Multi-ancestry genome-wide association study of cannabis use disorder yields insight into disease biology and public health implications.

As recreational use of cannabis is being decriminalized in many places and medical use widely sanctioned, there are growing concerns about increases in cannabis use disorder (CanUD), which is associated with numerous medical comorbidities. Here we performed a genome-wide association study of CanUD in the Million Veteran Program (MVP), followed by meta-analysis in 1,054,365 individuals (ncases = 64,314) from four broad ancestries designated by the reference panel used for assignment (European n = 886,025, African n = 123,208, admixed American n = 38,289 and East Asian n = 6,843). Population-specific methods were applied to calculate single nucleotide polymorphism-based heritability within each ancestry. Statistically significant single nucleotide polymorphism-based heritability for CanUD was observed in all but the smallest population (East Asian). We discovered genome-wide significant loci unique to each ancestry: 22 in European, 2 each in African and East Asian, and 1 in admixed American ancestries. A genetically informed causal relationship analysis indicated a possible effect of genetic liability for CanUD on lung cancer risk, suggesting potential unanticipated future medical and psychiatric public health consequences that require further study to disentangle from other known risk factors such as cigarette smoking.

The relationship between cannabis use, schizophrenia, and bipolar disorder: a genetically informed study.

BACKGROUND: The relationship between psychotic disorders and cannabis use is heavily debated. Shared underlying genetic risk is one potential explanation. We investigated the genetic association between psychotic disorders (schizophrenia and bipolar disorder) and cannabis phenotypes (lifetime cannabis use and cannabis use disorder). METHODS: We used genome-wide association summary statistics from individuals with European ancestry from the Psychiatric Genomics Consortium, UK Biobank, and International Cannabis Consortium. We estimated heritability, polygenicity, and discoverability of each phenotype. We performed genome-wide and local genetic correlations. Shared loci were identified and mapped to genes, which were tested for functional enrichment. Shared genetic liabilities to psychotic disorders and cannabis phenotypes were explored using causal analyses and polygenic scores, using the Norwegian Thematically Organized Psychosis cohort. FINDINGS: Psychotic disorders were more heritable than cannabis phenotypes and more polygenic than cannabis use disorder. We observed positive genome-wide genetic correlations between psychotic disorders and cannabis phenotypes (range 0·22-0·35) with a mixture of positive and negative local genetic correlations. Three to 27 shared loci were identified for the psychotic disorder and cannabis phenotype pairs. Enrichment of mapped genes implicated neuronal and olfactory cells as well as drug-gene targets for nicotine, alcohol, and duloxetine. Psychotic disorders showed a causal effect on cannabis phenotypes, and lifetime cannabis use had a causal effect on bipolar disorder. Of 2181 European participants from the Norwegian Thematically Organized Psychosis cohort applied in polygenic risk score analyses, 1060 (48·6%) were females and 1121 (51·4%) were males (mean age 33·1 years [SD 11·8]). 400 participants had bipolar disorder, 697 had schizophrenia, and 1044 were healthy controls. Within this sample, polygenic scores for cannabis phenotypes predicted psychotic disorders independently and improved prediction beyond the polygenic score for the psychotic disorders. INTERPRETATION: A subgroup of individuals might have a high genetic risk of developing a psychotic disorder and using cannabis. This finding supports public health efforts to reduce cannabis use, particularly in individuals at high risk or patients with psychotic disorders. Identified shared loci and their functional implications could facilitate development of novel treatments. FUNDING: US National Institutes of Health, the Research Council Norway, the South-East Regional Health Authority, Stiftelsen Kristian Gerhard Jebsen, EEA-RO-NO-2018-0535, European Union's Horizon 2020 Research and Innovation Programme, the Marie Sklodowska-Curie Actions, and University of Oslo Life Science.

Cannabinoid receptor type 2 gene is associated with comorbidity of schizophrenia and cannabis dependence and fatty acid amide hydrolase gene is associated with cannabis dependence in the Spanish population. / El gen del receptor cannabinoide tipo 2 se asocia con la comorbilidad entre esquizofrenia y dependencia de cannabis y el gen de la enzima amidohidrolasa de ácidos grasos se asocia con la dependencia de cannabis en población española.

