Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10-13) and African ancestries (rs2066702; P = 2.2 × 10-9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.

Risky behaviors, such as substance use and unprotected sex, are associated with various physical and mental health problems. Recent genome-wide association studies indicated that variation in the cell adhesion molecule 2 (CADM2) gene plays a role in risky behaviors and self-control. In this phenome-wide scan for risky behavior, it was tested if underlying common vulnerability could be (partly) explained by pleiotropic effects of this gene and how large the effects were. Single nucleotide polymorphism (SNP)-level and gene-level association tests within four samples (25 and Up, Spit for Science, Netherlands Twin Register, and UK Biobank and meta-analyses over all samples (combined sample of 362,018 participants) were conducted to test associations between CADM2, substance- and sex-related risk behaviors, and various measures related to self-control. We found significant associations between the CADM2 gene, various risky behaviors, and different measures of self-control. The largest effect sizes were found for cannabis use, sensation seeking, and disinhibition. Effect sizes ranged from 0.01% to 0.26% for single top SNPs and from 0.07% to 3.02% for independent top SNPs together, with sufficient power observed only in the larger samples and meta-analyses. In the largest cohort, we found indications that risk-taking proneness mediated the association between CADM2 and latent factors for lifetime smoking and regular alcohol use. This study extends earlier findings that CADM2 plays a role in risky behaviors and self-control. It also provides insight into gene-level effect sizes and demonstrates the feasibility of testing mediation. These findings present a good starting point for investigating biological etiological pathways underlying risky behaviors.

As the architecture of complex traits incorporates a widening spectrum of genetic variation, analyses integrating common and rare variation are needed. Body mass index (BMI) represents a model trait, since common variation shows robust association but accounts for a fraction of the heritability. A combined analysis of single nucleotide polymorphisms (SNP) and copy number variation (CNV) was performed using 1850 European and 498 African-Americans from the Study of Addiction: Genetics and Environment. Genetic risk sum scores (GRSS) were constructed using 32 BMI-validated SNPs and aggregate-risk methods were compared: count versus weighted and proxy versus imputation.

Depressive symptoms and alcohol misuse contribute substantially to the global health burden. These phenotypes often manifest, and frequently co-occur, during adolescence. However, few studies have examined whether both baseline levels of depressive symptoms and change in symptoms are associated with alcohol outcomes. In addition, inconsistent findings could be due to sex differences or the use of different alcohol outcomes. Using data from a prospective population-based cohort in the UK, we estimated trajectories of depressive symptoms from 12 years 10 months to 17 years 10 months, separately for male and female participants. We assessed whether baseline and change in depressive symptoms were associated with use and harmful use of alcohol at 18 years 8 months. Among females, increasing depressive symptoms were associated with increased alcohol use; whilst for males, there was little evidence of this. When examining harmful levels of alcohol use, baseline levels of depressive symptoms in males were weakly related to later harmful alcohol use but this association was attenuated substantially through adjustment for confounders. In contrast, both baseline symptoms and increase in symptoms were associated with later harmful alcohol use in females and these associations were not diminished by confounder adjustment. Elevated depressive symptoms during adolescence are positively associated with increases in both use and harmful use of alcohol at 18 years 8 months. These findings differ between the sexes. Further research is needed to examine the mechanisms underlying the link between depressive symptoms and harmful alcohol use to identify potentially modifiable factors for intervention.

Family-based and genome-wide association studies (GWAS) of alcohol dependence (AD) have reported numerous associated variants. The clinical validity of these variants for predicting AD compared with family history information has not been reported. Using the Collaborative Study on the Genetics of Alcoholism (COGA) and the Study of Addiction: Genes and Environment (SAGE) GWAS samples, we examined the aggregate impact of multiple single nucleotide polymorphisms (SNPs) on risk prediction. We created genetic sum scores by adding risk alleles associated in discovery samples, and then tested the scores for their ability to discriminate between cases and controls in validation samples. Genetic sum scores were assessed separately for SNPs associated with AD in candidate gene studies and SNPs from GWAS analyses that met varying P-value thresholds. Candidate gene sum scores did not exhibit significant predictive accuracy. Family history was a better classifier of case-control status, with a significant area under the receiver operating characteristic curve (AUC) of 0.686 in COGA and 0.614 in SAGE. SNPs that met less stringent P-value thresholds of 0.01-0.50 in GWAS analyses yielded significant AUC estimates, ranging from mean estimates of 0.549 for SNPs with P < 0.01 to 0.565 for SNPs with P < 0.50. This study suggests that SNPs currently have limited clinical utility, but there is potential for enhanced predictive ability with better understanding of the large number of variants that might contribute to risk.

