Cross-ancestry genetic investigation of schizophrenia, cannabis use disorder, and tobacco smoking.

Individuals with schizophrenia frequently experience co-occurring substance use, including tobacco smoking and heavy cannabis use, and substance use disorders. There is interest in understanding the extent to which these relationships are causal, and to what extent shared genetic factors play a role. We explored the relationships between schizophrenia (Scz; European ancestry N = 161,405; African ancestry N = 15,846), cannabis use disorder (CanUD; European ancestry N = 886,025; African ancestry N = 120,208), and ever-regular tobacco smoking (Smk; European ancestry N = 805,431; African ancestry N = 24,278) using the largest available genome-wide studies of these phenotypes in individuals of African and European ancestries. All three phenotypes were positively genetically correlated (rgs = 0.17-0.62). Genetic instrumental variable analyses suggested the presence of shared heritable factors, but evidence for bidirectional causal relationships was also found between all three phenotypes even after correcting for these shared genetic factors. We identified 327 pleiotropic loci with 439 lead SNPs in the European ancestry data, 150 of which were novel (i.e., not genome-wide significant in the original studies). Of these pleiotropic loci, 202 had lead variants which showed convergent effects (i.e., same direction of effect) on Scz, CanUD, and Smk. Genetic variants convergent across all three phenotypes showed strong genetic correlations with risk-taking, executive function, and several mental health conditions. Our results suggest that both shared genetic factors and causal mechanisms may play a role in the relationship between CanUD, Smk, and Scz, but longitudinal, prospective studies are needed to confirm a causal relationship.

Genetic influences and causal pathways shared between cannabis use disorder and other substance use traits.

Cannabis use disorder (CanUD) has increased with the legalization of the use of cannabis. Around 20% of individuals using cannabis develop CanUD, and the number of users has grown with increasing ease of access. CanUD and other substance use disorders (SUDs) are associated phenotypically and genetically. We leveraged new CanUD genomics data to undertake genetically-informed analyses with unprecedented power, to investigate the genetic architecture and causal relationships between CanUD and lifetime cannabis use with risk for developing SUDs and substance use traits. Analyses included calculating local and global genetic correlations, genomic structural equation modeling (genomicSEM), and Mendelian Randomization (MR). Results from the genetic correlation and genomicSEM analyses demonstrated that CanUD and cannabis use differ in their relationships with SUDs and substance use traits. We found significant causal effects of CanUD influencing all the analyzed traits: opioid use disorder (OUD) (Inverse variant weighted, IVW ß = 0.925 ± 0.082), problematic alcohol use (PAU) (IVW ß = 0.443 ± 0.030), drinks per week (DPW) (IVW ß = 0.182 ± 0.025), Fagerström Test for Nicotine Dependence (FTND) (IVW ß = 0.183 ± 0.052), cigarettes per day (IVW ß = 0.150 ± 0.045), current versus former smokers (IVW ß = 0.178 ± 0.052), and smoking initiation (IVW ß = 0.405 ± 0.042). We also found evidence of bidirectionality showing that OUD, PAU, smoking initiation, smoking cessation, and DPW all increase risk of developing CanUD. For cannabis use, bidirectional relationships were inferred with PAU, smoking initiation, and DPW; cannabis use was also associated with a higher risk of developing OUD (IVW ß = 0.785 ± 0.266). GenomicSEM confirmed that CanUD and cannabis use load onto different genetic factors. We conclude that CanUD and cannabis use can increase the risk of developing other SUDs. This has substantial public health implications; the move towards legalization of cannabis use may be expected to increase other kinds of problematic substance use. These harmful outcomes are in addition to the medical harms associated directly with CanUD.

Pleiotropy and genetically inferred causality linking multisite chronic pain to substance use disorders.

Individuals suffering from chronic pain develop substance use disorders (SUDs) more often than others. Understanding the shared genetic influences underlying the comorbidity between chronic pain and SUDs will lead to a greater understanding of their biology. Genome-wide association statistics were obtained from the UK Biobank for multisite chronic pain (MCP, Neffective = 387,649) and from the Million Veteran Program and the Psychiatric Genomics Consortium meta-analyses for alcohol use disorder (AUD, Neffective = 296,974), cannabis use disorder (CanUD, Neffective = 161,053), opioid use disorder (OUD, Neffective = 57,120), and problematic tobacco use (PTU, Neffective = 270,120). SNP-based heritability was estimated for each of the traits and genetic correlation (rg) analyses were performed to assess MCP-SUD pleiotropy. Bidirectional Mendelian Randomization analyses evaluated possible causal relationships. Finally, to identify and characterize individual loci, we performed a genome-wide pleiotropy analysis and a brain-wide analysis using imaging phenotypes available from the UK Biobank. MCP was positively genetically correlated with AUD (rg = 0.26, p = 7.55 × 10-18), CanUD (rg = 0.37, p = 8.21 × 10-37), OUD (rg = 0.20, p = 1.50 × 10-3), and PTU (rg = 0.29, p = 8.53 × 10-12). Although the MR analyses supported bi-directional relationships, MCP had larger effects on AUD (pain-exposure: beta = 0.18, p = 8.21 × 10-4; pain-outcome: beta = 0.07, p = 0.018), CanUD (pain-exposure: beta = 0.58, p = 2.70 × 10-6; pain-outcome: beta = 0.05, p = 0.014) and PTU (pain-exposure: beta = 0.43, p = 4.16 × 10-8; pain-outcome: beta = 0.09, p = 3.05 × 10-6) than the reverse. The genome-wide analysis identified two SNPs pleiotropic between MCP and all SUD investigated: IHO1 rs7652746 (ppleiotropy = 2.69 × 10-8), and CADM2 rs1248857 (ppleiotropy = 1.98 × 10-5). In the brain-wide analysis, rs7652746 was associated with multiple cerebellum and amygdala imaging phenotypes. When analyzing MCP pleiotropy with each SUD separately, we found 25, 22, and 4 pleiotropic variants for AUD, CanUD, and OUD, respectively. To our knowledge, this is the first large-scale study to provide evidence of potential causal relationships and shared genetic mechanisms underlying MCP-SUD comorbidity.

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.

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.

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).

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.

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.

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.

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.