Scholarly article on topic 'Pharmacogenomics for personalized pain medicine'

Pharmacogenomics for personalized pain medicine Academic research paper on "Clinical medicine"

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Acta Anaesthesiologica Taiwanica
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{"adverse drug reactions" / "genome wide association studies" / "personalized medicine" / pharmacogenomics}

Abstract of research paper on Clinical medicine, author of scientific article — Tai-Ming Ko, Chih-Shung Wong, Jer-Yuarn Wu, Yuan-Tsong Chen

Abstract Pharmacogenomics aims to unravel the way that human genetic variation affects drug efficacy and toxicity. Genome-wide association studies and candidate gene findings suggest that genetic approaches may help choose the most appropriate drug and dosage while preventing adverse drug reactions (ADRs). Pain is an unpleasant feeling that usually results from tissue damage. The management of different types of pain (acute, chronic, inflammatory, neuropathic, or cancer) is challenging. Currently, drug intervention is the first-line therapy for resolving pain. However, differences in drug efficacy between individuals are common with pain medications. Moreover, some patients experience ADRs after being treated with specific pain drugs. This review discusses the use of drugs for pain management in the context of the recent pharmacogenomic studies on ADRs and drug efficacy.

Academic research paper on topic "Pharmacogenomics for personalized pain medicine"

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Review Article

Pharmacogenomics for personalized pain medicine

Tai-Ming Ko 12, Chih-Shung Wong 3, Jer-Yuarn Wu 14, Yuan-Tsong Chen 15 *

Pharmacogenomics aims to unravel the way that human genetic variation affects drug efficacy and toxicity. Genome-wide association studies and candidate gene findings suggest that genetic approaches may help choose the most appropriate drug and dosage while preventing adverse drug reactions (ADRs). Pain is an unpleasant feeling that usually results from tissue damage. The management of different types of pain (acute, chronic, inflammatory, neuropathic, or cancer) is challenging. Currently, drug intervention is the first-line therapy for resolving pain. However, differences in drug efficacy between individuals are common with pain medications. Moreover, some patients experience ADRs after being treated with specific pain drugs. This review discusses the use of drugs for pain management in the context of the recent pharmacogenomic studies on ADRs and drug efficacy.

Copyright © 2016, Taiwan Society of Anesthesiologists. Published by Elsevier Taiwan LLC. All rights


1 Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan

2 Graduate Institute of Integrated Medicine, China Medical University, Taichung, Taiwan

3 Department of Anesthesiology, Cathay General Hospital, Taipei, Taiwan

4 School of Chinese Medicine, China Medical University, Taichung, Taiwan

5 Department of Pediatrics, Duke University Medical Center, Durham, NC, USA


Article history: Received 11 November 2015 Received in revised form 28 January 2016 Accepted 1 February 2016


adverse drug reactions; genome wide association studies; personalized medicine; pharmacogenomics

1. Introduction

A medication with proven efficacy and safety in a series of rigorous clinical trials could still fail to work in some patients or cause serious adverse drug reactions (ADRs).1,2 The interindividual responses to drugs are most likely affected by genetic variations, which can be divided into two types: (1) inherited variants (i.e., germ-line genetic variants); and (2) acquired variants (i.e., somatic mutation). Germ-line variants of genes encoding drug-metabolizing enzymes, drug transporters, drug targets, and human-leukocyte antigen (HLA) can affect individual response to medications. Somatic variants of genes are frequently associated with the development or progression of cancer, and affect the drug response of tumors that carry specific mutations, so called target therapy. Because of the impact of genetic variants on medication responses, how to give the "right drug" at the "right dose" for the "right patient" is a major goal in the era of precision medicine.3,4

Conflicts of interest: The authors have nothing to disclose.

* Corresponding author. Institute of Biomedical Sciences, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei 11529, Taiwan. E-mail address: (Y.-T. Chen).

