Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.

Characteristics of women concordant and discordant for urine drug screens for cannabis exposure and self-reported cannabis use during pregnancy.

BACKGROUND: Increasing cannabis use among pregnant people and equivocal evidence linking prenatal cannabis exposure to adverse outcomes in offspring highlights the need to understand its potential impact on pregnancy and child outcomes. Assessing cannabis use during pregnancy remains a major challenge with potential influences of stigma on self-report as well as detection limitations of easily collected biological matrices. OBJECTIVE: This descriptive study examined the concordance between self-reported (SR) cannabis use and urine drug screen (UDS) detection of cannabis exposure during the first trimester of pregnancy and characterized concordant and discordant groups for sociodemographic factors, modes of use, secondhand exposure to cannabis and tobacco, and alcohol use and cotinine positivity. STUDY DESIGN: The Cannabis Use During Development and Early Life (CUDDEL) Study is an ongoing longitudinal study that recruits pregnant individuals presenting for obstetric care, who report lifetime cannabis use as well as using (n = 289) or not using cannabis (n = 169) during pregnancy. During the first trimester pregnancy visit, SR of cannabis use and a UDS for cannabis, other illicit drugs and nicotine are acquired from eligible participants, of whom 333 as of 05/01/2023 had both. RESULTS: Using available CUDDEL Study data on both SR and UDS (n = 333; age 26.6 ± 4.7; 88.6% Black; 45.4% below federal poverty threshold; 56.5% with paid employment; 89% with high school education; 22% first pregnancy; 12.3 ± 3.6 weeks gestation), we classified pregnant individuals with SR and UDS data into 4 groups based on concordance (k = 0.49 [95% C.I. 0.40-0.58]) between SR cannabis use and UDS cannabis detection during the first trimester: 1) SR+/UDS+ (n = 107); 2) SR-/UDS- (n = 142); 3) SR+/UDS- (n = 44); 4) SR-/UDS+ (n = 40). Those who were SR+/UDS- reported less frequent cannabis use and fewer hours under the influence of cannabis during their pregnancy. Those who were SR-/UDS+ were more likely to have joined the study at a lower gestational age with 62.5% reporting cannabis use during their pregnancy prior to being aware that they were pregnant. Of the 40 SR-/UDS+ women, 14 (i.e., 35%) reported past month secondhand exposure, or blunt usage. In the subset of individuals with SR and UDS available at trimester 2 (N = 160) and 3 (N = 140), concordant groups were mostly stable and > 50% of those in the discordant groups became concordant by the second trimester. Classifying individuals as exposed or not exposed who were SR+ and/or UDS+ resulted in minor changes in group status based on self-report at screening. CONCLUSION: Overall, there was moderate concordance between SR and UDS for cannabis use/exposure during pregnancy. Instances of SR+/UDS- discordancy may partially be attributable to lower levels of use that are not detected on UDS. SR-/UDS+ discordancy may arise from recent use prior to knowledge of pregnancy, extreme secondhand exposure, deception, and challenges with completing questionnaires. Acquiring both self-report and biological detection of cannabis use/exposure allows for the examination of convergent evidence. Classifying those who are SR+ and/or UDS+ as individuals who used cannabis during their first trimester after being aware of their pregnancy resulted in only a minor change in exposure status; thus, relying on self-report screening, at least in this population and within this sociocultural context likely provides an adequate approximation of cannabis use during pregnancy.

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.

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), cannabis use disorder (CanUD), and ever-regular tobacco smoking (Smk) 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). Causal inference analyses suggested the presence of horizontal pleiotropy, but evidence for bidirectional causal relationships was also found between all three phenotypes even after correcting for horizontal pleiotropy. We identified 439 pleiotropic loci 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 horizontal pleiotropy 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.

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.

Identifying genetic loci and phenomic associations of substance use traits: A multi-trait analysis of GWAS (MTAG) study.