The endocannabinoid system has been associated with various psychiatric disorders, such as schizophrenia or addictive disorders. Recent studies have found that some polymorphisms in the cannabinoid receptor type 2 (CNR2), cannabinoid receptor type 1 (CNR1) and fatty acid amide hydrolase (FAAH) genes could play an important role as risk factors in the etiology of these diseases. We analysed different cannabinoid gene polimorphisms from non-substance using patients diagnosed with schizophrenia (n = 379), schizophrenic patients with cannabis use disorders (n = 124), cannabis users who did not have psychoses (n = 71), and 316 controls from various Spanish hospitals and health centres. We found a statistical association between polymorphisms rs35761398 and rs12744386 in the CNR2 gene and comorbidity of schizophrenia and cannabis dependence, as well as an association between loss of heterozygosity (overdominance) for polymorphism rs324420 in the FAAH gene and cannabis dependence in a Spanish population sample. The rs35761398 and rs12744386 polymorphisms in the CNR2 gene are genetic risk factors for schizophrenia in cannabis-dependent subjects. Loss of heterozygosity for polymorphism rs324420 in the FAAH gene is a genetic risk factor for cannabis dependence in this population.

El sistema cannabinoide se ha asociado con varios trastornos psiquiátricos como la esquizofrenia y las adicciones. Diversos estudios han observado que algunos polimorfismos del receptor cannabinoide tipo 2 (CNR2), del receptor cannabinoide tipo 1 (CNR1) y del gen de la enzima amido hidrolasa de ácidos grasos (FAAH) pueden ser factores de riesgo de estos trastornos. Hemos analizado diversos polimorfismos del sistema cannabinoide en pacientes diagnosticados de esquizofrenia sin trastorno por uso de sustancias (n = 379), esquizofrenia con trastorno por uso de cannabis (n = 124), dependientes de cannabis sin psicosis asociada (n = 71) y un grupo de control (316) procedentes de diversos hospitales y centros de asistencia sanitaria españoles. Hemos encontrado una asociación entre los polimorfismos rs35761398 y rs12744386 del CNR2 con la presencia de esquizofrenia y trastorno por uso de cannabis comórbido y una pérdida de heterocigosidad en el polimorfismo rs324420 del gen FAAH con la dependencia de cannabis en población española. Los polimorfismos rs35761398 y rs12744386 en CNR2 son factores de riesgo para esquizofrenia en sujetos dependientes de cannabis. La pérdida de heterocigosidad en el polimorfismo rs324420 en el gen FAAH es un factor de riesgo para la dependencia de cannabis.

Genetic support of a causal relationship between cannabis use and educational attainment: a two-sample Mendelian randomization study of European ancestry.

BACKGROUND AND AIMS: Excessive cannabis use may lead to lower educational attainment. However, this association may be due to confounders and reverse causality. We tested the potential causal relationship between cannabis use disorder (CUD) or life-time cannabis use (LCU) and educational attainment. DESIGN: Bidirectional two-sample Mendelian randomization (MR) study was conducted. Our primary method was inverse-variance weighted (IVW) MR, with a series of sensitivity analyses. Multivariable MR (MVMR) was performed to estimate any direct effect independent of intelligence, smoking initiation or attention deficit hyperactivity disorder (ADHD). SETTING AND PARTICIPANTS: European ancestry individuals. The sample sizes of the genome-wide association study ranged from 55 374 to 632 802 participants. MEASUREMENTS: Genetic variants of CUD, LCU or educational attainment. FINDINGS: Using univariable MR, we found evidence of a potential causal effect of genetic liability to CUD on a lower educational attainment [MR, 95% confidence interval (CI)inverse variance weighted (IVW) = -1.2 month (-1.9 month, -0.5 month); P = 0.0008]. However, we found no evidence of an effect of genetic liability to LCU on educational attainment [MR, 95% CIIVW = 0.5 month (-1.5 month, 2.6 month), P = 0.6032]. Reverse direction analysis suggested that genetic liability to higher educational attainment had a potential causal effect on lower risk of CUD [odds ratio (OR), 95% CIIVW = 0.39 (0.29, 0.52), P = 1.69 × 10-10 ]. We also found evidence of potential causal effect from genetic liability to higher educational attainment to higher risk of LCU [OR, 95% CIIVW = 1.35 (1.11, 1.66), P = 0.0033]. CONCLUSIONS: Genetic liability to cannabis use disorder may lead to lower educational attainment. Genetic liability to higher educational attainment may also lead to higher life-time cannabis use risk and lower cannabis use disorder risk. However, the bidirectional effect between cannabis use disorder and educational attainment may be due to shared risk factors (e.g. attention-deficit hyperactivity disorder).

