Study links lifetime cannabis use with substance use, mood disorders, celiac, and infectious diseases

In a recent study posted to the medRxiv preprint server, researchers identified genetic loci associated with the lifetime and frequency of cannabis use and explored their heritability, genetic correlations, and clinical implications. 

Study: Genome-wide association studies of lifetime and frequency cannabis use in 131,895 individuals. Image Credit: Janon Stock / Shutterstock.com

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

The causes of cannabis use disorder

In 2020, approximately 209 million people globally reported using cannabis, a number that is expected to rise with increasing decriminalization. While cannabis is used for medicinal purposes, evidence indicates the use of this drug has adverse psychiatric, cognitive, and physical effects.

Up to 27% of users may develop cannabis use disorder (CUD). The factors that contribute to CUD remain unclear; however, between 51-78% of CUD cases may be heritable.

Recent genome-wide association studies (GWAS) have identified numerous loci associated with CUD; however, these studies focus on extreme addiction and overlook other stages of use. Thus, further research is needed to understand better the genetic and environmental factors contributing to cannabis use and its progression to CUD.

About the study 

GWASs for lifetime and frequency of cannabis use involved male and female 23andMe research participants of European genetic similarity who completed an online survey under an approved protocol. Study participants were asked if they had ever used marijuana and, if yes, the number of days used during their heaviest 30 days. GWASs analyzed up to 33,419,581 imputed genetic variants using linear regression and included age, sex, genetic principal components, and genotype platform indicators as covariates.

Functional annotation of single nucleotide polymorphisms (SNPs) was performed using the Functional Mapping and Annotation (FUMA) platform to identify novel SNPs and genes. Multi-marker Analysis of GenoMic Annotation (MAGMA) gene-based and pathway analyses annotated SNPs to protein-coding genes and assessed tissue-specific gene expression.

Hi-C coupled (H)-MAGMA incorporated chromatin interaction profiles from human brain tissue to assign non-coding SNPs to genes. S-PrediXcan identified Expression Quantitative Trait Locus (eQTL)-linked genes associated with cannabis use through a transcriptome-wide association study.

Linkage Disequilibrium Score regression (LDSC) calculated SNP-based heritability and genetic correlations with 292 traits. Polygenic score (PGS) analyses tested associations between cannabis use PGSs and cannabis traits in the All of Us (AoU) Research Program.

Phenome- and laboratory-wide association analyses in the Vanderbilt University Medical Center’s Biobank (BioVU) cohort examined medical condition liability and laboratory biomarkers in relation to cannabis use PGSs. To this end, logistic regression models and sensitivity analyses were utilized to account for substance use disorder mediation.

Study findings 

The study cohort, which was predominantly female with a mean age of 52.8 years, provided data on the lifetime and frequency of cannabis use. Quality control measures ensured SNP integrity, with genomic control inflation factors indicating minimal population stratification. SNP-based heritability was 12.88% for lifetime cannabis use and 4.12% for frequency of use.

Two significant loci for lifetime cannabis use were found on chromosomes three and seven. The most significant SNP, rs11922956, upstream of CADM2, replicated previous findings, while a novel SNP, rs12673181, near GRM3, was also identified. For frequency of cannabis use, rs4856591 near CADM2 showed a significant association and was in linkage disequilibrium with rs11922956.

GWASs for lifetime and frequency of cannabis use identified significant associations with the cell 93 adhesion molecule 2 gene (CADM2) and metabotropic glutamate receptor 3 gene (GRM3). Gene-based and transcriptome-wide association study analyses identified 40 genes associated with lifetime cannabis use and four with frequency of use, with CADM2 being the only overlapping gene.

Genetic correlations were found with psychiatric, cognitive, and physical health traits, thus indicating partial genetic overlap between lifetime and frequency of cannabis use. Positive genetic correlations were observed between cannabis use and other substance use traits, including CUD.

PGS analyses tested associations with cannabis use traits in the AoU cohort. Lifetime cannabis use PGS was significantly associated with lifetime, daily, and problematic cannabis use.

In the BioVU cohort, phenome- and laboratory-wide association studies (PheWAS/LabWAS) analyses revealed associations between lifetime cannabis use PGS and various psychiatric and infectious diseases. Some associations persisted even after controlling for CUD and tobacco use disorder (TUD).

Lifetime cannabis use PGS was positively associated with psychiatric disorders such as TUD, substance addiction, mood disorders, anxiety, depression, bipolar disorder, and suicide ideation. Positive associations were also found with infectious diseases like human immunodeficiency virus (HIV) and viral hepatitis.

Negative associations were observed with celiac disease and certain blood biomarkers. Immune biomarkers like leukocytes and complement component 4 (C4) showed positive associations with lifetime cannabis use.

Conclusions 

The current study presents new GWASs for the lifetime and frequency of cannabis use in a large European cohort. Significant associations were found with CADM2 and a novel locus near GRM3, with both traits exhibiting genetic correlations with substance use, including CUD. Furthermore, PGSs associated with cannabis use phenotypes revealed links to mood disorders, anxiety, infectious diseases, and red blood cell biomarkers.

Taken together, these findings highlight the genetic factors influencing cannabis use and its health impacts, thus supporting the value of cannabis use phenotypes in genetic research.

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:
Vijay Kumar Malesu

Written by

Vijay Kumar Malesu

Vijay holds a Ph.D. in Biotechnology and possesses a deep passion for microbiology. His academic journey has allowed him to delve deeper into understanding the intricate world of microorganisms. Through his research and studies, he has gained expertise in various aspects of microbiology, which includes microbial genetics, microbial physiology, and microbial ecology. Vijay has six years of scientific research experience at renowned research institutes such as the Indian Council for Agricultural Research and KIIT University. He has worked on diverse projects in microbiology, biopolymers, and drug delivery. His contributions to these areas have provided him with a comprehensive understanding of the subject matter and the ability to tackle complex research challenges.    

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