Polygenic risk scores for smoking: predictors for alcohol and cannabis use?

Associations between polygenic risk scores and accelerated brain ageing in smokers

BACKGROUND

Smoking contributes to a variety of neurodegenerative diseases and neurobiological abnormalities, suggesting that smoking is associated with accelerated brain aging. However, the neurobiological mechanisms affected by smoking, and whether they are genetically influenced, remain to be investigated.

METHODS

Using structural magnetic resonance imaging data from the UK Biobank (n = 33 293), a brain age predictor was trained on non-smoking healthy groups and tested on smokers to obtain the BrainAge Gap (BAG). The cumulative effect of multiple common genetic variants associated with smoking was then calculated to acquire a polygenic risk score (PRS). The relationship between PRS, BAG, total gray matter volume (tGMV), and smoking parameters was explored and further genes included in the PRS were annotated to identify potential molecular mechanisms affected by smoking.

RESULTS

The BrainAge in smokers was predicted with very high accuracy (r = 0.725, MAE = 4.16). Smokers had a greater BAG (Cohen's d = 0.074, p < 0.0001) and higher PRS (Cohen's d = 0.63, p < 0.0001) than non-smokers. A higher PRS was associated with increased amount of smoking, mediated by BAG and tGMV. Several neurotransmitters and ion channel pathways were enriched in the group of smoking-related genes involved in addiction, brain synaptic plasticity, and some neurological disorders.

CONCLUSION

By using a simplified single indicator of the entire brain (BAG) in combination with the PRS, this study highlights the greater BAG in smokers and its linkage with genes and smoking behavior, providing insight into the neurobiological underpinnings and potential features of smoking-related aging.

Associations of polygenic risk scores for smoking heaviness and lifetime cannabis use with tobacco and cannabis co-use trajectories among African Americans

BACKGROUND

We aimed to identify distinct trajectories of tobacco, cannabis, and their co-use among African Americans, and to investigate whether these patterns were associated with polygenic risk scores (PRS) for tobacco and cannabis use.

METHOD

Participants (N=428 participants; 50.9% male) were initially recruited for an elementary school-based prevention in a Mid-Atlantic city when they were in first grade. From ages 14-26, participants reported on their frequency of tobacco and cannabis use in the past year during annual assessments. DNA was collected from participants at age 21. PRS for smoking heaviness (i.e., cigarettes per day) and lifetime cannabis use were created based on genome-wide association study results derived from Liu et al. (2019) and Pasman et al. (2018), respectively.

RESULTS

We identified five distinct trajectories of tobacco and cannabis co-use, including (1) Low Tobacco and Cannabis Use, (2) Adolescent Limited Tobacco and Cannabis Use, (3) Experimental Cannabis, Young Adult Increasing Tobacco, (4) Experimental Tobacco, Young Adult Increasing Cannabis, and (5) High, Chronic Tobacco and Cannabis Use. Compared to the Low Tobacco and Cannabis Use subgroup, individuals in the High, Chronic Tobacco and Cannabis Use subgroup had greater PRS for smoking heaviness, and individuals in the Experimental Cannabis, Young Adult Increasing Tobacco subgroup had higher PRS for lifetime cannabis use.

CONCLUSIONS

Polygenic risk for lifetime cannabis use and smoking heaviness is associated with the developmental progression of tobacco and cannabis co-use among African Americans, furthering knowledge on the etiology of co-use in this population.

Risk for alcohol use problems in severe mental illness: Interactions with sex and racial/ethnic minority status

BACKGROUND

Alcohol use disorder (AUD) is exceedingly common among individuals with bipolar disorder and schizophrenia. However, studies on alcohol use in psychiatric illness rely largely on population surveys with limited representation of severe mental illness (SMI); schizophrenia and bipolar disorder.

METHODS

Using data from the Genomic Psychiatry Cohort (GPC) (Pato MT, 2013), associations of bipolar disorder and schizophrenia with alcohol use problems were examined in a diverse US based sample, considering the influence of self-described race (African Ancestry (AA), European Ancestry (EA), or Latinx Ancestry (LA)), sex, and tobacco use. Participants answered alcohol use problem items derived from the CAGE instrument, yielding a summed "probable" alcohol use disorder (pAUD) risk score.

RESULTS

This study included 1952 individuals with bipolar disorder with psychosis (BDwP), 409 with bipolar disorder without psychosis (BD), 9218 with schizophrenia (SCZ), and 10,416 unaffected individuals. We found that SMI (BDwP, BD, SCZ) was associated with elevated AUD risk scores (B = 0.223, p < 0.001), an association which was strongest in females, particularly those of AA and LA, and in tobacco users. Schizophrenia was associated with the greatest increase in pAUD score (B = 0.141, p < 0.001). pAUD risk scores were increased among participants with bipolar disorder, with greater increases in BDwP (B = 0.125, p < 0.001) than in BD without psychosis (B = 0.027, p < 0.001).

LIMITATIONS

Limitations include reliance on self-report data, screening items for AUD, voluntary recruitment bias, and differences in race/sex distribution between groups, which were statistically adjusted for in analytic models.

CONCLUSIONS

SMI is associated with risk for AUD, particularly among females from racial minority groups, smokers, and those with psychotic disorders.

Orbitofrontal cortex volume links polygenic risk for smoking with tobacco use in healthy adolescents

BACKGROUND

Tobacco smoking remains one of the leading causes of preventable illness and death and is heritable with complex underpinnings. Converging evidence suggests a contribution of the polygenic risk for smoking to the use of tobacco and other substances. Yet, the underlying brain mechanisms between the genetic risk and tobacco smoking remain poorly understood.

METHODS

Genomic, neuroimaging, and self-report data were acquired from a large cohort of adolescents from the IMAGEN study (a European multicenter study). Polygenic risk scores (PGRS) for smoking were calculated based on a genome-wide association study meta-analysis conducted by the Tobacco and Genetics Consortium. We examined the interrelationships among the genetic risk for smoking initiation, brain structure, and the number of occasions of tobacco use.

RESULTS

A higher smoking PGRS was significantly associated with both an increased number of occasions of tobacco use and smaller cortical volume of the right orbitofrontal cortex (OFC). Furthermore, reduced cortical volume within this cluster correlated with greater tobacco use. A subsequent path analysis suggested that the cortical volume within this cluster partially mediated the association between the genetic risk for smoking and the number of occasions of tobacco use.

CONCLUSIONS

Our data provide the first evidence for the involvement of the OFC in the relationship between smoking PGRS and tobacco use. Future studies of the molecular mechanisms underlying tobacco smoking should consider the mediation effect of the related neural structure.

Polygenic Score for Physical Activity Is Associated with Multiple Common Diseases

INTRODUCTION

Genetic pleiotropy, in which the same genes affect two or more traits, may partially explain the frequently observed associations between high physical activity (PA) and later reduced morbidity or mortality. This study investigated associations between PA polygenic risk scores (PRS) and cardiometabolic diseases among the Finnish population.

METHODS

PRS for device-measured overall PA were adapted to a FinnGen study cohort of 218,792 individuals with genomewide genotyping and extensive digital longitudinal health register data. Associations between PA PRS and body mass index, diseases, and mortality were analyzed with linear and logistic regression models.

RESULTS

A high PA PRS predicted a lower body mass index (β = -0.025 kg·m-2 per one SD change in PA PRS, SE = 0.013, P = 1.87 × 10-80). The PA PRS also predicted a lower risk for diseases that typically develop later in life or not at all among highly active individuals. A lower disease risk was systematically observed for cardiovascular diseases (odds ratio [OR] per 1 SD change in PA PRS = 0.95, P = 9.5 × 10-19) and, for example, hypertension [OR = 0.93, P = 2.7 × 10-44), type 2 diabetes (OR = 0.91, P = 4.1 × 10-42), and coronary heart disease (OR = 0.95, P = 1.2 × 10-9). Participants with high PA PRS had also lower mortality risk (OR = 0.97, P = 0.0003).

CONCLUSIONS

Genetically less active persons are at a higher risk of developing cardiometabolic diseases, which may partly explain the previously observed associations between low PA and higher disease and mortality risk. The same inherited physical fitness and metabolism-related mechanisms may be associated both with PA levels and with cardiometabolic disease risk.

