Whole genome sequence study of cannabis dependence in two independent cohorts

Genetic Risk for Alcohol Use Disorder in Relation to Individual Symptom Criteria: Do Polygenic Indices Provide Unique Information for Understanding Severity and Heterogeneity?

Alcohol Use Disorder (AUD) is a heterogenous category with many unique configurations of symptoms. Previous investigations of AUD heterogeneity using molecular genetics methods studied the association between genetic liability and individual AUD symptoms at the latent level or focusing on a small number of genetic variants. Notably, these studies did not investigate potential severity differences between symptoms in their genetic analyses. Therefore, the current study aimed to examine the genetic risk for individual AUD symptom criteria by using a polygenic risk score (PRS) approach to assess the relative severity of each AUD symptom and test for associates with AUD symptoms above and beyond a unidimensional AUD construct. An AUD PRS was created using summary statistics obtained from published genome-wide association studies (GWAS), and Multiple Indicators Multiple Causes (MIMIC) models were employed to examine the effect of the PRS on overall AUD severity as well as on individual symptoms after accounting for this overall effect. The phenotypic severity of AUD symptoms was highly correlated with the genetic severity of AUD symptoms (r = 0.78). Results of MIMIC models indicated that the AUD PRS significantly predicted the AUD factor. Regression paths testing the unique, direct effects of the PRS on individual AUD symptoms, independent of the latent AUD factor, were not significant. These results imply that PRSs derived from GWAS of AUD influence symptom expression through a single genetic factor that is highly correlated with the relative severity of individual symptoms when measured at the phenotypic level. Item-level GWAS of AUD symptoms are needed to further parse heterogeneous symptom expression and allow for more nuanced tests of these conclusions.

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.

Astrocytic transcriptional and epigenetic mechanisms of drug addiction

Addiction is a leading cause of disease burden worldwide and remains a challenge in current neuroscience research. Drug-induced lasting changes in gene expression are mediated by transcriptional and epigenetic regulation in the brain and are thought to underlie behavioral adaptations. Emerging evidence implicates astrocytes in regulating drug-seeking behaviors and demonstrates robust transcriptional response to several substances of abuse. This review focuses on the astrocytic transcriptional and epigenetic mechanisms of drug action.

Pleiotropic loci for cannabis use disorder severity in multi-ancestry high-risk populations

Cannabis use disorder (CUD) is common and has in part a genetic basis. The risk factors underlying its development likely involve multiple genes that are polygenetic and interact with each other and the environment to ultimately lead to the disorder. Co-morbidity and genetic correlations have been identified between CUD and other disorders and traits in select populations primarily of European descent. If two or more traits, such as CUD and another disorder, are affected by the same genetic locus, they are said to be pleiotropic. The present study aimed to identify specific pleiotropic loci for the severity level of CUD in three high-risk population cohorts: American Indians (AI), Mexican Americans (MA), and European Americans (EA). Using a previously developed computational method based on a machine learning technique, we leveraged the entire GWAS catalog and identified 114, 119, and 165 potentially pleiotropic variants for CUD severity in AI, MA, and EA respectively. Ten pleiotropic loci were shared between the cohorts although the exact variants from each cohort differed. While majority of the pleiotropic genes were distinct in each cohort, they converged on numerous enriched biological pathways. The gene ontology terms associated with the pleiotropic genes were predominately related to synaptic functions and neurodevelopment. Notable pathways included Wnt/β-catenin signaling, lipoprotein assembly, response to UV radiation, and components of the complement system. The pleiotropic genes were the most significantly differentially expressed in frontal cortex and coronary artery, up-regulated in adipose tissue, and down-regulated in testis, prostate, and ovary. They were significantly up-regulated in most brain tissues but were down-regulated in the cerebellum and hypothalamus. Our study is the first to attempt a large-scale pleiotropy detection scan for CUD severity. Our findings suggest that the different population cohorts may have distinct genetic factors for CUD, however they share pleiotropic genes from underlying pathways related to Alzheimer's disease, neuroplasticity, immune response, and reproductive endocrine systems.

