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

Shared genetic architecture and bidirectional clinical risks within the psycho-metabolic nexus

BACKGROUND

Increasing evidence suggests a complex interplay between psychiatric disorders and metabolic dysregulations. However, most research has been limited to specific disorder pairs, leaving a significant gap in our understanding of the broader psycho-metabolic nexus.

METHODS

This study leveraged large-scale cohort data and genome-wide association study (GWAS) summary statistics, covering 8 common psychiatric disorders and 43 metabolic traits. We introduced a comprehensive analytical strategy to identify shared genetic bases sequentially, from key genetic correlation regions to local pleiotropy and pleiotropic genes. Finally, we developed polygenic risk score (PRS) models to translate these findings into clinical applications.

FINDINGS

We identified significant bidirectional clinical risks between psychiatric disorders and metabolic dysregulations among 310,848 participants from the UK Biobank. Genetic correlation analysis confirmed 104 robust trait pairs, revealing 1088 key genomic regions, including critical hotspots such as chr3: 47588462-50387742. Cross-trait meta-analysis uncovered 388 pleiotropic single nucleotide variants (SNVs) and 126 shared causal variants. Among variants, 45 novel SNVs were associated with psychiatric disorders and 75 novel SNVs were associated with metabolic traits, shedding light on new targets to unravel the mechanism of comorbidity. Notably, RBM6, a gene involved in alternative splicing and cellular stress response regulation, emerged as a key pleiotropic gene. When psychiatric and metabolic genetic information were integrated, PRS models demonstrated enhanced predictive power.

INTERPRETATION

The study highlights the intertwined genetic and clinical relationships between psychiatric disorders and metabolic dysregulations, emphasising the need for integrated approaches in diagnosis and treatment.

FUNDING

The National Key Research and Development Program of China (2023YFC2506200, SHH). The National Natural Science Foundation of China (82273741, SY).

The impact of schizophrenia genetic load and heavy cannabis use on the risk of psychotic disorder in the EU-GEI case-control and UK Biobank studies

BACKGROUND

The association between cannabis and psychosis is established, but the role of underlying genetics is unclear. We used data from the EU-GEI case-control study and UK Biobank to examine the independent and combined effect of heavy cannabis use and schizophrenia polygenic risk score (PRS) on risk for psychosis.

METHODS

Genome-wide association study summary statistics from the Psychiatric Genomics Consortium and the Genomic Psychiatry Cohort were used to calculate schizophrenia and cannabis use disorder (CUD) PRS for 1098 participants from the EU-GEI study and 143600 from the UK Biobank. Both datasets had information on cannabis use.

RESULTS

In both samples, schizophrenia PRS and cannabis use independently increased risk of psychosis. Schizophrenia PRS was not associated with patterns of cannabis use in the EU-GEI cases or controls or UK Biobank cases. It was associated with lifetime and daily cannabis use among UK Biobank participants without psychosis, but the effect was substantially reduced when CUD PRS was included in the model. In the EU-GEI sample, regular users of high-potency cannabis had the highest odds of being a case independently of schizophrenia PRS (OR daily use high-potency cannabis adjusted for PRS = 5.09, 95% CI 3.08-8.43, p = 3.21 × 10-10). We found no evidence of interaction between schizophrenia PRS and patterns of cannabis use.

CONCLUSIONS

Regular use of high-potency cannabis remains a strong predictor of psychotic disorder independently of schizophrenia PRS, which does not seem to be associated with heavy cannabis use. These are important findings at a time of increasing use and potency of cannabis worldwide.

Enriching ultra-high risk for psychosis cohorts based on accumulated exposure to environmental risk factors for psychotic disorders

BACKGROUND AND HYPOTHESIS

Transition to psychosis rates within ultra-high risk (UHR) services have been declining. It may be possible to 'enrich' UHR cohorts based on the environmental characteristics seen more commonly in first-episode psychosis cohorts. This study aimed to determine whether transition rates varied according to the accumulated exposure to environmental risk factors at the individual (migrant status, asylum seeker/refugee status, indigenous population, cannabis/methamphetamine use), family (family history or parental separation), and neighborhood (population density, social deprivation, and fragmentation) level.

