BACKGROUND:Romantic relationships are important contexts for substance use and emotional well-being. We tested the hypotheses that (i) genetic predispositions for alcohol consumption would be positively associated with partner substance use, (ii) partner substance use would moderate genetic influences on one's own alcohol outcomes, and (iii) partner discordance in substance use would be associated with lower emotional well-being and relationship quality. METHODS:Analyses included 2,357 participants (Mage = 51.4, 58.2% female) from the Collaborative Studies on the Genetics of Alcoholism. Focal measures included participants' reports of their own and their current partner's past-year substance use (frequencies of alcohol use, heavy drinking, drunkenness, cannabis use, and nicotine use), emotional well-being, and relationship quality. Participants' genetic predispositions were indexed with genome-wide polygenic scores for alcohol consumption (PGSAlc). Participant-partner substance use discordance was calculated as the difference between the participant's and their partner's use for each substance use measure, separately. RESULTS:Participant PGSAlc was not significantly associated with partners' perceived substance use. Frequent perceived partner alcohol use and heavy drinking significantly amplified the association between PGSAlc and alcohol use or drunkenness. Frequent perceived partner drunkenness and cannabis use significantly attenuated the association between PGSAlc and heavy drinking or frequency of alcohol use. Participant-partner discordance for several substance use measures was significantly associated with lower emotional well-being and relationship quality, controlling for participant and partner substance use main effects. CONCLUSIONS:The results highlight the importance of partner substance use in etiological models of alcohol use, emotional health outcomes, and relationship quality.

Abstract Cannabis use is widespread, with genetic differences partly explaining variation in individual patterns of use. We performed the largest-to-date genome-wide association study (GWAS) meta-analysis of cannabis ever-use (N=736,322, 76% European ancestry) and various measures of frequency of use (N=269,160 cannabis users, 84% European ancestry). We identified 54 independent genome-wide significant loci for ever-use and 6 for frequency and show that the genetic architecture of ever-use, frequency, and cannabis use disorder (CUD) are overlapping but distinguishable. We identified 63 loci that were associated with common liability (‘ All-cannabis ’) to different cannabis use traits in European-ancestry individuals. Across analyses, we identified 75 unique loci that had not previously been implicated in cannabis use. Gene prioritization analyses identified 349 genes for ever-use, 5 genes for frequency of use, and 429 for All-cannabis , including previously identified and novel genes. We found enrichment of genetic signals for cannabis use in biologically meaningful categories and relevant human brain cell types, including excitatory neuronal populations. There were substantial genetic correlations between cannabis use and a range of psychiatric disorders and substance use traits, while cannabis polygenic scores were associated with increased risk of psychiatric disorders. Mendelian Randomization showed evidence for (bidirectional) causal associations between cannabis use and ADHD, bipolar disorder, schizophrenia and PTSD.

Emerging adults of color face significant sleep disparities, yet we know less about underlying mechanisms. The goal of the current study was to investigate whether racial discrimination was associated with hours of sleep and sleep dissatisfaction. Further, we tested whether social media and television/digital media use moderated these associations. Participants included 464 emerging adult students of color (i.e., students who identified as Black/African American, Asian, Latine, Native Hawaiian/Other Pacific Islander and/or American Indian/Native Alaskan) in college. The results indicated that television/digital media use was associated with more hours of sleep, and social media use was not significantly associated with either sleep outcome. The relation between racial discrimination and hours of sleep was moderated by television/digital media use. Simple slopes analysis indicated that when individuals had low television/digital media use or average television/digital media use, racial discrimination was associated with fewer hours of sleep, but this relation was not significant at high levels of television/digital media use. Further, the relation between racial discrimination and sleep dissatisfaction was significantly moderated by social media use. Simple slopes analysis indicated that racial discrimination was associated with more sleep dissatisfaction at low or average levels of social media use, but this relation was not significant at high levels of social media use. Findings suggest that social media and television/digital media use may serve as coping tools for college students of color navigating the negative effects of racial discrimination on sleep.