Genetics of substance use disorders in the era of big data

Substance use disorders (SUDs) are conditions in which the use of legal or illegal substances, such as nicotine, alcohol or opioids, results in clinical and functional impairment. SUDs and, more generally, substance use are genetically complex traits that are enormously costly on an individual and societal basis. The past few years have seen remarkable progress in our understanding of the genetics, and therefore the biology, of substance use and abuse. Various studies - including of well-defined phenotypes in deeply phenotyped samples, as well as broadly defined phenotypes in meta-analysis and biobank samples - have revealed multiple risk loci for these common traits. A key emerging insight from this work establishes a biological and genetic distinction between quantity and/or frequency measures of substance use (which may involve low levels of use without dependence), versus symptoms related to physical dependence.

Multi-polygenic Analysis of Nicotine Dependence in Individuals of European Ancestry

INTRODUCTION

Heritability estimates of nicotine dependence (ND) range from 40-70%, but discovery GWAS of ND are underpowered and have limited predictive utility. In this work, we leverage genetically correlated traits and diseases to increase the accuracy of polygenic risk prediction.

METHODS

We employed a multi-trait model using summary statistic-based best linear unbiased predictors (SBLUP) of genetic correlates of DSM-IV diagnosis of ND in 6,394 individuals of European Ancestry (prevalence = 45.3%, %female = 46.8%, µage = 40.08 [s.d. = 10.43]) and 3,061 individuals from a nationally-representative sample with Fagerström Test for Nicotine Dependence symptom count (FTND; 51.32% female, mean age = 28.9 [s.d. = 1.70]). Polygenic predictors were derived from GWASs known to be phenotypically and genetically correlated with ND (i.e., Cigarettes per Day (CPD), the Alcohol Use Disorders Identification Test (AUDIT-Consumption and AUDIT-Problems), Neuroticism, Depression, Schizophrenia, Educational Attainment, Body Mass Index (BMI), and Self-Perceived Risk-Taking); including Height as a negative control. Analyses controlled for age, gender, study site, and the first 10 ancestral principal components.

RESULTS

The multi-trait model accounted for 3.6% of the total trait variance in DSM-IV ND. Educational Attainment (β=-0.125; 95% confidence interval (CI): [-0.149,-0.101]), CPD (0.071 [0.047,0.095]), and Self-Perceived Risk-Taking (0.051 [0.026,0.075]) were the most robust predictors. PGS effects on FTND were limited.

CONCLUSIONS

Risk for ND is not only polygenic, but also pleiotropic. Polygenic effects on ND that are accessible by these traits are limited in size and act additively to explain risk.

Genomics and epigenomics of addiction

Recent progress in the genomics and epigenomics of addiction has contributed to improving our understanding of this complex mental disorder's etiology, filling the gap between genes, environment, and behavior. We review the behavioral genetic studies reporting gene and environment interactions that explain the polygenetic contribution to the resilience and vulnerability to develop addiction. We discuss the evidence of polymorphic candidate genes that confer susceptibility to develop addiction as well as the studies of specific epigenetic marks that contribute to vulnerability and resilience to addictive-like behavior. A particular emphasis has been devoted to the miRNA changes that are considered potential biomarkers. The increasing knowledge about the technology required to alter miRNA expression may provide promising novel therapeutic tools. Finally, we give future directions for the field's progress in disentangling the connection between genes, environment, and behavior.

Genetic overlap and causality between substance use disorder and attention-deficit and hyperactivity disorder

Substance use disorder (SUD) often co-occur at high prevalence with other psychiatric conditions. Among them, attention-deficit and hyperactivity disorder (ADHD) is present in almost one out of every four subjects with SUD and is associated with higher severity, more frequent polysubstance dependence and increased risk for other mental health problems in SUD patients. Despite studies suggesting a genetic basis in the co-occurrence of these two conditions, the genetic factors involved in the joint development of both disorders and the mechanisms mediating these causal relationships are still unknown. In this study, we tested whether the genetic liability to five SUD-related phenotypes share a common background in the general population and clinically diagnosed ADHD individuals from an in-house sample of 989 subjects and further explored the genetic overlap and the causal relationship between ADHD and SUD using pre-existing GWAS datasets. Our results confirm a common genetic background between ADHD and SUD and support the current literature on the causal effect of the liability to ADHD on the risk for SUD. We added novel findings on the effect of the liability of lifetime cannabis use on ADHD and found evidence of shared genetic background underlying SUD in general population and in ADHD, at least for lifetime cannabis use, alcohol dependence and smoking initiation. These findings are in agreement with the high comorbidity observed between ADHD and SUD and highlight the need to control for substance use in ADHD and to screen for ADHD comorbidity in all SUD patients to provide optimal clinical interventions.

Evaluating the genetic effects of sex hormone traits on the development of mental traits: a polygenic score analysis and gene-environment-wide interaction study in UK Biobank cohort

OBJECTIVE

To evaluate the genetic effects of sex hormone traits on the development of mental traits in middle-aged adults.

METHODS

The SNPs associated with sex hormone traits were derived from a two-stage genome-wide association study (GWAS). Four sex hormone traits were selected in the current study, including sex hormone-binding globulin (SHBG), testosterone, bioavailable testosterone and estradiol. The polygenic risk score (PRS) of sex hormone traits were calculated from individual-level genotype data of the United Kingdom (UK) Biobank cohort. We then used logistic and linear regression models to assess the associations between individual PRS of sex hormone traits and the frequency of alcohol consumption, anxiety, intelligence and so on. Finally, gene-environment-wide interaction study (GEWIS) was performed to detect novel candidate genes interacting with the sex hormone traits on the development of fluid intelligence and the frequency of smoking and alcohol consumption by PLINK2.0.

RESULTS

We observed positive association between SHBG and the frequency of alcohol consumption (b = 0.0101, p = 3.84 × 10-11) in middle-aged males and females. In addition, estradiol was positively associated with the frequency of alcohol consumption (b = 0.0128, p = 1.96 × 10-8) in middle-aged males. Moreover, bioavailable testosterone was associated with the fluid intelligence (b = - 0.0136, p = 5.74 × 10-5) in middle-aged females. Finally, GEWIS identified one significant loci, Tenascin R (TNR) (rs34633780, p = 3.45 × 10-8) interacting with total testosterone for fluid intelligence.

CONCLUSION

Our study results support the genetic effects of sex hormone traits on the development of intelligence and the frequency of alcohol consumption in middle-aged adults in UK.

Illicit drug use and the genetic overlap with Cannabis use

BACKGROUND

The use of illicit substances is correlated, meaning that individuals who use one illicit substance are more likely to also use another illicit substance. This association could (partly) be explained by overlapping genetic factors. Genetic overlap may indicate a common underlying genetic predisposition, or can be the result of a causal association.

METHODS

Polygenic scores for lifetime cannabis use were generated in a sample of Dutch participants (N = 8348). We tested the association of a PGS for cannabis use with ecstasy, stimulants and a broad category of illicit drug use. To explore the nature of the relationship: (1) these analyses were repeated separately in cannabis users and non-users and (2) monozogytic twin pairs discordant for cannabis use were compared on their drug use.

RESULTS

The lifetime prevalence was 24.8 % for cannabis, 6.2 % for ecstasy, 6.5 % for stimulants and 7.1 % for any illicit drug use. Significant, positive associations were found between PGS for cannabis use with ecstasy use, stimulants and any illicit drug use. These associations seemed to be stronger in cannabis users compared to non-users for both ecstasy and stimulant use, but only in people born after 1968 and not significant after correction for multiple testing. The discordant twin pair analyses suggested that cannabis use could play a causal role in drug use.

CONCLUSIONS

The genetic liability underlying cannabis use significantly explained variability in ecstasy, stimulant and any illicit drug use. Further research should further explore the underlying mechanism to understand the nature of the association.

Genetic Vulnerability for Smoking and Cannabis Use: Associations With E-Cigarette and Water Pipe Use

INTRODUCTION

Cigarette smoking and cannabis use are heritable traits and share, at least in part, a common genetic substrate. In recent years, the prevalence of alternative methods of nicotine intakes, such as electronic cigarette (e-cigarette) and water pipe use, has risen substantially. We tested whether the genetic vulnerability underlying cigarettes smoking and cannabis use explained variability in e-cigarette and water pipe use phenotypes, as these vaping methods are alternatives for smoking tobacco cigarettes and joints.