Transcriptome-wide association study by different approaches reveals candidate causal genes for cannabis use disorder.

Cannabis is one of the most commonly used psychoactive substances, which could induce moderate-severe cannabis use disorders (CUD). Here, a tissue-specific transcriptome-wide association study (TWAS) of CUD was performed by FUSION and S-PrediXcan, utilizing a genome-wide association study (GWAS) dataset of CUD (including 43,380 cases and 141,385 controls of European ancestry) and gene expression reference data from 17 different brain-related and non-brain related tissues, with totally 26 TWAS-associated genes were identified, including CADM2 (P = 2.13 × 10-17), SRR (P = 8.09 × 10-9) and TUFM (P = 1.24 × 10-8). Fine-mapping of causal gene sets (FOCUS) was used to prioritize genes with strong evidence for causality, and SRR, CADM2-AS1, and SH2B1 were prioritized with a posterior probability of 0.973, 0.951, and 0.788, respectively. Furthermore, gene ontology (GO) and pathway enrichment analysis on CUD-associated genes were performed, including cytosol, protein binding, nucleoplasm, metabolic pathways, and herpes simplex virus 1 infection. These findings could provide new insights for understanding the mechanism of CUD.

Association between Polymorphism rs1799732 of DRD2 Dopamine Receptor Gene and Personality Traits among Cannabis Dependency.

Compared to other addictive substances, patients with cannabis addiction are significantly outnumbered by those who report dependence on other, more addictive substances. Unfortunately, most cannabis addiction goes untreated, and among those who choose treatment, the requirements are much higher for adolescents and young adults. THE AIM OF THE STUDY: To examine the relationship of cannabinoid dependency in the genetic context-the association between the rs1799732 polymorphism of the DRD2 gene and psychological traits and anxiety. METHODS: The study group consisted of 515 male volunteers. Of these, 214 patients were diagnosed with cannabis addiction and 301 were non-addicted. Patients were diagnosed with NEO Five-Factor Personality Inventory (NEO-FFI), and State-Trait Anxiety Inventory (STAI) questionnaires. The interactions between personality traits and polymorphisms in the DRD2 rs1799732 gene were investigated in a group of cannabis-addicted patients and non-addicted controls using the real-time PCR method. RESULTS: Compared to the control group, the case group obtained significantly higher scores on the STAI State, STAI Trait, Neuroticism and Openness scales, as well as lower scores on the Extraversion, Agreeableness, and Conscientiousness scales. There was no statistically significant difference between addicts and the control group in the frequency of genotypes, but there was a statistically significant difference between addicts and the control group in the frequency of the DRD2 allele rs179973. The multivariate ANOVA analysis showed a statistically significant influence of the DRD2 rs1799732 genotype on the NEO-FFI agreeableness scale and a statistically significant effect of addiction to cannabinoids or its absence on the NEO-FFI agreeableness scale score. CONCLUSIONS: Studying homogeneous subgroups-as in our study-seems reasonable, particularly when combined with genetic determinants and psychological traits. In multigenic and multifactorial entities, such a strategy has a future.

Influences on the Genetic Relationship Between Cannabis Use and Schizophrenia: The Role of the Externalizing Spectrum.