Ongoing efforts to identify genes involved in substance use disorders (SUDs) often focus on individual disorders despite high rates of co-occurrence with each other and other externalizing traits. Here we investigate whether incorporating data on other externalizing traits can boost power to detect without sacrificing specificity of SUD genetic signal. We used multivariate genomic analyses and downstream biological annotation and genetic association analyses to explore this question. We found that joint analysis of SUDs and other externalizing traits resulted in increased insights into the neurobiology of broad and substance-specific SUD risk. We found no evidence of loss of specificity for SUD genetic signal but note improvements in our ability to characterize the neurobiology of broad and substance-specific SUD genetic effects. Our findings suggest that genetic risk for SUDs operates largely via pathways shared with other behaviors characterized by behavioral disinhibition, with additional substance-specific risk, and that modeling this shared disposition improves gene discovery.

Outreach in psychiatric genetics bridges the gaps across research advancements, clinical practice, and public understanding. Effective communication with a range of audiences faces multiple challenges, including the complex nature of psychiatric disorders and of genetic findings, the chronicled and ongoing misuse of genetic data, and the rapid growth of direct-to-consumer genetic testing. This is particularly true in the internet and social media era, which has accelerated the spread of inaccurate information with serious consequences, including perpetuating stigma and increasing shame. Yet a significant gap remains in outreach: a recent survey found that only 51% of psychiatric genetics researchers participate in outreach, largely attributed to their perceived lack of skill and support. The Psychiatric Genomics Consortium (PGC) developed an Outreach Committee to organize and catalyze initiatives including: the Worldwide Lab, an online seminar series covering new and important approaches that is then posted on YouTube; the PGC Video Textbook, which has resources for clinicians, researchers, educators, and the broader public; patient and family engagement programs; and social media campaigns designed to inform both researchers and affected communities about new developments in psychiatric genetics. These initiatives were developed to demystify psychiatric genetics research and empower broad audiences with reliable, actionable information. Along with research and traditional teaching, the psychiatric genomics community should continue to prioritize and recognize engagement as a core component of our academic mission and values.

Psychiatric disorders unfold over the life course; however, genomic studies of these conditions overwhelmingly rely on phenotypes collected at a single time point, often in adulthood. Therefore, genome-wide association studies (GWASs) of psychiatric conditions may miss genetic variants with time-varying relevance to etiology, prevention, and treatment, such as those that influence trajectories of symptoms and behaviors, age at onset, course of treatment response, and the co-evolution of comorbidities. With recent advances in longitudinal biobanks and analytic tools, we posit that incorporating a life course perspective in psychiatric genetics will enable critically relevant insights into each of these areas of investigation. We propose that the current inconsistent portability of polygenic scores across age groups can be reconciled through the design of carefully considered longitudinal GWASs in age-diverse samples. Pioneering longitudinal GWASs in psychiatry have revealed novel genomic signals associated with time-dependent phenotypes that are distinct from those influencing lifetime diagnosis, suggesting that the study of longitudinal phenotypes will complement cross-sectional approaches and empower biological and therapeutic discoveries. Advances in post-GWAS functional annotation resources and analytic approaches now enable us to contextualize the genetic contributions to psychiatric disorders as dynamic age- and exposure-dependent processes. Although longitudinal GWASs pose unique challenges with regard to data availability, selection bias, and missing data, integrating temporality into psychiatric genetics at scale is now attainable and promises to reveal novel biology and therapeutic opportunities for psychiatric conditions.

