Pharmacogenetics and Pain Management
In recent years, pharmacogenetic testing has become more common in pain management. During this time, a few cytochrome P450 (CYP450) enzymes have been identified as being particularly important to the metabolism of certain pharmaceutical agents commonly used in pain treatment, such as opioids, antidepressants, and anti-inflammatory agents.
More recently, 2 non-cytochrome P450 “pharmacodynamic” genetic tests have been identified that help explain opioid dosage requirements in pain patients. The first measures, opioid mu receptor 1 (OPRM1), which determines the ability of opioids to bind to the mu opioid receptor site. The other measures catechol-o methyltransferase (COMT), the enzyme that degrades catecholamines in the central nervous system.
All pain practitioners who prescribe opioids should know that a patient with an OPRM1 with a low sensitivity rating and/or a COMT with a high activity rating likely will require a higher opioid dose than normal to obtain relief from a severe pain problem.
This article presents an up-to-date status and review of the pharmacogenetic markers that have relevance to pain practice.
Classification of Pharmacogenetic Biomarkers
Pharmacogenetic (PGx) biomarkers can be classified into 2 general categories—pharmacokinetic (PK) and pharmacodynamic (PD) biomarkers. Pharmacokinetics is what the body does to the drug (illustrated in Figure 1 of a plasma concentration time profile), whereas pharmacodynamics is what the drug does to the body.
Different examples of PK biomarkers include CYP2D6, CYP2C9, and CYP2B6. If a drug is metabolized via one of these CYP pathways, variations in the genetic code for these enzymes may result in differences in the activity or the expressed amount of enzyme and, therefore, differences in the blood levels of drug. This, in turn, can influence the effectiveness and toxicity of the medication.
Transporters are another type of PK biomarker. Transporters move drugs in and out of cells. Variation in the genes that code for transporters also may result in changes in blood levels. Different examples of pharmacokinetic biomarkers include CYP2D6, CYP2C9 and CYP2B6.
Examples of PD response to an opioid include analgesia, sedation, respiratory depression, and constipation. Some PD biomarkers are the actual molecular receptors of a drug and, thus, they can impact drug response directly. OPRM1 is one example. Multiple studies have found that variation in the gene that codes for this receptor is associated with analgesic and addiction response.
Some PD biomarkers affect drug response indirectly. Examples include variation in human leucocyte antigen genes that influence risk of hypersensitivity to drugs such as the anticonvulsant carbamazepine or the non-steroidal anti-inflammatory drug meloxicam. COMT is another example that will be discussed below.
Generally speaking, the understanding of PK biomarkers is more advanced than that of PD biomarkers. This is because PK genes can be analyzed, and then the changes in blood levels of a drug secondary to the genetic variation can be objectively measured, allowing for a very clear cause and effect relationship.
Measuring the association between a gene responsible for PD response can be much more challenging to accomplish in an objective manner. Pain, for example is influenced by gender, age, ethnicity, and many environmental factors other than genetics. There also is no perfect tool for monitoring an individual’s pain level.
Another challenge with PD biomarkers is that the mechanism of action of drugs is not always fully understood. This can make it very difficult to elucidate the therapeutic consequences of a particular genetic mutation. Mutations resulting in changes to the receptor binding site or receptor density may or may not result in a predictable response. PD biomarkers that are indirectly associated with drug response may be even more challenging to understand and predict.
The biomarkers included in Genelex’s analgesic panel include both PK and PD biomarkers. The PK biomarkers included are CYP2D6, CYP2C9, CYP3A4, CYP3A5, and CYP2B6. The PD biomarkers included are OPRM1 and COMT.
PK biomarkers are all very similar with regards to clinical interpretation and indication for testing. CYP2D6, CYP2C9, and CYP2B6 genes have a poor, intermediate, and normal metabolizer phenotype. CYP2D6 and CYP2C19 also have an ultra rapid metabolizer phenotype. CYP3A4 has an intermediate and normal metabolizer phenotype and CYP3A5 has a non-expresser, intermediate expresser, and expresser phenotype. For CYP3A5, the majority of patients are non-expressers, which is the equivalent of a poor metabolizer.
The indication for testing is the same for all PK biomarkers—the results of therapeutic drug monitoring are not within normal limits and the drug is known to be metabolized by the enzyme being genotyped (tested). Other contributing factors—such as drug interactions, the timing of analysis relative to dose administration, compliance, prescribing error, and malabsorption—should be ruled out prior to testing. In pain management, therapeutic drug monitoring may apply to blood levels, urinary drug screening (UDS), and oral fluid/saliva sampling.
The following 3 cases illustrate when PK testing may be indicated:
Case Example #1
JS was a 43-year-old man who developed chronic neck pain after a motor vehicle accident. As a new patient, he underwent a standard medical history and physical examination. After he was assessed for risk, he was de-termined to be a candidate for opioid therapy and he agreed to a pain contract. According to the terms of the contract, UDS is to be completed at the first visit, monthly after initiating opioid therapy, and randomly.
The initial screening (before opioid use) was unremarkable, but the second screening conducted 1 month later was abnormal, showing no hydromorphone present, despite the patient being on a scheduled dose of hydrocodone (Table 1).
Hydrocodone is metabolized to hydromorphone by CYP2D6. Review of the patient’s medication list showed no concomitant drugs that would interfere with the metabolism of hydrocodone (ie, CYP2D6 inhibitors such as paroxetine, fluoxetine, bupropion, duloxetine, quinidine, etc.). Furthermore, the patient claimed to be taking all medications as prescribed.
The patient agreed to PGx testing to see how he metabolized the hydrocodone. Results showed that the patient was a CYP2D6 poor metabolizer, which helped explain why hydromorphone was undetectable with the UDS and restored the physician’s trust in the patient.
A second indication would be if the patient has in the past or currently is experiencing adverse drug reactions or treatment failure to a medication known to be metabolized by the enzyme being considered for testing. Similar to the first indication, other factors such as drug interactions should be ruled out prior to ordering the genetic test based on this indication.