Each year, more than 770,000 individuals are injured or die from adverse drug events.1 This number exceeds those who die from heart disease, which causes approximately 630,000 deaths each year.2 In 2014, an estimated 1.6 million hospital stays were a result of adverse drug events that started during a hospital stay, and 1.1 million hospital stays were documented for adverse drug reactions present on admission, which increased significantly from 2010 to 2014.3 Of the approximately 4 billion prescriptions filled in the US in 2013, 18% had actionable pharmacogenetics.4 Pharmacogenetic testing can prevent adverse drug events including hospitalization and death, increase approval time for drugs, and decrease complications that may arise from delayed treatment of disease through early detection, which would improve patient outcomes and patient-provider trust as well as decrease healthcare costs.5
Primary care providers should use pharmacogenetic testing when standard medication regimens are unsuccessful, adverse drug reactions are present, or misuse or diversion is suspected. This provides an additional resource for primary care providers to personalize treatment and provide appropriate, effective, and safe care. Evidence from systematic reviews and guidelines shows that pharmacogenetic testing is an effective method of reducing adverse drug reactions.1
Case example #1
A 51-year-old man presented to a family practice clinic for treatment of chronic low back pain, which he had suffered from for over 15 years secondary to spinal enthesopathy with reported radicular symptoms. He enrolled in a pain management program but failed several different pain management regimens, including nonsteroidal anti-inflammatory drugs (NSAIDs), opioids, and skeletal muscle relaxants. He completed physical therapy, chiropractic treatments, epidural injections, and lumbar radiofrequency ablation procedures because of the limited pain relief his medications provided him. At the time of his clinic visit, the patient was taking methadone 10 mg orally three times daily and oxycodone 10 mg and acetaminophen 325 mg orally four times daily equaling 300 morphine milligram equivalents (MMEs) with only 50% pain relief.6 Because of the high dosage of MMEs and limited pain relief, the patient's provider recommended pharmacogenetic testing.
The patient's pharmacogenetic test results showed that current medications were genetically ineffective in managing his pain. For instance, methadone was found to have significant gene-drug interaction caused by the CYP2B6 (ultrarapid metabolizer), CYP2D6 (intermediate metabolizer), CYP3A4 (intermediate metabolizer), and CYP2D6 (intermediate metabolizer) genes in this patient. This showed an inability to predict dosage adjustment because of conflicting variations of metabolism and genotype that may impact drug metabolism, resulting in reduced efficacy. Further, oxycodone was found to have significant gene-drug interaction with the CYP2B6 (ultrarapid metabolizer), CYP3A4 (intermediate metabolizer), and CYP2D6 (intermediate metabolizer) genes in this patient. In this patient, this may cause serum levels to be too high and require lower dosages, and genotype may impact drug mechanism of action, resulting in reduced efficacy.
After a review and an interpretation of the pharmacogenetic testing results, the clinic's pain management department was notified and the patient was placed on tapentadol and buprenorphine transdermal, both of which provided more effective pain relief. The patient has been on this treatment with only small adjustments of dosing with a reported 80% control of pain symptoms and higher quality of life.
Case example #2
A 59-year-old woman presented to a family practice clinic for treatment of chronic pain secondary to bilateral knee osteoarthritis and lumbar disk degeneration with spondylosis with reported radicular symptoms. She had been experiencing this pain for more than 10 years. Referrals to pain management and orthopedics in the past included failed treatments with NSAIDs, including celecoxib, as well as gabapentin, tramadol, hydrocodone, and acetaminophen. Additionally she had severe drug reactions to pregabalin, tizanidine, and cyclobenzaprine. The patient had a left total knee replacement and right knee injections, along with physical therapy and epidural injections for her back pain with limited relief. At the time of her visit, she was taking oxycodone 10 mg and acetaminophen 325 mg orally twice daily and morphine 15 mg extended release totaling an MME of 45 and her pain was reported to be only 20% controlled with this treatment. She was also on duloxetine for pain and depression, provided by her psychiatrist, though she stated this caused her too much drowsiness. The FDA-approved indications for duloxetine include major depressive disorder and chronic musculoskeletal pain.
The patient decided to stop all pain medications as she was not happy with how she was feeling, and her pain was not well controlled. She was referred to a medication-assisted treatment (MAT) program due to symptoms of withdrawal and was started on naltrexone. The patient reported limited relief with naltrexone and started taking more than was directed and was subsequently released from the program because of medication misuse.
The patient returned to the family practice clinic in search of other options to control her symptoms. At that time, pharmacogenetic testing was recommended because of the limited control of her symptoms and suspected misuse of naltrexone.
Based on her pharmacogenetic results, duloxetine was found to have a moderate gene-drug interaction because of the CYP2D6 (intermediate metabolizer) gene causing serum levels to be too high and requiring lower dosages. She was on higher doses of duloxetine to manage pain and depression and was likely causing increased adverse reactions, such as drowsiness. Her psychotropic testing also revealed that she was positive for the SLC6A4 gene, showing that she has a decreased expression of serotonin transporters that may cause a decreased response to selective serotonin reuptake inhibitor (SSRI) medications in general. Last, naltrexone was found to have moderate gene-drug interactions impacting the drug mechanism of action and resulting in reduced efficacy. This could account for her limited relief with higher dosages and resultant medication misuse.