Background and Aims:Substance use disorders (SUDs) are heritable and share genetic variance with externalizing and internalizing psychopathology. Although recent gene identification efforts have demonstrated the value of modeling the shared genetic architecture among SUDs and externalizing, most research has thus far failed to account for overlap with internalizing. In this study, we aim to characterize the genetic relationships of both externalizing and internalizing with SUDs. Design and setting:We used genome-wide association study (GWAS) summary statistics derived from previously published studies of externalizing, internalizing, and SUD outcomes to quantify the genetic overlap between these phenotypes. We characterize this overlap using omnibus, partial, and local genetic correlations, estimates of their shared polygenic effects, genetic causality models, polygenic score (PGS) analyses, and estimates of each SUDs residual variance derived from models in Genomic SEM. Participants:We used GWAS summary statistics from individuals whose genomes were most similar to those from reference panels sampled from Europe (Ns ranged from 45,395 to 1,565,618) and Africa (Ns ranged from 30,000 to 122,571). For polygenic scores analyses, we used data from individuals of European and African ancestry groups available in the Collaborative Study on the Genetics of Alcoholism (COGA) sample (N Maximum = 7,394 for European-like genomes and 3,238 for African-like genomes). Measurements:Measurements in this study include GWAS summary statistics for externalizing, internalizing, and four substance use disorders: problematic alcohol use (PAU), cannabis use disorder (CUD), opioid use disorder (OUD), and tobacco use disorder (TUD). SUD outcomes in COGA were DSM-IV symptom counts of AUD, CUD, and OUD and scores on the Fagerstrom Test for Nicotine Dependence. Findings:We found strong genetic relationships of externalizing and, to a lesser extent, internalizing with all SUDs across methods. Despite their more modest associations, internalizing emerged as an important genetic correlate of SUDs. After accounting for variance shared with externalizing, partial genetic correlations between internalizing and SUDs were attenuated but, with the exception of TUD, still significant. Similarly, the PGSINT accounted for a statistically significant increase in variance over and above PGSEXT. Two SUD specific patterns emerged such that TUD was least associated with both psychopathology spectra and OUD was most strongly related to internalizing relative to other SUDs. Conclusions:From these findings we conclude that shared genetic influences may explain comorbidity observed between SUDs and internalizing disorders and suggest that genetic risk for internalizing should be incorporated into SUD identification and prevention efforts. Future gene identification efforts should study SUDs in the context of both externalizing and internalizing psychopathology.

BACKGROUND:The field's conventional understanding of how genetic factors impact risk for alcohol use disorder (AUD) typically focuses on direct genetic effects, or how an individual's own genetic predispositions are associated with the likelihood of experiencing clinically significant alcohol problems. More recently, studies of behavioral health outcomes in preclinical and human studies have demonstrated the potential importance of social genetic effects or the influence of a social partner's genotype on substance use and related outcomes. In this study, we sought to characterize social genetic effects for AUD, specifically in the context of marriage. METHODS:The sample included 660 opposite-sex spousal dyads from the Collaborative Study on the Genetics of Alcoholism, restricted to individuals who were genetically similar to European reference panels. Measured and latent indicators of genetic risk included polygenic scores of problematic alcohol use (PGSPAU) and parental history of AUD (PHAUD), respectively. The outcome was Diaganostic and Statistical Manual (DSM)-5 alcohol use disorder criterion count (AUDcrit) during marriage. Multilevel models accounted for the non-independence of partners' data, including correlations between partners' genetic risk and residual covariance in AUDcrit. RESULTS:After accounting for direct genetic effects (i.e., the influence of one's own genetic predispositions) and the correlations between partners' genetic predispositions, we found that having a spouse with higher PGSPAU was associated with higher AUDcrit (B = 0.084, 95% CI [0.035, 0.132]). This social genetic effect was robust after adjusting for both partners' educational attainment. Spousal PHAUD was not associated with AUDcrit. Exploratory analyses indicated that the social genetic effect of spousal PGSPAU was stronger among male target individuals. CONCLUSIONS:Findings highlight the potential importance of social genetic effects for understanding the pathways from genotype to alcohol use disorder and the need for further investigation of latent measures of genetic predispositions in studies of social genetic effects.

Externalizing spectrum disorders-spanning attention-deficit/hyperactivity disorder, conduct disorder, substance use disorders, and other disorders characterized by disinhibition-frequently co-occur within individuals due, in part, to shared genetic etiology. To advance understanding of this genetic architecture, we conducted a multi-ancestry, multivariate genome-wide association analysis of more than 4 million individuals, identifying 1,294 genomic regions linked to an externalizing factor. Fine-mapping and gene prioritization efforts identified 961 effector genes, with the putative causal variant associations showing robust replication in the All of Us Research Program sample. Bioinformatic analyses revealed a broadly distributed neural architecture with early and sustained involvement of GABAergic and glutamatergic neurons. Drug repurposing analyses further highlighted the role of GABAA receptors, as well as dopaminergic signaling, excitatory-inhibitory balance, and neurosteroid pathways. A genome-wide polygenic index predicted ~12% of the variance in externalizing in independent cohorts of individuals with European-like ancestry, compared to ~3% in individuals with African-like ancestry, and was associated with myriad health and life outcomes. Together, these findings map the shared genetic etiology of externalizing psychopathology and identify neurodevelopmental and synaptic mechanisms with translational relevance.