In 1990, Blum and colleagues first reported an association between DRD2 and alcoholism. While there have been subsequent replications of this genetic association, there have also been numerous studies that failed to detect an association between DRD2 and alcohol dependence. We propose that one aspect contributing to this inconsistency is the variation in alcohol phenotype used across studies. Within the population-based Finnish twin sample, FinnTwin16, we previously performed multivariate twin analyses to extract latent genetic factors, which account for the variation across seven measures of alcohol consumption (frequency of drinking, frequency × quantity, frequency of heavy drinking, frequency of intoxication and maximum drinks in a 24-hour period) and problems (the Rutgers Alcohol Problem Index-RAPI and the Mälmö-modified Michigan Alcohol Screen Test-MmMAST) in 3065 twins. In the present study, we examined the association between 31 DRD2/ANKK1 single-nucleotide polymorphisms (SNPs) and the genetic factor scores generated by twin analyses in a subset of FinnTwin16 (n = 602). We focus on two of the genetic factors: a general alcohol consumption and problems factor score, which represents shared genetic variance across alcohol measures, and a alcohol problems genetic factor score, which loads onto the two indices of problematic drinking (MAST and RAPI). After correction for multiple testing across SNPs and phenotypes, of the 31 SNPs genotyped across DRD2/ANKK1, one SNP (rs10891549) showed significant association with the general alcohol consumption and problems factor score (P = 0.004), and four SNPs (rs10891549, rs1554929, rs6275, rs6279), representing two independent signals after accounting for linkage disequilibrium, showed significant association with the alcohol problems genetic factor score (P = 0.005, P = 0.005, P = 0.003, P = 0.003). In this study, we provide additional positive evidence for the association between DRD2/ANKK1 and alcohol outcomes, including frequency of drinking and drinking problems. Additionally, post hoc analyses indicate stronger association signals using genetic factor scores than individual measures, which suggest that accounting for the genetic architecture of the alcohol measures reduces genetic heterogeneity in alcohol dependence outcomes in this sample and enhances the ability to detect association.

Alcoholism is a complex disease with both genetic and environmental risk factors. To identify genes that affect the risk for alcoholism, we systematically ascertained and carefully assessed individuals in families with multiple alcoholics. Linkage and association analyses suggested that a region of chromosome 4p contained genes affecting a quantitative endophenotype, brain oscillations in the beta frequency range (13-28 Hz), and the risk for alcoholism. To identify the individual genes that affect these phenotypes, we performed linkage disequilibrium analyses of 69 single-nucleotide polymorphism (SNPs) within a cluster of four GABA(A) receptor genes, GABRG1, GABRA2, GABRA4, and GABRB1, at the center of the linked region. GABA(A) receptors mediate important effects of alcohol and also modulate beta frequencies. Thirty-one SNPs in GABRA2, but only 1 of the 20 SNPs in the flanking genes, showed significant association with alcoholism. Twenty-five of the GABRA2 SNPs, but only one of the SNPs in the flanking genes, were associated with the brain oscillations in the beta frequency. The region of strongest association with alcohol dependence extended from intron 3 past the 3' end of GABRA2; all 43 of the consecutive three-SNP haplotypes in this region of GABRA2 were highly significant. A three-SNP haplotype was associated with alcoholism, with P=.000000022. No coding differences were found between the high-risk and low-risk haplotypes, suggesting that the effect is mediated through gene regulation. The very strong association of GABRA2 with both alcohol dependence and the beta frequency of the electroencephalogram, combined with biological evidence for a role of this gene in both phenotypes, suggest that GABRA2 might influence susceptibility to alcohol dependence by modulating the level of neural excitation.

We conducted a genomewide linkage screen of a simple heavy-smoking quantitative trait, the maximum number of cigarettes smoked in a 24-h period, using two independent samples: 289 Australian and 155 Finnish nuclear multiplex families, all of which were of European ancestry and were targeted for DNA analysis by use of probands with a heavy-smoking phenotype. We analyzed the trait, using a regression of identity-by-descent allele sharing on the sum and difference of the trait values for relative pairs. Suggestive linkage was detected on chromosome 22 at 27-29 cM in each sample, with a LOD score of 5.98 at 26.96 cM in the combined sample. After additional markers were used to localize the signal, the LOD score was 5.21 at 25.46 cM. To assess the statistical significance of the LOD score in the combined sample, 1,000 simulated genomewide screens were conducted, resulting in an empirical P value of .006 for the LOD score of 5.21. This linkage signal is driven mainly by the microsatellite marker D22S315 (22.59 cM), which had a single-point LOD score of 5.41 in the combined sample and an empirical P value <.001 from 1,000 simulated genomewide screens. This marker is located within an intron of the gene ADRBK2, encoding the beta-adrenergic receptor kinase 2. Fine mapping of this linkage region may reveal variants contributing to heaviness of smoking, which will lead to a better understanding of the genetic mechanisms underlying nicotine dependence.