BACKGROUND AND AIMS: Genome-wide association studies (GWAS) of opioid use disorder (OUD) and cannabis use disorder (CUD) have lagged behind those of alcohol use disorder (AUD) and smoking, where many more loci have been identified. We sought to identify novel loci for substance use traits (SUTs) in both African- (AFR) and European- (EUR) ancestry individuals to enhance our understanding of the traits' genetic architecture. DESIGN: We used multi-trait analysis of GWAS (MTAG) to analyze four SUTs in EUR subjects (OUD, CUD, AUD and smoking initiation [SMKinitiation]), and three SUTs in AFR subjects (OUD, AUD and smoking trajectory [SMKtrajectory]). We conducted gene-set and protein-protein interaction analyses and calculated polygenic risk scores (PRS) in two independent samples. SETTING: This study was conducted in the United States. PARTICIPANTS: A total of 5692 EUR and 4918 AFR individuals in the Yale-Penn sample and 29 054 EUR and 10 265 AFR individuals in the Penn Medicine BioBank sample. FINDINGS: MTAG identified genome-wide significant (GWS) single nucleotide polymorphisms (SNPs) for all four traits in EUR: 41 SNPs in 36 loci for OUD; 74 SNPs in 60 loci for CUD; 63 SNPs in 52 loci for AUD; and 183 SNPs in 144 loci for SMKinitiation. MTAG also identified GWS SNPs in AFR: 2 SNPs in 2 loci for OUD; 3 SNPs in 3 loci for AUD; and 1 SNP in 1 locus for SMKtrajectory. In the Yale-Penn sample, the MTAG-derived PRS consistently yielded more significant associations with both the corresponding substance use disorder diagnosis and multiple related phenotypes than the GWAS-derived PRS. CONCLUSIONS: Multi-trait analysis of genome-wide association studies boosted the number of loci found for substance use traits, identifying genes not previously linked to any substance, and increased the power of polygenic risk scores. Multi-trait analysis of genome-wide association studies can be used to identify novel associations for substance use, especially those for which the samples are smaller than those for historically legal substances.

Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders.

Genetic liability to substance use disorders can be parsed into loci that confer general or substance-specific addiction risk. We report a multivariate genome-wide association meta-analysis that disaggregates general and substance-specific loci for published summary statistics of problematic alcohol use, problematic tobacco use, cannabis use disorder, and opioid use disorder in a sample of 1,025,550 individuals of European descent and 92,630 individuals of African descent. Nineteen independent SNPs were genome-wide significant (P < 5e-8) for the general addiction risk factor (addiction-rf), which showed high polygenicity. Across ancestries, PDE4B was significant (among other genes), suggesting dopamine regulation as a cross-substance vulnerability. An addiction-rf polygenic risk score was associated with substance use disorders, psychopathologies, somatic conditions, and environments associated with the onset of addictions. Substance-specific loci (9 for alcohol, 32 for tobacco, 5 for cannabis, 1 for opioids) included metabolic and receptor genes. These findings provide insight into genetic risk loci for substance use disorders that could be leveraged as treatment targets.

The association between reasons for first using cannabis, later pattern of use, and risk of first-episode psychosis: the EU-GEI case-control study.

BACKGROUND: While cannabis use is a well-established risk factor for psychosis, little is known about any association between reasons for first using cannabis (RFUC) and later patterns of use and risk of psychosis. METHODS: We used data from 11 sites of the multicentre European Gene-Environment Interaction (EU-GEI) case-control study. 558 first-episode psychosis patients (FEPp) and 567 population controls who had used cannabis and reported their RFUC.We ran logistic regressions to examine whether RFUC were associated with first-episode psychosis (FEP) case-control status. Path analysis then examined the relationship between RFUC, subsequent patterns of cannabis use, and case-control status. RESULTS: Controls (86.1%) and FEPp (75.63%) were most likely to report 'because of friends' as their most common RFUC. However, 20.1% of FEPp compared to 5.8% of controls reported: 'to feel better' as their RFUC (χ2 = 50.97; p < 0.001). RFUC 'to feel better' was associated with being a FEPp (OR 1.74; 95% CI 1.03-2.95) while RFUC 'with friends' was associated with being a control (OR 0.56; 95% CI 0.37-0.83). The path model indicated an association between RFUC 'to feel better' with heavy cannabis use and with FEPp-control status. CONCLUSIONS: Both FEPp and controls usually started using cannabis with their friends, but more patients than controls had begun to use 'to feel better'. People who reported their reason for first using cannabis to 'feel better' were more likely to progress to heavy use and develop a psychotic disorder than those reporting 'because of friends'.

Multi-ancestry meta-analysis of tobacco use disorder prioritizes novel candidate risk genes and reveals associations with numerous health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviors, and although strides have been made using genome-wide association studies (GWAS) to identify risk variants, the majority of variants identified have been for nicotine consumption, rather than TUD. We leveraged five biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records, EHR) in 898,680 individuals (739,895 European, 114,420 African American, 44,365 Latin American). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviors in children, and hundreds of medical outcomes, including HIV infection, heart disease, and pain. This work furthers our biological understanding of TUD and establishes EHR as a source of phenotypic information for studying the genetics of TUD.

