Abstract Cannabis use is widespread, with genetic differences partly explaining variation in individual patterns of use. We performed the largest-to-date genome-wide association study (GWAS) meta-analysis of cannabis ever-use (N=736,322, 76% European ancestry) and various measures of frequency of use (N=269,160 cannabis users, 84% European ancestry). We identified 54 independent genome-wide significant loci for ever-use and 6 for frequency and show that the genetic architecture of ever-use, frequency, and cannabis use disorder (CUD) are overlapping but distinguishable. We identified 63 loci that were associated with common liability (‘ All-cannabis ’) to different cannabis use traits in European-ancestry individuals. Across analyses, we identified 75 unique loci that had not previously been implicated in cannabis use. Gene prioritization analyses identified 349 genes for ever-use, 5 genes for frequency of use, and 429 for All-cannabis , including previously identified and novel genes. We found enrichment of genetic signals for cannabis use in biologically meaningful categories and relevant human brain cell types, including excitatory neuronal populations. There were substantial genetic correlations between cannabis use and a range of psychiatric disorders and substance use traits, while cannabis polygenic scores were associated with increased risk of psychiatric disorders. Mendelian Randomization showed evidence for (bidirectional) causal associations between cannabis use and ADHD, bipolar disorder, schizophrenia and PTSD.

Despite extensive research on DNA methylation (DNAm) signatures associated with alcohol use disorder (AUD), findings are often inconsistent and not replicated. We conducted a large-scale meta-analysis of epigenome-wide association studies (EWAS) to identify reliable, reproducible epigenetic markers of AUD. Seven cohorts, comprising 3,775 individuals (1,325 with AUD), contributed to this meta-analysis within the framework of the Psychiatric Genomics Consortium Substance Use Disorders Epigenetics Working Group. Downstream analyses included the identification of differentially methylated regions, overrepresentation analyses, and the construction of a methylation risk score (MRS). We identified 118 significant CpG sites associated with AUD, with the strongest association found at cg24889777 ( p =5.12×10 -17 ) in the long non-coding RNA LOC100505942. CpG sites were enriched for pathways related to GTPase signaling and transmembrane transporter activity, as well as EWAS signals of alcohol consumption. The MRS explained 10.44% of variance in heavy drinking in an independent cohort (N=2,534, AUC=0.657). This large-scale meta-analysis offers key insights into the epigenetic mechanisms of AUD and lays the groundwork for future research on methylation risk scores for the diagnosis, prognosis, and treatment in AUD.

Human genetic studies of smoking behavior have been thus far largely limited to common variants. Studying rare coding variants has the potential to identify drug targets. We performed an exome-wide association study of smoking phenotypes in up to 749,459 individuals and discovered a protective association in CHRNB2 , encoding the β2 subunit of the α4β2 nicotine acetylcholine receptor. Rare predicted loss-of-function and likely deleterious missense variants in CHRNB2 in aggregate were associated with a 35% decreased odds for smoking heavily (odds ratio (OR) = 0.65, confidence interval (CI) = 0.56–0.76, P = 1.9 × 10 −8 ). An independent common variant association in the protective direction ( rs2072659 ; OR = 0.96; CI = 0.94–0.98; P = 5.3 × 10 −6 ) was also evident, suggesting an allelic series. Our findings in humans align with decades-old experimental observations in mice that β2 loss abolishes nicotine-mediated neuronal responses and attenuates nicotine self-administration. Our genetic discovery will inspire future drug designs targeting CHRNB2 in the brain for the treatment of nicotine addiction.

Alcohol and tobacco are the most commonly used addictive substances, with high comorbidity rates between alcohol use disorder and tobacco use disorder. Risk for alcohol and nicotine addiction is highly heritable, and they share common genetic factors. A GWAS in over 1 million individuals has revealed 566 genetic variants in 406 loci associated with multiple stages of alcohol and tobacco use. Three novel genes-SLC39A8, GRK4 and HGFAC-within loci associated with altered alcoholic drinks per week (ADW) or cigarettes per day (CPD) were selected to further study their role in alcohol and tobacco use disorder. The role of these genes was assessed using the two-bottle choice addiction paradigm in transgenic mice for each of the genes. We found significant decreases in chronic alcohol consumption and preference in female Hgfac knockout (KO) mice, and decreased nicotine preference in male Hgfac KO compared with wild-type (WT) mice. Additionally, male Slc39a8 hypomorph mice showed greater overall nicotine preference compared with WT mice, while no differences were detected for Grk4 KO mice in alcohol or nicotine consumption and preference in either sex. Thus, this study implicates Hgfac and Slc39a8 in alcohol and tobacco use in a sex-specific manner.