METHODS

On the basis of the summary statistics of the International Cannabis Consortium and the Tobacco and Genetics Consortium, we generated polygenic risk scores (PRSs) for smoking and cannabis use traits, and used these to predict e-cigarette and water pipe use phenotypes in a sample of 5025 individuals from the Netherlands Twin Register.

RESULTS

PRSs for cigarettes per day were positively associated with lifetime e-cigarette use and early initiation of water pipe use, but only in ex-smokers (odds ratio = 1.43, R2 = 1.56%, p = .011) and never cigarette smokers (odds ratio = 1.35, R2 = 1.60%, p = .013) respectively.

CONCLUSIONS

Most associations of PRSs for cigarette smoking and cannabis use with e-cigarette and water pipe use were not significant, potentially due to a lack of power. The significant associations between genetic liability to smoking heaviness with e-cigarette and water pipe phenotypes are in line with studies indicating a common genetic background for substance-use phenotypes. These associations emerged only in nonsmokers, and future studies should investigate the nature of this observation.

IMPLICATIONS

Our study showed that genetic vulnerability to smoking heaviness is associated with lifetime e-cigarette use and age at initiation of water pipe use. This finding has implications for the current debate on whether alternative smoking methods, such as usage of vaping devices, predispose to smoking initiation and related behaviors.

Redefining phenotypes to advance psychiatric genetics: Implications from hierarchical taxonomy of psychopathology

Genetic discovery in psychiatry and clinical psychology is hindered by suboptimal phenotypic definitions. We argue that the hierarchical, dimensional, and data-driven classification system proposed by the Hierarchical Taxonomy of Psychopathology (HiTOP) consortium provides a more effective approach to identifying genes that underlie mental disorders, and to studying psychiatric etiology, than current diagnostic categories. Specifically, genes are expected to operate at different levels of the HiTOP hierarchy, with some highly pleiotropic genes influencing higher order psychopathology (e.g., the general factor), whereas other genes conferring more specific risk for individual spectra (e.g., internalizing), subfactors (e.g., fear disorders), or narrow symptoms (e.g., mood instability). We propose that the HiTOP model aligns well with the current understanding of the higher order genetic structure of psychopathology that has emerged from a large body of family and twin studies. We also discuss the convergence between the HiTOP model and findings from recent molecular studies of psychopathology indicating broad genetic pleiotropy, such as cross-disorder SNP-based shared genetic covariance and polygenic risk scores, and we highlight molecular genetic studies that have successfully redefined phenotypes to enhance precision and statistical power. Finally, we suggest how to integrate a HiTOP approach into future molecular genetic research, including quantitative and hierarchical assessment tools for future data-collection and recommendations concerning phenotypic analyses. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Genomic prediction of alcohol-related morbidity and mortality

While polygenic risk scores (PRS) have been shown to predict many diseases and risk factors, the potential of genomic prediction in harm caused by alcohol use has not yet been extensively studied. Here, we built a novel polygenic risk score of 1.1 million variants for alcohol consumption and studied its predictive capacity in 96,499 participants from the FinnGen study and 39,695 participants from prospective cohorts with detailed baseline data and up to 25 years of follow-up time. A 1 SD increase in the PRS was associated with 11.2 g (=0.93 drinks) higher weekly alcohol consumption (CI = 9.85-12.58 g, p = 2.3 × 10-58). The PRS was associated with alcohol-related morbidity (4785 incident events) and the risk estimate between the highest and lowest quintiles of the PRS was 1.83 (95% CI = 1.66-2.01, p = 1.6 × 10-36). When adjusted for self-reported alcohol consumption, education, marital status, and gamma-glutamyl transferase blood levels in 28,639 participants with comprehensive baseline data from prospective cohorts, the risk estimate between the highest and lowest quintiles of the PRS was 1.58 (CI = 1.26-1.99, p = 8.2 × 10-5). The PRS was also associated with all-cause mortality with a risk estimate of 1.33 between the highest and lowest quintiles (CI = 1.20-1.47, p = 4.5 × 10-8) in the adjusted model. In conclusion, the PRS for alcohol consumption independently associates for both alcohol-related morbidity and all-cause mortality. Together, these findings underline the importance of heritable factors in alcohol-related health burden while highlighting how measured genetic risk for an important behavioral risk factor can be used to predict related health outcomes.

Genome-Wide Association Study of Opioid Cessation

The United States is experiencing an epidemic of opioid use disorder (OUD) and overdose-related deaths. However, the genetic basis for the ability to discontinue opioid use has not been investigated. We performed a genome-wide association study (GWAS) of opioid cessation (defined as abstinence from illicit opioids for >1 year or <6 months before the interview date) in 1130 African American (AA) and 2919 European ancestry (EA) participants recruited for genetic studies of substance use disorders and who met lifetime Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) criteria for OUD. Association tests performed separately within each ethnic group were combined by meta-analysis with results obtained from the Comorbidity and Trauma Study. Although there were no genome-wide significant associations, we found suggestive associations with nine independent loci, including three which are biologically relevant: rs4740988 in PTPRD (p_{AA + EA} = 2.24 × 10⁻⁶), rs36098404 in MYOM2 (p_EA = 2.24 × 10⁻⁶), and rs592026 in SNAP25-AS1 (p_EA = 6.53 × 10⁻⁶). Significant pathways identified in persons of European ancestry (EA) are related to vitamin D metabolism (p = 3.79 × 10⁻²) and fibroblast growth factor (FGF) signaling (p = 2.39 × 10⁻²). UK Biobank traits including smoking and drinking cessation and chronic back pain were significantly associated with opioid cessation using GWAS-derived polygenic risk scores. These results provide evidence for genetic influences on opioid cessation, suggest genetic overlap with other relevant traits, and may indicate potential novel therapeutic targets for OUD.

Associations between polygenic risk for tobacco and alcohol use and liability to tobacco and alcohol use, and psychiatric disorders in an independent sample of 13,999 Australian adults

BACKGROUND

Substance use, substance use disorders (SUDs), and psychiatric disorders commonly co-occur. Genetic risk common to these complex traits is an important explanation; however, little is known about how polygenic risk for tobacco or alcohol use overlaps the genetic risk for the comorbid SUDs and psychiatric disorders.

METHODS

We constructed polygenic risk scores (PRSs) using GWAS meta-analysis summary statistics from a large discovery sample, GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN), for smoking initiation (SI; N = 631,564), age of initiating regular smoking (AI; N = 258,251), cigarettes per day (CPD; N = 258,999), smoking cessation (SC; N = 312,273), and drinks per week (DPW; N = 527,402). We then estimated the fixed effect of these PRSs on the liability to 15 phenotypes related to tobacco and alcohol use, substance use disorders, and psychiatric disorders in an independent target sample of Australian adults.

RESULTS

After adjusting for multiple testing, 10 of 75 combinations of discovery and target phenotypes remained significant. PRS-SI (R² range: 1.98%-5.09 %) was positively associated with SI, DPW, and with DSM-IV and FTND nicotine dependence, and conduct disorder. PRS-AI (R²: 3.91 %) negatively associated with DPW. PRS-CPD (R²: 1.56 %-1.77 %) positively associated with DSM-IV nicotine dependence and conduct disorder. PRS-DPW (R²: 3.39 %-6.26 %) positively associated with only DPW. The variation of DPW was significantly influenced by sex*PRS-SI, sex*PRS-AI and sex*PRS-DPW. Such interaction effect was not detected in the other 14 phenotypes.

CONCLUSIONS

Polygenic risks associated with tobacco use are also associated with liability to alcohol consumption, nicotine dependence, and conduct disorder.

Psychosocial moderation of polygenic risk for cannabis involvement: the role of trauma exposure and frequency of religious service attendance

Cannabis use and disorders (CUD) are influenced by multiple genetic variants of small effect and by the psychosocial environment. However, this information has not been effectively incorporated into studies of gene-environment interaction (GxE). Polygenic risk scores (PRS) that aggregate the effects of genetic variants can aid in identifying the links between genetic risk and psychosocial factors. Using data from the Pasman et al. GWAS of cannabis use (meta-analysis of data from the International Cannabis Consortium and UK Biobank), we constructed PRS in the Collaborative Study on the Genetics of Alcoholism (COGA) participants of European (N: 7591) and African (N: 3359) ancestry. The primary analyses included only individuals of European ancestry, reflecting the ancestral composition of the discovery GWAS from which the PRS was derived. Secondary analyses included the African ancestry sample. Associations of PRS with cannabis use and DSM-5 CUD symptom count (CUDsx) and interactions with trauma exposure and frequency of religious service attendance were examined. Models were adjusted for sex, birth cohort, genotype array, and ancestry. Robustness models were adjusted for cross-term interactions. Higher PRS were associated with a greater likelihood of cannabis use and with CUDsx among participants of European ancestry (p < 0.05 and p < 0.1 thresholds, respectively). PRS only influenced cannabis use among those exposed to trauma (R2: 0.011 among the trauma exposed vs. R2: 0.002 in unexposed). PRS less consistently influenced cannabis use among those who attend religious services less frequently; PRS × religious service attendance effects were attenuated when cross-term interactions with ancestry and sex were included in the model. Polygenic liability to cannabis use was related to cannabis use and, less robustly, progression to symptoms of CUD. This study provides the first evidence of PRS × trauma for cannabis use and demonstrates that ignoring important aspects of the psychosocial environment may mask genetic influences on polygenic traits.

