Toward precision prescribing for methadone: Determinants of methadone deposition

BACKGROUND: Despite the World Health Organization listing methadone as an essential medication, effective dose selection is challenging, especially in racial and ethnic minority populations. Subtherapeutic doses can result in withdrawal symptoms while supratherapeutic doses can result in overdose and death. Although CYP3A4 was conventionally considered the principal methadone metabolizing enzyme, more recent data have identified CYP2B6 as the principal enzyme. CYP2B6 has ethnically-associated polymorphisms that affect the metabolic rate. Our objective was to investigate the effects of genetic and nongenetic factors on methadone metabolism. METHODS: We measured trough plasma methadone levels in 100 participants with opioid use disorder. We assessed methadone metabolism by calculating the metabolite ratio (major metabolite: 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine [EDDP] divided by methadone concentration). We assessed hepatic fibrosis and steatosis by transient elastography and CYP2B6 alleles, principally responsible for methadone metabolism. Mixed effects models modeled the data in 97 participants. RESULTS: Participants were largely male (58%), minority (61% African American) and non-Hispanic (68%). Forty percent were HCV mono-infected, 40% were uninfected, and 20% were HCV/HIV co-infected. Female sex had significant effects on (R)- and (S)-methadone metabolism (p = 0.016 and p = 0.044, respectively). CYP2B6 loss of function (LOF) alleles significantly affected (S)-methadone metabolism (p = 0.012). Body mass index (BMI) significantly affected (R)-methadone metabolism (p = 0.034). Methadone metabolism appeared to be lower in males, in individuals with LOF alleles, and elevated BMI. CONCLUSIONS: Genetic analysis, especially in minority populations, is essential to delivering individualized treatments. Although the principal methadone metabolizing enzyme remains controversial, our results suggest that sex, CYP2B6 genotype, and BMI should be incorporated into multivariate models to create methadone dosing algorithms. Methadone dosing algorithms should facilitate medication delivery, improve patient satisfaction, and diminish overdose potential.