2. Pharmacogenomics

Pharmacogenomics is the application of current technology for the precise determination of genetic variants that influence drug response, and to develop personalized strategies that maximize therapeutic efficacy and assure drug safety. Large-scale genome-wide association studies and smaller-scale studies with a candidate-gene approach, that are used to study genes involved in drug metabolism enzymes, drug transporters, drug receptors, and HLA, have helped advance our understanding of the underlying mechanisms of ADRs and drug efficacy (Figure 1). Next-generation whole-genome sequencing, which provides a diverse genome map of multiple populations, will be useful for the future of pharma-cogenetic studies.5 These studies take into account ancestral genetic structure, complex haplotypes, gene—gene interactions, and rare variants. They aim to detect and replicate novel pharmacoge-netic loci of clinical significance. Based on these studies, the United States Food and Drug Administrations (FDA) have relabeled over 100 approved drugs with genetic information. A list of valid genomic biomarkers for clinical guidance can be found on the FDA website "Table of Pharmacogenomic Biomarkers in Drug Labels" ( Pharmacogenetics/ucm083378.htm). Some of these biomarkers have been implemented in medical practice.6—8

1875-4597/Copyright © 2016, Taiwan Society of Anesthesiologists. Published by Elsevier Taiwan LLC. All rights reserved.

Useful pharmacogenetic test when prescribing pain medication including:

immune-mediated ADR (e.g., HLA-B*15:02) Drug metabolism (e.g., CYP2D6)

Table 2

Use of antidepressants and antiepileptic drugs in Taiwan.


Poor responder

Adverse drug reactions

♦ ft

Figure 1. Pharmacogenetic testing for pain management. Pharmacogenetic tests provide information about a patient's likelihood to have an adverse drug reaction (ADR) and/or a therapeutic response to a medication before prescribing pain medication. For giving the right drugs and right doses for right patients, a precise therapeutic intervention (i.e., adjust drug dosage or avoid use the drug) should be based on the information of the pharmacogenetic tests.

3. Pain medication

Most clinical pain management options involve pharmacological interventions. Pain therapy has evolved over the years into a large specialty field. Ideal pain management approaches must provide adequate analgesia without excessive adverse effects. However, there are large interindividual differences in response to pain medications, concerning efficacy and the development of severe ADRs.9-13 Current pain management strategies are devised using the World Health Organization pain ladder, which begins with nonopioid medications, such as nonsteroidal anti-inflammatory drugs (NSAlDs), progressing to weak opioids, and culminating with strong opioids.9 Other pain medications include anticonvulsant drugs for neuralgia. Additionally, adjuvant therapies using antidepressant medications can aid in reducing chronic pain-associated anxiety.14,15 In Taiwan, based on the National Health lnsurance Research Database, we found the drugs that are most frequently used for pain management (Tables 1 and 2).

The field of pain medications is a valuable one to study germline variants using a pharmacogenomic approach, because of the

Table 1

Use of opioids and nonsteroidal anti-inflammatory drugs (NSAlDs) in Taiwan.

Group Main ingredient Use (tablets/y)

Opioids Tramadol HCL 1,512,775

Opioids Morphine sulfate 401,810

Opioids Meperidine HCL 349,312

Opioids Propoxyphene HCL 308,707

Opioids Fentanyl 74,036

Opioids Nalbuphine hydrochloride 34,888

Opioids Buprenorphine (hydrochloride) 13,145

NSAlDs Diclofenac sodium (diethylammonium) 8,199,279

NSAlDs lbuprofen 3,398,801

NSAlDs Glucosamine sulphate D-(crystalline) 1,850,207

NSAlDs Acemetacin 1,754,514

NSAlDs Celecoxib 1,081,972

NSAlDs Flurbiprofen 657,754

NSAlDs Etodolac 517,955

NSAlDs Etoricoxib 253,513

NSAlDs Fenbufen 103,317

NSAlDs Flufenamic acid 64,139

NSAlDs Benzydamine HCL 35,190

Group Main ingredient Use (tablets/y)