Is smoking heaviness causally associated with alcohol use? A Mendelian randomization study in four European cohorts

Background

Observational studies have shown that tobacco and alcohol use co-occur, but it is not clear whether this relationship is causal.

Methods

Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK Biobank, we used observational methods to test the hypothesis that smoking heaviness increases alcohol consumption. Mendelian randomization (MR) analyses were then used to test the causal relationship between smoking heaviness and alcohol consumption using 55 967 smokers from four European studies [ALSPAC, The Nord-Trøndelag Health Study (HUNT), the Copenhagen General Population Study (CGPS) and UK Biobank]. MR analyses used rs1051730/rs16969968 as a genetic proxy for smoking heaviness.

Results

Observational results provided evidence of an association between cigarettes per day and weekly alcohol consumption (increase in units of alcohol per additional cigarette smoked per day = 0.10, 95% confidence interval (CI) 0.05 to 0.15, P ≤ 0.001 in ALSPAC; and 0.48, 95% CI 0.45 to 0.52, P ≤ 0.001 in UK Biobank). However, there was little evidence for an association between rs1051730/rs16969968 and units of alcohol consumed per week across ALSPAC, HUNT, CGPS and UK Biobank (standard deviation increase in units of alcohol per additional copy of the risk allele = –0.004, 95% CI –0.023 to 0.016, P=0.708, I² = 51.9%). We had 99% and 88% power to detect a change of 0.03 and 0.02 standard deviation units of alcohol per additional copy of the risk allele, respectively.

Conclusions

Previously reported associations between smoking and alcohol are unlikely to be causal, and may be the result of confounding and/or reverse causation. This has implications for public health research and intervention research.

Association between polygenic risk for tobacco or alcohol consumption and liability to licit and illicit substance use in young Australian adults

BACKGROUND

Co-morbid substance use is very common. Despite a historical focus using genetic epidemiology to investigate comorbid substance use and misuse, few studies have examined substance-substance associations using polygenic risk score (PRS) methods.

METHODS

Using summary statistics from the largest substance use GWAS to date (258,797- 632,802 subjects), GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN), we constructed PRSs for smoking initiation (PRS-SI), age of initiation of regular smoking (PRS-AI), cigarettes per day (PRS-CPD), smoking cessation (PRS-SC), and drinks per week (PRS-DPW). We then estimated the fixed effect of individual PRSs on 22 lifetime substance use and substance use disorder phenotypes collected in an independent sample of 2463 young Australian adults using genetic restricted maximal likelihood (GREML) in Genome-wide Complex Trait Analysis (GCTA), separately in females, males and both sexes together.

RESULTS

After accounting for multiple testing, PRS-SI significantly explained variation in the risk of cocaine (0.67%), amphetamine (1.54%), hallucinogens (0.72%), ecstasy (1.66%) and cannabis initiation (0.97%), as well as DSM-5 alcohol use disorder (0.72%). PRS-DPW explained 0.75%, 0.59% and 0.90% of the variation of cocaine, amphetamine and ecstasy initiation respectively. None of the 22 phenotypes including emergent classes of substance use were significantly predicted by PRS-AI, PRS-CPD, and PRS-SC.

CONCLUSIONS

To our knowledge, this is the first study to report significant genetic overlap between the polygenic risks for smoking initiation and alcohol consumption and the risk of initiating major classes of illicit substances. PRSs constructed from large discovery GWASs allows the detection of novel genetic associations.

Genome-Wide Association Study Meta-Analysis of the Alcohol Use Disorders Identification Test (AUDIT) in Two Population-Based Cohorts

OBJECTIVE

Alcohol use disorders are common conditions that have enormous social and economic consequences. Genome-wide association analyses were performed to identify genetic variants associated with a proxy measure of alcohol consumption and alcohol misuse and to explore the shared genetic basis between these measures and other substance use, psychiatric, and behavioral traits.

METHOD

This study used quantitative measures from the Alcohol Use Disorders Identification Test (AUDIT) from two population-based cohorts of European ancestry (UK Biobank [N=121,604] and 23andMe [N=20,328]) and performed a genome-wide association study (GWAS) meta-analysis. Two additional GWAS analyses were performed, a GWAS for AUDIT scores on items 1-3, which focus on consumption (AUDIT-C), and for scores on items 4-10, which focus on the problematic consequences of drinking (AUDIT-P).

RESULTS

The GWAS meta-analysis of AUDIT total score identified 10 associated risk loci. Novel associations localized to genes including JCAD and SLC39A13; this study also replicated previously identified signals in the genes ADH1B, ADH1C, KLB, and GCKR. The dimensions of AUDIT showed positive genetic correlations with alcohol consumption (rg=0.76-0.92) and DSM-IV alcohol dependence (rg=0.33-0.63). AUDIT-P and AUDIT-C scores showed significantly different patterns of association across a number of traits, including psychiatric disorders. AUDIT-P score was significantly positively genetically correlated with schizophrenia (rg=0.22), major depressive disorder (rg=0.26), and attention deficit hyperactivity disorder (rg=0.23), whereas AUDIT-C score was significantly negatively genetically correlated with major depressive disorder (rg=-0.24) and ADHD (rg=-0.10). This study also used the AUDIT data in the UK Biobank to identify thresholds for dichotomizing AUDIT total score that optimize genetic correlations with DSM-IV alcohol dependence. Coding individuals with AUDIT total scores ≤4 as control subjects and those with scores ≥12 as case subjects produced a significant high genetic correlation with DSM-IV alcohol dependence (rg=0.82) while retaining most subjects.

CONCLUSIONS

AUDIT scores ascertained in population-based cohorts can be used to explore the genetic basis of both alcohol consumption and alcohol use disorders.

Genome-wide association study of alcohol use disorder identification test (AUDIT) scores in 20 328 research participants of European ancestry

Genetic factors contribute to the risk for developing alcohol use disorder (AUD). In collaboration with the genetics company 23andMe, Inc., we performed a genome-wide association study of the alcohol use disorder identification test (AUDIT), an instrument designed to screen for alcohol misuse over the past year. Our final sample consisted of 20 328 research participants of European ancestry (55.3% females; mean age = 53.8, SD = 16.1) who reported ever using alcohol. Our results showed that the 'chip-heritability' of AUDIT score, when treated as a continuous phenotype, was 12%. No loci reached genome-wide significance. The gene ADH1C, which has been previously implicated in AUD, was among our most significant associations (4.4 × 10-7 ; rs141973904). We also detected a suggestive association on chromosome 1 (2.1 × 10-7 ; rs182344113) near the gene KCNJ9, which has been implicated in mouse models of high ethanol drinking. Using linkage disequilibrium score regression, we identified positive genetic correlations between AUDIT score, high alcohol consumption and cigarette smoking. We also observed an unexpected positive genetic correlation between AUDIT and educational attainment and additional unexpected negative correlations with body mass index/obesity and attention-deficit/hyperactivity disorder. We conclude that conducting a genetic study using responses to an online questionnaire in a population not ascertained for AUD may represent a cost-effective strategy for elucidating aspects of the etiology of AUD.