Background: Prior studies have established the importance of genetic contributions to the etiology of alcohol dependence (AD), and suggested an early onset of alcohol use represents an initial marker of this genetic risk, which is associated with a more rapid progression to AD and increased risk for AD itself. Building on prior work, the current study examined whether the additive effects of AD risk variants predicted the rate of progression to AD from the onset of regular drinking, a drinking milestone with high clinical relevance to AD prevention. Methods: Data from 1501 European-ancestry adults from the University of California - San Francisco Family Alcoholism Study were used to examine whether polygenic risk scores for AD (PRSAD) and age-at-onset of regular drinking contributed uniquely to the likelihood of having a lifetime AD diagnosis and the rate of progression from regular drinking to AD. Mixed effects logistic regression and Cox proportional hazards regression analyses were employed. Results: Increases in PRSAD were associated with a faster progression from regular drinking to AD independent of age-at-onset of regular drinking. An independent effect of age-at-onset of regular drinking was also observed indicating that a one-year delay in regular drinking was associated with a 7% decrease in the hazard of progression to AD among drinkers with an early onset (<= 18), but a 3% increase among drinkers with a late onset (> 18) of regular drinking. Conclusions: These results broaden our understanding of the contributions of measured genotypes underlying ADrisk on the etiology and clinical course of AD.

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury 1 – 4 . These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries 5 . Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

Background and Aims Smoking is a leading cause of premature death. Although genome-wide association studies have identified many loci that influence smoking behaviors, much of the genetic variance in these traits remains unexplained. We sought to characterize the genetic architecture of four smoking behaviors through SNP-based heritability ( h 2 SNP ) analyses. Design We applied recently-developed partitioned h 2 SNP approaches to smoking behavior traits assessed in the UK Biobank. Setting UK Biobank. Participants UK Biobank participants of European ancestry. The number of participants varied depending on the trait, from 54,792 to 323,068. Measurements Smoking initiation, age of initiation, cigarettes per day (CPD; count, log-transformed, binned, and dichotomized into heavy versus light), and smoking cessation. Imputed genome-wide SNPs. Findings We estimated h 2 SNP (SE)=0.18(0.01) for smoking initiation and 0.12(0.02) for smoking cessation, which were more than twice the previously reported estimates. Estimated age of initiation h 2 SNP =0.05(0.01) and binned CPD h 2 SNP =0.1(0.01) were similar to previous reports. These estimates remained substantially below published twin-based h 2 of roughly 50%. CPD encoding strongly influenced estimates, with dichotomized CPD h 2 SNP =0.28. We found significant contributions of low-frequency variants and variants in low linkage-disequilibrium (LD) with surrounding genomic regions. Functional annotations related to LD, allele frequency, sequence conservation, and selective constraint also contributed significantly to the partitioned heritability. We found no evidence of dominance genetic variance for any trait. Conclusion h 2 SNP of these four specific smoking behaviors is modest overall. The patterns of partitioned h 2 SNP for these highly polygenic traits is consistent with negative selection. We found a predominant contribution of common variants, and our results suggest a role of low-frequency or rare variants, poorly tagged by surrounding regions. Deep sequencing of large samples and/or improved imputation will be required to fully assess the role of rare variants.

Background. Substance use is associated with significant public health and economic consequences and a rich literature exists on the development of substance use. However, no systematic review has attempted to synthesize this literature across alcohol, nicotine, and cannabis, nor attempted to characterize the wide variety of samples and methodology employed in modeling change in use over time. Methods. We conducted a systematic literature review to evaluate the samples, measures, and analytical approaches in publications reporting random effects or mixture modeling in longitudinal substance use across the lifespan. Results. Across 317 included publications, the mean number of assessment waves was 5.5 (range=2-52), spanning an average of 7.3 years from baseline (range=1-38). Almost all publications included some coverage between ages 14-30, few studied mid-adulthood or older age. Most publications (72%) evaluated only one substance and 14% of publications evaluated all three. The average number of classes found via mixture modeling was four (range=2-12). Continuous random effects models of change primarily returned linear or quadratic solutions as best fitting. We found no significant differences between substances for number of classes (hybrid p=.50, class p=.13), nor curve shape identified (curve p=.98, hybrid p=.95).Discussion. No one statistical method was predominant in the literature, nor was there evidence of growing consensus on preferred model as a function of publication date. Studies of middle and older age were largely absent from the literature. We offer recommendations in reporting to assist in the replication, extension, and interpretation of this body of work.

