUIDE THERAPY

Potential benefits of genotyping

Improve time to effective treatment – (See "Personalized medicine".)

Reduce racial bias and undertreatment – Genotyping for variants that affect drug metabolism can provide more accurate and less biased information than using surrogates such as race. Use of genotyping has the potential to improve outcomes, although data are lacking.

As an example, some individuals who have a biallelic variant in the ACKR1 gene (which encodes the atypical chemokine receptor 1, also known as the Duffy blood group antigen), have lower baseline neutrophil counts, a finding referred to as Duffy-null associated neutrophil count (DANC). This finding was formerly called constitutional neutropenia or benign ethnic neutropenia (BEN). DANC is especially common in individuals with African ancestry and certain ethnic backgrounds; it is thought to have evolved as a protection against malaria and has no deleterious effect on neutrophil function or infection risk.

If potentially myelosuppressive therapy is being administered, these individuals may be at risk for undertreatment because of their low baseline neutrophil count, which may lead to treatment discontinuation, a decision that is typically based on the post-treatment absolute neutrophil count (table 2) and does not take into account the individual's baseline. In a retrospective study involving 1466 individuals receiving azathioprine, rates of discontinuation for potential hematologic toxicity were almost threefold higher in individuals with the DANC genotype than those without (3.92 versus 1.34 per 100 person years) [95]. The higher likelihood of discontinuation in individuals with DANC remained after several adjusted analyses and fully accounted for higher discontinuation rates in Black individuals. Discontinuation in some of these cases may have occurred due to misattribution of reduced thiopurine metabolism. (See 'Thiopurines and polymorphisms in TPMT and NUDT15' above.)

The authors of the study and an accompanying editorial noted that testing for the DANC genotype (or for absence of the Duffy antigen on red blood cells, which may be faster) in individuals with low baseline or on-treatment neutrophil counts could reduce the likelihood of unnecessary drug discontinuation or dose reduction during therapy [95,96]. Both discussions emphasized that Duffy antigen status rather than race is the more appropriate indicator of lower baseline neutrophil counts. The editorialists emphasized that benign variants tend to be less well characterized in Black individuals, and they provided other examples in which using race as a surrogate for genotype could be problematic.

Further information on the Duffy antigen and mechanisms of neutropenia are presented separately. (See "Approach to the adult with unexplained neutropenia", section on 'Causes of neutropenia' and "Red blood cell antigens and antibodies", section on 'Duffy blood group system' and "Protection against malaria by variants in red blood cell (RBC) genes", section on 'Duffy blood group system'.)

Reduced medication-related adverse effects – Pharmacogenomic testing may allow individuals with altered metabolism to avoid drug-related adverse effects, such as described in the PREPARE trial below. (See 'Pharmacogenomics gene panels' below.)

Reduce cost – Some pharmacogenomic testing may reduce the costs of care. As an example, a modeling study suggested that implementation of a pharmacogenomic testing approach for individuals with major depressive disorder could save nearly $5000 USD per patient and improve quality of life years by avoiding or slowing progression to refractory depression [97]. An earlier meta-analysis of four randomized trials and two observational studies also suggested a better response with pharmacogenomic-guided treatment [98]. Real-world validation would be helpful.

Cost analyses for other uses of pharmacogenomic testing are needed, as some testing may not be cost-effective. (See 'Lack of cost-effectiveness analyses' below.)

Pharmacogenomics gene panels — There has been interest in using gene panels to guide drug dosing in various patient populations. Gene panels assay for variants in a group of genes and can be done in advance of drug prescribing, rather than testing for a specific gene prior to drug administration. (See "Next-generation DNA sequencing (NGS): Principles and clinical applications", section on 'Whole genome, exome, or gene panel'.)

