Abstract
Background Cannabis is the most widely used illicit drug in the world. Cannabis Use Disorder (CUD) is associated with adverse consequences, including psychiatric symptoms, cognitive decline, anxiety disorder and poor quality of life. 35–40% of adults in Denmark and the United States are reported with life-time use of cannabis. The prevalence of diagnosed CUD in Europeans and Americans is estimated to 1–1.5% and the heritability of CUD is estimated to 51–70%. With respect to the amount of risk explained by common variants, the SNP heritability has been estimated to 0.06–0.2. The difference between total heritability and SNP heritability suggests that rare variants might contribute to the risk of CUD, which require sequencing to find them. Methods We performed whole-exome sequencing of ~7,366 Danish individuals identified in the Danish Newborn Screening Biobank (DNSB), including 1,236 affected with CUD, and ~6,100 unaffected controls. We aligned exome sequence data against GRCh37 human genome reference with bwa and identified variants using GATK. We performed quality control of variants and individuals (including principal component analysis for exclusion of non-Europeans), annotated variants with respect to gene, functional impact and presence in the ExAC non-psych database using Hail. Subsequently various burden tests were performed. Results Here we will present results from analysis of the impact of Ultra-Rare Variants (URVs) in CUD. We will especially focus on the burden of these variants in CUD cases compared to controls in highly evolutionary constrained genes as well as specific gene-sets relevant to CUD. Furthermore, we will assess whether CUD risk genes identified based on the common variant analysis also carry an increased burden of URVs. In addition, we will conduct gene-based association analysis to identify top-ranking genes most frequently hit by rare deleterious variants in CUD cases compared with controls. Discussion We will discuss our comprehensive analyses of the role of URVs in CUD, which will further contribute to the understanding of the genetic architecture underlying the disorder, and help elucidating relevant biological mechanism contributing to disease risk.
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