Individuals with schizophrenia have higher lifetime rates of substance use disorders than the general population, and research suggests high comorbidity rates may be partially explained by shared genetic influences related to common underlying etiology. Moreover, deficits in executive functions are thought to be central to the diagnosis of schizophrenia and are likewise associated with alcohol and tobacco use. The current study examined the associations between schizophrenia polygenic risk scores and tobacco and alcohol use and the mediation of these associations by executive function sub-domains. Results from the Psychiatric Genomics Consortium's meta-analysis of genome-wide association studies of schizophrenia were used to calculate polygenic risk scores in a sample of moderate drinkers. Schizophrenia risk scores were significantly associated with shifting-specific executive function deficits and tobacco use phenotypes. However, risk scores were not significantly associated with alcohol use and executive functions were not significantly associated with either tobacco or alcohol use. These findings extend previous research by suggesting that genetic risk for schizophrenia may be associated with specific sub-domains of executive function as well as smoking. The lack of a relation with alcohol use suggests genetic factors related to schizophrenia and executive functioning may not influence drinking in a non-disordered, social-drinking sample.

Objective: Epidemiological estimates suggest that nearly half of individuals diagnosed with alcohol use disorder will be diagnosed with another mental health disorder, with strong associations involving other externalizing disorders. Molecular genetic studies investigating the relation between alcohol use disorder and externalizing behaviors (e.g., antisocial behavior) have focused on a cluster of chromosome 4 γ-aminobutyric acid (GABA) receptor genes (GABRG1-A2-A4-B1) but have generated varying results. Method: The current study examined associations between common and rare variation in this region with alcohol use disorder and antisocial behavior using genetic sequencing data. Specifically, the University of California at San Francisco Family Alcoholism Sample (n = 1,610; 62% female) was used to conduct common and rare variant association tests in the GABRG1-A2-A4-B1 cluster with DSM-5 alcohol use disorder symptom counts, antisocial behavior, and a product term representing their interaction. Results: Gene-based analyses of rare variation resulted in a significant association between rare GABRA2 variation and the interaction term. Single-variant analysis yielded only nominally significant associations. The strongest association for alcohol use disorder (rs3756007) was located in GABRA2, the strongest association for antisocial behavior (rs11941860) was located in GABRG1, and the interaction term yielded top associations in GABRA2 (rs2119183) and the intergenic region between GABRA2 and GABRG1 (rs536599). Common and rare variant associations for the interaction remained similar when covarying for the effects of the other type of variation, suggesting that the significant rare variant signal is independent of common variant contributions. Conclusions: The present study suggests that both rare and common variant associations in GABRA2 confer risk for alcohol use disorder and antisocial behaviors, indicating a potential liability toward externalizing behavior more broadly.

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Alcohol and tobacco use and dependence are known to be influenced by the effects of common variants enriched in non-coding gene regulatory regions, as well as rare protein-coding variation. In contrast, the role of rare non-coding regulatory variation is unknown. Epigenetic factors such as DNA methylation also influence gene expression, and some of these effects are under genomic control. The current study investigated the effects of rare coding and non-coding variation in regions susceptible to DNA methylation, and whether differential levels of methylation mediated their effects in association with alcohol and tobacco use and dependence. Data from whole-genome sequencing and DNA methylation microarrays for participants in the UCSF Family Alcoholism Study (N = 1,852) were used for set-based tests of rare variation, region-based differential methylation, and epigenetic mediation in relation to quantitative measures of alcohol and tobacco use and DSM-IV dependence diagnoses. Rare variants in exonic and intronic regions, as well as CpG islands, were weighted by a measure of deleteriousness and were significantly associated with alcohol and tobacco use phenotypes. Similarly, differential levels of DNA methylation exhibited significant association with lifetime and current measures of use and dependence. However, there was a relative lack of evidence for epigenetic mediation of rare variation, likely due to a lack of power. Findings from the current study suggest that rare regulatory DNA sequence variation and differential levels of DNA methylation influence risk for alcohol and tobacco use, but whether there exists epigenetic mediation of rare variation requires larger sample sizes in future studies.