Using Classification Trees to Examine Predictors of Marijuana Use Among a Wide Range of Variables

Background: Young adults have elevated risk for negative marijuana use-related outcomes, and there is heterogeneity among users. Identifying risk factors for marijuana user status will improve understanding of different populations of users, which may inform prediction of individuals most likely to experience negative outcomes. Objectives: To identify predictors of marijuana use initiation in young adults. We simultaneously examined a broad range of potential predictors and all their possible interactions, including constructs that have not been previously studied in substance use initiation research. Methods: Data were repeated cross-sectional survey responses from college students in Colorado (N = 4052, 77% White, 61% female, mean age = 22.77). Measures came from the National College Health Assessment, which assesses numerous health and behavioral constructs. We used recursive partitioning and random forest models to identify predictors of ever having used marijuana out of 206 variables. Results: Classification trees identified engagement in increased alcohol use and sexual behavior as salient correlates of marijuana use initiation. Parsimonious recursive partitioning trees explained a substantial amount of variability in marijuana user status (39% in the full model and 24% when alcohol variables were excluded). Random forest models predicted user status with 74.11% and 66.91% accuracy in the full model and when alcohol variables were excluded, respectively. Conclusions: Results support the use of exploratory analyses to explain heterogeneity among marijuana users and non-users. Since engagement in other health-risk behaviors were salient predictors of use initiation, prevention efforts to reduce harm from marijuana use may benefit from targeting risk factors for health-risk behaviors in general.

Genetics of alcohol use disorder: a review

Alcohol use disorder (AUD) represents a significant and ongoing public health concern with 12-month prevalence estimates of ∼5.6%. Quantitative genetic studies suggest a heritability of approximately 50% for AUD, and as a result, significant efforts have been made to identify specific variation within the genome related to the etiology of AUD. Given the limited number of replicable findings that have emerged from genome-wide linkage and candidate gene association studies, more recent efforts have focused on the use of genome-wide association studies (GWAS). These studies have suggested that hundreds of variants across the genome, most of small effect (R² < 0.002), contribute to the genetic etiology of AUD. The present review describes the initial, though limited, successes of GWAS to identify loci related to risk for AUD as well as other etiologically relevant traits (e.g. alcohol consumption). In addition, 'Post-GWAS' approaches that rely on GWAS data to estimate the heritability and co-heritability of traits, test causal relations between traits, and aid in gene discovery are described. Together, the described research findings illustrate the importance of molecular genetic research on AUD as we seek to better understand the mechanisms through which genetic variation leads to increased risk for AUD.

Investigating causal associations between use of nicotine, alcohol, caffeine and cannabis: a two-sample bidirectional Mendelian randomization study

BACKGROUND AND AIMS

Epidemiological studies consistently show co-occurrence of use of different addictive substances. Whether these associations are causal or due to overlapping underlying influences remains an important question in addiction research. Methodological advances have made it possible to use published genetic associations to infer causal relationships between phenotypes. In this exploratory study, we used Mendelian randomization (MR) to examine the causality of well-established associations between nicotine, alcohol, caffeine and cannabis use.

METHODS

Two-sample MR was employed to estimate bidirectional causal effects between four addictive substances: nicotine (smoking initiation and cigarettes smoked per day), caffeine (cups of coffee per day), alcohol (units per week) and cannabis (initiation). Based on existing genome-wide association results we selected genetic variants associated with the exposure measure as an instrument to estimate causal effects. Where possible we applied sensitivity analyses (MR-Egger and weighted median) more robust to horizontal pleiotropy.

RESULTS

Most MR tests did not reveal causal associations. There was some weak evidence for a causal positive effect of genetically instrumented alcohol use on smoking initiation and of cigarettes per day on caffeine use, but these were not supported by the sensitivity analyses. There was also some suggestive evidence for a positive effect of alcohol use on caffeine use (only with MR-Egger) and smoking initiation on cannabis initiation (only with weighted median). None of the suggestive causal associations survived corrections for multiple testing.

CONCLUSIONS

Two-sample Mendelian randomization analyses found little evidence for causal relationships between nicotine, alcohol, caffeine and cannabis use.

Exploring the role of low-frequency and rare exonic variants in alcohol and tobacco use

BACKGROUND

Alcohol and tobacco use are heritable phenotypes. However, only a small number of common genetic variants have been identified, and common variants account for a modest proportion of the heritability. Therefore, this study aims to investigate the role of low-frequency and rare variants in alcohol and tobacco use.

METHODS

We meta-analyzed ExomeChip association results from eight discovery cohorts and included 12,466 subjects and 7432 smokers in the analysis of alcohol consumption and tobacco use, respectively. The ExomeChip interrogates low-frequency and rare exonic variants, and in addition a small pool of common variants. We investigated top variants in an independent sample in which ICD-9 diagnoses of "alcoholism" (N = 25,508) and "tobacco use disorder" (N = 27,068) had been assessed. In addition to the single variant analysis, we performed gene-based, polygenic risk score (PRS), and pathway analyses.

RESULTS

The meta-analysis did not yield exome-wide significant results. When we jointly analyzed our top results with the independent sample, no low-frequency or rare variants reached significance for alcohol consumption or tobacco use. However, two common variants that were present on the ExomeChip, rs16969968 (p = 2.39 × 10^-7) and rs8034191 (p = 6.31 × 10^-7) located in CHRNA5 and AGPHD1 at 15q25.1, showed evidence for association with tobacco use.

DISCUSSION

Low-frequency and rare exonic variants with large effects do not play a major role in alcohol and tobacco use, nor does the aggregate effect of ExomeChip variants. However, our results confirmed the role of the CHRNA5-CHRNA3-CHRNB4 cluster of nicotinic acetylcholine receptor subunit genes in tobacco use.

The genetic and environmental architecture of substance use development from early adolescence into young adulthood: a longitudinal twin study of comorbidity of alcohol, tobacco and illicit drug use

AIMS

To investigate how use of alcohol, illicit drugs and tobacco come from substance-specific pathways and from pathways general to all three substances through adolescent development.

DESIGN

Analysis of population-based survey. Adolescent twins reported alcohol use (AU), tobacco use (TU) and illicit drug use (IDU) in three waves (2006, 2008, 2010). Restructuring data by age allowed for variance decomposition into age- and substance-specific and common genetic and environmental variance components.

SETTING

Norway.

PARTICIPANTS

Seven national twin birth cohorts from 1988 to 1994, totalling 1483 pairs (558 monozygotic; 925 dizygotic, same and opposite sex).

MEASUREMENTS

Six-point Likert scores of AU, TU and IDU on items from the Monitoring the Future Study.

FINDINGS

Substance use was found to be highly heritable; a²  = 0.73 [95% confidence interval (CI) = 0.61-0.94] for AU, a²  = 0.36 (CI = 0.18-0.52); d²  = 0.49 (95% CI = 0.29-0.62) for IDU and a²  = 0.46 (95% CI = 0.23-0.54); d²  = 0.05 (95% CI = 0.00-0.07) for TU during the whole adolescence period. General substance use (GSU) was also highly heritable at each age and averaged a²  = 0.57 (95% CI = 0.48-0.66). There was a high genetic carry-over from earlier age to later age. Genetic effects on GSU at ages 12-14 years were still detectable 4 years later. New substance (general and specific)-genetic effects also appeared. IDU demonstrated significant non-additive genetic effects (ages 12-14 years). Shared environment had a small impact on AU only. There was almost no non-shared environmental carry-over from age to age, the effect probably due partly to reliability deficiency. Common genetic effects among substance and substance-specific genetic effects were observed at each age-period.

CONCLUSIONS

Among Norwegian adolescents, there appear to be strong genetic effects on both substance-specific and comorbid use of alcohol, illicit drugs and tobacco; individual differences in alcohol use can be explained partially by family background.

Polygenic risk for alcohol consumption and its association with alcohol-related phenotypes: Do stress and life satisfaction moderate these relationships?

BACKGROUND

Genetic and environmental factors contribute about equally to alcohol-related phenotypes in adulthood. In the present study, we examined whether more stress at home or low satisfaction with life might be associated with heavier drinking or more alcohol-related problems in individuals with a high genetic susceptibility to alcohol use.

METHODS

Information on polygenic scores and drinking behavior was available in 6705 adults (65% female; 18-83 years) registered with the Netherlands Twin Register. Polygenic risk scores (PRSs) were constructed for all subjects based on the summary statistics of a large genome-wide association meta-analysis on alcohol consumption (grams per day). Outcome measures were quantity of alcohol consumption and alcohol-related problems assessed with the Alcohol Use Disorders Identification Test (AUDIT). Stress at home and life satisfaction were moderating variables whose significance was tested by Generalized Estimating Equation analyses taking familial relatedness, age and sex into account.

