In a recent study submitted to the medRxiv preprint server, researchers identified genetic loci associated with lifetime and heavy cannabis use and analyzed their patterns, genetic patterns, and clinical effects.
Research: Genome-wide association study of lifetime and cannabis use in 131,895 people. Image Credit: Janon Stock / Shutterstock.com
* Important notice: medRxiv Previously published scientific reports are not peer-reviewed and, therefore, should not be considered definitive, guiding clinical practice. /health behavior, or treated as concrete information.
Reasons for using cannabis
In 2020, an estimated 209 million people worldwide reported using cannabis, a number that is expected to rise with increasing legalization. Although cannabis is used for medical purposes, evidence shows that the use of this drug has negative effects on the mind, spirit, and body.
Up to 27% of users may develop cannabis use disorder (CUD). The causes of CUD remain unclear; however, between 51-78% of CUD cases are treatable.
Recent genome-wide association studies (GWAS) have identified several loci associated with CUD; however, these studies focus on severe addiction and ignore other aspects of use. Therefore, more research is needed to better understand the genetic and environmental factors that cause cannabis use and its progression to CUD.
About the study
GWASs for lifetime and frequency of cannabis use involving men and women 23andMe study European researchers of similar proportions who completed an online survey under an informed consent. Participants were asked if they had ever used marijuana and, if yes, the number of days they had used it during the 30 heaviest days. GWASs analyzed up to 33,419,581 gene sequence comparisons using linear regression and included age, sex, major genetic groups, and genotype-based markers as covariates.
Functional annotation of single nucleotide polymorphisms (SNPs) was performed using the Mapping and Annotation (FUMA) method to identify novel SNPs and genes. Multiplexed GenoMic Annotation (MAGMA)-based method to detect SNPs in protein-encoded genes and to analyze the expression of specific genes.
Hi-C hybrid (H)-MAGMA hybridization of chromatin network data from human brain tissue assigns nonspecific SNPs to genes. S-PrediXcan identifies Expression Quantitative Trait Locus (eQTL)-associated genes associated with cannabis use through a comprehensive association analysis .
Linkage Disequilibrium Score regression (LDSC) calculates the SNP-based gene and gene sequence with 292 traits. The Polygenic score (PGS) analyzes the sample between the four PGS cannabis use and cannabis characteristics in the All of Us (AoU) Research Programme.
Special and general research at the Vanderbilt University Medical Center’s Biobank (BioVU) has examined clinical liability and research findings by related to the use of cannabis PGSs. In this context, it was used statistical modeling and sensitivity analysis based on the discussion of drug use.
Research findings
The study group, mostly women with a mean age of 52.8 years, provided information on lifetime and frequency of cannabis use. Quality control procedures ensured SNP integrity, with multiple breeding sites indicating minimal the population. The baseline SNP was 12.88% for lifetime cannabis use and 4.12% for regular use.
Two key loci for lifelong cannabis use were found on chromosomes three and seven. The most important SNP, rs11922956, on CADM2, replicated the previous findings, while also showing a novel SNP, rs12673181, near GRM3. For the greater use of cannabis, rs4856591 near CADM2 showed a significant association and was in a neutral association with rs11922956.
GWASs for lifetime and frequency of cannabis use have identified significant associations with the cell 93 adhesion molecule 2 gene (CADM2) and metabotropic glutamate receptor 3 gene (GRM3). Genetic and transcriptome-wide genetic analysis identified 40 genes associated with cannabis use in lifetime and four with normal use, and CADM2 is the only grease attached.
Genetic associations were found with mental, emotional, and physical health, suggesting a causal link between longevity and obesity. use of cannabis. Positive psychosocial associations were observed between cannabis use and other substance use behaviors, including CUD.
The PGS examines patterns with cannabis use behavior in the AoU cohort. Lifetime cannabis use of PGS was significantly associated with lifetime, daily, and problematic cannabis use.
In the BioVU cohort, clinical studies and laboratory studies (PheWAS/LabWAS) showed associations between the lifetime of cannabis use PGS and disease and infectious diseases. Some associations persisted even after controlling for CUD and tobacco use (TUD).
Lifetime cannabis use in PGS was positively associated with psychiatric disorders such as TUD, drug addiction, psychotic disorders, anxiety, depression, bipolar disorder, and suicide. Positive associations were also found with infectious diseases such as human immunodeficiency virus (HIV) and viral hepatitis.
Negative correlations have been observed in celiac disease and some blood markers. Immune markers such as leukocytes and complement factor 4 (C4) showed positive associations with lifetime cannabis use.
Conclusion
The present study provides new GWAS for lifetime and prevalence of cannabis use in a large European cohort. Significant associations were found with CADM2 and a new locus near GRM3, with both traits showing structural associations with drug use, including CUD. In addition, PGS associated with cannabis use phenotypes show relationships to mental disorders, anxiety, infectious diseases, and red blood cell biomarkers.
Together, these studies highlight the specific factors that influence cannabis use and its health effects, and support the importance of cannabis use phenotypes in genetic research.
* Important notice: medRxiv Previously published scientific reports are not peer-reviewed and, therefore, should not be considered definitive, guiding clinical practice. /health behavior, or treated as concrete information.
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