BACKGROUND AND AIMS:Previous studies have suggested that Alcohol Use Disorder (AUD) might result from separable genetic influences with symptoms reflecting differing degrees of genetic risk related to distinct risk mechanisms. The present study aimed to examine the genetic risk for individual AUD symptom criteria using a polygenic risk score (PRS) approach to assess the relative severity of each symptom and test for a multidimensional genetic structure of AUD. DESIGN:This retrospective study examined the correlation between genetic severity (i.e. PRS) and Item Response Theory (IRT) severity indices for each AUD symptom. Multiple Indicators Multiple Causes (MIMIC) models were employed to examine the effect of the PRS on individual AUD symptoms after accounting for overall AUD severity. SETTING AND PARTICIPANTS:The study made use of summary-level data produced in Finland, United Kingdom and the United States of America as well as individual-level data from 1639 participants of the University of California - San Francisco Family Alcoholism Study. MEASUREMENTS:Phenotypic measures included the 11 Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) AUD symptom criteria assessed using a modified version of the Semi-Structured Assessment for the Genetics of Alcoholism. AUD, Problematic Alcohol Use (PAU) and alcohol consumption [i.e. drinks per week (DPW)] PRSs were created using summary statistics obtained from published genome-wide association studies (GWAS). FINDINGS:Phenotypic and genotypic severities of AUD symptoms were statistically significantly correlated for the PAU PRS and AUD PRS (r range = 0.77-0.89), but not for the DPW PRS (r = 0.45). MIMIC models indicated that the PRSs statistically significantly predicted the AUD factor. Regression paths testing the direct effects of the PRSs on individual AUD symptoms, independent of the latent AUD factor, were statistically nonsignificant. CONCLUSIONS:Polygenic risk scores derived from genome-wide association studies (GWAS) of alcohol use disorder (AUD) appear to influence AUD symptom expression through a single genetic factor that is highly correlated with the relative severity of individual symptoms measured at the phenotypic level. Item-level GWAS of AUD symptoms are needed to further parse heterogeneous symptom expression and allow for more nuanced tests of these conclusions.

Despite extensive research on DNA methylation (DNAm) signatures associated with alcohol use disorder (AUD), findings are often inconsistent and not replicated. We conducted a large-scale meta-analysis of epigenome-wide association studies (EWAS) to identify reliable, reproducible epigenetic markers of AUD. Seven cohorts, comprising 3,775 individuals (1,325 with AUD), contributed to this meta-analysis within the framework of the Psychiatric Genomics Consortium Substance Use Disorders Epigenetics Working Group. Downstream analyses included the identification of differentially methylated regions, overrepresentation analyses, and the construction of a methylation risk score (MRS). We identified 118 significant CpG sites associated with AUD, with the strongest association found at cg24889777 ( p =5.12×10 -17 ) in the long non-coding RNA LOC100505942. CpG sites were enriched for pathways related to GTPase signaling and transmembrane transporter activity, as well as EWAS signals of alcohol consumption. The MRS explained 10.44% of variance in heavy drinking in an independent cohort (N=2,534, AUC=0.657). This large-scale meta-analysis offers key insights into the epigenetic mechanisms of AUD and lays the groundwork for future research on methylation risk scores for the diagnosis, prognosis, and treatment in AUD.

Bipolar disorder is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 bipolar disorder risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci and prioritized 17 likely causal SNPs for bipolar disorder. We mapped these SNPs to genes and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci and results from rare variant exome sequencing in bipolar disorder. Convergent lines of evidence supported the roles of genes involved in neurotransmission and neurodevelopment, including SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, FKBP2, RASGRP1, FURIN, FES, MED24 and THRA among others in bipolar disorder. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance of bipolar disorder polygenic risk scores across diverse populations and present a high-throughput fine-mapping pipeline.