BACKGROUND AND HYPOTHESIS: The nature of the robust association between cannabis use and schizophrenia remains undetermined. Plausible hypotheses explaining this relationship include the premise that cannabis use causes schizophrenia, increased liability for schizophrenia increases the risk of cannabis use initiation (eg, self-medication), or the bidirectional causal hypothesis where both factors play a role in the development of the other. Alternatively, factors that confound the relationship between schizophrenia and cannabis use may explain their association. Externalizing behaviors are related to both schizophrenia and cannabis use and may influence their relationship. STUDY DESIGN: This study aimed to evaluate whether externalizing behaviors influence the genetic relationship between cannabis use and schizophrenia. We conducted a multivariate genome-wide association analysis of 6 externalizing behaviors in order to construct a genetic latent factor of the externalizing spectrum. Genomic structural equation modeling was used to evaluate the influence of externalizing behaviors on the genetic relationship between cannabis use and schizophrenia. RESULTS: We found that externalizing behaviors partially explained the association between cannabis use and schizophrenia by up to 42%. CONCLUSIONS: This partial explanation of the association by externalizing behaviors suggests that there may be other unidentified confounding factors, alongside a possible direct association between schizophrenia and cannabis use. Future studies should aim to identify further confounding factors to accurately explain the relationship between cannabis use and schizophrenia.

Comorbidity and Coaggregation of Major Depressive Disorder and Bipolar Disorder and Cannabis Use Disorder in a Controlled Family Study.

Importance: Cannabis use disorder (CUD) is increasing in the US. Clarification of the potential mechanisms underlying the comorbidity between mood disorders and CUD may help prevent CUD. Objective: To examine co-occurrence and familial aggregation of CUD and mood disorder subtypes. Design, Setting, and Participants: In this cross-sectional, community-based study in the Washington, DC, metropolitan area, semistructured diagnostic interviews and family history reports assessed lifetime DSM-IV disorders in probands and relatives. Familial aggregation and coaggregation of CUD with mood disorders were estimated via mixed-effects models, adjusting for age, sex, recruitment source, and comorbid mood, anxiety, and other substance use disorders. A total of 586 adult probands (186 with bipolar disorder; 55 with CUD) and 698 first-degree relatives (91 with bipolar disorder; 68 with CUD) were recruited from a community screening of the greater Washington, DC, metropolitan area from May 2004 to August 2020. Inclusion criteria were ability to speak English, and availability and consent to contact at least 2 living first-degree relatives. Main Outcomes and Measures: Lifetime CUD in first-degree relatives. Results: Of 586 probands, 395 (67.4%) were female; among 698 relatives, 437 (62.6%) were female. The mean (SD) age was 47.5 (15.2) years for probands and 49.6 (18.0) years for relatives. In the proband group, 82 participants (14.0%) self-identified as African American or Black, 467 (79.7%) as White, and 37 (6.3%) as American Indian or Alaska Native, Asian, more than one race, or another race or ethnicity or declined to respond. In the relative group, 53 participants (7.6%) self-identified as African American or Black, 594 (85.1%) as White, and 51 (7.3%) as American Indian or Alaska Native, Asian, more than one race, or another race or ethnicity or declined to respond. These groups were combined to protect privacy owing to small numbers. CUD in probands (55 [9.4%]) was associated with an increase in CUD in relatives (adjusted odds ratio [aOR], 2.64; 95% CI, 1.20-5.79; P = .02). Bipolar disorder II (BP-II) in probands (72 [12.3%]) was also associated with increased risk of CUD in relatives (aOR, 2.57; 95% CI, 1.06-6.23; P = .04). However, bipolar disorder I (114 [19.5%]) and major depressive disorder (192 [32.8%]) in probands were not significantly associated with CUD in relatives. Among relatives, CUD was associated with BP-II (aOR, 4.50; 95% CI, 1.72-11.77; P = .002), major depressive disorder (aOR, 3.64; 95% CI, 1.78-7.45; P < .001), and mean (SD) age (42.7 [12.8] years with CUD vs 50.3 [18.3] years without CUD; aOR, 0.98; 95% CI, 0.96-1.00; P = .02). Familial coaggregation of BP-II with CUD was attenuated by the inclusion of comorbid anxiety disorders. Further, rates of CUD were highest in relatives with both a familial and individual history of BP-II (no familial or individual history of BP-II: 41 [7.2%]; familial history but no individual history of BP-II: 13 [19.1%]; individual history but no familial history of BP-II: 10 [22.2%]; familial and individual history of BP-II: 4 [28.6%]; Fisher exact test, P < .001). The onset of mood disorder subtypes preceded CUD in probands and relatives in most cases. Conclusions and Relevance: The findings confirmed a familial aggregation of CUD. The increase in risk of CUD among relatives of probands with BP-II suggests that CUD may share a common underlying diathesis with BP-II. Taken together with the temporal precedence of depression and mania with respect to CUD onset, these findings highlight a potential role for BP-II intervention as CUD prevention.

