Fundamental Considerations for Genetically-Guided Pain Management with Opioids Based on CYP2D6 and OPRM1 Polymorphisms.

BACKGROUND: A major challenge for effective pharmacotherapy in pain management is to provide the drug best suited to the patient's innate characteristics.
OBJECTIVE: The article illustrates pharmacogenetic principles to optimize treatments for patients and increase the likelihood of pain relief without dependence. Genetic variances are particularly relevant to opioid drugs used in pain control, and can now be harvested for predictive clinical decision support. STUDY
DESIGN: Clinically actionable polymorphisms in CYP2D6 (cytochrome p450 2D6) and OPRM1 (mu 1 opioid receptor), the most important gene coding, respectively, for a metabolizing enzyme and receptor for opioids are reviewed, and functional effects described.
METHODS: Risk of dysfunction is calculated from the frequency of the alleles with null function for CYP2D6, and from the low function polymorphism for OPRM1. Integration of genetic variability was performed for 9 combinatorial scenarios for CYP2D6 and OPRM1. Each combination was quantified in frequency and classified for clinical impact. A rational and pharmacological basis for personalized pain management based on pharmacokinetic and pharmacodynamic modeling is extracted from the frequency of the combinations.
RESULTS: Patients can be classified in 3 broad risk categories for opioid side effects and dependence. Patients at high-risk with dysfunctional CYP2D6 or OPRM1 account for ~14% of the population and are best managed with non-opioids. Patients at medium risk with subnormal CYP2D6 or OPRM1 account for ~48% of the population and can be managed with dose monitoring. Patients at low risk with functional CYP2D6 and OPRM1 account for ~38% of the population and should be availed to opioid therapy. LIMITATIONS: Heuristic clinical decision support considerations are not validated yet by deployment in large clinical practices. Environmental modifiers such as other drugs and dietary supplements interact with innate characteristics to modify the genetic predictions.
CONCLUSION: Through clinical decision support interpreting the genotyping data, drug choices and doses can then be tailored to provide safe and effective therapy for individual patients. This precision affords personalized medicine to be practiced in pain treatment. Genetic factors could help determine why some patients seem more vulnerable than others to opioid side effects and dependence. KEY WORDS: Pain management, opioids, CYP2D6, OPRM1, clinical decision support, pharmacokinetics, pharmacodynamics, pharmacogenetics, combinatorial genotypes.