Characterisation of the genetic relationship between the domains of sleep and circadian-related behaviours with substance use phenotypes.

Sleep problems and substance use frequently co-occur. While substance use can result in specific sleep deficits, genetic pleiotropy could explain part of the relationship between sleep and substance use and use disorders. Here we use the largest publicly available genome-wide summary statistics of substance use behaviours (N = 79,729-632,802) and sleep/activity phenotypes to date (N = 85,502-449,734) to (1) assess the genetic overlap between substance use behaviours and both sleep and circadian-related activity measures, (2) estimate clusters from genetic correlations and (3) test processes of causality versus genetic pleiotropy. We found 31 genetic correlations between substance use and sleep/activity after Bonferroni correction. These patterns of overlap were represented by two genetic clusters: (1) tobacco use severity (age of first regular tobacco use and smoking cessation) and sleep health (sleep duration, sleep efficiency and chronotype) and (2) substance consumption/problematic use (drinks per day and cigarettes per day, cannabis use disorder, opioid use disorder and problematic alcohol use) and sleep problems (insomnia, self-reported short sleep duration, increased number of sleep episodes, increased sleep duration variability and diurnal inactivity) and measures of circadian-related activity (L5, M10 and sleep midpoint). Latent causal variable analyses determined that horizontal pleiotropy (rather than genetic causality) underlies a majority of the associations between substance use and sleep/circadian related measures, except one plausible genetically causal relationship for opioid use disorder on self-reported long sleep duration. Results show that shared genetics are likely a mechanism that is at least partly responsible for the overlap between sleep and substance use traits.

Associations between cognition and polygenic liability to substance involvement in middle childhood: Results from the ABCD study.

BACKGROUND: Cognition is robustly associated with substance involvement. This relationship is attributable to multiple factors, including genetics, though such contributions show inconsistent patterns in the literature. For instance, genome-wide association studies point to potential positive relationships between educational achievement and common substance use but negative relationships with heavy and/or problematic substance use. METHODS: We estimated associations between polygenic risk for substance involvement (i.e., alcohol, tobacco, and cannabis use and problematic use) and cognition subfacets (i.e., general ability, executive function, learning/memory) derived from confirmatory factor analysis among 3205 substance naïve children (ages 9-10) of European ancestry who completed the baseline session of the Adolescent Brain Cognitive Development (ABCD) Study. FINDINGS: Polygenic risk for lifetime cannabis use was positively associated with all three facets of cognitive ability (Bs ≥ 0.045, qs ≤ 0.044). No other substance polygenic risk scores showed significant associations with cognition after adjustment for multiple testing (|Bs|≤0.033, qs ≥ 0.118). CONCLUSIONS: Polygenic liability to lifetime cannabis use, but not use disorder, was positively associated with cognitive performance among substance-naïve children, possibly reflecting shared genetic overlap with openness to experience or the influence of genetic variance associated with socioeconomic status. Our lack of findings for the other polygenic scores may reflect ascertainment differences between the genome-wide association study (GWAS) samples and the current sample and/or the young age of the present sample. As longitudinal data in ABCD are collected, this sample may be useful for disentangling putatively causal or predispositional influences of substance use and misuse on cognition.

The addiction risk factor: A unitary genetic vulnerability characterizes substance use disorders and their associations with common correlates.

Substance use disorders commonly co-occur with one another and with other psychiatric disorders. They share common features including high impulsivity, negative affect, and lower executive function. We tested whether a common genetic factor undergirds liability to problematic alcohol use (PAU), problematic tobacco use (PTU), cannabis use disorder (CUD), and opioid use disorder (OUD) by applying genomic structural equation modeling to genome-wide association study summary statistics for individuals of European ancestry (Total N = 1,019,521; substance-specific Ns range: 82,707-435,563) while adjusting for the genetics of substance use (Ns = 184,765-632,802). We also tested whether shared liability across SUDs is associated with behavioral constructs (risk-taking, executive function, neuroticism; Ns = 328,339-427,037) and non-substance use psychopathology (psychotic, compulsive, and early neurodevelopmental disorders). Shared genetic liability to PAU, PTU, CUD, and OUD was characterized by a unidimensional addiction risk factor (termed The Addiction-Risk-Factor, independent of substance use. OUD and CUD demonstrated the largest loadings, while problematic tobacco use showed the lowest loading. The Addiction-Risk-Factor was associated with risk-taking, neuroticism, executive function, and non-substance psychopathology, but retained specific variance before and after accounting for the genetics of substance use. Thus, a common genetic factor partly explains susceptibility for alcohol, tobacco, cannabis, and opioid use disorder. The Addiction-Risk-Factor has a unique genetic architecture that is not shared with normative substance use or non-substance psychopathology, suggesting that addiction is not the linear combination of substance use and psychopathology.