RESULTS

PRSs for alcohol were significantly associated with quantity of alcohol consumption and alcohol-related problems in the past year (R²=0.11% and 0.10% respectively). Participants who reported to have experienced more stress in the past year and lower life satisfaction, scored higher on alcohol-related problems (R²=0.27% and 0.29 respectively), but not on alcohol consumption. Stress and life satisfaction did not moderate the association between PRSs and the alcohol outcome measures.

CONCLUSIONS

There were significant main effects of polygenic scores and of stress and life satisfaction on drinking behavior, but there was no support for PRS-by-stress or PRS-by-life satisfaction interactions on alcohol consumption and alcohol-related problems.

The genetic epidemiology of substance use disorder: A review

BACKGROUND

Substance use disorder (SUD) remains a significant public health issue. A greater understanding of how genes and environment interact to regulate phenotypes comprising SUD will facilitate directed treatments and prevention.

METHODS

The literature studying the neurobiological correlates of SUD with a focus on the genetic and environmental influences underlying these mechanisms was reviewed. Results from twin/family, human genetic association, gene-environment interaction, epigenetic literature, phenome-wide association studies are summarized for alcohol, nicotine, cannabinoids, cocaine, and opioids.

RESULTS

There are substantial genetic influences on SUD that are expected to influence multiple neurotransmission pathways, and these influences are particularly important within the dopaminergic system. Genetic influences involved in other aspects of SUD etiology including drug processing and metabolism are also identified. Studies of gene-environment interaction emphasize the importance of environmental context in SUD. Epigenetic studies indicate drug-specific changes in gene expression as well as differences in gene expression related to the use of multiple substances. Further, gene expression is expected to differ by stage of SUD such as substance initiation versus chronic substance use. While a substantial literature has developed for alcohol and nicotine use disorders, there is comparatively less information for other commonly abused substances.

CONCLUSIONS

A better understanding of genetically-mediated mechanisms involved in the neurobiology of SUD provides increased opportunity to develop behavioral and biologically based treatment and prevention of SUD.

Genome-wide association study of alcohol consumption and genetic overlap with other health-related traits in UK Biobank (N=112 117)

Alcohol consumption has been linked to over 200 diseases and is responsible for over 5% of the global disease burden. Well-known genetic variants in alcohol metabolizing genes, for example, ALDH2 and ADH1B, are strongly associated with alcohol consumption but have limited impact in European populations where they are found at low frequency. We performed a genome-wide association study (GWAS) of self-reported alcohol consumption in 112 117 individuals in the UK Biobank (UKB) sample of white British individuals. We report significant genome-wide associations at 14 loci. These include single-nucleotide polymorphisms (SNPs) in alcohol metabolizing genes (ADH1B/ADH1C/ADH5) and two loci in KLB, a gene recently associated with alcohol consumption. We also identify SNPs at novel loci including GCKR, CADM2 and FAM69C. Gene-based analyses found significant associations with genes implicated in the neurobiology of substance use (DRD2, PDE4B). GCTA analyses found a significant SNP-based heritability of self-reported alcohol consumption of 13% (se=0.01). Sex-specific analyses found largely overlapping GWAS loci and the genetic correlation (rG) between male and female alcohol consumption was 0.90 (s.e.=0.09, P-value=7.16 × 10^-23). Using LD score regression, genetic overlap was found between alcohol consumption and years of schooling (rG=0.18, s.e.=0.03), high-density lipoprotein cholesterol (rG=0.28, s.e.=0.05), smoking (rG=0.40, s.e.=0.06) and various anthropometric traits (for example, overweight, rG=-0.19, s.e.=0.05). This study replicates the association between alcohol consumption and alcohol metabolizing genes and KLB, and identifies novel gene associations that should be the focus of future studies investigating the neurobiology of alcohol consumption.

Patterns of cannabis use during adolescence and their association with harmful substance use behaviour: findings from a UK birth cohort

BACKGROUND

Evidence on the role of cannabis as a gateway drug is inconsistent. We characterise patterns of cannabis use among UK teenagers aged 13-18 years, and assess their influence on problematic substance use at age 21 years.

METHODS

We used longitudinal latent class analysis to derive trajectories of cannabis use from self-report measures in a UK birth cohort. We investigated (1) factors associated with latent class membership and (2) whether latent class membership predicted subsequent nicotine dependence, harmful alcohol use and recent use of other illicit drugs at age 21 years.

RESULTS

5315 adolescents had three or more measures of cannabis use from age 13 to 18 years. Cannabis use patterns were captured as four latent classes corresponding to 'non-users' (80.1%), 'late-onset occasional' (14.2%), 'early-onset occasional' (2.3%) and 'regular' users (3.4%). Sex, mother's substance use, and child's tobacco use, alcohol consumption and conduct problems were strongly associated with cannabis use. At age 21 years, compared with the non-user class, late-onset occasional, early-onset occasional and regular cannabis user classes had higher odds of nicotine dependence (OR=3.5, 95% CI 0.7 to 17.9; OR=12.1, 95% CI 1.0 to 150.3; and OR=37.2, 95% CI 9.5 to 144.8, respectively); harmful alcohol consumption (OR=2.6, 95% CI 1.5 to 4.3; OR=5.0, 95% CI 2.1 to 12.1; and OR=2.6, 95% CI 1.0 to 7.1, respectively); and other illicit drug use (OR=22.7, 95% CI 11.3 to 45.7; OR=15.9, 95% CI 3.9 to 64.4; and OR=47.9, 95% CI 47.9 to 337.0, respectively).

CONCLUSIONS

One-fifth of the adolescents in our sample followed a pattern of occasional or regular cannabis use, and these young people were more likely to progress to harmful substance use behaviours in early adulthood.

The Impact of Peer Substance Use and Polygenic Risk on Trajectories of Heavy Episodic Drinking Across Adolescence and Emerging Adulthood

BACKGROUND

Heavy episodic drinking is developmentally normative among adolescents and young adults, but is linked to adverse consequences in later life, such as drug and alcohol dependence. Genetic and peer influences are robust predictors of heavy episodic drinking in youth, but little is known about the interplay between polygenic risk and peer influences as they impact developmental patterns of heavy episodic drinking.

METHODS

Data were from a multisite prospective study of alcohol use among adolescents and young adults with genome-wide association data (n = 412). Generalized linear mixed models were used to characterize the initial status and slopes of heavy episodic drinking between age 15 and 28. Polygenic risk scores (PRS) were derived from a separate genome-wide association study for alcohol dependence and examined for their interaction with substance use among the adolescents' closest friends in predicting the initial status and slopes of heavy episodic drinking.

RESULTS

Close friend substance use was a robust predictor of adolescent heavy episodic drinking, even after controlling for parental knowledge and peer substance use in the school. PRS were predictive of the initial status and early patterns of heavy episodic drinking in males, but not in females. No interaction was detected between PRS and close friend substance use for heavy episodic drinking trajectories in either males or females.

CONCLUSIONS

Although substance use among close friends and genetic influences play an important role in predicting heavy episodic drinking trajectories, particularly during the late adolescent to early adult years, we found no evidence of interaction between these influences after controlling for other social processes, such as parental knowledge and broader substance use among other peers outside of close friends. The use of longitudinal models and accounting for multiple social influences may be crucial for future studies focused on uncovering gene-environment interplay. Clinical implications are also discussed.

Genome-Wide Association of Heroin Dependence in Han Chinese

Drug addiction is a costly and recurring healthcare problem, necessitating a need to understand risk factors and mechanisms of addiction, and to identify new biomarkers. To date, genome-wide association studies (GWAS) for heroin addiction have been limited; moreover they have been restricted to examining samples of European and African-American origin due to difficulty of recruiting samples from other populations. This is the first study to test a Han Chinese population; we performed a GWAS on a homogeneous sample of 370 Han Chinese subjects diagnosed with heroin dependence using the DSM-IV criteria and 134 ethnically matched controls. Analysis using the diagnostic criteria of heroin dependence yielded suggestive evidence for association between variants in the genes CCDC42 (coiled coil domain 42; p = 2.8x10^-7) and BRSK2 (BR serine/threonine 2; p = 4.110⁻⁶). In addition, we found evidence for risk variants within the ARHGEF10 (Rho guanine nucleotide exchange factor 10) gene on chromosome 8 and variants in a region on chromosome 20q13, which is gene-poor but has a concentration of mRNAs and predicted miRNAs. Gene-based association analysis identified genome-wide significant association between variants in CCDC42 and heroin addiction. Additionally, when we investigated shared risk variants between heroin addiction and risk of other addiction-related and psychiatric phenotypes using polygenic risk scores, we found a suggestive relationship with variants predicting tobacco addiction, and a significant relationship with variants predicting schizophrenia. Our genome wide association study of heroin dependence provides data in a novel sample, with functionally plausible results and evidence of genetic data of value to the field.

