Analysis of genetic and clinical factors associated with buprenorphine response

Personalized medicine and opioid use disorder

Opioid use disorder (OUD) is a major public health problem affecting millions of people worldwide. Although OUD is a chronic and relapsing disorder, a variety of pharmacological and non-pharmacological interventions are available. Medication-assisted treatment of OUD generally relies on competition for opioid receptors against the addictive substance. The mechanisms of this competition are to block or inactivate the opioid receptor or activate the receptor with a substance that is intermittent or long acting. Methadone and buprenorphine are two United States Food and Drug Administration-approved medications that have long-term positive effects on the health of opioid-dependent individuals. Although clinical studies of drugs generally demonstrate efficacy in thousands of people and toxicity is excluded, it cannot be predicted whether the given drug will cause side effects in one of the patients at the treatment dose. Individual differences can be explained by many biological and environmental factors. Variations in genes encoding drug metabolism or cellular drug targets significantly explain the variability in drug response between individuals. Therefore, for the effects of candidate genes to be accepted and included in individual treatment protocols, it is important to repeat studies on individuals of different ethnic backgrounds and prove a similar effect.

The genetic landscape of substance use disorders

Substance use disorders represent a significant public health concern with considerable socioeconomic implications worldwide. Twin and family-based studies have long established a heritable component underlying these disorders. In recent years, genome-wide association studies of large, broadly phenotyped samples have identified regions of the genome that harbour genetic risk variants associated with substance use disorders. These regions have enabled the discovery of putative causal genes and improved our understanding of genetic relationships among substance use disorders and other traits. Furthermore, the integration of these data with clinical information has yielded promising insights into how individuals respond to medications, allowing for the development of personalized treatment approaches based on an individual's genetic profile. This review article provides an overview of recent advances in the genetics of substance use disorders and demonstrates how genetic data may be used to reduce the burden of disease and improve public health outcomes.

Pharmacogenetics of Biochemically Verified Abstinence in an Opioid Agonist Therapy Randomized Clinical Trial of Methadone and Buprenorphine/Naloxone

Methadone and buprenorphine/naloxone are opioid agonist therapies for opioid use disorder treatment. Genetic factors contribute to individual differences in opioid response; however, little is known regarding genetic associations with clinical outcomes in people receiving opioid agonist therapies. Participants diagnosed with opioid use disorder, principally consisting of prescription opioids (licit or illicit), were randomized to methadone or buprenorphine/naloxone for 24 weeks of daily treatment (NCT03033732). Urine was collected at 12 biweekly study visits and analyzed for non-treatment opioids. Variants in genes involved in methadone metabolism (CYP2B6, CYP2C19, and CYP3A4), buprenorphine metabolism (CYP3A4 and UGT2B7), and μ-opioid receptor function (OPRM1) were genotyped and analyzed for their association with the number of non-treatment opioid-free urine screens. Primary analyses focused on the last 12 weeks (6 study visits, post-titration) of treatment among those reporting White ethnicity. Additional sensitivity and exploratory analyses were performed. Among methadone-treated participants (n = 52), the OPRM1 rs1799971 AA genotype (vs. G-genotypes, i.e., having one or two G alleles) was associated with greater opioid-free urine screens (incidence rate ratio = 5.24, 95% confidence interval (CI) = 2.43-11.26, P = 0.000023); longitudinal analyses showed a significant genotype-by-time interaction over the full 24 weeks (12 study visits, β = -0.28, 95% CI = -0.45 to -0.11, P = 0.0015). Exploratory analyses suggest an OPRM1 rs1799971 genotype effect on retention. No evidence of association was found between other genetic variants, including in metabolic variants, and non-treatment opioid-free urine screens in the methadone or buprenorphine/naloxone arms. Those with the OPRM1 rs1799971 G-genotypes may have a poorer response to methadone maintenance treatment, an effect that persisted through 24 weeks of treatment.

Assessing Opioid Use Disorder Treatments in Trials Subject to Non-Adherence via a Functional Generalized Linear Mixed-Effects Model

The opioid crisis in the United States poses a major threat to public health due to psychiatric and infectious disease comorbidities and death due to opioid use disorder (OUD). OUD is characterized by patterns of opioid misuse leading to persistent heavy use and overdose. The standard of care for treatment of OUD is medication-assisted treatment, in combination with behavioral therapy. Medications for opioid use disorder have been shown to improve OUD outcomes, including reduction and prevention of overdose. However, understanding the effectiveness of such medications has been limited due to non-adherence to assigned dose levels by study patients. To overcome this challenge, herein we develop a model that views dose history as a time-varying covariate. Proceeding in this fashion allows the model to estimate dose effect while accounting for lapses in adherence. The proposed model is used to conduct a secondary analysis of data collected from six efficacy and safety trials of buprenorphine maintenance treatment. This analysis provides further insight into the time-dependent treatment effects of buprenorphine and how different dose adherence patterns relate to risk of opioid use.