In the 2023 PREPARE (preemptive pharmacogenomic testing for preventing adverse drug reactions) trial, which randomly assigned nearly 7000 adults to be tested or not tested with a pharmacogenetic genotyping panel, clinically significant adverse drug reactions were fewer in the genotyping group (22 versus 29 percent; odds ratio [OR] 0.70, 95% CI 0.61-0.79) [99]. The benefit of genotyping was similar when the analysis was restricted to individuals with an actionable genetic test result for the index drug. The panel consisted of 50 variants in 12 genes that regulate drug metabolism, selected from recommendations of the Dutch Pharmacogenetics Working Group (DPWG) consortium [100-102].

Additional findings from the PREPARE trial included:

Gene variants – At least one actionable variant was identified in 94 percent of participants; many participants had two or three actionable variants identified. Overall, 25 percent of participants had an actionable variant for the index drug they were prescribed.

Drugs – The greatest number and severity of reactions was in a population of cancer patients receiving high dose chemotherapy. Overall, the most common index drug was atorvastatin, followed by clopidogrel and tacrolimus.

There was an approximately 70 percent adoption rate of DPWG recommendations based on the findings from pharmacogenetic testing.

Concerns were raised about lack of blinding, use of patient-reported outcomes, and a large number of patients lost to follow-up that was greater in the testing group (11 percent) than the usual care group (7.9 percent) [103-105]. However, this study demonstrates that actionable pharmacogenetic variants are common and that their early identification can decrease adverse drug reactions.

Online resources for clinicians — The details of all known specific drug-gene interactions are beyond the scope of this overview. Updated information regarding most of the known associations can be obtained through the following resources:

PharmGKB – The National Institute of General Medical Sciences of the National Institutes of Health (NIH) hosts the Pharmacogenomics Knowledge Base (www.pharmgkb.org) [47]. PharmGKB is an online database that consolidates and organizes pharmacogenetic data for more than 650 drugs [106]. It contains over 20,000 pharmacogenetic variants, over 3000 clinical pharmacogenetic annotations, and 100 dosing guidelines that can be queried by drug, gene target, or pharmacologic pathway. There is also information on clinical guidelines; drug-related genotype-phenotype relationships; and a catalog of pharmacogenetic drug labels from the US Food and Drug Administration (FDA), European Medicines Agency (EMA), and Japan's Pharmaceuticals and Medical Devices Agency.

A full list of recommendations from professional societies is available on the PharmGKB website (www.pharmgkb.org/guidelines).

CPIC – The Clinical Pharmacogenetics Implementation Consortium (CPIC) was developed through partnership between PharmGKB and the Pharmacogenomics Research Network (PGRN). The website (www.cpicpgx.org) posts peer-reviewed, evidence-based practice guidelines for specific clinical indications. These recommendations are developed and updated by consortium members and follow a standardized format using formal evidence grading systems [43,67,82,107-119]. The guidelines are meant to provide rationales and explanations to facilitate appropriate clinical decision-making (ie, they are intended to be instructive on how pharmacogenomic testing can be integrated into clinical practice, rather than proscriptive regarding whether this testing should or should not be used to make treatment decisions in individual patients). As an example, the first branch of the CPIC decision-making algorithm to guide warfarin dosing depends on the availability of VKORC1 and CYP2C9 genotypes [120]. If available, the algorithm provides instruction for genotype-based dosing; if genotypes are not available, the algorithm promotes clinical dosing and does not recommend routine pharmacogenetic testing. Recommendations on whether testing is justified in clinical practice emanate predominantly from subspecialty-based expert clinical groups.

FDA – A webpage listing genomic biomarkers that have established roles in determining drug response is available through the US Food and Drug Administration (FDA) [72]. The website was updated in 2020 to include associations that the FDA has evaluated for sufficient scientific evidence of the reported effect. These are additionally subdivided into three tables:

Pharmacogenetic associations for which the data support therapeutic management recommendations

Pharmacogenetic associations for which the data indicate a potential impact on safety or response

Pharmacogenetic associations for which the data demonstrate a potential impact on pharmacokinetic properties only

While the FDA does not provide specific recommendations for use of pharmacogenetic tests (aside from companion diagnostics), the first table may be of most interest to the clinician interested in applied pharmacogenomics.