METHODS

The study included UHR people aged 15-24 who attended the PACE clinic from 2012 to 2016. Cox proportional hazards models (frequentist and Bayesian) were used to assess the association between individual and accumulated factors and transition to psychosis. UHR status and transition was determined using the CAARMS. Benjamini-Hochberg was used to correct for multiple comparisons in frequentist analyses.

RESULTS

Of the 461 young people included, 55.5% were female and median follow-up was 307 days (IQR: 188-557) and 17.6% (n = 81) transitioned to a psychotic disorder. The proportion who transitioned increased incrementally according to the number of individual-level risk factors present (HR = 1.51, 95% CIs 1.19-1.93, p < 0.001, pcorr = 0.01). The number of family- and neighborhood-level exposures did not increase transition risk (p > 0.05). Cannabis use was the only specific risk factor significantly associated with transition (HR = 1.89, 95% CIs 1.22-2.93, pcorr = 0.03, BF = 6.74).

CONCLUSIONS

There is a dose-response relationship between exposure to individual-level psychosis-related environmental risk factors and transition risk in UHR patients. If replicated, this could be incorporated into a novel approach to identifying the highest-risk individuals within clinical services.

Comorbidity alters the genetic relationship between anxiety disorders and major depression

Importance-

There is extensive comorbidity between anxiety disorders (ANX) and major depression (MD). Most studies on the genetics of ANX do not exclude comorbid cases of MD, and vice versa, therefore confounding genetic association analyses. Disorder-specific analysis of genomic data may reveal more precise biological pathways and causal relationships.

Objective-

To investigate the genetic relationship between disorder-specific ANX and MD compared to samples with comorbidity, including their causal relationship.

Design Setting and Participants-

Data from UK Biobank was used to perform genome-wide association studies (GWAS) of ANX-only and MD-only, and generate disorder-specific polygenic risk scores (PRS). The Norwegian Mother, Father, and Child Cohort (MoBa) was used to test the associations of PRS with diagnosis and symptoms. MD and ANX GWAS data including comorbidities (MD-co and ANX-co) were used as comparators. Genetic correlation was assessed using LDSC, and Mendelian randomization was employed to infer causal relationships.

Main Outcomes and Measures

GWAS of ICD-10 diagnoses of ANX, MD, or both. Genetic correlations between pairs of ANX and MD phenotypes. PRS associations with diagnoses of ANX, MD, and their comorbid states, and anxiety or depressive symptoms.

Results-

The GWAS of ANX-only (9,980 cases and 179,442 controls) and MD-only (15,301 cases and 179,038 controls) showed a lower genetic correlation (0.53) than the one between ANX-co and MD-co (0.90). ANX-only showed a causal relationship with MD-only (PFDR=1.5e-02), but not vice versa, while comorbid cases showed a significant bidirectional causal relationship (PFDR=2.9e-12, PFDR =9.3e-06). The PRS-MD-only were differentially associated with MD-only compared to ANX-only cases (β= -0.08; 95%CI: -0.11, -0.03); however, this differential association was not observed for the PRS-MD-co. A similar pattern of differential association with anxiety and depressive symptoms was observed for PRS-ANX-only, but not for PRS-MD-co.

Conclusions and Relevance-

The genetics and underlying biology of ANX and MD are more distinct when comorbid cases are excluded from analyses and reveals that ANX may be causal for MD. This confounding of genetic relationships as a result of comorbidity is likely to apply to other psychiatric disorders. Disorder-specific genetic studies may help uncover more relevant biological mechanisms and guide more targeted clinical interventions.

The genetic landscape of substance use disorders

Substance use disorders represent a significant public health concern with considerable socioeconomic implications worldwide. Twin and family-based studies have long established a heritable component underlying these disorders. In recent years, genome-wide association studies of large, broadly phenotyped samples have identified regions of the genome that harbour genetic risk variants associated with substance use disorders. These regions have enabled the discovery of putative causal genes and improved our understanding of genetic relationships among substance use disorders and other traits. Furthermore, the integration of these data with clinical information has yielded promising insights into how individuals respond to medications, allowing for the development of personalized treatment approaches based on an individual's genetic profile. This review article provides an overview of recent advances in the genetics of substance use disorders and demonstrates how genetic data may be used to reduce the burden of disease and improve public health outcomes.