Antidepressants Trazodone hydrochloride 1,351,687

Antidepressants lmipramine HCL 1,021,355

Antidepressants Fluoxetine (HCL) 587,716

Antidepressants Sertraline(as hydrochloride) 432,102

Antidepressants Mirtazapine 331,711

Antidepressants Paroxetine hydrochloride 314,050

Antidepressants Amitriptyline HCL 253,003

Antidepressants Escitalopram oxalate 248,157

Antidepressants Venlafaxine 219,911

Antidepressants Venlafaxine (HCL) 211,960

Antidepressants Duloxetine hydrochloride 190,550

Antidepressants Citalopram hydrobromide 156,348

Antidepressants Doxepin (HCL) 155,567

Antidepressants Bupropion hydrochloride 146,207

Antidepressants Fluvoxamine maleate 114,074

Antidepressants Moclobemide 65,511

Antidepressants Maprotiline HCL 28,018

Antidepressants Clomipramine HCL 9,180

Antidepressants Dothiepin HCL 8,055

Antidepressants Oxitriptan 672

Anticonvulsants Clonazepam 2,807,476

Anticonvulsants Valproate sodium 1,103,829

Anticonvulsants Phenytoin sodium 1,057,080

Anticonvulsants Carbamazepine 913,882

Anticonvulsants Gabapentin 456,504

Anticonvulsants Topiramate 284,457

Anticonvulsants Lamotrigine 276,418

Anticonvulsants Levetiracetam 187,679

Anticonvulsants Phenobarbital 183,202

Anticonvulsants Valproic acid 153,492

Anticonvulsants Vigabatrin 57,493

Anticonvulsants Divalproex (sodium) 44,485

Anticonvulsants Oxcarbazepine 3161

Anticonvulsants Phenobarbital sodium 210

considerable repercussions of these medications on the biological, psychological, sociological, and economical welfare of patients. Genetic studies have identified several polymorphic loci that govern the pharmacodynamics and kinetics of analgesic drugs.16-18 The aim of this review is to highlight recent advances in the pharmacogenomics of pain medicine.

3.1. Drug metabolism enzymes

The metabolism of drugs and other xenobiotics is often divided into multiple phases. Phase I enzymes are responsible for chemical modifications of the drugs. They include cytochrome P450 (CYP), cytochrome b5, and nicotinamide adenine dinucleotide phosphate-cytochrome P450 reductase. Phase II enzymes are involved in further conjugation of the active drug metabolites, some examples are glutathione S-transferases, aryl sulfatase, and uridine-glucuronosyltransferase. The hepatic CYPs are a multigene family of enzymes that play a critical role in the metabolism of many drugs, with each cytochrome isozyme displaying unique substrate specificities and susceptibility to induction and inhibition by exogenous chemicals. One of the most common CYPs involved in drug metabolism is cytochrome P450, family 2, subfamily D, polypeptide 6 (CYP2D6), whose metabolic rate can fluctuate by over 100-fold between the allelic variants expressed in different ethnic groups.19 For example, approximately 10% of the Caucasian population carries an autosomal recessive trait that yields a nonfunctional variant.20 Patients homozygous for this variant, known as poor metabolizers (PM), may have either a higher risk of adverse side effects because of drug overdose (i.e., tricyclic antidepressants or antiarrhythmics) or no drug efficacy due to poor transformation of the prodrug into its active metabolite. Conversely, in ultra-rapid

metabolizers (UM), amplification of the CYP2D6 gene is correlated with enhanced enzyme activity and ultrarapid metabolism, which could decrease the optimal dosage for UM (Figure 1).21~23

3.2. Opioid analgesics-codeine: CYP2D6

Opioids are the pillar of pharmacological pain management.24 They have been used in therapeutics for centuries, and there are > 30 opioids currently marketed worldwide. However, opioid over dosage is highly correlated with respiratory depression, a harmful and life-threatening adverse effect.25 Careful therapeutic drug monitoring of the plasma concentrations can help provide effective pain relief while minimizing adverse effects. Morphine and diamorphine have been shown to have a wider therapeutic range or "safety margin" than some other opioids. Since it is not possible to tell which patients will require low or high doses, commencement dose is always low, unless it is a therapy change from another strong opioid.26 Thus, opioid treatment requires an individualized approach to ensure safety. Ample studies have demonstrated that this individualized treatment might rely on pharmacogenomics. The future promise of pharmacogenetics involves a rational drug regimen that maximizes efficacy and minimizes adverse events. However, variation in responses to pain medication is partially explained or predicted by patient's genetics, and pharmacogenetic testing for opioids is not widely applied in current clinical practice.

Codeine is widely administered after operations and is used in certain drug combinations for acute and chronic pain manage-ment.27,28 Because codeine is a less potent m-opioid receptor agonist than morphine, it has been classified as a weak opioid.29,30 Codeine is a prodrug with a low affinity for the opioid receptor and