The genetic aetiology of cannabis use: from twin models to genome-wide association studies and beyond

Cannabis is among the most widely consumed psychoactive substances worldwide. Individual differences in cannabis use phenotypes can partly be explained by genetic differences. Technical and methodological advances have increased our understanding of the genetic aetiology of cannabis use. This narrative review discusses the genetic literature on cannabis use, covering twin, linkage, and candidate-gene studies, and the more recent genome-wide association studies (GWASs), as well as the interplay between genetic and environmental factors. Not only do we focus on the insights that these methods have provided on the genetic aetiology of cannabis use, but also on how they have helped to clarify the relationship between cannabis use and co-occurring traits, such as the use of other substances and mental health disorders. Twin studies have shown that cannabis use is moderately heritable, with higher heritability estimates for more severe phases of use. Linkage and candidate-gene studies have been largely unsuccessful, while GWASs so far only explain a small portion of the heritability. Dozens of genetic variants predictive of cannabis use have been identified, located in genes such as CADM2, FOXP2, and CHRNA2. Studies that applied multivariate methods (twin models, genetic correlation analysis, polygenic score analysis, genomic structural equation modelling, Mendelian randomisation) indicate that there is considerable genetic overlap between cannabis use and other traits (especially other substances and externalising disorders) and some evidence for causal relationships (most convincingly for schizophrenia). We end our review by discussing implications of these findings and suggestions for future work.

Association of Predicted Expression and Multimodel Association Analysis of Substance Abuse Traits

Introduction

Genome-wide association studies (GWAS) have played a critical role in identifying many thousands of loci associated with complex phenotypes and diseases. This has led to several translations of novel disease susceptibility genes into drug targets and care. This however has not been the case for analyses where sample sizes are small, which suffer from multiple comparisons testing. The present study examined the statistical impact of combining a burden test methodology, PrediXcan, with a multimodel meta-analysis, cross phenotype association (CPASSOC).

Methods

The analysis was conducted on 5 addiction traits: family alcoholism, cannabis craving, alcohol, nicotine, and cannabis dependence and 10 brain tissues: anterior cingulate cortex BA24, cerebellar hemisphere, cortex, hippocampus, nucleus accumbens basal ganglia, caudate basal ganglia, cerebellum, frontal cortex BA9, hypothalamus, and putamen basal ganglia. Our sample consisted of 1,640 participants from the University of California, San Francisco (UCSF) Family Alcoholism Study. Genotypes were obtained through low pass whole genome sequencing and the use of Thunder, a linkage disequilibrium variant caller.

Results

The post-PrediXcan, gene-phenotype association without aggregation resulted in 2 significant results, HCG27 and SPPL2B. Aggregating across phenotypes resulted no significant findings. Aggregating across tissues resulted in 15 significant and 5 suggestive associations: PPIE, RPL36AL, FOXN2, MTERF4, SEPTIN2, CIAO3, RPL36AL, ZNF304, CCDC66, SSPOP, SLC7A9, LY75, MTRF1L, COA5, and RRP7A; RPS23, GNMT, ERV3-1, APIP, and HLA-B, respectively.

Discussion

Given the relatively small size of the cohort, this multimodel approach was able to find over a dozen significant associations between predicted gene expression and addiction traits. Of our findings, 8 had prior associations with similar phenotypes through investigation of the GWAS Atlas. With the onset of improved transcriptome data, this approach should increase in efficacy.

Effects of genetic risk for alcohol dependence and onset of regular drinking on the progression to alcohol dependence: A polygenic risk score approach

BACKGROUND

Prior studies have established the importance of genetic contributions to the etiology of alcohol dependence (AD), and suggested an early onset of alcohol use represents an initial marker of this genetic risk, which is associated with a more rapid progression to AD and increased risk for AD itself. Building on prior work, the current study examined whether the additive effects of AD risk variants predicted the rate of progression to AD from the onset of regular drinking, a drinking milestone with high clinical relevance to AD prevention.