MeHA: A Computational Framework in Revealing the Genetic Basis of Animal Mental Health Traits Under an Intensive Farming System-A Case Study in Pigs

Intensively farmed animals such as pigs inevitably experience a certain degree of psychological stress, which leads to a reduction in production performance. Mental health traits are currently difficult to measure, resulting in a gap in understanding their genetic basis. To address this challenge, we propose a computational framework called mental health of animals (MeHA), capable of revealing genes related to animal mental health traits. Using MeHA, we identified 109 candidate genes associated with pig mental health and discovered their intricate connections with critical functions, such as memory, cognition, and neural development, which are essential components of mental health and cognitive performance. Importantly, our findings provide evidence of the potential impact of these genes on economically important traits, including meat quality and piglet survival. This research underscores the importance of genetic studies in enhancing our understanding of animal behavior and cognition, as well as promoting agricultural practices. By applying our approach to study the genetic basis of mental health in pigs as a case, we confirmed that our framework is an effective way to reveal genetic factors affecting animal mental health traits, which contributes to animal welfare and has potential implications for understanding human mental disorders.

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.

Leveraging the Genetics of Psychiatric Disorders to Prioritize Potential Drug Targets and Compounds

Background

Genetics has the potential to inform biologically relevant drug treatment and repurposing which may ultimately improve patient care. In this study, we combine methods which leverage the genetics of psychiatric disorders to prioritize potential drug targets and compounds.

Methods

We used the largest available genome-wide association studies, in European ancestry, of four psychiatric disorders [i.e., attention deficit hyperactivity disorder (ADHD), bipolar disorder, depression, and schizophrenia] along with genes encoding drug targets. With this data, we conducted drug enrichment analyses incorporating the novel and biologically specific GSA-MiXeR tool. We then conducted a series of molecular trait analyses using large-scale transcriptomic and proteomic datasets sampled from brain and blood tissue. This included the novel use of the UK Biobank proteomic data for a proteome-wide association study of psychiatric disorders. With the accumulated evidence, we prioritize potential drug targets and compounds for each disorder.

Findings

We reveal candidate drug targets shared across multiple disorders as well as disorder-specific targets. Drug prioritization indicated genetic support for several currently used psychotropic medications including the antipsychotic paliperidone as the top ranked drug for schizophrenia. We also observed genetic support for other commonly used psychotropics (e.g., clozapine, risperidone, duloxetine, lithium, and valproic acid). Opportunities for drug repurposing were revealed such as cholinergic drugs for ADHD, estrogens for depression, and gabapentin enacarbil for schizophrenia. Our findings also indicate the genetic liability to schizophrenia is associated with reduced brain and blood expression of CYP2D6, a gene encoding a metabolizer of drugs and neurotransmitters, suggesting a genetic risk for poor drug response and altered neurotransmission.

Interpretation

Here we present a series of complimentary and comprehensive analyses that highlight the utility of genetics for informing drug development and repurposing for psychiatric disorders. Our findings present novel opportunities for refining psychiatric treatment.

Genome-wide association studies of lifetime and frequency cannabis use in 131,895 individuals

Cannabis is one of the most widely used drugs globally. Decriminalization of cannabis is further increasing cannabis consumption. We performed genome-wide association studies (GWASs) of lifetime (N=131,895) and frequency (N=73,374) of cannabis use. Lifetime cannabis use GWAS identified two loci, one near CADM2 (rs11922956, p=2.40E-11) and another near GRM3 (rs12673181, p=6.90E-09). Frequency of use GWAS identified one locus near CADM2 (rs4856591, p=8.10E-09; r2 =0.76 with rs11922956). Both traits were heritable and genetically correlated with previous GWASs of lifetime use and cannabis use disorder (CUD), as well as other substance use and cognitive traits. Polygenic scores (PGSs) for lifetime and frequency of cannabis use associated cannabis use phenotypes in AllofUs participants. Phenome-wide association study of lifetime cannabis use PGS in a hospital cohort replicated associations with substance use and mood disorders, and uncovered associations with celiac and infectious diseases. This work demonstrates the value of GWASs of CUD transition risk factors.

