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Genetic influence on methadone treatment outcomes in patients undergoing methadone maintenance treatment for opioid addiction: a pilot study

Authors Samaan Z, Bawor M, Dennis BB, Plater C, Varenbut M, Daiter J, Worster A, Marsh DC, Tan C, Desai D, Thabane L, Pare G

Received 15 April 2014

Accepted for publication 9 May 2014

Published 19 August 2014 Volume 2014:10 Pages 1503—1508

DOI https://doi.org/10.2147/NDT.S66234

Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 3

Zainab Samaan,1–4 Monica Bawor,3,4 Brittany B Dennis,2,3 Carolyn Plater,5 Michael Varenbut,5 Jeffrey Daiter,5 Andrew Worster,5,6 David C Marsh,5,7 Charlie Tan,8 Dipika Desai,3 Lehana Thabane,2,9,10 Guillaume Pare11

1Department of Psychiatry and Behavioural Neurosciences, 2Department of Clinical Epidemiology and Biostatistics, 3Population Genomics Program, Chanchlani Research Centre, 4MiNDS Neuroscience Program, McMaster University, Hamilton, Ontario, Canada; 5Ontario Addiction Treatment Centres, Richmond Hill, Ontario, Canada; 6Department of Medicine, McMaster University, Hamilton, Ontario, Canada; 7Northern Ontario School of Medicine, Laurentian University, Sudbury, Ontario, Canada; 8Michael G. DeGroote School of Medicine, McMaster University, 9Biostatistics Unit, Centre for Evaluation of Medicine, 10System Linked Research Unit, 11Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada

Introduction: Treatment of opioid addiction with methadone is effective; however, it is known to produce interindividual variability. This may be influenced in part by genetic variants, which can increase the initial risk of developing opioid addiction as well as explain differences in response to treatment. This pilot study aimed to assess the feasibility of conducting a full-scale genetic analysis to identify genes that predict methadone treatment outcomes in this population.
Methods: This was a cross-sectional observational study of patients admitted to a methadone maintenance treatment program for opioid addiction. We obtained demographic and clinical characteristics in addition to blood and urine samples, for the assessment of treatment outcomes.
Results: The recruitment process yielded 252 patients, representing a 20% recruitment rate. We conducted genetic testing based on a 99.6% rate of provision of DNA samples. The average retention in treatment was 3.4 years, and >50% of the participants reported psychiatric and medical comorbidities. BDNF rs6265 and DRD2 rs1799978 were the common single nucleotide polymorphisms (SNPs) selected for the feasibility study.
Discussion: This study met our predetermined feasibility criteria; recruitment, response rates, and genetic testing were feasible; treatment duration was sufficient for follow up; and the prevalence of comorbid conditions indicated the need for reliable psychiatric and chronic pain measures. The study strengths included effective collaboration with clinics and the generalizability of sample population. Key learning points show the need for assessment of treatment outcomes on multiple domains, implementation of follow up, and the development of standardized training for the study clinical staff.

Keywords: genetics, substitute opioid therapy, treatment response, risk factors

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