GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal influence of schizophrenia

Abstract

Cannabis use is a heritable trait that has been associated with adverse mental health outcomes. In the largest genome-wide association study (GWAS) for lifetime cannabis use to date (N = 184,765), we identified eight genome-wide significant independent single nucleotide polymorphisms in six regions. All measured genetic variants combined explained 11% of the variance. Gene-based tests revealed 35 significant genes in 16 regions, and S-PrediXcan analyses showed that 21 genes had different expression levels for cannabis users versus nonusers. The strongest finding across the different analyses was CADM2, which has been associated with substance use and risk-taking. Significant genetic correlations were found with 14 of 25 tested substance use and mental health-related traits, including smoking, alcohol use, schizophrenia and risk-taking. Mendelian randomization analysis showed evidence for a causal positive influence of schizophrenia risk on cannabis use. Overall, our study provides new insights into the etiology of cannabis use and its relation with mental health.

Figure 1.

a) QQ-plot of the distribution of the −log ₁₀(p-values) observed for the SNP associations with lifetime cannabis use against those expected under the null hypothesis Expected −log ₁₀(p-values) under the null hypothesis are indicated by the red line. Genomic inflation is indicated with λ in the plot. There was no evidence for population stratification (LD score regression b₀=1.00, SE=0.007). b) Manhattan plot for the SNP-based GWAS meta-analysis Results are based on N=184,764 individuals and N_SNPs=11,733,371 SNPs. The SNP with the lowest p-value per independent (R²<0.1, window size 250 kb) genome-wide significant locus is annotated (red circle with rs-number). The red line represents the conventional genome-wide significance threshold of p<5e-08. The statistical test comprised linear regression; significance was tested two-sided.

Figure 2.. Regional plots of the genome-wide significant SNPs

Underlined in yellow are the genes that were significant in the gene-based test (tested two-sided; p<2.74e-06, Bonferroni corrected p-value threshold of p<0.05 adjusted for 18,293 tests); underlined in green the genes that were identified in the S-PrediXcan analysis only (p<1.92e-07, Bonferroni corrected p-value threshold of p<0.05 adjusted for 259,825 tests). Colors of the dots indicate the level of LD (blue for low and red for high LD) with the lead SNP (purple; independent defined as R²<0.1, window size 250 kb).

Figure 3.

a) QQ-plot of the distribution of the −log₁₀(p-values) for the gene-based association with lifetime cannabis use against those expected under the null hypothesis Expected −log ₁₀(p-values) under the null hypothesis are indicated by the red line. Genomic inflation is indicated with λ. The gene-based test was performed in MAGMA, which uses multiple regression (tested two-sided). b) Manhattan plot for the gene-based test of association The red line represents the genome-wide significance threshold of p<2.74e-06, (Bonferroni corrected p-value threshold of p<0.05 adjusted for 18,293 tests; N_SNPs=5,710,956 were mapped to at least one gene). The top-gene (with the lowest p-value) per locus is annotated (red circle with gene symbol).

Figure 4.. Genetic overlap between lifetime cannabis use and other phenotypes

Blue dots represent point estimates of the genetic correlation, blue error bars represent 95% confidence intervals and red asterisks indicate significant associations after correction for multiple testing (two-sided p<0.002, Bonferroni corrected p-value threshold of p<0.05 adjusted for 25 tests). MDD=Major Depressive Disorder; ADHD=Attention Deficit Hyperactivity Disorder; BMI=Body Mass Index