Pharmacogenomic information is included in a small number of labels for drugs approved by the FDA. Although most of the FDA labeling recommendations have involved variants that influence drug pharmacokinetics, there are a few examples within each of the pharmacogenetic categories described above of medications for which the FDA recommends testing prior to administration [72]. (See 'Altered pharmacodynamics' above.)

Although the FDA has officially approved a few tests, the major contribution of the agency in the field of pharmacogenetics has been in the updating of drug labels to contain information on pharmacogenomic issues that are applicable to a given pharmacologic agent.

Other professional societies – Additional guidelines have been developed by other professional societies such as the Royal Dutch Association for the Advancement of Pharmacy – Pharmacogenetics Working Group (DPWG), the Canadian Pharmacogenomics Network for Drug Safety (CPNDS), and others. These guidelines are designed to provide peer-reviewed, updated, evidence-based, freely accessible guidelines for gene/drug pairs focused on how to adjust medications on the basis of the genetic test results [109]. This information is available on PharmGKB.

Detailed information about dosing of specific medications is provided in topic reviews on specific diseases.

Concerns with direct-to-consumer testing — Certain companies are marketing FDA-authorized direct-to-consumer (DTC) testing for genetic variants that may be associated with medication metabolism. We agree with the FDA that this DTC testing should not be used to guide decisions about whether a medication is appropriate for a patient or about how to administer a medication [121].

This subject is discussed in more detail separately. (See "Personalized medicine", section on 'Direct-to-consumer testing'.)

CHALLENGES TO WIDESPREAD USE OF GENOTYPING — Despite the labeling changes implemented by the US Food and Drug Administration (FDA) and the increasing number of pharmacogenetic studies in the published literature, integration of pharmacogenetic testing into clinical care has been slow, and many of the tests recommended by the FDA for individual drugs are not in routine use. Among the reasons for lack of implementation are:

Limitations in the design of published pharmacogenetic studies (in particular, the lack of prospective randomized trials demonstrating improved clinical outcomes when drug therapy or specific dose is selected on the basis of genotype)

Regulatory and ethical concerns

Lack of cost effectiveness analyses

Limitations in the number of available pharmacogenetic tests and lack of guidelines for test implementation

A lack of education on the benefits of pharmacogenetic testing, both for patients and providers

Potential for delay in therapy while awaiting results of genotyping

Study design limitations — Several problems in study design have limited the translation of pharmacogenetics into the clinical sphere.

The initially reported genetic and pharmacogenetic associations often have not been reproducible (ie, many of the initial reports represented "false-positive" findings) [122,123]. In many cases, the original pharmacogenetic studies were "spin-offs" from clinical trials and, thus, were underpowered for genetic association studies given the small sample sizes allocated to a given treatment arm. Replication of results from genome-wide association studies requires identification of a large and appropriate sample, and this can be both difficult and expensive [8].

Another contributor to the failure to replicate initial findings is heterogeneity among studies, which can be phenotypic (ie, the selective use of different endpoints, times of assessment, types of interventions, and genetic groups across studies) or genotypic (ie, evaluation of disparate markers within the same gene or varying genetic allele frequencies due to ethnicity, which may be overt or subtle) [124].

In addition to the study design problems of small sample size and phenotypic/genotypic heterogeneity, the identified variants themselves may not be amenable to clinical application. Most pharmacogenetic variants identified to date are either rare traits with relatively strong phenotypic effects, or common traits that have relatively weak phenotypic effects [125].

Regulatory and ethical concerns — From an ethics perspective, a longstanding concern has been whether the identification of pharmacogenetic variants (in particular those associated with a poor treatment response or prognosis) in an individual could result in stigmatization (eg, denial of insurance) [126].