low intrinsic activity at the m-opioid receptor. The initial metabolism of codeine is through glucuronidation with O-demethyla-tion,32 resulting in morphine formation. The O-demethylation of codeine to morphine is mediated by CYP2D6.33 UMs (CYP2D6*1/*1 and *1/*2) should avoid codeine due to its potential for toxicity (Table 3). The Clinical Pharmacogenetics Implementation Consortium guidelines have provided information for guiding the dosing of codeine based on CYP2D6 genotypes.34 It is suggested to consider alternative analgesics for UMs such as morphine or a nonopioid. A recommended dose of 15—60 mg every 4 hours is suggested for extensive metabolizers. For the intermediate metabolizer phenotype it is suggested to begin with 15—60 mg every 4 hours and consider alternative analgesics in cases where there is no response. For PM it is suggested to directly consider alternative analgesics such as morphine or a nonopioid due to lack of opioid efficacy. Thus, CYP2D6 is an example of the impact of genetic polymorphisms on pain medicine, including codeine and tramadol analgesia.35 By contrast, the clinical relevance of CYP2D6 polymorphisms on other opioids (i.e., oxycodone, methadone, and dihydrocodeine) are still not clear.36,37

3.3. Opioid analgesics: drug receptors and transporters

In addition to the association between CYP2D6 (metabolism) and opioid response, the major candidate genetic contributors to opioid efficacy and adverse effects are ABCB1 (drug transporter) and OPRM1 (receptor interaction).23,26,38—41 The m-opioid receptor (OPRM1) is the primary binding site of action for many opioid drugs and for binding of beta-endorphins. The m-opioid receptor is a transmembrane protein which belongs to the rhodopsin family of G-protein coupled receptors. The downstream signaling of m-opioid

Table 3

Useful pharmacogenomics tests in predicting adverse drug reactions and dosage for pain medicine.

Drug Type Response or ADR Gene: polymorphism(s) Importance Ethnicity

Codeine Opioid Respiratory depression Metabolism: CYP2D6, CYP2B6 Ultra-rapid metabolizers (CYP2D6*1/*1 and *1/*2) should avoid usage due to potential for toxicity. Caucasian, Han Chinese, Japanese, korean

Morphine Opioid Respiratory depression Drug transporter: ABCB1; receptor interaction: OPRM1 OPRM1 c.118A>G or ABCB1 c.3435C>T genotype might be a reference for postoperative doses during the 24 h after major painful surgeries. Caucasian

Methadone Opioid Cardiac arrhythmia CYP3A4, CYP2B6, and CYP2D6 CYP3A4 and CYP2B6 are the major CYP isoforms involved in methadone metabolism, with CYP2D6 contributing to a minor extent, preferentially in metabolism of the R-enantiomer Caucasian, Han Chinese

Celecoxib NSAIDs Serious adverse cardiovascular events CYP2C9 Consider starting treatment at half the lowest recommended dose in poor metabolizers (CYP2C9*3/*3) to avoid adverse cardiovascular and gastrointestinal events Caucasian

Flurbiprofen NSAIDs Adverse cardiovascular, renal, and gastrointestinal events (including bleeding and ulceration) CYP2C9 Poor metabolizers (CYP2C9*3/*3) should administrated with caution to avoid adverse cardiovascular and gastrointestinal events Caucasian, Korean

Doxepin Cyclic antidepressants Cardiac arrhythmia, myelosuppression CYP2D6 Poor metabolizers (CYP2D6*3/*3) should reduce dose by 60% to avoid arrhythmia and myelosuppression Caucasian

Carbamazepine Antiepilepticdrug SJS, TEN HLA-B*1502 HLA-A*3101 Avoid usage in HLA-B*1502 carriers to prevent SJS/TEN Avoid usage in HLA-B*3101 carriers to prevent SJS/TEN Han Chinese Japanese, Northern European

Phenytoin Antiepilepticdrug SJS, TEN HLA-B*1502 Avoid usage in carriers with risk HLA genotypes to prevent SJS/TEN Thai

Lamotrigine Antiepilepticdrug SJS, TEN HLA-B*1502, HLA-B*3801 Avoid usage in carriers with risk HLA genotypes to prevent SJS/TEN Han Chinese, European

Clozapine Antipsychoticdrug Agranulocytosis HLA-DQB1 (126Q), HLA-B (158T) Avoid usage in carriers with risk HLA genotypes to prevent Agranulocytosis Caucasian

ADR = adverse drug reaction; HLA = human leukocyte antigen; NSAIDs = nonsteroidal anti-inflammatory drugs; SJS = Stevens—Johnson syndrome; TEN = toxic epidermal necrolysis.

receptors is through interactions with heterotrimeric G proteins.42 To date, over 100 genetic polymorphisms have been found in the OPRM1 gene. The most common studied nonsynonymous single nucleotide polymorphism is rs1799971, which is located in exon 1, and is a nucleotide change from adenosine (A) to guanosine (G) (A118G). Depending on the ethnicity, the polymorphism can be found in a proportion from 2% to nearly 50%. The m-opioid receptor polymorphism was also found to be associated with opioid effects43. The functional study of OPRM1 revealed that the G allele (A118G) creates a novel CpG-methylation site. This methylation would suppress the increase of the OPRM1 expression level that takes place after a prolonged opioid administration. Patients with an inactive OPRMI allele might benefit from a k-agonist such as buprenorphine instead of a m-agonist such as morphine.

