Methadone (MET) and buprenorphine/naloxone (BUP) are two distinct FDA-approved agonist medications for treatment of opioid addiction. There are prominent pharmacologic differences between BUP and MET. MET is a full mu agonist, while BUP is a partial mu agonist~ BUP has kappa antagonist properties, while MET is devoid of kappa antagonism. At present it is not possible to use clinical or biomarker predictors to determine who will most likely benefit from one medication versus the other. Recent research has suggested that a common variation in the delta opioid receptor gene (OPRD1), single nucleotide polymorphism (SNP) rs678849, may predict response (urine drug screen for illicit opioids) among African-Americans (AAs) to these medications. AA opioid addicts with a CC genotype at rs678849 have a greater probability of gaining substantial therapeutic benefit from MET, while those with alternative genotypes (C/T + TT) have a greater probability to responding well to BUP (relative risk = 2.8~ p = 2.2 x 10-5). The current project represents an attempt to confirm the original finding in an independent population. Individuals of AA ethnicity, age at leas 18, being treated with methadone (n = 150) or buprenorphine/naloxone (n = 150) for opioid addiction at treatment centers in New Haven and the Philadelphia Veterans Administration Medical Center, will be invited to participate. Participation involves review of medical records (t determine eligibility and response to treatment), a brief semi-structured interview and a single small (5 ml) venous blood sample. Blood will be used for DNA extraction and the rs678849 SNP will be genotyped. Genotype x treatment interaction analysis is planned, including as co-variates age, gender, age-at-onset of opioid addiction, co-morbid disorders urine drug screen results for opioids during the most recent 20 weeks is the sole endpoint. This phenotype will be analyzed also using generalized estimating equation methods, with the urine drug screen results treated as repeated measures. If the original observation is confirmed, this research may lead to a simple and inexpensive test for optimal agonist treatment of opioid addiction among African- Americans.

Public Health Relevance

There are two medications, methadone and buprenorphine, which are both approved for treatment of opioid (e.g., heroin) addiction. Currently, physicians have no method to predict which medicine is optimal for which patient. Recent research suggests that variation in DNA for a gene which produces a brain opioid receptor may have predict which medication produces a better treatment outcome among African-American opioid addicts. This proposal is designed to confirm this effect. If it is confirmed, then the DNA variatin may be used to improve treatment outcomes for African-American opioid addicts.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21DA036808-02
Application #
8856538
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Pollock, Jonathan D
Project Start
2014-06-01
Project End
2017-05-31
Budget Start
2015-06-01
Budget End
2017-05-31
Support Year
2
Fiscal Year
2015
Total Cost
Indirect Cost
Name
University of Pennsylvania
Department
Psychiatry
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Crist, R C; Doyle, G A; Nelson, E C et al. (2018) A polymorphism in the OPRM1 3'-untranslated region is associated with methadone efficacy in treating opioid dependence. Pharmacogenomics J 18:173-179
Crist, Richard C; Li, James; Doyle, Glenn A et al. (2018) Pharmacogenetic analysis of opioid dependence treatment dose and dropout rate. Am J Drug Alcohol Abuse 44:431-440
Berrettini, Wade (2017) A brief review of the genetics and pharmacogenetics of opioid use disorders. Dialogues Clin Neurosci 19:229-236
Crist, R C; Doyle, G A; Kampman, K M et al. (2016) A delta-opioid receptor genetic variant is associated with abstinence prior to and during cocaine dependence treatment. Drug Alcohol Depend 166:268-71