Cannabis induced psychosis: A systematic review on the role of genetic polymorphisms.

OBJECTIVE: Cannabis sativa is a recreational drug commonly consumed in Europe and is getting popularity for both recreational and therapeutic use. In some individuals, the use of cannabis leads to psychotic disorders. This systematic review summarizes the current evidence linking genetic polymorphisms and inter-individual susceptibility to psychosis induced by cannabis. METHOD: Studies published from 2005 to 2020 were identified through Medline using PubMed, Web of Science and Scopus database and searches were conducted according to PRISMA guidelines. Initial search was performed with terms: "cannabis induced psychosis" AND "genetics". RESULTS: From the initial group of 108 papers, 18 studies met our inclusion criteria. Many of the findings revealed associations with genetic polymorphisms modulations of genes involved directly (COMT, DRD2 and DAT) or indirectly (AKT1) to dopamine pathways. The most consistent finding was with COMT rs4680, where the presence of the Val allele was associated with a higher risk for cannabis-induced psychosis. This higher susceptibility was also reported for AKT1 (rs2494732) with the CC genotype. Of note, the only genome-wide association study identified a significant signal close to the cholinergic receptor muscarinic 3 represented by rs115455482 and rs74722579 predisposing to cannabis-induced hallucinations and remarkably no dopaminergic target was found. CONCLUSION: Actual evidence supports the role of dopamine in cannabis induced psychosis. However, most of genetic polymorphism studies have as a starting point the pre-existing dopaminergic theoretical basis for psychosis. This alerts to the importance of more broad genetic studies. Integrate genetic results into biological systems may enhance our knowledge of cannabis induced psychosis and could help in the prevention and treatment of these patients.

Genome-wide identification of the shared genetic basis of cannabis and cigarette smoking and schizophrenia implicates NCAM1 and neuronal abnormality.

OBJECTIVES: Confirming the existence and composition of the shared genetic basis of Schizophrenia and cannabis and cigarette smoking has critical values for the clinical prevention and intervention of psychosis. METHODS: To achieve this goal, we leveraged Genome-Wide summary statistics of Schizophrenia (n = 99,934), cigarette smoking (n = 518,633) and cannabis usage (n = 162,082). We applied Causal Analysis Using Summary Effect Estimates (CAUSE) and genomic structural equation modeling (GenomicSEM) to quantify the contribution of a common genetic factor of cannabis and cigarette smoking and schizophrenia (referred to as SCZ_SMO), then identified genome-wide loci that made up SCZ_SMO. RESULTS: We estimated that SCZ_SMO explained 8.6% of Schizophrenia heritability (Z score <-2.5 in CAUSE, p<10-20 in Genomic SEM). There were 20 independent loci showing association with SCZ_SMO at the genome-wide threshold of p<5 × 10-8. At the top locus on chromosome 11, fine-mapping identified rs7945073 (posterior inclusion probability =0.12, p = 2.24 × 10-32) as the top risk variants. Gene-level association and fine-mapping highlighted NCAM1, PHC2, and SEMA6D as risk genes of SCZ_SMO. Other risk genes were enriched in cortex, neuron, and dendritic spines (adjusted p<0.05). SCZ_SMO showed significant positive correlation (p<10-6) with the genetic risk of attention deficit hyperactivity disorder (r = 0.50), lifestyle problems (r = 0.83), social deprivation (r = 0.58) and all-cause pregnant loss (r = 0.60). CONCLUSION: Our result provided new evidence on the shared genetic basis model for the association between Schizophrenia and smoking and provided genetic and biological insights into their shared mechanism.

Novel Insights into Potential Cannabis-Related Cancerogenesis from Recent Key Whole Epigenome Screen of Cannabis Dependence and Withdrawal: Epidemiological Commentary and Explication of Schrott et al.