3.4. Opioid analgesics-methadone: CYP3A4, CYP2B6, and CYP2D6

Methadone is an old opioid drug, having been discovered and developed during World War II.44 It is an opioid with a completely different chemical structure to morphine and oxycodone. Currently, methadone (including R- and S-methadone) are used as second-line opioids for the treatment of patients suffering from cancer pain.45 Methadone is a useful alternative in individuals who have had no responses to other opioids or suffering from adverse side effects (ADRs).46—48 It has demonstrated its efficacy in neuropathic pain conditions,49 with several case reports highlighting this specific indication owing to methadone's N-methyl-D-aspartate-re-ceptor agonistic properties.50,51 Both methadone enantiomers (Rand S-methadone) bind to the noncompetitive site of the N-methyl-D-aspartate receptor. In addition, R-methadone proved to be a stronger m-opioid receptor agonist than S-methadone. However, because the pharmacokinetics of methadone was still unclear, the methadone has a narrow therapeutic index.52 Studies on the metabolism of methadone have mainly been carried out on cohorts of opioid addicts under methadone maintenance treatment. In vivo, CYP3A4 and CYP2B6 are the major CYP isoforms involved in methadone metabolism, with CYP2D6 contributing to a minor extent, preferentially in metabolism of the R-enantiomer (Table 3).53

3.5. NSAIDs as nonopioid analgesics: CYP2C9

NSAIDs are a group of nonopioid analgesics commonly used for the treatment of acute pain after surgery or chronic pain. Although multimodal pain management by NSAIDS and opioids is important to enhance the efficacy of treatment and reduce the adverse effects, some adverse events including gastrointestinal side effects and cardiovascular side effects have been reported after long-term treatment.54 It implies that an interindividual variation limits the clinical utility and safety of NSAIDS. Based on the previous reports, CYP2C9 polymorphisms might play a significant role in the analgesic efficacy and toxicity of traditional NSAIDs (Table 3), such as flurbiprofen and celecoxib (Table 3).54,55 For NSAIDs used as analgesics, treatment should start at half the lowest recommended dose in poor metabolizers (CYP2C9*3/*3 genotype) to avoid adverse cardiovascular and gastrointestinal events (Table 3). For traditional NSAIDs or selective cyclooxygenase-2 inhibitors, few data are currently available on the possible impact of these single nucleotide polymorphisms on analgesic efficacy.56

3.6. Cyclic antidepressant drugs as co-analgesics: CYP2D6 and CYP2C19

Cyclic antidepressants tackle depression by regulating the levels of neurotransmitters in the brain.57,58 Currently, a major issue of the

treatment with tricyclic antidepressants is their narrow therapeutic index, which results in their replacement by other antidepressants such as selective serotonin reuptake inhibitors.59,60 However, because of their significant efficacy for pain management, cyclic antidepressants are frequently used as "co-analgesics" in the treatment of chronic pain, especially neuropathic pain61; they are also used for migraine prophylaxis. Some of the most commonly prescribed co-analgesics include amitriptyline, desipramine, imip-ramine, nortriptyline, doxepin, clomipramine, and protriptyline. Maprotiline (a tetracyclic compound) and amoxapine (a tricyclic dibenzoxazepine) are newer compounds that have a slightly different structure and toxicological profile.

Cyclic antidepressants are activated in the liver, after hydrox-ylation by CYP2D6 and demethylation by CYP2C19.62 CYP2D6 PMs have higher plasma concentrations of cyclic antidepressants than extensive metabolizers.63 PMs with CYP2D6*3/*3 genotypes should have the dose reduced by 60% to avoid arrhythmia and myelosup-pression (Table 3). Therefore, the PMs have a higher risk of ADRs. By contrast, carriers of the CYP2D6 gene duplications would have ultrarapid metabolism of cyclic antidepressants, which may result in lower drug concentrations and poorer therapeutic responses.64 Thus, genetic variants may affect plasma concentrations of anti-depressants, and dose adjustments before treatment are recommended.