Differences in the connectivity of large-scale functional brain networks among individuals with alcohol use disorders (AUD), as well as those at risk for AUD, point to dysfunctional neural communication and related cognitive impairments. In this study, we examined how polygenic risk scores (PRS), derived from a recent GWAS of DSM-IV Alcohol Dependence (AD) conducted by the Psychiatric Genomics Consortium, relate to longitudinal measures of interhemispheric and intrahemispheric EEG connectivity (alpha, theta, and beta frequencies) in adolescent and young adult offspring from the Collaborative Study on the Genetics of Alcoholism (COGA) assessed between ages 12 and 31. Our findings indicate that AD PRS (p-threshold < 0.001) was associated with increased fronto-central, tempo-parietal, centro-parietal, and parietal-occipital interhemispheric theta and alpha connectivity in males only from ages 18-31 (beta coefficients ranged from 0.02-0.06, p-values ranged from 10-6-10-12), but not in females. Individuals with higher AD PRS also demonstrated more performance deficits on neuropsychological tasks (Tower of London task, visual span test) as well as increased risk for lifetime DSM-5 alcohol and opioid use disorders. We conclude that measures of neural connectivity, together with neurocognitive performance and substance use behavior, can be used to further understanding of how genetic risk variants from large GWAS of AUD may influence brain function. In addition, these data indicate the importance of examining sex and developmental effects, which otherwise may be masked. Understanding of neural mechanisms linking genetic variants emerging from GWAS to risk for AUD throughout development may help to identify specific points when neurocognitive prevention and intervention efforts may be most effective.

Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder.

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

Risk for cannabis use and schizophrenia is influenced in part by genetic factors, and there is evidence that genetic risk for schizophrenia is associated with subclinical psychotic-like experiences (PLEs). Few studies to date have examined whether genetic risk for schizophrenia is associated with cannabis-related PLEs.

Predictive models for recovering from alcohol use disorder (AUD) and identifying related predisposition biomarkers can have a tremendous impact on addiction treatment outcomes and cost reduction. Our sample (N = 1376) included individuals of European (EA) and African (AA) ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA) who were initially assessed as having AUD (DSM-5) and reassessed years later as either having AUD or in remission. To predict this difference in AUD recovery status, we analyzed the initial data using multimodal, multi-features machine learning applications including EEG source-level functional brain connectivity, Polygenic Risk Scores (PRS), medications, and demographic information. Sex and ancestry age-matched stratified analyses were performed with supervised linear Support Vector Machine application and were calculated twice, once when the ancestry was defined by self-report and once defined by genetic data. Multifeatured prediction models achieved higher accuracy scores than models based on a single domain and higher scores in male models when the ancestry was based on genetic data. The AA male group model with PRS, EEG functional connectivity, marital and employment status features achieved the highest accuracy of 86.04%. Several discriminative features were identified, including collections of PRS related to neuroticism, depression, aggression, years of education, and alcohol consumption phenotypes. Other discriminated features included being married, employed, medication, lower default mode network and fusiform connectivity, and higher insula connectivity. Results highlight the importance of increasing genetic homogeneity of analyzed groups, identifying sex, and ancestry-specific features to increase prediction scores revealing biomarkers related to AUD remission.

Alcohol misuse (AM) is highly prevalent and harmful, with theorized subgroups differing on internalizing and externalizing dimensions. Despite known heterogeneity, genome-wide association studies (GWAS) are usually conducted on unidimensional phenotypes. These approaches have identified important genes related to AM but fail to capture a large part of the heritability, even with recent increases in sample sizes. This study aimed to address phenotypic heterogeneity in GWAS to aid gene finding and to uncover the etiology of different types of AM. Genetic and phenotypic data from 410,414 unrelated individuals of multiple ancestry groups (primarily European) in the UK Biobank were obtained. Mixture modeling was applied to measures of alcohol misuse and internalizing/externalizing psychopathology to uncover phenotypically homogenous subclasses, which were carried forward to GWAS and functional annotation. A four-class model emerged with "low risk", "internalizing-light/non-drinkers", "heavy alcohol use-low impairment", and "broad high risk" classes. SNP heritability ranged from 3 to 18% and both known AM signals and novel signals were captured by genomic risk loci. Class comparisons showed distinct patterns of regional brain tissue enrichment and genetic correlations with internalizing and externalizing phenotypes. Despite some limitations, this study demonstrated the utility of genetic research on homogenous subclasses. Not only were novel genetic signals identified that might be used for follow-up studies, but addressing phenotypic heterogeneity allows for the discovery and investigation of differential genetic vulnerabilities in the development of AM, which is an important step towards the goal of personalized medicine.