A major step in the protection of individuals' rights came with the passage of H.R. 493, the Genetic Information Nondiscrimination Act of 2008 [127]. This law protects Americans against discrimination based on their genetic information in matters related to health insurance and employment and should translate into increased acceptance of pharmacogenetic testing by the public in the future.

Lack of cost-effectiveness analyses — Circumstances that favor cost effectiveness of a pharmacogenetic test include a high prevalence of the genetic variant of interest in the target population, a good correlation between phenotype and genotype, satisfactory diagnostic test criteria, a disease that is associated with significant morbidity or mortality if left untreated, and a significant reduction in adverse drug reactions resulting from testing [128].

Despite the multitude of pharmacogenetic association studies in the literature, relatively few cost-effective analyses have been performed. These studies are crucial to determine reimbursement for routine pharmacogenetic testing, but their performance is problematic for two reasons [128]:

Historically, there have been limited data addressing how often pharmacogenetic testing actually prevents clinically significant adverse drug reactions [86,129-134]. However, studies evaluating HLA contributions to adverse drug reactions suggest that in several drug-specific instances (abacavir, carbamazepine, clozapine) local, country-specific application of pharmacogenetic testing may be cost effective [135-137].

The price of pharmacogenetic tests is likely to drop continuously over the next few years.

The first issue can be illustrated by pharmacogenetic testing for CYP2C9 and VKORC1 variants in patients being started on the anticoagulant warfarin (see 'Warfarin and VKORC1 polymorphisms' above). VKORC1 variants account for approximately 25 percent of the phenotypic variability in warfarin dosing, with CYP2C9 variants adding an additional 6 to 10 percent [87]. The available data suggest that combining knowledge of genetic variants with clinical characteristics can explain between 55 and 71 percent of the variability in warfarin dosing [132,133].

A 2006 working paper from the American Enterprise Institute-Brookings Joint Center for Regulatory Studies (and partially published in 2008) estimated that formally integrating genetic testing into routine warfarin therapy could allow American warfarin users to avoid 85,000 serious bleeding events and 17,000 strokes annually, resulting in estimated savings of USD $1.1 billion annually, with a range of approximately USD $100 million to USD $2 billion [129,130]. However, routine genotyping is not widely accepted (or recommended in guidelines from the American College of Chest Physicians [88]), especially after randomized trials that compared genotype-guided initial dosing with standard initial dosing found no differences in rates of bleeding or thromboembolism. (See "Warfarin and other VKAs: Dosing and adverse effects", section on 'Baseline testing'.)

Furthermore, a cost-effectiveness study of using pharmacogenomic information for warfarin dosing concluded that routine genotyping before warfarin dosing was unlikely to be cost-effective for typical patients with nonvalvular atrial fibrillation (ie, with the estimated cost-effectiveness of testing exceeding USD $170,000 per quality-adjusted life-year gained) (QALY) [134]. The authors concluded that on the basis of available data and cost of testing (approximately USD $400 in 2007), there was only a 10 percent chance that genotype-guided dosing is likely to be cost-effective (ie, <USD $50,000 per QALY).

Lack of tests and guidelines for test implementation — Compared with other clinical tests, relatively few pharmacogenetic tests are available for use in clinical practice, and even when tests are available, there has been slow adoption of these tests to inform clinical decision making [8]. Limitations cited in the development and implementation of new tests include:

The difficulty of identifying and incorporating multiple (interacting) variants in the same test

The translation of a test developed based upon average population responses to the case of a specific individual

The need to develop tests that can be interpreted within a clinical context

The need for a test associated with biologically meaningful differences

The need for tests to undergo formal regulatory approval (eg, Clinical Laboratory Improvement Amendment [CLIA] in the United States) [138]

The lack of clear, peer-reviewed evidence-based guidelines that translate laboratory test results into actionable prescribing decisions for specific drugs

Nonetheless, as the use of clinical exome sequencing and whole genome sequencing increases, approaches to rapidly identify relevant pharmacogenomic variants have been developed [139-141]. This may provide a more direct "existing data" approach to clinical drug-genotype pharmacogenomics.