4. Pharmacogenomics for pain medicine: immune-mediated drug hypersensitivity

4.1. Antiepileptic drugs for neuralgia: HLA association of drug-induced cutaneous ADRs

Antiepileptic drugs (AEDs) typically are used to control epilepsy or to treat some psychiatric disorders, e.g., bipolar disorder. These drugs, particularly carbamazepine, trileptal, lamotrigine, gabapentin, and topiramate, may also be used to treat some painful conditions, such as postherpetic neuralgia and fibromyalgia. However, anticonvulsants are a common cause of cutaneous ADRs (cADRs).65 The spectrum of cADRs ranges from a mild mac-uloepapular exanthema to life-threatening severe cutaneous reactions (SCARs) including drug rash with eosinophilia and systemic signs, Stevens—Johnson syndrome (SJS), and toxic epidermal necrolysis (TEN). More than 90% of SCARs occur within 2 months of AED use.66 The AEDs with risk of SCARs include carbamazepine, phenobarbital, phenytoin, and lamotrigine.66 cADRs represent a significant burden on the healthcare system, and SCAR with its most severe form, TEN, still carries a mortality rate as high as 35%.67 These life-threatening conditions could not be predicted and prevented until the recent advancement of pharmacogenomics in discovering of a strong association between a HLA allele (HLA-B*15:02) and carbamazepine-induced SJS/TEN in Han Chinese residing in Taiwan; these results were subsequently replicated in different populations (Figure 2).13,68—72 The strong genetic association suggests a direct involvement of HLA in the pathogenesis of drug hypersensitivity. It has been shown that the HLA molecule presents an antigenic drug and results in clonal expansion and activation of CD8+ cytotoxic T cells. A pharmacogenomic study also identified an unusual form of granulysin secreted by these cytotoxic T lymphocytes and natural killer cells responsible for the rapid and disseminated keratinocyte death in SJS/TEN.73 The high sensitivity and specificity of genetic markers provides a plausible basis for developing tests to identify individuals at risk for drug hypersen-sitivity. A large prospective study has shown that HLA-B*15:02 screening before carbamazepine treatment can effectively reduce the incidence of carbamazepine-induced SJS/TEN.74,75 Translational research demonstrates that preventing drug toxicity by screening





Figure 2. Severe adverse drug reactions with human leukocyte antigen (HLA) association. The interaction of HLA—T-cell receptor (TCR) drugs is the essential event for some types of severe adverse drug reactions. Some polymorphisms of genetic variants (e.g., HLA-B*15:02) related to this critical event could be used in clinical practice. APCs = antigen presenting cells.

people at risk before prescription of a drug is a clinical reality.75 Application of HLA-B*15:02 genotyping as a screening tool for high risk populations taking carbamazepine is now recommended by many regulatory agencies worldwide, including Taiwan, USA, Thailand, Hong-Kong, and Singapore.

This genetic association, albeit weaker, has also been found with phenytoin and lamotrigine (Table 3).76,77 In Caucasian and Japanese populations the risk of developing hypersensitivity reactions to carbamazepine was found to be associated with another allele, HLA-A*31:01.78,79 In addition to HLA, carbamazepine-induced SJS/ TEN, a common type of AED-induced SCARs, was found to be associated with a specific T-cell receptor (Figure 2) clonotypes,80 which could be another supportive biomarker to enhance the positive predictive value.81

4.2. Clozapine: HLA association of clozapine-induced agranulocytosis

Clozapine is a second-generation antipsychotic agent that belongs to the benzodiazepine group. It is indicated for the treatment of resistant schizophrenia or schizoaffective disorder and other psychotic conditions. Although clozapine has several advantages over conventional antipsychotics, the risk of agranulocytosis restricts its use. Based on a retrospective study, clozapine-induced agranulocytosis is associated with the rare HLA-DQB1 (126Q) and HLA-B (158T) alleles. The pharmacogenetic test using these two polymorphisms has a sensitivity of 36% and specificity of 89% (Table 3).82 In addition, clozapine FDA label recommends for some CYP2D6 genotype-carrying patients a lower dose of clozapine (Table 3). However, a prospective study demonstrating whether a pharmacogenetic test based on this genetic association could have clinical utility and prevent clozapine-induced agranulocytosis has not yet been done.

