Sex Differences in Associations Between CYP2D6 Phenotypes and Response to Opioid Analgesics
Received 19 November 2019
Accepted for publication 3 March 2020
Published 13 March 2020 Volume 2020:13 Pages 71—79
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Martin Bluth
Guilherme S Lopes,1,2 Suzette J Bielinski,2 Ann M Moyer,3 John Logan Black III,3 Debra J Jacobson,1 Ruoxiang Jiang,1 Nicholas B Larson,1 Jennifer L St Sauver2
1Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; 2Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; 3Division of Laboratory Genetics and Genomics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
Correspondence: Guilherme S Lopes
Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
Tel +1 507 422 6094
Background: Several small studies have previously investigated associations between the cytochrome P450 2D6 (CYP2D6) metabolism and response to opioids. We used a large sample of patients to study associations between CYP2D6 phenotypes and estimated CYP2D6 enzymatic activity scores with pain control and adverse reactions related to codeine and tramadol use. We conducted additional analyses to determine whether our results were consistent among men and women.
Methods: We used data from 2,877 participants in the RIGHT Protocol who were prescribed codeine and/or tramadol between 01/01/2005 and 12/31/2017 and who were not prescribed CYP2D6 inhibitors within 1 year prior to the opioid prescription. CYP2D6 phenotype categories were condensed into four groups: (1) Ultra-rapid and Rapid (n = 61), (2) Normal and Intermediate to Normal (n = 1,448), (3) Intermediate and Intermediate to Poor (n = 1,175), and (4) Poor metabolizer status (n = 193). Opioid-related outcomes included indications of poor pain control or adverse reactions related to medication use. We modeled the risk of each outcome using logistic regression, adjusting for age, sex, race, and ethnicity.
Results: The results revealed a trend from poor to ultra-rapid and rapid CYP2D6 phenotypes in which the risk of adverse reactions incrementally increased and the risk of poor pain control incrementally decreased. This trend reached statistical significance among female (but not male) participants. Among normal and intermediate to normal metabolizers, a larger proportion of women experienced adverse reactions relative to men.
Discussion: We replicated and extended the findings of previous research indicating associations between CYP2D6 phenotypes and response to opioids. In addition, the observed associations were stronger in women than in men. We recommend sex differences to be factored in future research investigating associations between pharmacogenomics and response to medications.
Keywords: opioids, codeine, tramadol, pharmacogenomics, sex differences, CYP2D6
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