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BACKGROUND AND AIMS: Cannabis is one of the most commonly used substances among adolescents and young adults. Earlier age at cannabis initiation is linked to adverse life outcomes including multi-substance use and dependence. This study estimated the heritability of age at first cannabis use and identify associations with genetic variants.METHODS: A twin-based heritability analysis using 8,055 twins from three cohorts was performed. We then carried-out a genome wide survival meta-analysis of age at first cannabis use in a discovery sample of 24,953 individuals from nine European, North American, and Australian cohorts, and a replication sample of 3,735 individuals.RESULTS: The twin-based heritability for age at first cannabis use was 38% (95% confidence interval [CI] 19-60%). Shared and unique environmental factors explained 39% (95% CI 20-56%) and 22% (95% CI 16-29%). The genome wide survival meta-analysis identified five SNPs on chromosome 16 within the Calcium-transporting ATPase gene (ATP2C2) at P < 5E-08. All five SNPs are in high LD (r2 >0.8) with the strongest association at the intronic variant rs1574587 (P=4.09E-09). Gene-based tests of association identified the ATP2C2 gene on 16q24.1 (P=1.33e-06). Although the five SNPs and ATP2C2 did not replicate, ATP2C2 has been associated with cocaine dependence in a previous study. ATP2B2, which is a member of the same calcium signalling pathway, has been previously associated with opioid dependence. SNP-based heritability for age at first cannabis use was non-significant.CONCLUSION: Age at cannabis initiation appears to be moderately heritable in Western countries, and individual differences in onset can be explained by separate but correlated genetic liabilities. The significant association between age of initiation and ATP2C2 is consistent with the role of calcium signalling mechanisms in substance use disorders.

Cannabis is the most frequently used illicit psychoactive substance worldwide; around one in ten users become dependent. The risk for cannabis use disorder (CUD) has a strong genetic component, with twin heritability estimates ranging from 51 to 70%. Here we performed a genome-wide association study of CUD in 2,387 cases and 48,985 controls, followed by replication in 5,501 cases and 301,041 controls. We report a genome-wide significant risk locus for CUD (P = 9.31 × 10−12) that replicates in an independent population (Preplication = 3.27 × 10−3, Pmeta-analysis = 9.09 × 10−12). The index variant (rs56372821) is a strong expression quantitative trait locus for cholinergic receptor nicotinic α2 subunit (CHRNA2); analyses of the genetically regulated gene expression identified a significant association of CHRNA2 expression with CUD in brain tissue. At the polygenic level, analyses revealed a significant decrease in the risk of CUD with increased load of variants associated with cognitive performance. The results provide biological insights and inform on the genetic architecture of CUD. The study reports a genome-wide significant locus for cannabis use disorder, replicating in an independent cohort, and implicates CHRNA2, which encodes an acetylcholine receptor subunit, in the disorder by analyses of genetically regulated gene expression.

Background and aims: Cannabis is one of the most commonly used substances among adolescents and young adults. Earlier age at cannabis initiation is linked to adverse life outcomes, including multi-substance use and dependence. This study estimated the heritability of age at first cannabis use and identified associations with genetic variants. Methods: A twin-based heritability analysis using 8055 twins from three cohorts was performed. We then carried out a genome-wide association meta-analysis of age at first cannabis use in a discovery sample of 24 953 individuals from nine European, North American and Australian cohorts, and a replication sample of 3735 individuals. Results: The twin-based heritability for age at first cannabis use was 38% [95% confidence interval (CI) = 19–60%]. Shared and unique environmental factors explained 39% (95% CI = 20–56%) and 22% (95% CI = 16–29%). The genome-wide association meta-analysis identified five single nucleotide polymorphisms (SNPs) on chromosome 16 within the calcium-transporting ATPase gene (ATP2C2) at P 2 > 0.8), with the strongest association at the intronic variant rs1574587 (P = 4.09E-09). Gene-based tests of association identified the ATP2C2 gene on 16q24.1 (P = 1.33e-06). Although the five SNPs and ATP2C2 did not replicate, ATP2C2 has been associated with cocaine dependence in a previous study. ATP2B2, which is a member of the same calcium signalling pathway, has been associated previously with opioid dependence. SNP-based heritability for age at first cannabis use was non-significant. Conclusion: Age at cannabis initiation appears to be moderately heritable in western countries, and individual differences in onset can be explained by separate but correlated genetic liabilities. The significant association between age of initiation and ATP2C2 is consistent with the role of calcium signalling mechanisms in substance use disorders.