BACKGROUND:Genetic research on nicotine dependence has utilized multiple assessments that are in weak agreement. METHODS:We conducted a genome-wide association study (GWAS) of nicotine dependence defined using the Diagnostic and Statistical Manual of Mental Disorders (DSM-NicDep) in 61,861 individuals (47,884 of European ancestry [EUR], 10,231 of African ancestry, and 3,746 of East Asian ancestry) and compared the results to other nicotine-related phenotypes. RESULTS:We replicated the well-known association at the CHRNA5 locus (lead single-nucleotide polymorphism [SNP]: rs147144681, p = 1.27E-11 in EUR; lead SNP = rs2036527, p = 6.49e-13 in cross-ancestry analysis). DSM-NicDep showed strong positive genetic correlations with cannabis use disorder, opioid use disorder, problematic alcohol use, lung cancer, material deprivation, and several psychiatric disorders, and negative correlations with respiratory function and educational attainment. A polygenic score of DSM-NicDep predicted DSM-5 tobacco use disorder criterion count and all 11 individual diagnostic criteria in the independent National Epidemiologic Survey on Alcohol and Related Conditions-III sample. In genomic structural equation models, DSM-NicDep loaded more strongly on a previously identified factor of general addiction liability than a "problematic tobacco use" factor (a combination of cigarettes per day and nicotine dependence defined by the Fagerström Test for Nicotine Dependence). Finally, DSM-NicDep showed a strong genetic correlation with a GWAS of tobacco use disorder as defined in electronic health records (EHRs). CONCLUSIONS:Our results suggest that combining the wide availability of diagnostic EHR data with nuanced criterion-level analyses of DSM tobacco use disorder may produce new insights into the genetics of this disorder.

Bipolar disorder is a leading contributor to the global burden of disease1. Despite high heritability (60-80%), the majority of the underlying genetic determinants remain unknown2. We analysed data from participants of European, East Asian, African American and Latino ancestries (n = 158,036 cases with bipolar disorder, 2.8 million controls), combining clinical, community and self-reported samples. We identified 298 genome-wide significant loci in the multi-ancestry meta-analysis, a fourfold increase over previous findings3, and identified an ancestry-specific association in the East Asian cohort. Integrating results from fine-mapping and other variant-to-gene mapping approaches identified 36 credible genes in the aetiology of bipolar disorder. Genes prioritized through fine-mapping were enriched for ultra-rare damaging missense and protein-truncating variations in cases with bipolar disorder4, highlighting convergence of common and rare variant signals. We report differences in the genetic architecture of bipolar disorder depending on the source of patient ascertainment and on bipolar disorder subtype (type I or type II). Several analyses implicate specific cell types in the pathophysiology of bipolar disorder, including GABAergic interneurons and medium spiny neurons. Together, these analyses provide additional insights into the genetic architecture and biological underpinnings of bipolar disorder.