Adverse childhood experiences (ACEs) are an established risk factor for substance use (Dube et al., 2003), but limited work has tested the moderating role of cultural factors. The current study tested whether ACEs were related to cannabis use, and whether ERI components moderated this relation among 733 emerging adults. We also tested ethnic-racial group differences between Black, White, and Asian participants. A series of nested multigroup path analysis models were used, and findings indicated that among all participants, ACEs were associated with more cannabis use ( p = .03), but ERI exploration moderated this association for Black participants ( p = .01) and White participants ( p = .00). At low ERI exploration, ACEs were associated with greater cannabis use, but at high ERI exploration ACES were not associated with cannabis use. Further, among Asian participants, ERI exploration ( p = .00) and resolution ( p = .02) were directly associated with less cannabis use.

BACKGROUND:The goal of this paper is to identify environmental, behavioral, and genetic predictors and early midlife correlates of problematic alcohol Use (PAU) patterns from adolescence to early midlife. METHODS:The data are from 1463 twin individuals (60.5% female) in the population-based FinnTwin12 cohort born 1983-1987. PAU was assessed at ages 14, 22 and 37 using symptoms of alcohol use disorder (AUD) obtained from psychiatric interviews, mmMAST scores, and the AUDIT. Self-reported health and well-being were assessed at age 37. A behavioral and environmental risk index (BERI) was created by summing six risk factors: low socioeconomic status in childhood, family history of AUD, childhood externalizing and internalizing behaviors, adolescent substance use, peer substance use, and stressful life events in adolescence. The twins' genetic predispositions were indexed using polygenic scores for externalizing behavior (PGSEXT), PAU (PGSPAU), and depression (PGSMDD). RESULTS:Twins were classified into four PAU groups: Never (n = 599, reference), Remitted (n = 480), Persistent (n = 271), and Late-onset (n = 113). When included in the same model, both BERI and PGSEXT were significantly associated with Remitted PAU, while BERI scores and PGSPAU were significantly associated with Persistent PAU. Compared to the Never PAU group, individuals in the Persistent and Late-onset PAU groups reported lower educational attainment, poorer physical health, lower relationship satisfaction, lower life satisfaction, a worse financial situation, more depressive symptoms, recurrent pain, and sleep problems, and were less likely to be partnered or have children. CONCLUSIONS:Persistent PAU was associated with the most negative outcomes in early midlife, and childhood and adolescent risk factors and genetic risk as indexed by PGSPAU were strong predictors of group membership. Late-onset PAU may be the result of novel stressors in adulthood, given the lack of association with childhood and adolescent environmental risk or genetic risk.

Personality traits describe stable differences in how people think, feel and behave, and how they interact with and experience their social and physical environments1,2. Many questions remain unanswered about associations between DNA and personality traits, such as their robustness, their generalizability and the biological and social pathways through which they act. Here we meta-analyse data across 46 cohorts comprising 611,037 to 1.14 million participants with European-like and African-like genomes for genome-wide association studies (GWAS) of the Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism and openness to experience), and data from up to 50,725 participants for within-family GWAS. We identify 1,260 lead genetic variants associated with personality, including 824 novel variants3. Common genetic variants explain a moderate 4.8-9.3% of the variance in measures of each trait, and 9.3-13.3% among instruments with typical measurement reliability. Genetic associations with personality are highly consistent but not identical across geography, reporter (self versus close other), age group and measurement instrument, and we find minimal spousal assortment for personality in recent history. In contrast to many other social and behavioural traits4,5, within-family GWAS and polygenic index analyses indicate that genetic associations with personality are minimally confounded by the shared family environment. Polygenic prediction, genetic correlation and Mendelian randomization analyses indicate that personality traits have widespread, potentially causal associations with consequential behaviours and life outcomes. Overall, we find that the genetic architecture of personality is robustly generalizable, minimally confounded and widely relevant to human experience.