Whilst the cannabis-cancer link has been traditionally described as controversial recent whole nation and whole continent studies have demonstrated that well documented laboratory-based multimodal cannabinoid genotoxicity is indeed reflected in numerous cancer types in larger epidemiological series. A recent longitudinal human sperm epigenome-wide DNA methylation screen in both cannabis dependence and cannabis withdrawal has revealed remarkable insights into the manner in which widespread perturbations of DNA methylation may lead to cancerogenic changes in both the exposed and subsequent generations as a result of both cannabis exposure and withdrawal. These results therefore powerfully strengthen and further robustify the causal nature of the relationship between cannabinoid exposure and cancerous outcomes well beyond the previously published extensive mechanistic literature on cannabinoid genotoxicity. The reported epigenomic results are strongly hypothesis generating and call powerfully for further work to investigate oncogenic mechanisms in many tissues, organs and preclinical models. These epigenomic results provide an extraordinarily close predictive account for the epidemiologically observed pattern of cannabis-related malignant disease and indicate that malignant and multigenerational cannabinoid epigenotoxicity is potentially a significant and major public health concern.

Experimentally exploring the potential behavioral effects of personalized genetic information about marijuana and schizophrenia risk.

Marijuana use may increase schizophrenia risk, and this effect may be genetically moderated. We investigated how hypothetical genetic test results indicating the presence or absence of heightened schizophrenia risk in reaction to marijuana use would affect attitudes toward marijuana use. In two experiments, participants were randomized to hypothetical scenarios in which genetic testing showed the presence or absence of a predisposition for marijuana use to increase their schizophrenia risk, or to a control condition with no mention of genetic testing. Experiment 1 used a sample of 801 U.S. young adults recruited via Amazon.com's Mechanical Turk platform. Experiment 2 replicated the same procedures with a nationally representative sample of 800 U.S. adults aged 18-30. In Experiment 1, those in the predisposition condition, compared to the control condition, rated the likelihood and importance of their avoiding marijuana as significantly higher, whereas those in the no-predisposition condition rated both as significantly lower. In experiment 2, these findings were largely replicated for the predisposition condition but not the no-predisposition condition, and prior marijuana use was a significant moderator, with the effects of the predisposition condition confined to participants who reported having used marijuana. If these results are predictive of responses to actual genetic testing, they suggest that genetic test results indicating that marijuana use will increase one's schizophrenia risk may incentivize abstinence, especially for those with prior marijuana use. Future research could further investigate whether genetic test results indicating the absence of such a predisposition might disincentivize abstinence from marijuana use.

Bipolar disorder and cannabis use: A bidirectional two-sample Mendelian randomization study.

Cannabis use is associated with a number of psychiatric disorders; however, the causal nature of these associations has been difficult to establish. Mendelian randomization (MR) offers a way to infer causality between exposures with known genetic predictors (genome-wide significant single nucleotide polymorphisms [SNPs]) and outcomes of interest. MR has previously been applied to investigate the relationship between lifetime cannabis use (having ever used cannabis) and schizophrenia, depression, and attention deficit hyperactivity disorder (ADHD), but not bipolar disorder, representing a gap in the literature. We conducted a two-sample bidirectional MR study on the relationship between bipolar disorder and lifetime cannabis use. Genetic instruments (SNPs) were obtained from the summary statistics of recent large genome-wide association studies (GWAS). We conducted a two-sample bidirectional MR study on the relationship between bipolar disorder and lifetime cannabis use using inverse variance weighted regression, weighted median regression, and Egger regression. Genetic liability to bipolar disorder was significantly associated with an increased risk of lifetime cannabis use; however, genetic liability to lifetime cannabis use showed no association with the risk of bipolar disorder. The sensitivity analyses showed no evidence for pleiotropic effects. The present findings support a causal effect of liability to bipolar disorder on the risk of using cannabis at least once. No evidence was found for a causal effect of liability to cannabis use on the risk of bipolar disorder. These findings add important new knowledge to the understanding of the complex relationship between cannabis use and psychiatric disorders.

Global and glucocorticoid receptor gene-specific (NR3C1) DNA methylation analysis in patients with cannabinoid or synthetic cannabinoid use disorder.