Exploration of a Polygenic Risk Score for Alcohol Consumption: A Longitudinal Analysis from the ALSPAC Cohort

BACKGROUND

Uncertainty remains about the true extent by which alcohol consumption causes a number of health outcomes. Genetic variants, or combinations of variants built into a polygenic risk score (PGRS), can be used in an instrumental variable framework to assess causality between a phenotype and disease outcome of interest, a method known as Mendelian randomisation (MR). We aimed to identify genetic variants involved in the aetiology of alcohol consumption, and develop a PGRS for alcohol.

METHODS

Repeated measures of alcohol consumption from mothers and their offspring were collected as part of the Avon Longitudinal Study of Parents and Children. We tested the association between 89 SNPs (identified from either published GWAS data or from functional literature) and repeated measures of alcohol consumption, separately in mothers (from ages 28-48) and offspring (from ages 15-21) who had ever reported drinking. We modelled log units of alcohol using a linear mixed model and calculated beta coefficients for each SNP separately. Cross-validation was used to determine an allelic score for alcohol consumption, and the AVENGEME algorithm employed to estimate variance of the trait explained.

RESULTS

Following correction for multiple testing, one SNP (rs1229984) showed evidence for association with alcohol consumption (β = -0.177, SE = 0.042, p = <0.0001) in the mothers. No SNPs showed evidence for association in the offspring after correcting for multiple testing. The optimal allelic score was generated using p-value cut offs of 0.5 and 0.05 for the mothers and offspring respectively. These scores explained 0.3% and 0.7% of the variance.

CONCLUSION

Our PGRS explains a modest amount of the variance in alcohol consumption and larger sample sizes would be required to use our PGRS in an MR framework.

Molecular genetic approaches to understanding the comorbidity of psychiatric disorders

Epidemiologic studies demonstrating high rates of co-occurrence among psychiatric disorders at the population level have contributed to large literatures focused on identifying the causal mechanisms underlying the patterns of co-occurrence among these disorders. Such efforts have long represented a core focus of developmental psychopathologists and have more recently been supported by the Research Domain Criteria initiative developed by the NIMH, which provides a further framework for how the hypothesized mechanisms can be studied at different levels of analysis. The present overview focuses on molecular genetic approaches that are being used currently to study the etiology of psychiatric disorders, and how these approaches have been applied in efforts to understand the biological mechanisms that give rise to comorbid conditions. The present report begins with a review of molecular genetic approaches used to identify individual variants that confer risk for multiple disorders and the intervening biological mechanisms that contribute to their comorbidity. This is followed by a review of molecular genetic approaches that use genetic data in aggregate to examine these questions, and concludes with a discussion of how developmental psychopathologists are uniquely positioned to apply these methods in a way that will further our understanding of the causal factors that contribute to the development of comorbid conditions.

Polygenic risk scores for cigarettes smoked per day do not generalize to a Native American population

BACKGROUND

Recent studies have demonstrated the utility of polygenic risk scores (PRSs) for exploring the genetic etiology of psychiatric phenotypes and the genetic correlations between them. To date, these studies have been conducted almost exclusively using participants of European ancestry, and thus, there is a need for similar studies conducted in other ancestral populations. However, given that the predictive ability of PRSs are sensitive to differences in linkage disequilibrium (LD) patterns and minor allele frequencies across discovery and target samples, the applicability of PRSs developed in European ancestry samples to other ancestral populations has yet to be determined. Therefore, the current study derived PRSs for cigarettes per day (CPD) from predominantly European-ancestry samples and examined their ability to predict nicotine dependence (ND) in a Native American (NA) population sample.

METHOD

Results from the Tobacco and Genetics Consortium's meta-analysis of genome-wide association studies of CPD were used to compute PRSs in a NA community sample (N=288). These scores were then used to predict ND diagnostic status.

RESULTS

The PRS was not significantly associated with liability for ND in the full sample. However, a significant interaction between PRS and percent NA ancestry was observed. Risk scores were positively associated with liability for ND at higher levels of European ancestry, but no association was observed at higher levels of NA ancestry.

CONCLUSION

These findings illustrate how differences in patterns of LD across discovery and target samples can reduce the predictive ability of PRSs for complex traits.

Commentary on Verweij et al. (2016): Conduct problems and substance use-genetic and environmental perspectives on sex differences

Genes influence the covariance between conduct disorder (CD) problems and substance use in males, but shared environment is more important in females. We now need to consider: (a) how genetic influences on CD affect correlations across substances from early to later stages of involvement; (b) whether polygenic liability to CD and substance use overlap; (c) environmental pathways of vulnerability (e.g. peers) in females; and (d) sex effects derived from opposite-sex twin pairs.

The genetic relationship between cannabis and tobacco cigarette use in European- and African-American female twins and siblings

BACKGROUND

Use of cigarettes and cannabis frequently co-occurs. We examine the role of genetic and environmental influences on variation in and covariation between tobacco cigarette and cannabis use across European-American (EA) and African-American (AA) women.

METHODS

Data on lifetime cannabis and cigarette use were drawn from interviews of 956 AA and 3557 EA young adult female twins and non-twin same sex female full siblings. Twin modeling was used to decompose variance in and covariance between cigarette and cannabis use into additive genetic, shared, special twin and non-shared environmental sources.

RESULTS

Cigarette use was more common in EAs (75.3%, 95% C.I. 73.8-76.7%) than AAs (64.2%, 95% C.I. 61.2-67.2%) while cannabis use was marginally more commonly reported by AAs (55.5%, 95% C.I. 52.5-58.8%) than EAs (52.4%, 95% C.I. 50.7-54.0%). Additive genetic factors were responsible for 43-66% of the variance in cigarette and cannabis use. Broad shared environmental factors (shared+special twin) played a more significant role in EA (23-29%) than AA (2-15%) women. In AA women, the influence of non-shared environment was more pronounced (42-45% vs. 11-19% in EA women). There was strong evidence for the same familial influences underlying use of both substances (rA=0.82-0.89; rC+T=0.70-0.75). Non-shared environmental factors were also correlated but less so (rE=0.48-0.66). No racial/ethnic differences were apparent in these sources of covariation.

CONCLUSION

Heritability of cigarette and cannabis use is comparable across racial/ethnic groups. Differences in the contribution of shared and non-shared environmental influences indicate that different factors may shape substance use in EA and AA women.

Genetic and Environmental Factors Associated with Cannabis Involvement

Approximately 50-70% of the variation in cannabis use and use disorders can be attributed to heritable factors. For cannabis use, the remaining variance can be parsed in to familial and person-specific environmental factors while for use disorders, only the latter contribute. While numerous candidate gene studies have identified the role of common variation influencing liability to cannabis involvement, replication has been elusive. To date, no genomewide association study has been sufficiently powered to identify significant loci. Despite this, studies adopting polygenic techniques and integrating genetic variation with neural phenotypes and measures of environmental risk, such as childhood adversity, are providing promising new leads. It is likely that the small effect sizes associated with variants related to cannabis involvement will only be robustly identified in substantially larger samples. Results of such large-scale efforts will provide valuable single variant targets for translational research in neurogenetic, pharmacogenetic and non-human animal models as well as polygenic risk indices that can be used to explore a host of other genetic hypotheses related to cannabis use and misuse.

Associations between smoking and caffeine consumption in two European cohorts

AIMS

To estimate associations between smoking initiation, smoking persistence and smoking heaviness and caffeine consumption in two population-based samples from the Netherlands and the United Kingdom.

DESIGN

Observational study employing data on self-reported smoking behaviour and caffeine consumption.

SETTING

Adults from the general population in the Netherlands and the United Kingdom.

PARTICIPANTS

Participants from the Netherlands Twin Register [NTR: n = 21 939, mean age 40.8, standard deviation (SD) = 16.9, 62.6% female] and the Avon Longitudinal Study of Parents and Children (ALSPAC: n = 9086, mean age 33.2, SD = 4.7, 100% female).