Excessive alcohol use is associated with adverse outcomes, underscoring the importance of identifying factors that may reduce alcohol use among diverse emerging adults, including ethnic-racial identity (ERI) and family factors. Limited work has examined factors that moderate the relations between ERI and alcohol use. The current study tested whether family factors (i.e., parent education and family history of alcohol problems) moderated the relations between ERI and alcohol use among 1850 diverse college students, ages 18–22 (M = 18.46, SD = .38). Findings indicated that moderation effects varied by students’ ethnicity/race. At high levels of parent education, greater ERI resolution predicted less alcohol use among Asian individuals, and greater alcohol use among White individuals. Among Multiracial individuals with lower family history of alcohol problems, greater ERI exploration was related to less alcohol use. Findings highlight nuanced ways that ERI, parent education, family history of alcohol problems, and racial differences influence college students’ alcohol use. Results have implications for alcohol prevention and intervention programs by highlighting that both ERI development and family influences should be discussed by therapists, program leaders, and mentors with emerging adults across racial backgrounds.

Despite drastic advances in psychiatric genetics, comparatively little attention has focused on the translation of those discoveries into real-world impact. This paper reviews the processes and considerations for integrating new techniques into clinical practice and provides an overview of areas of medicine where polygenic scores (PGS) are already being incorporated. We evaluate current PGS across three areas of psychiatry (depression, substance use disorders, and schizophrenia) against the criteria used by the National Electronic Medical Records and Genomics consortium to select PGS to study in a clinical context, finding that the PGS for psychiatric conditions are comparable to the PGS being implemented in clinical practice for other medical conditions. We conclude by discussing next steps for evaluating psychiatric PGS for clinical implementation including ethical issues that must be considered, and the need for more research on clinical utility to evaluate whether and how PGS can be used to improve behavioral health outcomes.

INTRODUCTION:Current best practice is for primary care physicians (PCPs) to screen patients for problematic substance use at checkups. However, this practice is not routine, is done in an unstandardized manner, and contributes to the overburdening of PCPs. Screening practices also target current, potentially problematic use behaviors, thus limiting their capacity to help patients prevent problems before they start. Recent scientific advances in identifying people at elevated risk for substance use problems as a means of facilitating prevention efforts have not yet been integrated into medical practice. To address these issues, our research team developed a freestanding platform called the Comprehensive Addiction Risk Evaluation System (CARES). CARES provides personalized information about genetic and behavioral/environmental risk for substance use disorder (SUD) and connects individuals to resources based on their risk profile. The present study evaluated the potential for adoption and implementation of CARES within a healthcare system through qualitative interviews with key stakeholders. METHODS:Semi-structured interviews were developed using the Consolidated Framework for Implementation Research (CFIR) and conducted with N = 15 interviewees. Transcripts were analyzed using rapid qualitative analysis. RESULTS:Key themes included perceived need for new SUD screening tools, current SUD screening procedures and their pros/cons, openness to new ideas and clinical tools, fit of CARES with organizational goals and priorities, considerations for use of CARES with adolescent populations, anticipated patient response to CARES, barriers to implementation and uptake of CARES, changes to CARES required for implementation, and possibility for integrating results from CARES into patient medical records. Interviewees generally expressed need for new screening tools and openness to using new tools, but expressed concern that existing provider burden, lack of SUD knowledge, and discomfort/stigma could stymie efforts to implement CARES. CONCLUSIONS:There is a clear need for a low-burden, easy-to-use tool for substance use prevention. CARES appears to be an acceptable and feasible approach to fill this gap. These findings will be used to inform pilot implementation of CARES in clinical care settings.

Eating disorders—including anorexia nervosa (AN), bulimia nervosa and binge-eating disorder—are clinically distinct but exhibit symptom overlap and diagnostic crossover. Genomic analyses have mostly examined AN. Here we conducted a genomic meta-analysis of case–control studies of binge-eating behavior (BE; 39,279 cases, 1,227,436 controls), alongside analyses of AN (24,223 cases, 1,243,971 controls) and its subtypes (all European ancestries). We identified six BE-associated loci, including loci associated with a higher body mass index and impulse-control behaviors. AN genome-wide association studies yielded eight loci, validating six loci. Subsequent polygenic risk score analysis demonstrated an association with AN in two East Asian ancestry studies. BE and AN exhibited similar positive genetic correlations with psychiatric disorders but opposing genetic correlations with anthropometric traits. Most of the genetic signal in BE and AN was not shared with body mass index. We have extended eating disorder genomics beyond AN; future work will incorporate multiple diagnoses and global ancestries. This research identified six areas in the genome that are associated with binge eating, and eight areas that are associated with anorexia nervosa, in people of European ancestry. Binge eating has both shared and distinct genetic features compared with anorexia nervosa.