This study investigates the relationship between cannabinoid use disorder (CUD) or synthetic cannabinoid use disorder (SCUD) and the global methylation, methylation of NR3C1 gene promotor, and NR3C1 BclI polymorphism, considering clinical parameters. Based on the DSM-5 criteria, 172 SCUD patients' and 44 CUD patients' diagnoses were confirmed with a positive urine test; 88 healthy volunteers were also included in the study. Global DNA methylation was measured using a 5-methylcytosine (5-mC) DNA ELISA Kit. Methylation-specific PCR was used to identify the methylation of the NR3C1 gene. The analysis of the BclI polymorphism of the NR3C1 gene was evaluated by using the PCR-RFLP. Our results demonstrated that the mean of 5-mC percentages of SCUD patients differed significantly from those of the control group. When comparing NR3C1 gene methylation and clinical parameters due to NR3C1 genotype distribution in patients, the genotype distribution was significantly different between the groups, due to the former polysubstance abuse. Additionally, there was a significantly positive correlation between the 5-mC percentages of SCUD patients and the reported durations of their disorders. In summary, whereas global DNA methylation may be associated with SCUD, the methylation of the NR3C1 gene and NR3C1 BclI polymorphism were not related to CUD or SCUD.

Cannabis use does not impact on type 2 diabetes: A two-sample Mendelian randomization study.

Cannabis has effects on the insulin/glucose metabolism. As the use of cannabis and the prevalence of type 2 diabetes increase worldwide, it is important to examine the effect of cannabis on the risk of diabetes. We conducted a Mendelian randomization (MR) study by using 19 single-nucleotide polymorphisms (SNPs) as instrumental variables for lifetime cannabis use and 14 SNPs to instrument cannabis use disorder and linking these to type 2 diabetes risk using genome-wide association study data (lifetime cannabis use [N = 184,765]; cannabis use disorder [2387 cases/48,985 controls], type 2 diabetes [74,124 cases/824,006 controls]). The MR analysis suggested no effect of lifetime cannabis use (inverse-variance weighted odds ratio [95% confidence interval] = 1.00 [0.93-1.09], P value = 0.935) and cannabis use disorder (OR = 1.03 [0.99-1.08]) on type 2 diabetes. Sensitivity analysis to assess potential pleiotropy led to no substantive change in the estimates. This study adds to the evidence base that cannabis use does not play a causal role in type 2 diabetes.

No evidence of associations between genetic liability for schizophrenia and development of cannabis use disorder.

BACKGROUND: Cannabis use and cannabis use disorder (CUD) is increased in patients with schizophrenia. It is important to establish if this is explained by non-causal factors, such as shared genetic vulnerability. We aimed to investigate whether the polygenic risk scores (PRS) for schizophrenia and other psychiatric disorders would predict CUD in controls, patients with schizophrenia, and patients with other psychiatric disorders. METHODS: We linked nationwide Danish registers and genetic information obtained from dried neonatal bloodspots in an observational analysis. We included people with schizophrenia, other psychiatric disorders, and controls. The exposures of interest were the PRS for schizophrenia, attention-deficit hyperactivity disorder (ADHD) autism spectrum disorder, and anorexia nervosa. The main outcome of interest was the diagnosis of CUD. RESULTS: The study included 88 637 individuals. PRS for schizophrenia did not predict CUD in controls [hazard ratio (HR) = 1.16, 95% CI 0.95-1.43 per standard-deviation increase in PRS, or HR = 1.47, 95% CI 0.72-3.00 comparing highest v. remaining decile], but PRS for ADHD did (HR = 1.27, 95% CI 1.08-1.50 per standard-deviation increase, or HR = 2.02, 95% CI 1.27-3.22 for the highest decile of PRS). Among cases with schizophrenia, the PRS for schizophrenia was associated with CUD. While CUD was a strong predictor of schizophrenia (HR = 4.91, 95% CI 4.36-5.53), the inclusion of various PRS did not appreciably alter this association. CONCLUSION: The PRS for schizophrenia was not associated with CUD in controls or patients with other psychiatric disorders than schizophrenia. This speaks against the hypothesis that shared genetic vulnerability would explain the association between cannabis and schizophrenia.

Significant, replicable, and functional associations between KTN1 variants and alcohol and drug codependence.

