Genotyping and Phenotyping in Pain Management
According to the American Academy of Pain Medicine, chronic pain is an epidemic affecting approximately 1.5 billion people worldwide. With age comes more pain related problems. Cross sectional studies of patients with neuropathic pain have shown that even with pharmacological treatment, moderate or severe pain continues. Part of the difficulty is the heterogeneity of causes and symptoms that vary from individual to individual. Physicians who treat patients with pain note a marked variability in pain responses among patients. Physicians often treat these patients with the same arsenal of medications on a trial and error basis. This method may be time consuming and even potentially harmful to patients. Response to pain and medications may be partially but significantly influenced by genetic and phenotypic makeup. In the 1890s, Wilhelm Johannsen was the first to introduce the terms genotype and phenotype.1 Genotype refers to the genetic components of an individual. Phenotype refers to the set of observable characteristics of an individual from the interaction of its genotype with the environment.
Under or overdosing is possible when patients respond differently to medications. Without knowledge of a patient’s genetic makeup, treatment plans cannot be tailored to individual patient’s needs. Pain is influenced by many factors, including genetic predisposition, prior experiences, physiological status, mood, coping skills, and sociocultural background.2 The extent to which each of these factors has on the pain experience is unclear.
Several genes likely affect the pain experience and analgesic response. Two hereditary disorders are known to make individuals insensitive to pain: hereditary insensitivity to pain with anhydrosis and familial dysautonomia. As our knowledge grows, so may our ability to understand why pain persists in some patients but not others—despite identical traumas—or why some people have a low tolerance to pain while others have a much higher tolerance.
A recent study presented by Dr. Onojjighofia at the American Academy of Neurology’s 66th Annual Meeting suggests that four genes may be involved in pain tolerance. His study examined 2,721 people diagnosed with chronic pain. The genes involved were catechol O methyltransferase (COMT), dopamine receptor D2 (DRD2), dopamine receptor D1 (DRD1), and opioid receptor kappa 1 (OPRK1). These four genes help to determine the pain threshold in individuals. Participants were taking opioid pain medications and rated pain from a 0 to 10. Patients with 0 pain were excluded from the study. Patients were divided into three groups according to pain perception: (1) low pain, a score of 1–3; (2) moderate pain, a score of 4–6; and (3) severe pain, a score of 7–10. The DRD1 gene variant was 33% more prevalent in the low pain group than in the severe pain group. COMT and OPRK variants were 25% and 19% more prevalent, respectively, in the moderate pain group compared to the severe pain group. The DRD2 variant was 25% more common among those with severe pain than those with moderate pain.3
While these sequence variations in DNA (SNPs) may help predict the likelihood of individual pain sensitivity, DNA testing should not be used to diagnose pain according to the Medical Treatment Utilization Schedule (MTUS) guidelines.4 Although we may not use genetic testing to diagnose pain, genetic testing may affect the selection of medications used to treat it.
There are several reasons to consider genetic testing. Medications may be metabolized slowly in individuals with a genetic polymorphism that eliminates or decreases enzyme activity. Such patients may be at risk of an adverse drug reaction (ADR) or therapeutic failure. In addition, drug therapy may be ineffective if a drug is metabolized too quickly because of genetic polymorphism. Knowledge of these polymorphisms before initiating drug therapy could help in choosing the most efficacious agent and in decreasing the risk of ADRs.
Patients can be classified by how effectively they metabolize a medication according to how many copies of normal versus abnormal alleles they have inherited (Table 1).
Approximately 7–10% of Caucasians are CYP2D6 deficient (poor metabolizers [PM]); only 1–2% of Asians and 2–4% of African Americans are PMs. Among Asians and African Americans, 30% are intermediate metabolizers of CYP2D6. Why are these variations important? Many of the medications we use to treat chronic pain are affected by these polymorphisms.
CYP Influence On Opiods
Various medications are pro drugs, inactive compounds that are metabolized to their active forms by CYP enzymes. Other medications are metabolized by P450 into clinically active metabolites. Table 2 shows common P450 substrates. Codeine, a pro drug, is metabolized by CYP2D6 into its active form, morphine. Therefore, if a patient is a poor metabolizer of CYP2D6, he or she will not convert codeine into its active form and will get no analgesic benefit from the drug. On the other hand, a patient who is an ultra-rapid metabolizer of CYP2D6 may experience dangerously high levels of morphine in his or her system. Two other commonly used opioids that are metabolized by CYP2D6 to stronger, more potent forms are hydrocodone (metabolized into hydromorphone) and tramadol.
Oxycodone has an active metabolite, oxymorphone, with significant analgesic effects. Because oxycodone depends on CYP2D6 for clearance, patients deficient in CYP2D6 alleles could be prone to overdose.
CYP3A4 is also involved in opioid metabolism. Patients taking fentanyl or buprenorphine who are poor metabolizers of CYP3A4 would have higher than usual blood levels of these mediations. Methadone, metabolized by CYP34A, is also metabolized by CYP3B6 6. Lower doses should be given to patients who are deficient in these alleles. Table 3 provides examples of clinical consequences of opioid cytochrome P450 interactions.