METHODS

Data from 1501 European-ancestry adults from the University of California - San Francisco Family Alcoholism Study were used to examine whether polygenic risk scores for AD (PRS_AD) and age-at-onset of regular drinking contributed uniquely to the likelihood of having a lifetime AD diagnosis and the rate of progression from regular drinking to AD. Mixed effects logistic regression and Cox proportional hazards regression analyses were employed.

RESULTS

Increases in PRS_AD were associated with a faster progression from regular drinking to AD independent of age-at-onset of regular drinking. An independent effect of age-at-onset of regular drinking was also observed indicating that a one-year delay in regular drinking was associated with a 7% decrease in the hazard of progression to AD among drinkers with an early onset (≤ 18), but a 3% increase among drinkers with a late onset (> 18) of regular drinking.

CONCLUSIONS

These results broaden our understanding of the contributions of measured genotypes underlying AD-risk on the etiology and clinical course of AD.

Genomic and Personalized Medicine Approaches for Substance Use Disorders (SUDs) Looking at Genome-Wide Association Studies

Drug addiction, or substance use disorder (SUD), is a chronic, relapsing disorder in which compulsive drug-seeking and drug-taking behaviour persist despite serious negative consequences. Drug abuse represents a problem that deserves great attention from a social point of view, and focuses on the importance of genetic studies to help in understanding the genetic basis of addiction and its medical treatment. Despite the complexity of drug addiction disorders, and the high number of environmental variables playing a role in the onset, recurrence, and duration of the symptoms, several studies have highlighted the non-negligible role of genetics, as demonstrated by heritability and genome-wide association studies. A correlation between the relative risk of addiction to specific substances and heritability has been recently observed, suggesting that neurobiological mechanisms may be, at least in part, inherited. All these observations point towards a scenario where the core neurobiological factors of addiction, involving the reward system, impulsivity, compulsivity, stress, and anxiety response, are transmitted, and therefore, genes and mutations underlying their variation might be detected. In the last few years, the development of new and more efficient sequencing technologies has paved the way for large-scale studies in searching for genetic and epigenetic factors affecting drug addiction disorders and their treatments. These studies have been crucial to pinpoint single nucleotide polymorphisms (SNPs) in genes that affect the reaction to medical treatments. This is critically important to identify pharmacogenomic approaches for substance use disorder, such as OPRM1 SNPs and methadone required doses for maintenance treatment (MMT). Nevertheless, despite the promising results obtained by genome-wide association and pharmacogenomic studies, specific studies related to population genetics diversity are lacking, undermining the overall applicability of the preliminary findings, and thus potentially affecting the portability and the accuracy of the genetic studies. In this review, focusing on cannabis, cocaine and heroin use, we report the state-of-the-art genomics and pharmacogenomics of SUDs, and the possible future perspectives related to medical treatment response in people that ask for assistance in solving drug-related problems.

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, abuse, and withdrawal: Cannabinergic mechanisms, clinical, and preclinical findings

Cannabis sativa is the most widely used illicit drug in the world. Its main psychoactive component is delta-9-tetrahydrocannabinol (THC), one of over 100 phytocannabinoid compounds produced by the cannabis plant. THC is the primary compound that drives cannabis abuse potential and is also used and prescribed medically for therapeutic qualities. Despite its therapeutic potential, a significant subpopulation of frequent cannabis or THC users will develop a drug use syndrome termed cannabis use disorder. Individuals suffering from cannabis use disorder exhibit many of the hallmarks of classical addictions including cravings, tolerance, and withdrawal symptoms. Currently, there are no efficacious treatments for cannabis use disorder or withdrawal symptoms. This makes both clinical and preclinical research on the neurobiological mechanisms of these syndromes ever more pertinent. Indeed, basic research using animal models has provided valuable evidence of the neural molecular and cellular actions of cannabis that mediate its behavioral effects. One of the main components being central action on the cannabinoid type-one receptor and downstream intracellular signaling related to the endogenous cannabinoid system. Back-translational studies have provided insight linking preclinical basic and behavioral biology research to better understand symptoms observed at the clinical level. This narrative review aims to summarize major research elucidating the molecular, cellular, and behavioral manifestations of cannabis/THC use that play a role in cannabis use disorder and withdrawal.