The gray matter volume (GMV) of the putamen has been reported to be regulated by kinectin 1 gene (KTN1). As a hub of the dopaminergic circuit, the putamen is widely implicated in the etiological processes of substance use disorders (SUD). Here, we aimed to identify robust and reliable associations between KTN1 SNPs and SUD across multiple samples. We examined the associations between SUD and KTN1 SNPs in four independent population-based or family-based samples (n = 10,209). The potential regulatory effects of the risk alleles on the putamen GMVs, the effects of alcohol, nicotine, marijuana and cocaine on KTN1 mRNA expression, and the relationship between KTN1 mRNA expression and SUD were explored. We found that a total of 23 SNPs were associated with SUD across at least two independent samples (1.4 × 10-4 ≤ p ≤ 0.049), including one SNP (rs12895072) across three samples (8.8 × 10-3 ≤ p ≤ 0.049). Four other SNPs were significantly or suggestively associated with SUD only in European-Australians (4.8 × 10-4 ≤ p ≤ 0.058). All of the SUD-risk alleles of these 27 SNPs increased (ß > 0) the putamen GMVs and represented major alleles (f > 0.5) in Europeans. Twenty-two SNPs were potentially biologically functional. Alcohol, nicotine and cocaine significantly affected the KTN1 mRNA expression, and the KTN1 mRNA was differentially expressed between nicotine or cocaine dependent and control subjects. We concluded that there was a replicable and robust relationship among the KTN1 variants, KTN1 mRNA expression, putamen GMVs, molecular effects of substances, and SUD, suggesting that some risk KTN1 alleles might increase kinectin 1 expression in the putamen, altering putamen structures and functions, and leading to SUD.

The contributions of the endocannabinoid system and stress on the neural processing of reward stimuli.

The brain's endocannabinoid system plays a crucial role in reward processes by mediating appetitive learning and encoding the reinforcing properties of substances. Evidence also suggests that endocannabinoids are an important constituent of neuronal substrates involved in emotional responses to stress. Thus, it is critical to understand how the endocannabinoid system and stress may affect reward processes given their importance in substance use disorders. We examined the relationship between factors that regulate endocannabinoid system signaling (i.e., cannabinoid receptor genes and prolonged cannabis exposure) and stress on fMRI BOLD response to reward cues using multivariate statistical analysis. We found that proxies for endocannabinoid system signaling (i.e., endocannabinoid genes and chronic exposure to cannabis) and stress have differential effects on neural response to cannabis cues. Specifically, a single nucleotide polymorphism (SNP) variant in the cannabinoid receptor 1 (CNR1) gene, early life stress, and current perceived stress modulated reward responsivity in long-term, heavy cannabis users, while a variant in the fatty acid amide hydrolase (FAAH) gene and current perceived stress modulated cue-elicited response in non-using controls. These associations were related to distinct neural responses to cannabis-related cues compared to natural reward cues. Understanding the contributions of endocannabinoid system factors and stress that lead to downstream effects on neural mechanisms underlying sensitivity to rewards, such as cannabis, will contribute towards a better understanding of endocannabinoid-targeted therapies as well as individual risks for cannabis use disorder.

High genes: Genetic underpinnings of cannabis use phenotypes.

Cannabis is one of the most widely used substances across the globe and its use has a substantial heritable component. However, the heritability of cannabis use varies according to substance use phenotype, suggesting that a unique profile of gene variants may contribute to the different stages of use, such as age of use onset, lifetime use, cannabis use disorder, and withdrawal and craving during abstinence. Herein, we review a subset of genes identified by candidate gene, family-based linkage, and genome-wide association studies related to these cannabis use phenotypes. We also describe their relationships with other substances, and their functions at the neurobiological, cognitive, and behavioral levels to hypothesize the role of these genes in cannabis use risk. Delineating genetic risk factors in the various stages of cannabis use will provide insight into the biological mechanisms related to cannabis use and highlight points of intervention prior to and following the development of dependence, as well as identify targets to aid drug development for treating problematic cannabis use.

A large-scale genome-wide association study meta-analysis of cannabis use disorder.

BACKGROUND: Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder. METHODS: To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations. FINDINGS: We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10-9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10-9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10-21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia. INTERPRETATION: These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder. FUNDING: National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.