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Study reveals specific cannabis dependence risk alleles

Recent findings identified specific cannabis dependence risk alleles and potential genetic factors contributing to major depression and schizophrenia comorbidity of cannabis dependence.

To assess potential genetic risk factors for DSM-IV cannabis dependence, Richard Sherva, PhD, of Boston University School of Medicine, and colleagues conducted a genome-wide association study in three independent substance dependence cohorts. Study participants (n = 14,754) had a mean age of 39.2 years. Data were collected from 2000 to 2013 for the Yale-Penn Study, from 1990 to 2007 for the Study of Addiction: Genetics and Environment, and from 2004 to 2009 for the International Consortium on the Genetics of Heroin Dependence.

Researchers found three independent regions with genome-wide significant single-nucleotide polymorphism associations. They included rs143244591 in novel antisense transcript RP11-206M11.7; rs146091982 in the solute carrier family 35 member G1 gene (SLC35G1); and rs77378271 in the CUB and Sushi multiple domains 1 gene (CSMD1).

There was evidence of genome-level pleiotropy between cannabis dependence and major depressive disorder and an association between single-nucleotide polymorphisms in genes associated with schizophrenia risk.

Several identified genes have functions related to neuronal calcium homeostasis or central nervous system development, according to researchers.

“The study by Sherva and colleagues describes in its title the shared genetic risk between schizophrenia and cannabis dependence severity. It seems that this evidence is limited to the observation that different [single-nucleotide polymorphisms] in the same gene (CSMD1) are implicated in both disorders,” James T. R. Walters, MRCPsych, PhD, and Michael J. Owen, FRCPsych, PhD, of Cardiff University, Wales, wrote in an accompanying editorial. “Given the unknown functional effects of the associated variants, the significance of this finding is uncertain, although it does highlight the potential value of identifying shared genetic risk variants between related disorders. In the current context, one of the main advantages of identifying such variants would be the application of mendelian randomization, a genetic epidemiological approach that can examine causal relationships between variables. Replicated evidence implicating risk variants associated with relevant outcomes is required to execute such studies.”– by Amanda Oldt

Disclosure: Sherva reports no relevant financial disclosures. Please see the full study for a list of all authors’ relevant financial disclosures.