Considerable evidence supports the role of present-moment attention, a central feature of mindfulness, in subjective wellbeing maintenance and enhancement. Yet it is not clear why such a relation exists. This study examined the genetic and environmental contributions of present-moment attention to subjective wellbeing. Consistent with the "generalist genes hypothesis" and prior evidence, we hypothesized that presence and subjective wellbeing would show a substantial genetic correlation and smaller environmental correlation. Using a large epidemiological sample of healthy 16-year-old twins in the United Kingdom (N = 1136 monozygotic (MZ) and dizygotic (DZ) twin pairs), genetic overlap was found between presence and the cognitive component of subjective wellbeing (life satisfaction), and to a lesser extent, the affective component of subjective wellbeing (operationalized as happiness). The non-shared environmental overlap between these constructs was substantial. This study provides the first evidence known to us showing that present-centered attention, a primary component of mindfulness, has both genetic and environmental overlap with subjective wellbeing. The findings have implications for understanding mechanisms by which presence is associated with positive emotions and life satisfaction, and suggest, pending additional research, that mindfulness-based interventions to enhance wellbeing may be best suited to those with a genetic propensity toward mindful presence.

Some sources report increases in alcohol use have been observed since the start of the COVID-19 pandemic, particularly among women. Cross-sectional studies suggest that specific COVID-19-related stressful experiences (e.g., social disconnection) may be driving such increases in the general population. Few studies have explored these topics among individuals with a history of Alcohol Use Disorders (AUD), an especially vulnerable population. Drawing on recent data collected by the Collaborative Study on the Genetics of Alcoholism (COGA; COVID-19 study N = 1651, 62% women, age range: 30-91) in conjunction with AUD history data collected on the sample since 1990, we investigated associations of COVID-19 related stressors and coping activities with changes in drunkenness frequency since the start of the pandemic. Analyses were conducted for those without a history of AUD (N: 645) and three groups of participants with a history of AUD prior to the start of the pandemic: (1) those experiencing AUD symptoms (N: 606), (2) those in remission who were drinking (N: 231), and (3) those in remission who were abstinent (had not consumed alcohol for 5+ years; N: 169). Gender-stratified models were also examined. Exploratory analyses examined the moderating effects of 'problematic alcohol use' polygenic risk scores (PRS) and neural connectivity (i.e., posterior interhemispheric alpha EEG coherence) on associations between COVID-19 stressors and coping activities with changes in the frequency of drunkenness. Increases in drunkenness frequency since the start of the pandemic were higher among those with a lifetime AUD diagnosis experiencing symptoms prior to the start of the pandemic (14% reported increased drunkenness) when compared to those without a history of AUD (5% reported increased drunkenness). Among individuals in remission from AUD prior to the start of the pandemic, rates of increased drunkenness were 10% for those who were drinking pre-pandemic and 4% for those who had previously been abstinent. Across all groups, women reported nominally greater increases in drunkenness frequency when compared with men, although only women experiencing pre-pandemic AUD symptoms reported significantly greater rates of increased drunkenness since the start of the pandemic compared to men in this group (17% of women vs. 5% of men). Among those without a prior history of AUD, associations between COVID-19 risk and protective factors with increases in drunkenness frequency were not observed. Among all groups with a history of AUD (including those with AUD symptoms and those remitted from AUD), perceived stress was associated with increases in drunkenness. Among the remitted-abstinent group, essential worker status was associated with increases in drunkenness. Gender differences in these associations were observed: among women in the remitted-abstinent group, essential worker status, perceived stress, media consumption, and decreased social interactions were associated with increases in drunkenness. Among men in the remitted-drinking group, perceived stress was associated with increases in drunkenness, and increased relationship quality was associated with decreases in drunkenness. Exploratory analyses indicated that associations between family illness or death with increases in drunkenness and increased relationship quality with decreases in drunkenness were more pronounced among the remitted-drinking participants with higher PRS. Associations between family illness or death, media consumption, and economic hardships with increases in drunkenness and healthy coping with decreases in drunkenness were more pronounced among the remitted-abstinent group with lower interhemispheric alpha EEG connectivity. Our results demonstrated that only individuals with pre-pandemic AUD symptoms reported greater increases in drunkenness frequency since the start of the COVID-19 pandemic compared to those without a lifetime history of AUD. This increase was more pronounced among women than men in this group. However, COVID-19-related stressors and coping activities were associated with changes in the frequency of drunkenness among all groups of participants with a prior history of AUD, including those experiencing AUD symptoms, as well as abstinent and non-abstinent participants in remission. Perceived stress, essential worker status, media consumption, social connections (especially for women), and relationship quality (especially for men) are specific areas of focus for designing intervention and prevention strategies aimed at reducing pandemic-related alcohol misuse among this particularly vulnerable group. Interestingly, these associations were not observed for individuals without a prior history of AUD, supporting prior literature that demonstrates that widespread stressors (e.g., pandemics, terrorist attacks) disproportionately impact the mental health and alcohol use of those with a prior history of problems.