After a review and an interpretation of the patient's pharmacogenetic testing, her psychiatrist was notified of the results, and the patient was placed on a mood stabilizer and referred back to the MAT program and started on sublingual buprenorphine and naloxone. She has been stable on this treatment regimen without adverse drug reactions and has adequate symptom relief and improved mood.
Pharmacogenetic testing can improve patient care and outcomes by allowing prescribers to tailor medications based on a patient's genetic profile.7 A genetic profile typically includes genetic variations that determine how individuals metabolize drugs based on their inherited alleles, which can directly affect enzymatic response. For example, when cytochrome P450 (CYP450) was discovered in 1955 it was found to have a major source of variability in drug pharmacokinetics and response.8 Since then, more biomarkers have been discovered that are known to directly affect the rate of drug metabolism. Currently, pharmacogenetic testing in primary care is focused on chronic pain management and psychiatric disorders, including attention-deficit hyperactivity disorder, but it is available for treatment considerations in cardiology, oncology, and gastroenterology.9
Understanding drug metabolism and genetics
The individual-specific response to medication can be attributed to multifold and complex factors, which may be determined by individual genetic makeup.10 A patient's ability to metabolize medications is largely determined by his or her enzymatic response. Enzymatic response is influenced by the type and number of copies of alleles inherited.11 There are four basic types of metabolizers that are scientifically accepted and evaluated:
- ultrarapid metabolizers—carry multiple copies of functional alleles leading to excessive activity
- extensive metabolizers—have two normal or “wild-type” alleles and have normal activity
- intermediate metabolizers—carry one normal and one nonfunctional or two reduced-functional alleles and have normal or close-to-normal activity
- poor metabolizers—carry two mutated alleles with very limited or completely lost enzymatic activity.12,13
Genetic polymorphisms influence the pharmacokinetics and pharmacodynamics of a drug response through an individual's body. Pharmacokinetics is the study of the absorption, distribution, metabolism, and excretion of a drug, whereas pharmacodynamics examines receptors, ion channels, enzymes, and the immune system's response.14 When this information is combined, it can analyze if the drug chosen will have little or no drug response, be too quickly metabolized, have zero drug response at normal dose (ultrafast metabolizer), have normal or close-to-normal drug response (extensive or intermediate metabolizer), or have an increased drug response from the drug being metabolized too slowly and leading to excessive high drug levels at normal doses and a higher chance of adverse drug reactions (poor metabolizers).12
Drugs are metabolized in two different phases: Phase 1 and Phase 2. Phase 1 metabolism uses chemical reactions via oxidation, reduction, and hydrolysis to result in three outcomes: drug and metabolites become inactive, metabolites become active but are less effective than the drug taken, or the drug taken is not active (prodrug). Phase 2 metabolism excretes the soluble compounds/conjugates formed in Phase 1 through urine; drugs using Phase 2 metabolism are typically pharmacologically inactive.13 For example, warfarin only uses Phase 2 metabolism, is excreted by the kidneys, and is not pharmacologically active.12,15
Because drugs break down into separate metabolites when being metabolized by the body, there are multiple alleles that influence cytochromes and can affect a drug's metabolism. For example, morphine is broken down into three metabolites: its nonactive form (normorphine), its active metabolite (identical to the pharmaceutical opioid hydromorphone), and its active metabolites that are not pharmaceutical opioids (Morphone-3-G glucuronide and Morphone-6-G glucuronide).16 Each category of metabolites can vary based on each drug's pharmacokinetics and pharmacodynamics, even within a drug class and its respective targets. For example, a drug that does not have active metabolites, such as methadone, instead has several inactive metabolites and induces its analgesic response through its affinity for the N-methyl-d-aspartate receptors. Although there is not an active metabolite, the intermediate products that are produced can either be toxic or have clinical usefulness.13 It is important to have a detailed understanding of each drug and its pharmacokinetic and pharmacodynamic properties and how they are used by pharmacogenetic databases to properly and efficiently produce safe prescribing guidelines.15
Pharmacogenetics and drug labeling
More than 70 FDA-approved US drugs contain pharmacogenetics information (biomarkers) on their label.17 These include commonly prescribed drugs, such as amitriptyline (CYP2D6), celecoxib (CYP2D6), citalopram (CYP2C19), escitalopram (CYP2D6 and CYP2C19), metoprolol (CYP2D6), omeprazole (CYP2C19), rosuvastatin (SLCO1B1), sulfamethoxazole and trimethoprim (G6PD), tramadol (CYP2D6), and warfarin (CYP2C9 and VKORC1). Drug labeling can describe:18
- drug exposure and clinical response variability
- risk of adverse reactions
- genotype-specific dosing
- mechanisms of drug action
- polymorphic drug target and disposition genes
- trial design features.