Urine Drug Screening
Genetic polymorphism affects urine drug screening. A patient may state that he or she is not getting benefit from oxycodone. A quantitative urine drug screen may show the results listed below in Examples 1 and 2. In Example 1, the level of oxycodone is high, and a small amount of oxymorphone appears in the urine. This patient, who is a poor metabolizer of CYP2D6, may benefit from a change to a different opioid. In Example 2, the level of oxycodone is high, but there is no evidence of metabolite in the urine, which may be consistent with adulteration.
Genetic testing, available through several companies, is generally economically feasible. The test is often performed from a buccal swab. Common available SNPs that can be tested include CYP 2D6, 2C9, 2C19, and 3A4. The test is easy to perform, and the results are often received quickly.
The pain phenotype is a window to determine underlying pathophysiological mechanisms and a guide for individualized treatment options. Phenotyping can classify patients into smaller subsets from one large disease group. It can introduce a new standard of healthcare and help clinicians select the most advantageous treatments to improve medical outcomes. It will eliminate the one size fits all model that has been widely accepted today. Phenotyping is a tool for clinical purposes that may help us improve pain management. We can classify patients with similar pain etiology based on pain related sensory abnormalities— otherwise known as “sensory profiling”—and then direct management based on this classification. It is difficult and costly to genotype a large number of patients, but phenotyping with large patient cohorts is possible. Obtaining the sensory profile of a patient may reflect an underlying mechanism or combination of mechanisms influencing pain. Once determined, medication trials would follow. Responses based on sensory profile and certain pain descriptors would lead to targeted treatment options. Detailed phenotypic data gathering is necessary to understand the factors that ultimately define a phenotype. It is something we do every day in clinical practice while gathering information on demographics, pain history, physical examination, and investigations.
An example of clinical phenotyping is the UPOINT (Urinary, Psychosocial, Organ Specific, Infection, Neurologic, and Tenderness of Skeletal Muscles) system for a patient with urological chronic pelvic pain.8 Instead of including all patients under one diagnosis, patients are classified into subtypes and managed according to the classification system. Based on the best available evidence, clinical phenotyping of patients directs management of individual phenotypes based on best available evidence. Multimodal therapy can then be selected as indicated by phenotype domains in the individual patient.
Another example of clinical phenotyping is a study conducted in patients with diabetic peripheral neuropathy (DPN), postherpetic neuralgia (PHN), radicular (neuropathic), or axial (nonradicular) low back pain (LBP). The investigators conducted 16 interview questions and 23 bedside examinations. They assessed symptoms and signs of 130 patients and performed a cluster analysis that revealed association patterns that characterized six subgroups with neuropathic pain and two subgroups with non neuropathic pain. There were eight subgroups of patients (clusters C1 to C8). Patients with DPN, PHN, and radicular LBP were distributed across the clusters C1 to C6, patients with axial LBP formed the clusters C7 and C8. When the investigators used classification tree analysis to determine the minimum number of interview questions and physical tests that would assign patients to clusters, interview questions were narrowed down to 6 and physical tests to 10. They then evaluated the diagnostic usefulness for LBP. Sensitivity and specificity in distinguishing neuropathic versus nociceptive LBP was more than 90%. They demonstrated a pain assessment tool independent of disease etiology based on symptoms and signs.9
Careful phenotyping of cases can identify subgroups of patients with the same etiology. Personalized pain treatment is in its infancy, but we are advancing. Phenotyping is a clinical tool that can identify underlying pathophysiological mechanisms and guide individualized treatment options. Although genetic testing currently cannot be used to predict and diagnose chronic pain, we can use this information to better treat patients with painful conditions and reduce the process of trial and error that is often frustrating for both physicians and patients. The hope for the future is that genotyping, along with phenotyping, can personalize and individualize pain therapy and improve patient care.
1. Wanscher JH. The history of Wilhelm Johannsen’s genetic terms and concepts from the period 1903 to 1926. Centaurus 1975; 19 (2): 125-147.
2. Edwards RR. Genetic predictors of acute and chronic pain. Curr Rheumatol Rep. 2008;8:411–417.
3. Onojighofia T. Perception of analgesia in narcotic users with chronic pain: a multi center cross sectional study comparing genotype to Pain VAS (P.A.I.N. study). PAIN Week: American Academy of Neurology 2014 Meeting, Las Vegas, Nevada. P4.349 2014.
4. MTUS: Medical Treatment Utilization Schedule: chronic pain medical treatment guidelines. 2009.
5. Indiana University School of Medicine. P450 Drug Interactions: Abbreviated “Clinically Relevant” Table, Substrates. Available at: http://medicine.iupui.edu/ clinpharm/DDIs/ClinicalTable.aspx. Accessed March 2017.
6. Oesterheld J. Cytochrome P 450 (CYP) Metabolism Reference Table. Seattle, WA: Genelex; 2012; Available at: http://youscript.com/healthcare-professionals/whyyouscript/cytochrome-p450-drug-table/. Accessed March 2017.
7. Tennant F, Hocum B. Pharmacogentics and pain management: clinical use and interpretation of the common pharmacogentics tests. Practic Pain Manage. 2015;15(7):64.
8. Nickel JC, Shoskes D. Phenotypic approach to the management of chronic prostatitis/chronic pelvic pain syndrome. Curr Urol Rep. 2009;10:307–312.
9. Scholz J, Mannion RJ, Hord DE, et al. A novel tool for the assessment of pain: validation in low back pain. PLoS Med. 2009;6(4):e1000047.
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