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 sub-stance 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.

The role of adolescents’ peer relationships in their use of alcohol has been of long-standing scientific interest. This work is driven by a well-established and still growing list of risks of excessive alcohol use for this population, for example, increased risk of depression, suicide, and other problems during adolescence (Reifman & Windle, 1995; Windle, Miller-Tutzauer, & Domenico, 1992), as well as risk for heavier drinking and alcohol dependence (Grant et al., 2006; Guttmannova et al., 2011) and cognitive impairment reaching into adulthood (Hanson, Medina, Padula, Tapert, & Brown, 2011; Sher, 2006). Adolescents who drink alcohol typically do so with similar-age friends, leading to ubiquitously observed drinking clusters (Bauman & Ennett, 1994). A number of increasingly sophisticated study designs and analyses have addressed the dynamics that form these clusters in natural settings (Ary, Tildesley, Hops, & Andrews, 1993; Kandel, 1978; Steglich, Snijders, & West, 2006; Urberg, Luo, Pilgrim, & Degirmencioglu, 2003). However, the role of peers in “onset to drinking”—defined here as the transition from no experience with drinking alcohol to having a “first full drink” (e.g., Guttmannova et al., 2011; McGue, Iacono, Legrand, & Elkins, 2006)—has received little attention, even though early onset is considered a major risk for later alcohol-related problems and dependence. In this study, we apply a stochastic actor-based model (SABM; Snijders, van de Bunt, & Steglich, 2010) of dynamic social network evolution to link early adolescents’ drinking onset to exposure to best friends who have already begun drinking. We use the term exposure instead of the more typical influence (or socialization) terminology, because it can apply to a range of mechanisms that may put youth at greater risk of onset if they have drinking friends, including, for instance, social reinforcement of attitudes, modeling, norms, and logistical and informational facilitation (Aral, 2011), not all of which are influence in the usual sense. Our study utilizes and illustrates a novel variant of the SABM that combines the conditional Markov model for network evolution first proposed by Snijders (2001) with a proportional hazard rate model for alcohol onset (Cox, 1972; Greenan, 2013). Hazard models are commonly used to evaluate risk factors for time to an event (Yamaguchi, 1991). Network evolution and alcohol onset are modeled jointly, in order to separate selection and exposure effects on drinking clusters. This approach also differs from previous models of joint network and behavioral evolution (Steglich, Snijders, & Pearson, 2010) in its focus on predictors of relative risk for initiating drinking, rather than simply whether (or how much) drinking takes place, regardless of whether it is an onset event. Early Onset to Drinking Many studies have reported a relationship between early age of onset and risk for later alcohol dependence (Chou & Pickering, 1992; Grant & Dawson, 1997; Guttmannova et al., 2011), suicidal behavior (Cho, Hallfors, & Iritani, 2007; Swahn, Bossarte, & Sullivent, 2008), and other problems (Hingson, Heeren, Jamanka, & Howland, 2000). Although there is evidence that after drinking is initiated, risk for additional problems is fundamentally genetic (McGue et al., 2006; Pagan et al., 2006; Prescott & Kendler, 1999), one must nevertheless begin drinking before such risk becomes relevant. Genetically informative studies have also found that risk of earlier onset is largely environmentally determined (Kendler, Schmitt, Aggen, & Prescott, 2008; Pagan et al., 2006), which could include exposure to drinking peers and lack of parental and other adult supervision. Peers and Onset to Drinking The theoretical case for peer drinking affecting onset is somewhat mixed. Although early adolescence is a time when peer relationships become especially important (Gardner & Steinberg, 2005), there is also evidence that middle to older adolescents perceive more peer pressure to drink (Steinberg & Monahan, 2007), perhaps because drinking does not become widespread in adolescent populations until then (Burk, van der Vorst, Kerr, & Stattin, 2012). Very few studies have examined the issue empirically. Jessor and Jessor (1975) found an association between friends’ drinking and onset to drinking among young adolescents, and Trucco and colleagues (2011) found a distinct peer exposure effect on onset while controlling for selection. Both studies measured friends’ drinking behavior by participant reports. Peers and Amount of Drinking A much larger literature has addressed peer exposure effects for alcohol quantity or frequency. Drinking is deviant only in relation to age but it is an attractive adult-like activity for many adolescents (Jessor & Jessor, 1977); it is associated with socializing and