Genes identified in rodent studies of alcohol intake are enriched for heritability of human substance use.

BACKGROUND: Rodent paradigms and human genome-wide association studies (GWAS) on drug use have the potential to provide biological insight into the pathophysiology of addiction. METHODS: Using GeneWeaver, we created rodent alcohol and nicotine gene-sets derived from 19 gene expression studies on alcohol and nicotine outcomes. We partitioned the SNP heritability of these gene-sets using four large human GWAS: (1) alcoholic drinks per week, (2) problematic alcohol use, (3) cigarettes per day, and (4) smoking cessation. We benchmarked our findings with curated human alcohol and nicotine addiction gene-sets and performed specificity analyses using other rodent gene-sets (e.g., locomotor behavior) and other human GWAS (e.g., height). RESULTS: The rodent alcohol gene-set was enriched for heritability of drinks per week, cigarettes per day, and smoking cessation, but not problematic alcohol use. However, the rodent nicotine gene-set was not significantly associated with any of these traits. Both rodent gene-sets showed enrichment for several non-substance-use GWAS, and the extent of this relationship tended to increase as a function of trait heritability. In general, larger gene-sets demonstrated more significant enrichment. Finally, when evaluating human traits with similar heritabilities, both rodent gene-sets showed greater enrichment for substance use traits. CONCLUSION: Our results suggest that rodent gene expression studies can help to identify genes that contribute to the heritability of some substance use traits in humans, yet there was less specificity than expected. We outline various limitations, interpretations, and considerations for future research.

Genetic Liability to Cannabis Use Disorder and COVID-19 Hospitalization.

BACKGROUND: Vulnerability to COVID-19 hospitalization has been linked to behavioral risk factors, including combustible psychoactive substance use (e.g., tobacco smoking). Paralleling the COVID-19 pandemic crisis have been increasingly permissive laws for recreational cannabis use. Cannabis use disorder (CUD) is a psychiatric disorder that is heritable and genetically correlated with respiratory disease, independent of tobacco smoking. We examined the genetic relationship between CUD and COVID-19 hospitalization. METHODS: We estimated the genetic correlation between CUD (case: n = 14,080; control: n = 343,726) and COVID-19 hospitalization (case: n = 9373; control: n = 1,197,256) using summary statistics from genome-wide association studies. Using independent genome-wide association studies conducted before the pandemic, we controlled for several covariates (i.e., tobacco use phenotypes, problematic alcohol use, body mass index, fasting glucose, forced expiratory volume, education attainment, risk taking, attention-deficit/hyperactivity disorder, Townsend deprivation index, chronic obstructive pulmonary disease, hypertension, and type 2 diabetes) using genomic structural equation modeling. Genetic causality between CUD and COVID-19 hospitalization was estimated using latent causal variable models. RESULTS: Genetic vulnerability to COVID-19 was correlated with genetic liability to CUD (r G  = 0.423 [SE = 0.0965], p = 1.33 × 10-6); this association remained when accounting for genetic liability to related risk factors and covariates (b = 0.381-0.539, p = .012-.049). Latent causal variable analysis revealed causal effect estimates that were not statistically significant. CONCLUSIONS: Problematic cannabis use and vulnerability to serious COVID-19 complications share genetic underpinnings that are unique from common correlates. While CUD may plausibly contribute to severe COVID-19 presentations, causal inference models yielded no evidence of putative causation. Curbing excessive cannabis use may mitigate the impact of COVID-19.

The relationship between cannabis and schizophrenia: a genetically informed perspective.