There are many studies related to pharmacogenetics and patient outcomes in primary care, and several large clinical trials are in process. The authors found more than 340 clinical trials involving pharmacogenetics that were recently completed and an additional 300 that were in process or recruiting patients worldwide at the time of this article's publication. Pérez and colleagues conducted a randomized, double-blind study of 280 patients with major depressive disorder over a 12-week period of time in Europe.19 Results showed a significant improvement of response in the pharmacogenetics treatment group versus the control group, but the results were more statistically significant in the patients who had failed on more than one medication before the trial started and they experienced significantly fewer adverse reactions.
Based on a 2017 study of 134 patients with noncancerous pain, after review of genetic testing results, physicians adjusted treatment plans for 40% of patients. When medication changes were made, there were fewer adverse drug reactions based on the genetic testing results, and a statistically significant 72% of patients showed improvement in clinical status.12
Lerman and colleagues conducted a study with 1,246 participants that used nicotine metabolite ratio as a genetically informed biomarker response to smoking cessation treatment. The study determined that treating normal metabolizers with varenicline and slow metabolizers with nicotine patch optimized quit rates and minimized adverse reactions for all smokers.16
The Clinical Pharmacogenetics Implementation Consortium has guidelines designed to help clinicians understand how available genetic test results should be used to optimize drug therapy, rather than whether tests should be ordered.18 They include guidelines for clopidogrel therapy, phenytoin dosing, and dosing of SSRIs, to name a few. This is a great resource for clinicians.
Current use in primary care
It is estimated that 50% of all opioid prescriptions are written by primary care providers and that pain control is one of the most common reason that patients visit their healthcare provider.18,19 According to a 2018 CDC report, an estimated 50 million individuals in the US have chronic pain.4 Not all patients respond to pain medication the same way, and there is a high potential for abuse, misuse, and addiction. Pharmacogenetic testing can predict the individual response to drug therapy either before therapy is initiated or when mainstream therapies are not effective in chronic pain management.20 The use of evidence-based guidelines when prescribing medication and treating diseases is recommended, but many times prescribers rely on trial-and-error, which may cause patients to undergo undue stress, time off work, and many unnecessary office visits. Not only can pharmacogenetic testing assist in the treatment of patients and their responses to pain medications, it can also help reduce adverse reactions. Genetics can explain the variability of responses, and testing can predict more effective medication choices and doses.21
For example, current guidelines recommend using standard urine drug screens (UDSs) to determine patient adherence to controlled medication regimens.20 When inconsistencies occur, typically the patient-provider relationship is terminated or controlled substances are discontinued because of suspected misuse or diversion. However, drug metabolism may differ between patients and may affect drug metabolites analyzed in standard UDSs.22,23 In their 2018 publication, Crist and colleagues provide a detailed chart about genetic variation associated with opioid use disorder and how it affects UDS results.24
In November 2017, the American Medical Association voted to advance the development of a comprehensive strategy that allows more consistent coverage of genomics and genetic tests and accessibility.24 Barriers may include limited provider knowledge in ordering and interpreting pharmacogenetic testing results and its benefits, including current research supporting its use.21 Health insurance policies may not cover pharmacogenetic testing for all patients, and pharmacogenetic companies often use different methods for reporting results, which make the application of clinical decision-making challenging.
Other barriers include patient concerns about genetic testing, which include consent, confidentiality, and inequality in healthcare.21 Ethical implications include genetic discrimination and the use of genetic information in research.25 In 2008, Congress passed the Genetic Information Nondiscrimination Act (GINA) to protect Americans from genetic discrimination. This Act prevents insurance companies from using that information to adjust premiums and deny coverage for preexisting conditions and employers from denying employment based on genetic testing. GINA does not apply to life insurance, disability or long-term care insurance, or care provided in the military, Veterans Affairs, or the Indian Health Service.12 Additionally, patients may confuse pharmacogenetic testing with genetic variant trait testing and may be resistant to testing if they believe it can affect coverage by their insurance carrier for a potential preexisting condition.12
In the rapidly advancing medical field, it is important for every healthcare practitioner to have a basic understanding of pharmacogenetic testing, when it should be used, and its benefits and limitations. This emerging science may give future practitioners the ability to lessen adverse drug reactions and reduce deaths and hospitalizations caused by drug interactions. Resources are available online to help clinicians calculate gene-drug interactions. (See Gene-drug interaction resources.) A patient given a chance to experience fewer adverse reactions, allowing for fewer errors in prescribing medications, could lead to more successful and prompt treatments in short- and long-term diseases. There is still more detailed research warranted, including larger, more diverse cohorts for a better understanding of how pharmacogenetic testing can be best used in primary care. NPs should not avoid using newer technology as long as they understand the potential benefits and limitations. Relying solely on pharmacogenetic testing for treatment in primary care is not recommended.
Gene-drug interaction resources
The Drug Gene Interaction Database
The FDA Table of Pharmacogenetic Biomarkers in Drug Labeling
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