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Are prescription misuse and illicit drug use etiologically distinct? A genetically-informed analysis of opioids and stimulants

Published online by Cambridge University Press:  18 January 2021

Genevieve F. Dash*
Affiliation:
Department of Psychological Sciences, University of Missouri, Columbia, MO, USA
Nicholas G. Martin
Affiliation:
Queensland Institute of Medical Research- Berghofer, Brisbane, QLD, Australia
Arpana Agrawal
Affiliation:
School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
Michael T. Lynskey
Affiliation:
Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
Wendy S. Slutske
Affiliation:
Department of Psychological Sciences, University of Missouri, Columbia, MO, USA
*
Author for correspondence: Genevieve F. Dash, E-mail: [email protected]

Abstract

Background

Drug classes are grouped based on their chemical and pharmacological properties, but prescription and illicit drugs differ in other important ways. Potential differences in genetic and environmental influences on the (mis)use of prescription and illicit drugs that are subsumed under the same class should be examined. Opioid and stimulant classes contain prescription and illicit forms differentially associated with salient risk factors (common route of administration, legality), making them useful comparators for addressing this etiological issue.

Methods

A total of 2410 individual Australian twins [Mage = 31.77 (s.d. = 2.48); 67% women] were interviewed about prescription misuse and illicit use of opioids and stimulants. Univariate and bivariate biometric models partitioned variances and covariances into additive genetic, shared environmental, and unique environmental influences across drug types.

Results

Variation in the propensity to misuse prescription opioids was attributable to genes (41%) and unique environment (59%). Illicit opioid use was attributable to shared (71%) and unique (29%) environment. Prescription stimulant misuse was attributable to genes (79%) and unique environment (21%). Illicit stimulant use was attributable to genes (48%), shared environment (29%), and unique environment (23%). There was evidence for genetic influence common to both stimulant types, but limited evidence for genetic influence common to both opioid types. Bivariate correlations suggested that prescription opioid use may be more genetically similar to prescription stimulant use than to illicit opioid use.

Conclusions

Prescription opioid misuse may share little genetic influence with illicit opioid use. Future research may consider avoiding unitary drug classifications, particularly when examining genetic influences.

Type
Original Article
Copyright
Copyright © The Author(s) 2021. Published by Cambridge University Press

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