Gender-specific association of functional prodynorphin 68 bp repeats with cannabis exposure in an African American cohort

Abstract

Background: Cannabis use disorders (CUDs) cause substantial neuropsychiatric morbidity and comorbidity. There is evidence for gender-based differences in CUDs, for instance, a greater prevalence in males than in females. The main active component of cannabis is delta 9-tetrahydrocannabinol (delta 9-THC), a partial agonist of the cannabinoid type 1 receptor. Preclinical studies show that genetic or pharmacological manipulation of the kappa opioid receptor/dynorphin system modulates the effects of delta 9-THC. Methods: In this case-control study of adult African Americans (n=476; 206 females, 270 males), we examined the association of the functional prodynorphin 68 bp (PDYN 68 bp) promoter repeats with categorical diagnoses of cannabis dependence (Diagnostic and Statistical Manual of Mental Disorders-IV criteria), as well as with a rapid dimensional measure of maximum lifetime cannabis exposure (the Kreek–McHugh–Schluger–Kellogg cannabis scale). Results: The PDYN 68 bp genotype (examined as short–short [SS], short–long [SL], or long– long [LL], based on the number of repeats) was not significantly associated with categorical cannabis-dependence diagnoses, either in males or in females. However, in males, the PDYN 68 bp SS+SL genotype was associated with both greater odds of any use of cannabis (p<0.05) and earlier age of first cannabis use, compared to the LL genotype (ie, 15 versus 16.5 years of age; p<0.045). Males in the SS+SL group also had greater odds of high lifetime exposure to cannabis, compared to the LL group (p<0.045). Of interest, none of the aforementioned genetic associations were significant in females. Conclusion: This study provides the first data on how the PDYN 68 bp genotype is associated with gender-specific patterns of exposure to cannabis. Overall, this study shows that PDYN 68 bp polymorphisms affect behaviors involved in early stages of nonmedical cannabis use and potentially lead to increasing self-exposure. These data may eventually lead to improvements in personalized medicine for the prevention and treatment of highly prevalent CUDs and neuropsychiatric comorbidities.