Binge drinking is a relatively common pattern of alcohol use among youth with normative trajectories peaking in emerging and early adulthood. Frequent binge drinking is a critical risk factor not only for the development of alcohol use disorders (AUDs) but also for increased odds of alcohol-related injury and death and thus constitutes a significant public health concern. Changes in binge drinking across development are strongly associated with individual differences and changes in impulsive personality traits, which have been hypothesized as intermediate phenotypes associated with genetic risk for heavy alcohol use and AUD. The current study examined the extent to which genetic influences underlying dual-systems impulsive personality traits (i.e., top-down [lack of self-control] and bottom-up [sensation seeking and urgency] constructs), alcohol consumption, and AUD are uniquely associated with longitudinal changes in binge drinking and intoxication frequency across adolescence and early adulthood. Associations were tested using conditional latent growth curve polygenic score (PGS) models in three independent longitudinal samples (N = 10,554). Results demonstrated consistent associations across all samples between sensation seeking PGSs and model intercepts (i.e., higher binge drinking frequency at first measurement occasion) and alcohol consumption PGSs and model slopes (i.e., steeper increases toward peak binge drinking frequency). Urgency PGSs were not associated with changes in binge drinking or intoxication frequency in any sample. Collectively, these findings demonstrate that genetic influences underlying sensation seeking and alcohol consumption explain unique variation in the emergence and escalation of binge drinking during adolescence and emerging adulthood, highlighting the multifaceted genetic etiology of these developmental trajectories. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Importance:The clinical heterogeneity of bipolar disorder (BD) is a major obstacle to improving diagnosis, predicting patient outcomes, and developing personalized treatments. A genetic approach is needed to deconstruct the disorder and uncover its fundamental biology. Previous genetic studies focusing on broad diagnostic categories have been limited in their ability to parse this complexity. Objective:To test the hypothesis that clinically distinct subphenotypes of BD are associated with different underlying common variant genetic architectures. Design Setting and Participants:This multicenter study included a primary genome-wide association study (GWAS) of up to 23,819 bipolar disorder (BD) cases and 163,839 controls. These results were integrated via multi-trait analysis of GWAS (MTAG) with external summary statistics for BD (59,287 cases; 781,022 controls) and schizophrenia (SCZ; 53,386 cases; 77,258 controls). Sample overlap was statistically accounted for. Main Outcomes and Measures:The primary outcomes were the genetic dimensions underlying BD heterogeneity, differentiated by single nucleotide polymorphism (SNP)-heritability (h 2 SNP ), genetic correlations, genomic loci ( P ≤5×10 -8 ), and functional, cell-type, and gene-expression pathway analyses. Results:We identified four genetically-informed dimensions of BD: Severe Illness, Core Mania, Externalizing/Impulsive Comorbidity, and Internalizing/Affective Comorbidity. The analyses yielded up to 181 subphenotype-associated loci, 53 of which are novel. The Severe Illness Dimension was characterized by a unique neuro-immune signature (a protective association with HLA-DMB , P =2.50×10 -273 ) evident only when leveraging SCZ genetic data. The Internalizing/Affective dimension was associated with neurodevelopmental genes (e.g., DCC ). Notably, the rapid-cycling subphenotype showed a unique signature of strong negative selection, a finding not observed in other subphenotypes. Conclusions and Relevance:The clinical heterogeneity of bipolar disorder appears to be defined by a complex and multi-layered genetic architecture. The presented findings provide an empirical framework that may advance psychiatric nosology beyond its current diagnostic boundaries. These results may also inform future research to identify targets for personalized interventions. The delineation of these genetically-informed dimensions offers specific, biologically-grounded hypotheses for subsequent therapeutic discovery. Establishing such a framework is an essential step toward refining diagnostic criteria and developing more effective, personalized treatments. This work lays the foundation for a transition from a uniform treatment model to the paradigm of precision psychiatry. Key Points:Question: What are the distinct genetic architectures underlying the clinical heterogeneity of bipolar disorder?Findings: In this genetic study of 23,819 bipolar disorder (BD) cases and 163,839 controls, clinical heterogeneity mapped onto four genetically-informed dimensions. A severe illness dimension was defined by a neuro-immune signature ( HLA-DMB ) shared with schizophrenia. An affective comorbidity dimension was distinguished by neurodevelopmental pathways involving axonal guidance ( DCC ). Notably, the rapid-cycling phenotype showed evidence of purifying selection, suggesting influence by rare, highly penetrant alleles. Meaning: These findings provide a data-driven biological framework for bipolar disorder, guiding future research toward patient stratification and targeted therapeutics.

Sensation seeking is bidirectionally associated with levels of alcohol consumption in both adult and adolescent samples and shared neurobiological and genetic influences may in part explain this association. Links between sensation seeking and alcohol use disorder (AUD) may primarily manifest via increased alcohol consumption rather than through direct effects on increasing problems and consequences. Here the overlap between sensation seeking, alcohol consumption, and AUD was examined using multivariate modeling approaches for genome-wide association study (GWAS) summary statistics in conjunction with neurobiologically-informed analyses at multiple levels of investigation. Meta-analytic and genomic structural equation modeling (GenomicSEM) approaches were used to conduct GWAS of sensation seeking, alcohol consumption, and AUD. Resulting summary statistics were used in downstream analyses to examine shared brain tissue enrichment of heritability and genome-wide evidence of overlap (e.g., stratified GenomicSEM, RRHO, genetic correlations with neuroimaging phenotypes) and to identify genomic regions likely contributing to observed genetic overlap across traits (e.g., HMAGMA, LAVA). Across approaches, results supported shared neurogenetic architecture between sensation seeking and alcohol consumption characterized by overlapping enrichment of genes expressed in midbrain and striatal tissues and variants associated with increased cortical surface area. Alcohol consumption and AUD evidenced overlap in relation to variants associated with decreased frontocortical thickness. Finally, genetic mediation models provided evidence of alcohol consumption mediating associations between sensation seeking and AUD. This study extends previous research by examining critical sources of neurogenetic and multi-omic overlap among sensation seeking, alcohol consumption, and AUD which may underlie observed phenotypic associations.