Both genetic and nongenetic risk factors, as well as interactions and correlations between them, are thought to contribute to the etiology of psychiatric and behavioral phenotypes. Genetic epidemiology consistently supports the involvement of genes in liability. Molecular genetic studies have been less successful in identifying liability genes, but recent progress suggests that a number of specific genes contributing to risk have been identified. Collectively, the results are complex and inconsistent, with a single common DNA variant in any gene influencing risk across human populations. Few specific genetic variants influencing risk have been unambiguously identified, Contemporary approaches, however hold great promise to further elucidate liability genes and variants, as well as their potential inter-relationships with each other and with the environment. We will review the fields of genetic epidemiology and molecular genetics, providing examples from the literature to illustrate the key concepts emerging from this work.

Alcohol problems represent a classic example of a complex behavioral outcome that is likely influenced by many genes of small effect. A polygenic approach, which examines aggregate measured genetic effects, can have predictive power in cases where individual genes or genetic variants do not. In the current study, we first tested whether polygenic risk for alcohol problems-derived from genome-wide association estimates of an alcohol problems factor score from the age 18 assessment of the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 4304 individuals of European descent; 57% female)-predicted alcohol problems earlier in development (age 14) in an independent sample (FinnTwin12; n = 1162; 53% female). We then tested whether environmental factors (parental knowledge and peer deviance) moderated polygenic risk to predict alcohol problems in the FinnTwin12 sample. We found evidence for both polygenic association and for additive polygene-environment interaction. Higher polygenic scores predicted a greater number of alcohol problems (range of Pearson partial correlations 0.07-0.08, all p-values ≤ 0.01). Moreover, genetic influences were significantly more pronounced under conditions of low parental knowledge or high peer deviance (unstandardized regression coefficients (b), p-values (p), and percent of variance (R2) accounted for by interaction terms: b = 1.54, p = 0.02, R2 = 0.33%; b = 0.94, p = 0.04, R2 = 0.30%, respectively). Supplementary set-based analyses indicated that the individual top single nucleotide polymorphisms (SNPs) contributing to the polygenic scores were not individually enriched for gene-environment interaction. Although the magnitude of the observed effects are small, this study illustrates the usefulness of polygenic approaches for understanding the pathways by which measured genetic predispositions come together with environmental factors to predict complex behavioral outcomes.

Starting college is a major life transition. This study aims to characterize patterns of substance use across a variety of substances across the first year of college and identify associated factors. We used data from the first cohort (N = 2056, 1240 females) of the "Spit for Science" sample, a study of incoming freshmen at a large urban university. Latent transition analysis was applied to alcohol, tobacco, cannabis, and other illicit drug uses measured at the beginning of the fall semester and midway through the spring semester. Covariates across multiple domains - including personality, drinking motivations and expectancy, high school delinquency, peer deviance, stressful events, and symptoms of depression and anxiety - were included to predict the patterns of substance use and transitions between patterns across the first year. At both the fall and spring semesters, we identified three subgroups of participants with patterns of substance use characterized as: (1) use of all four substances; (2) alcohol, tobacco, and cannabis use; and (3) overall low substance use. Patterns of substance use were highly stable across the first year of college: most students maintained their class membership from fall to spring, with just 7% of participants in the initial low substance users transitioning to spring alcohol, tobacco, and cannabis users. Most of the included covariates were predictive of the initial pattern of use, but covariates related to experiences across the first year of college were more predictive of the transition from the low to alcohol, tobacco, and cannabis user groups. Our results suggest that while there is an overall increase in alcohol use across all students, college students largely maintain their patterns of substance use across the first year. Risk factors experienced during the first year may be effective targets for preventing increases in substance use.

To investigate the genetic architecture of internalizing symptoms in childhood and adolescence.