The genetic etiology of cannabis use: from twin models to genome-wide association studies and beyond

Background

It is known that of individual differences in cannabis use phenotypes can be explained by genetic differences between people.  In this talk I will give a broad overview of what we know about the genetics of cannabis use, covering twin studies, early gene-finding studies, and the more recent genome-wide association studies (GWASs; including results of our new, unpublished GWAS on frequency of cannabis use). Not only will I explain the insights these methods have provided on the genetic etiology of cannabis use, but also on how they have helped to clarify the relationship between cannabis use and co-occurring traits, such as the use of other substances and mental health disorders.

Methods

First, I will review twin studies that estimated the heritability, as well gene-finding studies, including candidate gene and genome-wide association studies. In addition, I will discuss studies that applied multivariate genetics methods (e.g. polygenic score analyses, genetic correlations, Mendelian Randomization) investigating how cannabis clusters with and predicts other traits. Second, I will present unpublished results from the latest GWAS of the International Cannabis Consortium focussed on frequency of cannabis use. This study meta-analysed GWASs in 19 different cohorts (N>150,000). Association results will be used for several follow-up analyses: gene-based tests of association, SNP-based heritability analysis, and genetic correlations with a broad range of cognitive, socio-economic, mental health, personality, and substance use traits. With Mendelian Randomization the causal associations between cannabis use and key mental health outcomes will be investigated, elucidating to what extent observed associations could be due to direct causal effects

Results

Twin studies show that cannabis use is moderately heritable, with higher heritability estimates for more severe phases of use. Linkage and candidate-gene studies have been largely unsuccessful, while GWASs so far only explain a small portion of the heritability. Dozens of genetic variants predictive of cannabis use have been identified in genes such as CADM2, FOXP2, and CHRNA2, which have previously been implicated in educational attainment, BMI, and smoking. Multivariate genetics analyses indicate that there is considerable genetic overlap between cannabis use and other traits (especially other substances and externalising disorders) and some evidence for causal relationships. 

The new GWAS of frequency of use provides more fine-grained insight into which genes are important for which aspects of cannabis use behavior, and shows frequent use is associated with adverse health outcomes . 

Conclusion

Technical and methodological advances in genetics have increased our understanding of the genetic aetiology of cannabis use as well as the association between cannabis use and other traits. Implications of findings and suggestions for future work will be discussed.