BACKGROUND:Dual-systems models, positing an interaction between two distinct and competing systems (i.e. top-down self-control, and bottom-up reward- or emotion-based drive), provide a parsimonious framework for investigating the interplay between cortical and subcortical brain regions relevant to impulsive personality traits (IPTs) and their associations with psychopathology. Despite recent developments in multivariate analysis of genome-wide association studies (GWAS), molecular genetic investigations of these models have not been conducted.METHODS:Using IPT GWAS, we conducted confirmatory genomic structural equation models (GenomicSEM) to empirically evaluate dual-systems models of the genetic architecture of IPTs. Genetic correlations between dual-systems factors and relevant cortical and subcortical neuroimaging phenotypes (regional/structural volume, cortical surface area, cortical thickness) were estimated and compared.RESULTS:GenomicSEM dual-systems models underscored important sources of shared and unique genetic variance between top-down and bottom-up constructs. Specifically, a dual-systems genomic model consisting of sensation seeking and lack of self-control factors demonstrated distinct but related sources of genetic influences (rg = 0.60). Genetic correlation analyses provided evidence of differential associations between dual-systems factors and cortical neuroimaging phenotypes (e.g. lack of self-control negatively associated with cortical thickness, sensation seeking positively associated with cortical surface area). No significant associations were observed with subcortical phenotypes.CONCLUSIONS:Dual-systems models of the genetic architecture of IPTs tested were consistent with study hypotheses, but associations with relevant neuroimaging phenotypes were mixed (e.g. no associations with subcortical volumes). Findings demonstrate the utility of dual-systems models for studying IPT genetic influences, but also highlight potential limitations as a framework for interpreting IPTs as endophenotypes for psychopathology.

Background: Only a small proportion of individuals who initiate nonmedical use of prescription opioids (NUPO) transition to heroin, suggesting that more nuanced aspects of NUPO may be better indicators of risk for escalating opioid use trajectories. This study leveraged panel data to identify NUPO typologies based on NUPO characteristics associated with opioid risk trajectories (route of administration, motives) and compared rates of heroin initiation at follow-up across typologies. Methods: Latent class analyses were run among respondents with no history of heroin use from the Monitoring the Future Panel Study (base year N=10,408) at modal ages 18, 19/20, 21/22, 23/24, and 25/26. Indicators included oral NUPO, nonoral NUPO, and NUPO motives to experiment, have a good time with friends, get high, escape problems, manage pain, relax, and sleep. Heroin initiation at follow-ups through modal age 29/30 was predicted from class membership. Results: No NUPO, self-medication (oral, manage pain), recreational (oral, nonoral, experiment, get high, have a good time with friends), and mixed-motive (all routes, all motives) classes emerged. Heroin initiation rates did not differ across no NUPO and self-medication classes; recreational and mixed-motives classes initiated heroin at higher rates than the other classes and comparable rates to each other. Non-NUPO drug use prior to heroin initiation was prevalent in recreational and mixed-motive classes. Conclusions: NUPO does not uniformly or uniquely increase risk for heroin initiation. Leveraging more nuanced indicators of risk for heroin use and targeting polysubstance use in addition to opioid-specific programming may enhance the efficacy of public health efforts.

