How genes may distinguish cannabis use from addiction

Since cannabis use (CU) has increased substantially worldwide, understanding the neurobiological mechanisms differentiating CU from cannabis use disorder (CUD) has important public health implications. Leveraging genome-wide data available from UK Biobank, International Cannabis Consortium, the Psychiatric Genomics Consortium, and the Million Veteran Program, we characterized the pleiotropy differentially linking brain structural and functional variation to CU and CUD. Specifically, we conducted linkage disequilibrium score regression, local analysis of [co]variant association, and latent causal variable analysis. Distinct patterns of global genetic correlations were observed, where CU was specifically related to default mode network-related functional activity and the functional connectivity between default mode and central executive networks, while CUD was related to functional connectivity linking default mode and salience networks and with white matter microstructure. Latent causal variable analyses suggested partial genetic causality differentially linking the functional connectivity among salience, default mode, and central executive networks to CU and CUD. Local genetic correlation analyses further identified CU and CUD-specific shared genetic architecture with brain variation related to genes involved in neurodevelopment, chromatin regulation, synaptic signaling, and white matter biology. Through gene-set enrichment analyses, we identified pathways related to brain variation converging on inflammatory response and cell activation for CU, and on cellular stress-response and immune regulation for CUD. Applying gene2drug framework, our drug-repurposing analyses identified nine molecular compounds, also including raloxifene (a cannabinoid-receptor 2 inverse agonist) and albendazole (reported to interact with cannabis smoking). Overall, these findings provide new insights into the neurobiological pathways underlying CU and its progression to CUD.