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Genetic Variants May Predict Dropout Rates from Methadone Treatment

published:
July 1, 2018
Author:
Crist, RC, et al.
Citation:
Crist RC, et al. Pharmacogenetic Analysis of Opioid Dependence Treatment Dose and Dropout Rate. American Journal of Drug and Alcohol Abuse 2018;44(4):431-440.
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  • Opioid use disorder (OUD) treatment outcome is a complex trait that is dependent on both genetic and environmental factors.
  • If genetic variants that predicted dropout or relapse from OUD treatment could be identified, patients could be better supported through that treatment with additional or different interventions.
  • Currently, no pharmacogenetic tests for selecting an OUD medication have been approved by the U.S. Food and Drug Administration. As a step toward achieving that goal, this study aimed to determine the effects of variants in 11 genes on dropout rate and dose in patients receiving methadone or buprenorphine/naloxone.

Using samples from the CTN Starting Treatment with Agonist Replacement Therapy (START) study, CTN-0027,  a 24-week, randomized, open-label trial of methadone and buprenorphine/naloxone for treatment of OUD (n=764), variants in 6 pharmacokinetic genes and 5 pharmacodynamic genes were genotyped. (Pharmacokinetic variants alter the body’s impact on the drug, influencing things like absorption and metabolism. Pharmacodynamic variants alter the drug’s impact on the body, influencing more downstream effects like receptor binding and chemical interactions.)

Genotypes, the set of alleles responsible for a particular trait, were then used to determine the metabolism phenotype, the physical expression of that trait, for each pharmacokinetic gene. Phenotypes or genotypes for each gene were analyzed for association with dropout rate and mean dose.

Results found that a genotype encoding a serotonin transporter was nominally associated with dropout rate when the methadone and buprenorphine/naloxone groups were combined (5-HTTLPR in the SLC6A4 gene).

When the most significant variants associated with dropout rate were analyzed, that same genotype was found to have nominally significant associations with dropout rate in methadone patients in particular, as did a second one, COMT (Val158Met; rs4860), which encodes one of the enzymes responsible for metabolizing dopamine.

Serotonin and dopamine are neurotransmitters commonly affected by substance use, as they are related to mood and reward systems in the brain. Variations in the genes controlling an individual’s serotonin or dopamine function, then, could account for – and potentially also predict – differences in their responses to treatment with methadone.

Conclusions: This study suggests that differences in gene function related to synaptic dopamine or serotonin levels may predict dropout rates during methadone treatment. Patients with specific genetic variants can be identified using genetic testing, and may require additional treatment to improve their chances of completing addiction treatment. Replication in other methadone patient populations will be necessary to ensure the validity of these findings.

Find it in the CTN Dissemination Library: http://ctndisseminationlibrary.org/display/1313.htm

 

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