Laboratory-based paradigms allow for the collection of multimodal assessments. A fear conditioning (FC) paradigm, capturing one key risk factor for posttraumatic stress disorder (PTSD) and alcohol use disorder, has been administered in a lab-based format. Recently, a smartphone-based application (app, specifically called “Fear Learning and Anxiety Response, FLARe”) of this FC paradigm has been administered within control and anxiety samples. However, this app has not been administered to trauma-exposed individuals. Thus, the primary goal of this study was to test the feasibility of this app among those with a trauma history. Results suggest that this app can be administered to trauma-exposed individuals and that they acquire fear, defined as expectancy that a loud noise will occur, to previously neutral stimuli ( t = −12.55, p <.001), and then extinguish that fear immediately ( t = −4.95, p <.001), and the next day ( t = −4.01, p <.001). Thus, study findings provide preliminary evidence that this FC task is not functioning in the same way in the app as it does in the lab for trauma-exposed participants.

We investigated longitudinal associations between adolescent attention-deficit/hyperactivity disorder (ADHD) symptoms and later antisocial behavior and tested 1) whether these associations are independent of familial factors shared by co-twins and 2) whether cognitive performance moderates the associations. In a population-based sample of Finnish twins (N = 602-1330, 53% female), we assessed ADHD symptoms with teacher assessments and a diagnostic interview in adolescence, symptoms of antisocial personality disorder with a diagnostic interview in young adulthood, and criminal behavior across the lifespan with self-reports in early midlife. Cognitive performance was assessed with commonly used test measures in young adulthood. Adolescent ADHD symptoms were consistently associated with an increased risk for antisocial symptoms (incidence rate ratio [IRR] = 1.18-1.27) and criminal behavior (IRR = 1.16-1.20) later in life. Within-pair and interaction analyses suggested that the associations were to a large degree independent of familial factors, and cognitive performance level did not moderate them. In conclusion, subclinical ADHD symptoms are associated with an increased risk for antisocial behavior at the population level. The association is not fully explained by familial background, and it is independent of cognitive performance level.

The Collegiate Recovery Research Collaborative (CRRC) is a diverse group of academics and practitioners who have lived experience of recovery or who identify as allies, and addresses the lack of diverse, transdisciplinary research communities in addiction recovery. This article describes the process the CRRC used to facilitate a recent retreat focused on collegiate recovery research as a novel, replicable framework for identifying exploratory research ideas within the recovery community. This article also summarizes the insights and ideas derived from the retreat as the product of a collaborative and intentionally-fostered intellectual exercise, and identifies actionable next steps in collegiate recovery research.

We performed a genome-wide association meta-analysis (GWAMA) of 290,134 attention-deficit/hyperactivity disorder (ADHD) symptom measures of 70,953 unique individuals from multiple raters, ages and instruments (ADHDSYMP). Next, we meta-analyzed the results with a study of ADHD diagnosis (ADHDOVERALL). ADHDSYMP returned no genome-wide significant variants. We show that the combined ADHDOVERALL GWAMA identified 39 independent loci, of which 17 were new. Using a recently developed gene-mapping method, Fine-mapped Locus Assessment Model of Effector genes, we identified 22 potential ADHD effector genes implicating several new biological processes and pathways. Moderate negative genetic correlations (rg < -0.40) were observed with multiple cognitive traits. In three cohorts, polygenic scores (PGSs) based on ADHDOVERALL outperformed PGSs based on ADHD symptoms and diagnosis alone. Our findings support the notion that clinical ADHD is at the extreme end of a continuous liability that is indexed by ADHD symptoms. We show that including ADHD symptom counts helps to identify new genes implicated in ADHD.