Need to educate patients and providers — Pharmacogenomics and the promise of personalized medicine is frequently mentioned in the popular lay press. It is therefore incumbent upon both the developers of a given pharmacogenetic test as well as the health care professionals responsible for ordering the test to be cognizant of the test characteristics and interpretation, and to be able to effectively disseminate that information to patients. As noted above, a crucial part of testing efforts should be directed toward providing reassurance regarding the safety and privacy of testing. (See "Personalized medicine" and 'Regulatory and ethical concerns' above.)

SUMMARY

Mechanisms – Genetic variation (polymorphisms) for many drug metabolizing enzymes and drug targets (eg, receptors) have been identified and probably contribute to interpatient variability in drug response. There are four general mechanisms by which genetic factors can influence the response to pharmacologic agents (see 'Ways in which genetic factors influence drug response' above):

Effect on drug pharmacokinetics, which may include the drug's absorption, distribution, metabolism, and/or elimination

Effects on pharmacodynamics (the therapeutic response of a target, often a receptor, to the drug)

Effect on idiosyncratic reactions (eg, increased frequency of allergic reactions in individuals with certain genotypes)

Effect on disease pathogenesis, which in turn may make the disease more or less responsive to a specific therapy

Clinical use – Pharmacogenetic testing is available in conjunction with certain drug classes and may enable physicians to understand why patients experience different efficacy and toxicity from various drugs and to help them make better decisions about therapy. However, the goal of "individualized therapy" based upon pharmacogenetic testing has yet to be realized. (See "Personalized medicine".)

Use of these tests is not widespread, despite the promise of a growing body of research relating to pharmacogenetics and its impact on drug response, along with guidelines from the US Food and Drug Administration (FDA) on the use of genetic markers to guide therapy for a variety of agents, maintained in a Table of Pharmacogenetic Associations online. (See 'Altered pharmacokinetics' above and 'Altered pharmacodynamics' above.)

Notable exceptions include:

Some molecularly targeted agents used for treatment of specific cancers are restricted to those tumors that display certain genetic features (eg, use of the anti-HER2 monoclonal antibody trastuzumab is restricted to breast cancers that overexpress HER2). (See 'Ways in which genetic factors influence drug response' above and "HER2 and predicting response to therapy in breast cancer".)

Some molecularly targeted agents for cystic fibrosis are restricted to patients who harbor specific mutations in the cystic fibrosis transmembrane regulator (CFTR) gene (eg, ivacaftor for patients with the G551D mutation). (See 'Disease pathogenesis' above.)

Guidelines from expert groups endorse the use of the anti-HIV drug abacavir only in patients who have tested negative for HLA-B*5701. (See 'Effect on idiosyncratic reactions' above.)

Before starting treatment with azathioprine or 6-mercaptopurine, many (but not all) clinicians advocate screening patients for mutations in the thiopurine methyltransferase (TPMT) gene that cause TPMT deficiency. (See 'Thiopurines and polymorphisms in TPMT and NUDT15' above and "Thiopurines: Pretreatment testing and approach to therapeutic drug monitoring for adults with inflammatory bowel disease".)

Resources – Online resources for clinicians including the FDA website and the PharmGKB database and website are listed above. Concerns with direct-to-consumer marketing of pharmacogenomic testing are discussed separately. (See 'Online resources for clinicians' above and "Personalized medicine", section on 'Direct-to-consumer testing'.)

Barriers to use – Numerous barriers exist to the direct application of pharmacogenomics advances in knowledge to drug therapy in the context of clinical care, which will need to be overcome before personalized drug therapy becomes a routine component of mainstream medicine. (See 'Challenges to widespread use of genotyping' above.)

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Topic 2904 Version 76.0

References

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