MEASUREMENTS

Smoking initiation (ever versus never smoking), smoking persistence (current versus former smoking), smoking heaviness (number of cigarettes smoked) and caffeine consumption in mg per day through coffee, tea, cola and energy drinks.

FINDINGS

After correction for age, gender (NTR), education and social class (ALSPAC), smoking initiation was associated with consuming on average 52.8 [95% confidence interval (CI) = 45.6-60.0; NTR] and 59.5 (95% CI = 51.8-67.2; ALSPAC) mg more caffeine per day. Smoking persistence was also associated with consuming more caffeine [+57.9 (95% CI = 45.2-70.5) and +83.2 (95% CI = 70.2-96.3) mg, respectively]. Each additional cigarette smoked per day was associated with 3.7 (95% CI = 1.9-5.5; NTR) and 8.4 (95% CI = 6.9-10.0; ALSPAC) mg higher daily caffeine consumption in current smokers. Smoking was associated positively with coffee consumption and less strongly with cola and energy drinks. For tea, associations were positive in ALSPAC and negative in NTR.

CONCLUSIONS

There appears to be a positive association between smoking and caffeine consumption in the Netherlands and the United Kingdom.

Advanced brain aging: relationship with epidemiologic and genetic risk factors, and overlap with Alzheimer disease atrophy patterns

We systematically compared structural imaging patterns of advanced brain aging (ABA) in the general-population, herein defined as significant deviation from typical BA to those found in Alzheimer disease (AD). The hypothesis that ABA would show different patterns of structural change compared with those found in AD was tested via advanced pattern analysis methods. In particular, magnetic resonance images of 2705 participants from the Study of Health in Pomerania (aged 20-90 years) were analyzed using an index that captures aging atrophy patterns (Spatial Pattern of Atrophy for Recognition of BA (SPARE-BA)), and an index previously shown to capture atrophy patterns found in clinical AD (Spatial Patterns of Abnormality for Recognition of Early Alzheimer's Disease (SPARE-AD)). We studied the association between these indices and risk factors, including an AD polygenic risk score. Finally, we compared the ABA-associated atrophy with typical AD-like patterns. We observed that SPARE-BA had significant association with: smoking (P<0.05), anti-hypertensive (P<0.05), anti-diabetic drug use (men P<0.05, women P=0.06) and waist circumference for the male cohort (P<0.05), after adjusting for age. Subjects with ABA had spatially extensive gray matter loss in the frontal, parietal and temporal lobes (false-discovery-rate-corrected q<0.001). ABA patterns of atrophy were partially overlapping with, but notably deviating from those typically found in AD. Subjects with ABA had higher SPARE-AD values; largely due to the partial spatial overlap of associated patterns in temporal regions. The AD polygenic risk score was significantly associated with SPARE-AD but not with SPARE-BA. Our findings suggest that ABA is likely characterized by pathophysiologic mechanisms that are distinct from, or only partially overlapping with those of AD.

Genome-wide polygenic scores for age at onset of alcohol dependence and association with alcohol-related measures

Age at onset of alcohol dependence (AO-AD) is a defining feature of multiple drinking typologies. AO-AD is heritable and likely shares genetic liability with other aspects of alcohol consumption. We examine whether polygenic variation in AO-AD, based on a genome-wide association study (GWAS), was associated with AO-AD and other aspects of alcohol consumption in two independent samples. Genetic risk scores (GRS) were created based on AO-AD GWAS results from a discovery sample of 1788 regular drinkers from extended pedigrees from the Collaborative Study of the Genetics of Alcoholism (COGA). GRS were used to predict AO-AD, AD and Alcohol dependence symptom count (AD-SX), age at onset of intoxication (AO-I), as well as maxdrinks in regular drinking participants from two independent samples-the Study of Addictions: Genes and Environment (SAGE; n=2336) and an Australian sample (OZ-ALC; n=5816). GRS for AO-AD from COGA explained a modest but significant proportion of the variance in all alcohol-related phenotypes in SAGE. Despite including effect sizes associated with large numbers of single nucleotide polymorphisms (SNPs; >110 000), GRS explained, at most, 0.7% of the variance in these alcohol measures in this independent sample. In OZ-ALC, significant but even more modest associations were noted with variance estimates ranging from 0.03 to 0.16%. In conclusion, there is modest evidence that genetic variation in AO-AD is associated with liability to other aspects of alcohol involvement.

Cannabis use among Swedish men in adolescence and the risk of adverse life course outcomes: results from a 20 year-follow-up study

AIMS

To examine associations between cannabis use in adolescence (at age 18) and unemployment and social welfare assistance in adulthood (at age 40) among Swedish men.

DESIGN

Longitudinal cohort study.

SETTING AND PARTICIPANTS

A total of 49.321 Swedish men born in 1949-51, who were conscripted to compulsory military service at 18-20 years of age.

MEASUREMENTS

All men answered two detailed questionnaires at conscription and were subject to examinations of physical aptitude psychological functioning and medical status. By follow-up in national databases, information on unemployment and social welfare assistance was obtained.

FINDINGS

Individuals who used cannabis at high levels in adolescence had increased risk of future unemployment and of receiving social welfare assistance. Adjusted for all confounders (social background, psychological functioning, health behaviours, educational level, psychiatric diagnoses), an increased relative risk (RR) of unemployment remained in the group reporting cannabis use > 50 times [RR = 1.26, 95% confidence interval (CI) = 1.04-1.53] only. For social welfare assistance, RR in the group reporting cannabis use 1-10 times was 1.15 (95% CI = 1.06-1.26), RR for 11-50 times was 1.21 (95% CI = 1.04-1.42) and RR for > 50 times was 1.38 (95% CI = 1.19-1.62).

CONCLUSIONS

Heavy cannabis use among Swedish men in late adolescence appears to be associated with unemployment and being in need of social welfare assistance in adulthood. These associations are not explained fully by other health-related, social or behavioural problems.

Are genetic variants for tobacco smoking associated with cannabis involvement?

BACKGROUND

Cannabis users are highly likely to also be tobacco cigarette smokers and a proportion of this comorbidity is attributable to shared genetic influences. Three large meta-analyses of genomewide association studies (GWAS) of tobacco smoking have identified multiple genomewide significant (p<5×10(-8)) single nucleotide polymorphisms (SNPs). We examine whether these SNPs are associated with tobacco smoking and with cannabis involvement in an independent sample.

METHOD

Eleven SNPs associated with cigarettes per day (CPD), ever versus never smoking and current smoking/smoking cessation at p<5×10(-8) were selected from three published meta-analyses. Association analyses were conducted with similar tobacco smoking measures in 2716 European-American subjects from the Study of Addictions Genes and Environment (SAGE) and with lifetime and current cannabis use and DSM-IV cannabis abuse/dependence.

RESULTS

Cannabis use and tobacco smoking correlated at 0.54. Rs16969968 in CHRNA5 (and its proxy, rs1051730 in CHRNA3) and rs1451240, a proxy for rs13280604 in CHRNB3, were associated with CPD after Bonferroni correction (p<0.006). rs1451240 was also associated with DSM-IV cannabis abuse/dependence. Rs6265 in BDNF was associated with smoking initiation, as in the original meta-analysis and also with lifetime cannabis use. Associations with cannabis involvement were no longer significant upon adjustment for the tobacco smoking measures.

CONCLUSIONS

The modest associations between cannabis involvement and SNPs for tobacco smoking were not independent of the comorbidity between tobacco and cannabis involvement. Larger samples of individuals might be required to articulate the specific genetic architecture of cannabis involvement.

Genetics of alcoholism

Alcohol use and alcohol use disorders are substantially heritable. Variants in genes coding for alcohol metabolic enzymes have long been known to influence consumption. More recent studies in family-based samples have implicated GABRA2, nicotinic receptor genes such as CHRNB3, and a number of other specific single genes as associated with alcohol use disorders. The growing use of genetic analyses, in particular studies using polygenic risk scores; neurobiologic pathways; and methods for quantifying gene × gene and gene × environment interactions have also contributed to an evolving understanding of the genetic architecture of alcohol use disorders. Additionally, the study of behavioral traits associated with alcohol dependence such as impulsivity and sensation seeking, and the influences of demographic factors (i.e., sex and ethnicity) have significantly enhanced the genetics of alcoholism literature. This article provides a brief overview of the current topically relevant findings in the field to date and includes areas of research still requiring attention.