Cannabis use and cannabis use disorder

Cannabis use disorder (CUD) is an underappreciated risk of using cannabis that affects ~10% of the 193 million cannabis users worldwide. The individual and public health burdens are less than those of other forms of drug use, but CUD accounts for a substantial proportion of persons seeking treatment for drug use disorders owing to the high global prevalence of cannabis use. Cognitive behavioural therapy, motivational enhancement therapy and contingency management can substantially reduce cannabis use and cannabis-related problems, but enduring abstinence is not a common outcome. No pharmacotherapies have been approved for cannabis use or CUD, although a number of drug classes (such as cannabinoid agonists) have shown promise and require more rigorous evaluation. Treatment of cannabis use and CUD is often complicated by comorbid mental health and other substance use disorders. The legalization of non-medical cannabis use in some high-income countries may increase the prevalence of CUD by making more potent cannabis products more readily available at a lower price. States that legalize medical and non-medical cannabis use should inform users about the risks of CUD and provide information on how to obtain assistance if they develop cannabis-related mental and/or physical health problems.

A Contagion Model for Within-Family Transmission of Drug Abuse

OBJECTIVE

The purpose of this study was to determine whether, controlling for genetic effects, drug abuse was transmitted within families as predicted by a contagion model.

METHODS

The authors examined 65,006 parent-offspring, sibling, and cousin pairs ascertained from Swedish population registries in which the primary case subject had a drug abuse registration. The rate of drug abuse registration among at-risk secondary case subjects ages 19-23 was studied. Utilizing matched control pairs, a difference-in-difference approach was used to infer causal effects.

RESULTS

In offspring, risk for drug abuse registration in the 3 years after an index registration of a parent residing in the same household, neighborhood, or municipality increased 5.9%, 3.4%, and 1.8%, respectively. For siblings of sibling index case subjects, parallel results were 5.9%, 3.9%, and 1.2%. For cousins of cousin index case subjects, excess risk for those in the same neighborhood or municipality was 2.9% and 0.9%, respectively. In all sets of relatives, drug abuse transmission was strongest in male-male pairs and in pairs closest in age. In sibling pairs, stronger transmission was observed in older to younger siblings compared with younger to older siblings. Transmission was stronger within than across the two drug classes with sufficient data (opiates and cannabis).

CONCLUSIONS

These results suggest that drug abuse can be transmitted within families by an environmentally mediated temporally defined model of contagion. The most important methodological limitation is that drug abuse registration is an inaccurate measure of the onset of drug abuse. Indeed, as predicted, drug abuse risk increased among potential secondary case subjects in the year before drug abuse registration of the index case subject.

Gene variants and educational attainment in cannabis use: mediating role of DNA methylation

Genetic and sociodemographic risk factors potentially associated with cannabis use (CU) were investigated in 40 cannabis users and 96 control subjects. DNA methylation analyses were also performed to explore the possibility of epigenetic changes related to CU. We conducted a candidate gene association study that included variants involved in the dopaminergic (ANKK1, NCAM1 genes) and endocannabinoid (CNR1, CNR2 gene) pathways. Sociodemographic data included gender, marital status, level of education, and body mass index. We used MeDIP-qPCR to test whether variations in DNA methylation might be associated with CU. We found a significant association between SNP rs1049353 of CNR1 gene (p = 0.01) and CU. Differences were also observed related to rs2501431 of CNR2 gene (p = 0.058). A higher education level appears to decrease the risk of CU. Interestingly, females were less likely to use cannabis than males. There was a significantly higher level of DNA methylation in cannabis users compared to controls in two of the genes tested: hypermethylation at exon 8 of DRD2 gene (p = 0.034) and at the CpG-rich region in the NCAM1 gene (p = 0.0004). Both genetic variants and educational attainment were also related to CU. The higher rate of DNA methylation, evidenced among cannabis users, may be either a marker of CU or a consequence of long-term exposure to cannabis. The identified genetic variants and the differentially methylated regions may represent biomarkers and/or potential targets for designs of pharmacological therapeutic agents. Our observations also suggest that educational programs may be useful strategies for CU prevention.