The use and potential abuse of psychoactive plants in southern Africa: an overview of evidence and future potential

Background

Most Bantu ethnic groups in southern Africa utilize indigenous herbal medicines, some of which have psychoactive properties. Traditional medical practitioners (TMPs) commonly use them not only for divinatory purposes but to treat and manage mental and other illnesses. Unfortunately, the research on their results, risks, and benefits do not align. Little is known about their potential abuse among TMPs and community members in southern Africa. Herbal medicines are complex because whole plants are sometimes used, unlike in other treatments which use only one active ingredient. However, if the key mechanisms of action of these ethnomedicinal plants can be identified through socio-pharmacological research, useful botanical agents can be developed. A review of socio-pharmacological studies to evaluate the consequences of exposure to ethnomedicinal plants with psychoactive properties was conducted with the aim of identifying harm reduction strategies and investigating how the plants could be developed into useful botanicals.

Method

The search methods involved retrieval of records from PubMed/MEDLINE, Embase, Web of Science, Dissertations and Theses Global, and OpenGrey. The English language and human subjects were used as filters. In addition, some information was obtained from TMPs and community members.

Results

The following psychoactive plants were found to be commonly used or abused: Boophone disticha, Cannabis sativa, Datura stramonium, Leonotis leonurus, Psilocybe cubensis, and Sceletium tortuosum. The commercialization of Cannabis, L. leonurus, S. tortuosum, and Aspalathus is growing fast. The abuse liability of B. disticha, D. stramonium, and P. cubensis appears not to be appreciated. Five countries were found to have TMP policies and three with TMP Councils.

Conclusion

TMPs in the region are aware of the CNS effects of the identified psychoactive plants which can be explored further to develop therapeutic agents. There is a need to work closely with TMPs to reduce harm from the abuse of these plants.

Immigration status-related exclusive e-cigarette use and cannabis use and their dual use disparities associated with mental health disorder symptoms

INTRODUCTION

E-cigarette and cannabis use has been linked to various health risks, including respiratory and cardiovascular conditions. Yet, extant knowledge about the risk factors for exclusive and dual use of e-cigarettes and cannabis is limited, especially among immigrants. We examined exclusive e-cigarette and cannabis use and their dual use associated with mental health disorders among immigrants and U.S.-born.

METHODS

We analyzed national cross-sectional data collected between May 13, 2021, and January 9, 2022, among adults aged >18 years (n= 4766) living in U.S. Multinomial logistic regression analyses were conducted to model the associations of exclusivity and dual-use (reference group= non-use) with anxiety/depression.

RESULTS

The dual-use prevalence was higher than exclusive e-cigarette and cannabis use, especially among U.S.-born (dual use= 14.79% vs. cannabis use= 13.53% vs. e-cigarette use= 7.11%) compared to immigrants (dual use= 8.23% vs. cannabis use= 5.03% vs. e-cigarette use= 6.31%). Immigrants had lower risks of exclusive cannabis and dual use compared to U.S.-born. Anxiety/depression was associated with higher risks of exclusive cannabis use and dual use across immigration status, but was associated with exclusive e-cigarette use among only immigrants. While effect sizes of dual-use associated with anxiety/depression were higher among U.S.-born, the effect sizes of exclusive e-cigarette and cannabis use associated with anxiety/depression were higher among immigrants.

CONCLUSIONS

The findings revealed significant mental health risks for e-cigarette, cannabis, and their dual use among immigrants and U.S.-born, especially among U.S.-born. These findings highlight the need for public health research and interventions to consider immigration status-related disparities in substance use.

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.

Psychiatric disorders and brain white matter exhibit genetic overlap implicating developmental and neural cell biology