4.3. Moving pharmacogenomic findings into medical practice for pain therapy

Before developing pharmacogenetic tests, a trial-and-error approach for analgesics was used for decades in analgesic treatment. Available pharmacogenomics studies indicated that some of the genetic markers have potential to be used clinically to guide the physicians to choose a right analgesic drug with a right dose to a right person. Some of the examples are listed in Table 3. These are

based on well-defined genetic variants which have been replicated by others and have high predictive values (either high negative predictive value or high positive predictive value or both). These tests also have high sensitivity and specificity. Some of the tests have also been validated by a prospective clinical trial and already in routine medical practice; for example, HLA-B*15:02 screening to prevent carbamazepine-induced SJS.75 Many of the tests also have clinical guidelines for dose adjustment and alternative medications assembled by The Clinical Pharmacogenomics Implementation Consortium (e.g., codeine and carbamazepine). Although there have been clear advances in clinical implementation of pharma-cogenetics, some barriers slow down the speed of pharmacogenetic testing widespread.83 For example, long turnaround time of genetic tests, less value of genomic technologies after health economic evaluation, uncertain interpretation for the pharmacogenetic genetic test results, population restriction, and lack of prospective studies documenting superiority of the pharmacogenetic-guided treatment approach have to be overcome in the future of personalized medicine of pain.

5. Special consideration for pain medication: drug-drug interaction

"Drug-drug interaction," defined as an interaction between two or more drugs, could alter the effectiveness, toxicity, or half-life of the interacting drugs. Moreover, it may increase the risk for serious ADR. Drug-drug interaction has been estimated to contribute to approximately 6-10% of ADRs.84 For pain management, more than one analgesic drug may be administered. In addition, for treating other diseases at the same time, such as coronary artery disease, hypertension, diabetes mellitus, and infections, multiple drugs may be also administered.85 The CYP450 enzyme pathway has been thought to be primarily involved in the metabolism of drugs, especially certain opioids used for the management of severe chronic pain. Therefore, the events underlying drug-drug interactions in pain management using multiple drugs could explain why pharmacogenetic tests for the CYP gene are helpful for identification of the optimal drug dose and prevention of ADRs. Furthermore, some information regarding drug-drug interactions could be referred to on drug labels before administration of analgesic drugs. For example, the interaction between quetiapine (for the relief of pain or depression) and ritonavir (for the treatment of

human immunodeficiency virus infection) may lead to rapid and severe weight gain.86

6. Summary and future directions

Despite the pharmacogenomic studies that show that genetic variants may account for individual differences in drug responses, few genetic markers can be used clinically to guide the dosage for optimal efficacy of pain therapies.8 There are several reasons for the slow progress in this regard. Firstly, the pain sensitivity varies for individual patients and underlying causes of pain are not well characterized. The heterogeneous conditions could interfere with the evaluation of drug efficacy. More precise phenotypes are needed.87 Secondly, the prior usage of opioid and tolerance may affect the drug response. Thirdly, multiple genes may affect drug pharmacokinetics and pharmacodynamics and there are also drug—drug interactions, which may complicate the genetic studies. Fourthly, because the drugs used in pain management alter multiple signaling pathways, and the efficacy of drugs could not be easily measured due to the lack of key indicators or outcome. Therefore, pain management with drugs such as morphine using a "titration" method is currently still widely used in the clinic to guide dosage decisions.88,89 By contrast, clinically useful genetic variants for ADRs are easier to identify based on pharmacogenomic studies, because some ADR conditions have clear phenotypes (i.e., SJS or TEN), critical pathways (i.e., HLA—T-cell receptor; Table 3 and Figure 2),80 and specific indicators (i.e., granulysin).73

In conclusion, the clinically useful pharmacogenomic tests currently available for pain therapy are more direct toward at predicting drug toxicity or dose adjustment. More studies are needed to identify genetic variants that determine drug efficacy of pain medications. This area of research is likely rapidly accelerating with the reducing cost of next-generation sequencing and well-established biobanking system worldwide.


We gratefully acknowledge the members of the Translational Resource Center and the National Center for Genome Medicine at Academia Sinica for their support. This study was supported by the Academia Sinica Genomic Medicine Multicenter Study (40-05-GMM). The funders had no role in study design, data collection, or analysis, the decision to publish or preparation of the manuscript.


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