Objective: A propensity for aggression or alcohol use may be associated with alcohol-related aggression. Previous research has shown genetic overlap between alcohol use and aggression but has not looked at how alcohol-related aggression may be uniquely influenced by genetic risk for aggression or alcohol use. The present study examined the associations of genetic risk for trait aggression, alcohol use, and alcohol use disorder (AUD) with alcohol-related aggression using a polygenic risk score (PRS) approach. Method: Using genome-wide association study summary statistics, PRSs were created for trait aggression, alcohol consumption, and AUD. These PRSs were used to predict the phenotype of alcohol-related aggression among drinkers in two independent samples: the University of California at San Francisco (UCSF) Family Alcoholism Study (n = 1,162) and the National Longitudinal Study of Adolescent to Adult Health (Add Health; n = 4,291). Results: There were significant associations between the AUD PRS and lifetime alcohol-related aggression in the UCSF study sample. Additionally, the trait aggression PRS was associated with three or more experiences of hitting anyone else and getting into physical fights while under the influence of alcohol, along with a composite score of three or more experiences of alcohol-related aggression, in the UCSF study sample. No significant associations were observed in the Add Health sample. Limited sex-specific genetic effects were observed. Conclusions: These results provide preliminary evidence that genetic influences underlying alcohol use and aggression are uniquely associated with alcohol-related aggression and suggest that these associations may differ by type and frequency of alcohol-related aggression incidents. Public Health Significance Statement The findings in this report provide evidence for the multifaceted etiology of alcohol-related aggression and suggest that treatment goals related to alcohol-related aggression should target both alcohol use disorder and underlying trait aggression.

Patterns of association with externalizing and internalizing features differ across heroin use and prescription opioid misuse (POM). The present study examined whether heroin use and POM display differential etiologic overlap with symptoms of conduct disorder (CD), adult antisocial behavior (AAB), and major depressive episodes (MDEs), how aggregating heroin use and POM into a single phenotype may bias results, and explored potential sex differences. Seven thousand one hundred and sixty-four individual twins from the Australian Twin Registry (ATR; 59.81% female; Mage = 30.58 years) reported lifetime heroin use, POM, CD symptoms, AABs, and MDE symptoms within a semi-structured interview. Biometric models decomposed phenotypic variance and covariance into additive genetic, common environmental, and unique environmental effects. The proportion of variance in heroin use attributable to factors shared with CD, AAB, and MDE, respectively, was 41%, 41%, and 0% for men and 26%, 19%, and 42% for women; for POM, the proportions were 33%, 35%, and 20% for men and 15%, 9%, and 13% for women. CD and AAB were more strongly genetically correlated with heroin use among women and with POM among men. MDE was more strongly genetically correlated with POM than with heroin use among men, but more strongly genetically correlated with heroin use than with POM among women. Analyses using an aggregate opioid (mis)use variable were biased toward POM, which was the more prevalent phenotype. Magnitude and source of etiologic influence may differ across forms of opioid (mis)use and sex. Disaggregating heroin use and POM in future opioid research may be warranted.

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

Background:Executive functioning (EF) has been proposed as a transdiagnostic risk factor for externalizing disorders and behavior more broadly, including attention-deficit/hyperactivity disorder (ADHD), aggression, and alcohol use. Previous research has demonstrated both phenotypic and genetic overlap among these behaviors, but has yet to examine EF as a common causal mechanism. The current study examined reciprocal causal associations between EF and several externalizing behaviors using a Mendelian randomization (MR) approach. Methods:Two-sample MR was conducted to test causal associations between EF and externalizing behaviors. Summary statistics from several genome-wide association studies (GWASs) were used in these analyses, including GWASs of EF, ADHD diagnostic status, drinks per week, aggressive behavior, and alcohol use disorder (AUD) diagnostic status. Multiple estimation methods were employed to account for horizontal pleiotropy (e.g., inverse variance weighted, MR-PRESSO, MR-MIX). Results:EF demonstrated significant causal relationships with ADHD (P < 0.01), AUD (P < 0.03), and alcohol consumption (P < 0.01) across several estimation methods. Reciprocally, ADHD showed a significant causal influence on EF (P < 0.03). Nonetheless, caution should be used when interpreting these findings as there was some evidence for horizontal pleiotropy in the effect of EF on ADHD and significant heterogeneity in variant effects in the other relations tested. There were no significant findings for aggression. Conclusions:Findings suggest that EF may be a causal mechanism underlying some externalizing behaviors, including ADHD and alcohol use, and that ADHD may also lead to lower performance on EF tasks.