Improved understanding of the shared genetic architecture between psychiatric disorders and brain white matter may provide mechanistic insights for observed phenotypic associations. Our objective is to characterize the shared genetic architecture of bipolar disorder (BD), major depression (MD), and schizophrenia (SZ) with white matter fractional anisotropy (FA) and identify shared genetic loci to uncover biological underpinnings. We used genome-wide association study (GWAS) summary statistics for BD (n = 413,466), MD (n = 420,359), SZ (n = 320,404), and white matter FA (n = 33,292) to uncover the genetic architecture (i.e., polygenicity and discoverability) of each phenotype and their genetic overlap (i.e., genetic correlations, overlapping trait-influencing variants, and shared loci). This revealed that BD, MD, and SZ are at least 7-times more polygenic and less genetically discoverable than average FA. Even in the presence of weak genetic correlations (range = -0.05 to -0.09), average FA shared an estimated 42.5%, 43.0%, and 90.7% of trait-influencing variants as well as 12, 4, and 28 shared loci with BD, MD, and SZ, respectively. Shared variants were mapped to genes and tested for enrichment among gene-sets which implicated neurodevelopmental expression, neural cell types, myelin, and cell adhesion molecules. For BD and SZ, case vs control tract-level differences in FA associated with genetic correlations between those same tracts and the respective disorder (rBD = 0.83, p = 4.99e-7 and rSZ = 0.65, p = 5.79e-4). Genetic overlap at the tract-level was consistent with average FA results. Overall, these findings suggest a genetic basis for the involvement of brain white matter aberrations in the pathophysiology of psychiatric disorders.

An answered call for aid? Cannabinoid clinical framework for the opioid epidemic

BACKGROUND

The opioid crisis continues in full force, as physicians and caregivers are desperate for resources to help patients with opioid use and chronic pain disorders find safer and more accessible non-opioid tools.

MAIN BODY

The purpose of this article is to review the current state of the opioid epidemic; the shifting picture of cannabinoids; and the research, policy, and current events that make opioid risk reduction an urgent public health challenge. The provided table contains an evidence-based clinical framework for the utilization of cannabinoids to treat patients with chronic pain who are dependent on opioids, seeking alternatives to opioids, and tapering opioids.

CONCLUSION

Based on a comprehensive review of the literature and epidemiological evidence to date, cannabinoids stand to be one of the most interesting, safe, and accessible tools available to attenuate the devastation resulting from the misuse and abuse of opioid narcotics. Considering the urgency of the opioid epidemic and broadening of cannabinoid accessibility amidst absent prescribing guidelines, the authors recommend use of this clinical framework in the contexts of both clinical research continuity and patient care.

A Prospective Comparison of Bipolar I and II Subjects with and without Comorbid Cannabis Use Disorders from the COGA Dataset

OBJECTIVE

The comorbidity of alcohol and substance use disorders among persons with bipolar disorder is elevated, as indicated by epidemiological and clinical studies. Following alcohol use, cannabis is the most frequently used and abused illicit substance among bipolar individuals, and such use may lead to comorbid cannabis use disorders (CUD). Previous research indicated that CUDs were related to a more severe course of bipolar disorder and higher rates of other comorbid alcohol and substance use disorders. Few studies, however, have conducted longitudinal research on this comorbidity. The aim of this study is to investigate the influence of CUD on the course of bipolar I and II individuals during a 5-year follow-up.

METHODS

The characteristics of bipolar disorder, cannabis use disorders, and other alcohol and substance use disorders, as well as comorbid mental disorders, were assessed using a standardized semi-structured interview (SSAGA) at both baseline and the 5-year follow-up. N = 180 bipolar I and II patients were subdivided into groups of with and without comorbid cannabis use disorders (CUD).

RESULTS

Of the 77 bipolar I and 103 bipolar II patients, n = 65 (36.1%) had a comorbid diagnosis of any CUD (DSM-IV cannabis abuse or dependence). Comorbid bipolar patients with CUD had higher rates of other substance use disorders and posttraumatic stress disorders, more affective symptoms, and less psychosocial functioning at baseline and at 5-year follow-up. In contrast to previously reported findings, higher rates of anxiety disorders and bipolar disorder complications (e.g., mixed episodes, rapid cycling, and manic or hypomanic episodes) were not found. The effect of CUD on other substance use disorders was confirmed using moderation analyses.

CONCLUSIONS

A 5-year prospective evaluation of bipolar patients with and without CUD confirmed previous investigations, suggesting that the risk of other substance use disorders is significantly increased in comorbid individuals. CUD has a moderation effect, while no effect was found for other mental disorders. Findings from this study and previous research may be due to the examination of different phenotypes (Cannabis use vs. CUD) and sample variation (family study vs. clinical and epidemiological populations).