being accepted (Veenstra, Huitsing, Dijkstra, & Lindenberg, 2010), and perhaps for this reason, is typical among high-status youth (Allen, Chango, Szwedo, Schad, & Marston, 2012). This dynamic motivates both selection and influence effects in teen drinking. Three recent studies of adolescent drinking (Burk et al., 2012; Knecht, Burk, Weesie, & Steglich, 2011; Mercken, Steglich, Knibbe, & de Vries, 2012) provide a particularly relevant empirical context for our work. Each addressed alcohol use among early adolescent youth, employed a multiwave longitudinal design with complete-network friendship (all pairwise relationships) and behavioral data, and applied SABM. Results showed some similarities but important differences as well. Burk and colleagues (2012) compared selection and exposure effects associated with changes in drinking behavior for three age cohorts, addressing variation in exposure effects at different ages. They found that peer drinking clusters are mainly explained by selection effects up to about age 15, but exposure effects become important in midadolescence. In contrast, Mercken and colleagues (2012) found evidence of exposure effects at younger ages (ages 13–14) but not for older youth (ages 14–16), whereas alcohol-related selection appeared stronger for the older youth, although the alcohol selection effect approached significance for the youngest ages. Finally, Knecht et al. 2011 found drinking-related selection and a trend effect of exposure to drinking peers (ages predominantly 11–13). Note that none of these studies separated onset from subsequent drinking. In fact, conflating the two has been typical in empirical studies of peers and adolescent drinking, even though many theoretical treatments explicitly discuss onset as a distinct and salient phenomenon (Dodge et al., 2009; Petraitis, Flay, & Miller, 1995). Thus, it is possible that the selection and exposure effects reported have to do with onset only, subsequent drinking only, or both. In contrast, our analysis is limited to onset alone. The previous discussion suggests hypotheses concerning the role peer affiliations play in onset to drinking. Although our discussion so far has focused on exposure effects, selection is important also, as relationships must be created before they can affect subsequent drinking. H1. Same drinking onset status predicts friendship selection. H2. Exposure to already-drinking peers increases the risk for onset in nondrinking early adolescents. Gender, Grade, and Adult Monitoring Gender has not typically been found to moderate selection or exposure effects for alcohol use (cf. Burk et al., 2012), but it may for onset, as the hypothesized greater importance of close friendships to girls (Schulenberg et al., 1999) may be more important than the greater susceptibility to drinking sometimes found for boys (Anderson, Tomlinson, Robinson, & Brown, 2011; Windle, 2000). H3. Same alcohol onset status is a more important source of selection preference for girls compared to boys. H4. Exposure to already-drinking peers affects girls’ rate of onset more than boys. If, indeed, drinking becomes an increasingly important peer-related activity as youth progress through early adolescence (Burk et al., 2012), onset may play an increasing role as both a reason for friendship selection and an element of peer exposure. Even though Mercken et al. (2012) did not find an age effect in an early adolescent sample, the theoretical case is plausible for alcohol onset. Earlier onset may index environmental risks for early problem behavior; in contrast, drinking in older youth is much more normative and is associated with popularity (Allen et al., 2012; Burk et al., 2012). H5. Effects of exposure to drinking peers will be stronger at higher grades. H6. Selection preference for same drinking status will increase by grade. Besides peers, parents and other relevant adults are the most likely source of behavioral influence for early adolescent youth (Veronneau & Dishion, 2011). Previous studies have identified lack of monitoring and supervision as a key component of risk for substance use among adolescents (Dishion, Nelson, & Kavanagh, 2003; Ryan, Jorm, & Lubman, 2010), which may be a result of failure by parents to supervise peer affiliations (Dodge et al., 2009). Vitaro, Brendgen, and Tremblay (2000) found that, although parental monitoring had a direct effect on problem behavior, it did not moderate associations with exposure to problem-behaving peers. However, Veronneau and Dishion (2011) found that parental monitoring buffered risks for problem behavior associated with peer relationship difficulties. Because both opportunities to drink and perceived acceptability of drinking could be affected by supervision, more monitoring may delay onset. H7. Adult monitoring predicts delayed alcohol onset. H8. Adult monitoring interacts negatively with exposure to drinking peers in predicting alcohol onset.