Senthil Packiasabapathy1, Blessed W Aruldhas1,2,3, Nicole Horn1, Brian R Overholser2,4, Sara K Quinney2,5,6, Janelle S Renschler1, Senthilkumar Sadhasivam1. 1. Department of Anesthesia, Indiana University School of Medicine, Indianapolis, IN 46202, USA. 2. Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA. 3. Department of Pharmacology & Clinical Pharmacology, Christian Medical College, Vellore, 632002, India. 4. Department of Pharmacy Practice, Purdue University College of Pharmacy, Indianapolis, IN 47907, USA. 5. Department of Obstetrics & Gynecology, Indiana University School of Medicine, Indianapolis, IN 46202, USA. 6. Center for Computational Biology & Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
Abstract
Background: Methadone, a synthetic opioid with longer duration of action and lower abuse potential compared with morphine, is used to prevent opioid withdrawal, as well as to manage chronic and acute surgical pain. The variability in response to methadone has been widely recognized. The purpose of this article is to review the literature on the pharmacogenetic factors underlying this variability. Materials & methods: This is a narrative overview of the literature on the genetic variants affecting pharmacodynamics and pharmacokinetics of methadone, retrieved from searches of databases such as PubMed and google scholar. Discussion: Clinical responses to methadone may be affected by genetic variants in the opioidergic, dopaminergic and neurotrophic pathways. Polymorphisms in genes related to disposition and elimination of methadone alter the pharmacokinetics, and possibly pharmacodynamics of methadone. Cytochrome P450 enzymes and P-glycoprotein variants contribute to the interindividual variability in methadone pharmacokinetics. Evidence for single gene variants affecting methadone response remains weak. Multiple genetic variants must be considered in conjunction to improve predictive ability. Conclusion: Evidence remains scarce at this time, to recommend pharmacogenetic testing before methadone administration. Well-powered clinical studies are needed with population pharmacokinetic-pharmacodynamic modeling and multigenetic signature-based predictions to enable tailored use of methadone in clinical practice.
Background: Methadone, a synthetic opioid with longer duration of action and lower abuse potential compared with morphine, is used to prevent opioid withdrawal, as well as to manage chronic and acute surgical pain. The variability in response to methadone has been widely recognized. The purpose of this article is to review the literature on the pharmacogenetic factors underlying this variability. Materials & methods: This is a narrative overview of the literature on the genetic variants affecting pharmacodynamics and pharmacokinetics of methadone, retrieved from searches of databases such as PubMed and google scholar. Discussion: Clinical responses to methadone may be affected by genetic variants in the opioidergic, dopaminergic and neurotrophic pathways. Polymorphisms in genes related to disposition and elimination of methadone alter the pharmacokinetics, and possibly pharmacodynamics of methadone. Cytochrome P450 enzymes and P-glycoprotein variants contribute to the interindividual variability in methadone pharmacokinetics. Evidence for single gene variants affecting methadone response remains weak. Multiple genetic variants must be considered in conjunction to improve predictive ability. Conclusion: Evidence remains scarce at this time, to recommend pharmacogenetic testing before methadone administration. Well-powered clinical studies are needed with population pharmacokinetic-pharmacodynamic modeling and multigenetic signature-based predictions to enable tailored use of methadone in clinical practice.
Authors: Glenn S Murphy; Joseph W Szokol; Michael J Avram; Steven B Greenberg; Torin D Shear; Mark A Deshur; Jeffery S Vender; Jessica Benson; Rebecca L Newmark Journal: Anesthesiology Date: 2017-05 Impact factor: 7.892
Authors: Sarahbeth Howes; Alexandra R Cloutet; Jaeyeon Kweon; Taylor L Powell; Daniel Raza; Elyse M Cornett; Alan D Kaye Journal: Methods Mol Biol Date: 2022
Authors: Blessed W Aruldhas; Sara K Quinney; Brian R Overholser; Michael A Heathman; Andrea R Masters; Reynold C Ly; Hongyu Gao; Senthil Packiasabapathy; Senthilkumar Sadhasivam Journal: CPT Pharmacometrics Syst Pharmacol Date: 2021-08-26