Objective: Examine the nature of the relationship between adolescent polysubstance use and high school noncompletion. Method: Among a sample of 9,579 adult Australian twins (58.63% female, M-age = 30.59), we examined the association between the number of substances used in adolescence and high school noncompletion within a discordant twin design and bivariate twin analysis. Results: In individual-level models controlling for parental education, conduct disorder symptoms, childhood major depression, sex, zygosity, and cohort, each additional substance used in adolescence was associated with a 30% increase in the odds of high school noncompletion (OR = 1.30 [1.18, 1.42]). Discordant twin models found that the potentially causal effect of adolescent use on high school noncompletion was nonsignificant (OR = 1.19 [0.96, 1.47]). Follow-up bivariate twin models suggested genetic (35.4%, 95% CI [24.5%, 48.7%]) and shared environmental influences (27.8%, 95% CI [12.7%, 35.1%]) each contributed to the covariation in adolescent polysubstance use and early school dropout. Conclusions: The association between polysubstance use and early school dropout was largely accounted for by genetic and shared environmental factors, with nonsignificant evidence for a potentially causal association. Future research should examine whether underlying shared risk factors reflect a general propensity for addiction, a broader externalizing liability, or a combination of the two. More evidence using finer measurement of substance use is needed to rule out a causal association between adolescent polysubstance use and high school noncompletion.

Negative reinforcement effects of substance use (i.e., relief from negative affective states like stress, anxiety, or depressed mood) are associated with substance use disorder (SUD) development. Prominently featured in neurobiological models of addiction, shifts from positive to negative reinforcement are thought to reflect progression through stages of addiction. However, genetic influences underlying negative reinforcement motives, as precursors to developing addiction, are currently understudied in comparison to SUDs and other substance use-related consequences. Here we investigate genetic influences underlying negative reinforcement motives by conducting a genome-wide association study (GWAS) of using substances (i.e., drugs or alcohol) more than once to cope with symptoms of depression and anxiety (using to cope; UTC) among European ancestry individuals endorsing elevated anxious and depressive symptoms in the UK Biobank (ncases = 12,467, ncontrols = 72,457, neffective = 42,547). We also examine associations between UTC polygenic scores (PGSs) and AUD severity in the Collaborative Study on the Genetics of Alcoholism (COGA; N = 7,317). Our GWAS of UTC in the UK Biobank was conducted using a generalized linear mixed model approach controlling for sample relatedness by a sparse genetic relationship matrix (fastGWA) including sex, age, age × sex, age2, age2 × sex, and 20 genetic principal components as fixed effect covariates. LD-score regression was used to examine genetic correlations between UTC and other relevant traits including AUD, AUDIT-P scores, alcohol consumption, depression, anxiety, and neuroticism. Finally, SBayesR was used to calculate UTC and AUD PGSs in COGA, a family-based study ascertained for high prevalence of AUD. PGSs were used in mixed effects regression models, including fixed effect covariates of sex, age, age2, 10 genetic principal components, birth cohort, and genotyping array, and random effect of family membership, to predict AUD severity. Individuals reporting UTC demonstrated elevated AUDIT, PHQ-9, GAD-7 scores, and a higher prevalence of lifetime cannabis use compared to controls. A single variant for the UTC GWAS, rs1229984 in ADH1B, demonstrated genome-wide significance (P = 6.0 × 10-12). Genetic correlation analyses revealed a genetic correlation between UTC and AUD (rg = 0.73, SE = 0.07) that was significantly larger than between UTC and other mood disorder and negative affect traits analyzed (anxiety-rg = 0.39, SE = 0.09; depression-rg = 0.30, SE = 0.08; neuroticism-rg = 0.14, SE = 0.09) and between AUD and alcohol consumption (rg = 0.55, SE = 0.03). Further, the genetic correlation between UTC and AUDIT-P scores in the UK Biobank suggested near complete overlap (rg = 0.90, SE = 0.10). In COGA, UTC PGSs predicted greater AUD severity (β = 0.04, SE = 0.01, P = .006). This effect persisted with the inclusion of AUD PGSs in a multi-PGS model (β = 0.03, SE = 0.01, P = .019), suggesting unique associations between UTC PGSs and AUD severity not accounted for by AUD-specific genetic influences. These analyses provide preliminary evidence that negative reinforcement associated with substance use may be suitable as a partial genetic proxy for AUD. GWAS of specific characteristics or symptoms associated with disordered substance use can serve to refine our understanding of the genetic etiology of addiction. Future research aimed at further disentangling genetic liability reflecting domain-specific addiction risk is needed.