BACKGROUND AND AIMS: While epidemiological studies support a role for heavy, high-potency cannabis use on first-episode psychosis, genetic models of causation suggest reverse causal effects of schizophrenia on cannabis use liability. We estimated the genetic relationship between cannabis use disorder (CUD) and schizophrenia (SCZ) and tested whether liability for CUD is causally associated with increased liability to SCZ while adjusting for tobacco smoking. DESIGN: This study used summary statistics from published genome-wide association studies (GWAS). We used genomic structural equation modeling, latent causal variable analysis, and multivariable Mendelian randomization to examine genetic relationships between CUD, cannabis ever-use, ever-smoked tobacco regularly, nicotine dependence and SCZ, and to test for a causal relationship between liability to CUD and liability to SCZ. SETTING: Genome-wide association studies were published previously as part of international consortia. PARTICIPANTS: Sample sizes of the GWAS summary statistics used in this study ranged from 161 405 to 357 806 individuals of European ancestry. MEASUREMENTS: Genome-wide summary statistics for CUD and SCZ were the primary measurements, while summary statistics for cannabis ever-use, ever-smoked tobacco regularly and nicotine dependence were included as additional variables in the genomic structural equation models and the multivariable Mendelian randomization analyses. FINDINGS: Genetic liability to CUD was significantly associated with SCZ [ß = 0.29, 95% confidence interval (CI) = 0.11, 0.46, P = 0.001], even when accounting for cannabis ever-use, ever-smoked tobacco regularly and nicotine dependence as simultaneous predictors. We found mixed evidence of a causal relationship, with the latent causal variable analysis finding no evidence of causality (genetic causality proportion = -0.08, 95% CI = -0.40, 0.23, P = 0.87) but the multivariable Mendelian randomization analyses suggesting a significant, risk-increasing effect of CUD on liability to SCZ (ß = 0.10, 95% CI = 0.02, 0.18, P = 0.02), accounting for the additional risk factors (cannabis ever-use, ever-smoked tobacco regularly and nicotine dependence). CONCLUSIONS: Genetic liability for cannabis use disorder appears to be robustly associated with schizophrenia, above and beyond tobacco smoking and cannabis ever-use, with mixed evidence to support a causal relationship between cannabis use disorder and schizophrenia.

Genetics of substance use disorders: a review.

Substance use disorders (SUDs) are prevalent and result in an array of negative consequences. They are influenced by genetic factors (h2 = ~50%). Recent years have brought substantial progress in our understanding of the genetic etiology of SUDs and related traits. The present review covers the current state of the field for SUD genetics, including the epidemiology and genetic epidemiology of SUDs, findings from the first-generation of SUD genome-wide association studies (GWAS), cautions about translating GWAS findings to clinical settings, and suggested prioritizations for the next wave of SUD genetics efforts. Recent advances in SUD genetics have been facilitated by the assembly of large GWAS samples, and the development of state-of-the-art methods modeling the aggregate effect of genome-wide variation. These advances have confirmed that SUDs are highly polygenic with many variants across the genome conferring risk, the vast majority of which are of small effect. Downstream analyses have enabled finer resolution of the genetic architecture of SUDs and revealed insights into their genetic relationship with other psychiatric disorders. Recent efforts have also prioritized a closer examination of GWAS findings that have suggested non-uniform genetic influences across measures of substance use (e.g. consumption) and problematic use (e.g. SUD). Additional highlights from recent SUD GWAS include the robust confirmation of loci in alcohol metabolizing genes (e.g. ADH1B and ALDH2) affecting alcohol-related traits, and loci within the CHRNA5-CHRNA3-CHRNB4 gene cluster influencing nicotine-related traits. Similar successes are expected for cannabis, opioid, and cocaine use disorders as sample sizes approach those assembled for alcohol and nicotine.

Cannabis Use, Pulmonary Function, and Lung Cancer Susceptibility: A Mendelian Randomization Study.

INTRODUCTION: Because of widespread use, understanding the pulmonary effects of cannabis use is important; but its role independent from tobacco smoking is yet to be elucidated. We used Mendelian randomization (MR) to assess the effect of genetic liability to lifetime cannabis use and cannabis use disorder on pulmonary function and lung cancer. METHODS: We used four single nucleotide polymorphisms associated with lifetime cannabis use (p value <5 × 10-8) from a genome-wide association study (GWAS) of 184,765 individuals of European descent from the International Cannabis Consortium, 23andme, and U.K. Biobank as instrumental variables. Seven single nucleotide polymorphisms (p value <5 × 10-8) were selected as instruments for cannabis use disorder from a GWAS meta-analysis of 17,068 European ancestry cases and 357,219 controls of European descent from Psychiatric Genomics Consortium Substance Use Disorders working group, Lundbeck Foundation Initiative for Integrative PsychiatricResearch, and deCode. To assess lung function, GWAS included 79,055 study participants of the SpiroMeta Consortium, and for lung cancer GWAS from the International Lung Cancer Consortium contained 29,266 cases and 56,450 controls. RESULTS: MR revealed that genetic liability to lifetime cannabis use was associated with increased risk of squamous cell carcinoma (OR = 1.22, 95%, confidence interval = 1.07-1.39, p value = 0.003, q value = 0.025). Pleiotropy-robust methods and positive and negative control analyses did not indicate bias in the primary analysis. CONCLUSIONS: The findings of this MR analysis suggest evidence for a potential causal association between genetic liability for cannabis use and the risk of squamous cell carcinoma. Triangulating MR and observational studies and addressing orthogonal sources of bias are necessary to confirm this finding.

Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies.

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [rg ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (rg = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (rg = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (rgs = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.

Associations Between Prenatal Cannabis Exposure and Childhood Outcomes: Results From the ABCD Study.

Importance: In light of increasing cannabis use among pregnant women, the US Surgeon General recently issued an advisory against the use of marijuana during pregnancy. Objective: To evaluate whether cannabis use during pregnancy is associated with adverse outcomes among offspring. Design, Setting, and Participants: In this cross-sectional study, data were obtained from the baseline session of the ongoing longitudinal Adolescent Brain and Cognitive Development Study, which recruited 11 875 children aged 9 to 11 years, as well as a parent or caregiver, from 22 sites across the United States between June 1, 2016, and October 15, 2018. Exposure: Prenatal cannabis exposure prior to and after maternal knowledge of pregnancy. Main Outcomes and Measures: Symptoms of psychopathology in children (ie, psychotic-like experiences [PLEs] and internalizing, externalizing, attention, thought, and social problems), cognition, sleep, birth weight, gestational age at birth, body mass index, and brain structure (ie, total intracranial volume, white matter volume, and gray matter volume). Covariates included familial (eg, income and familial psychopathology), pregnancy (eg, prenatal exposure to alcohol and tobacco), and child (eg, substance use) variables. Results: Among 11 489 children (5997 boys [52.2%]; mean [SD] age, 9.9 [0.6] years) with nonmissing prenatal cannabis exposure data, 655 (5.7%) were exposed to cannabis prenatally. Relative to no exposure, cannabis exposure only before (413 [3.6%]) and after (242 [2.1%]) maternal knowledge of pregnancy were associated with greater offspring psychopathology characteristics (ie, PLEs and internalizing, externalizing, attention, thought and, social problems), sleep problems, and body mass index, as well as lower cognition and gray matter volume (all |ß| > 0.02; all false discovery rate [FDR]-corrected P < .03). Only exposure after knowledge of pregnancy was associated with lower birth weight as well as total intracranial volume and white matter volumes relative to no exposure and exposure only before knowledge (all |ß| > 0.02; all FDR-corrected P < .04). When including potentially confounding covariates, exposure after maternal knowledge of pregnancy remained associated with greater PLEs and externalizing, attention, thought, and social problems (all ß > 0.02; FDR-corrected P < .02). Exposure only prior to maternal knowledge of pregnancy did not differ from no exposure on any outcomes when considering potentially confounding variables (all |ß| < 0.02; FDR-corrected P > .70). Conclusions and Relevance: This study suggests that prenatal cannabis exposure and its correlated factors are associated with greater risk for psychopathology during middle childhood. Cannabis use during pregnancy should be discouraged.

Genetic Liability to Cannabis Use Disorder and COVID-19 Hospitalization.

Behavioral and life style factors plausibly play a role in likelihood of being hospitalized for COVID-19. Genetic vulnerability to hospitalization after SARS-CoV2 infection may partially relate to comorbid behavioral risk factors, especially the use of combustible psychoactive substances. Paralleling the COVID-19 crisis has been increasingly permissive laws for recreational cannabis use. Cannabis Use Disorder (CUD) is a psychiatric disorder that is heritable and genetically correlated with respiratory disease, independent of tobacco smoking. By leveraging genome-wide association summary statistics of CUD and COVID-19, we find that at least 1/3 rd of the genetic vulnerability to COVID-19 overlaps with genomic liability to CUD (rg=.34, p=0.0003). Genetic causality as a potential mechanism of risk could not be excluded. The association between CUD and COVID-19 remained when accounting for genetics of trying marijuana, tobacco smoking (ever smoking regularly, cigarettes per day, smoking cessation, age of smoking initiation), BMI, fasting glucose, forced expiration volume, education attainment, and Townsend deprivation index. Heavy problematic cannabis use may increase chances of hospitalization due to COVID-19 respiratory complications. Curbing excessive cannabis use may be an essential strategy in COVID-19 mitigation.