American Journal of Psychiatry

ObjectiveSubstance use disorders (SUD) are associated with risk of psychiatric comorbidities, with inconsistent sex differences, across studies. The objective of this study is to determine odds of psychiatric comorbidities based on sex, in persons with either primary opioid, alcohol or cannabis dependence diagnoses, from a national clinical data set. MethodsThis is a cross-sectional study of data from state-funded and state-run mental health programs in 2022 (Mental Health Client-Level Data, from the US Substance Abuse and Mental Health Administration). Data was obtained from adults (age [≥]18) with a primary diagnosis of either opioid (n=28,808), alcohol (n=23,281) or cannabis dependence (n=5,961). Individuals with each SUD were examined for psychiatric comorbidity outcomes, based on secondary diagnoses of either anxiety, bipolar, depression, schizophrenia or other psychotic disorders (SPD), or trauma and stressor-related disorders, versus no comorbidity. Data were analyzed with multinomial logistic regressions, examining sex, race, ethnicity and age as predictors. ResultsMales with primary diagnoses of either opioid, alcohol or cannabis dependence had lower adjusted odds of anxiety, bipolar, depression and trauma/stressor disorders, compared to females. However, males with opioid or cannabis dependence had higher adjusted odds of SPD, compared to females. Adjusted analyses also detected associations of race and ethnicity with specific comorbidities. ConclusionsIn this recent national clinical data set, there are specific sex-based differences in specific psychiatric comorbidities for each of these three SUDs. Future studies should examine biopsychosocial mechanisms that underlie these differences, with the goal of improving personalized care.

BackgroundRisk for Tourettes and related tic disorders (CTD) derives from a combination of genetic and environmental factors. While multiple studies have demonstrated the importance of direct additive genetic variation for CTD, little is known about the role of cross-generational transmission of genetic risks, such as maternal effects. Here, we partition sources of variation on CTD risk into direct additive genetic effect and maternal effects. MethodsThe study population consists of 2,522,677 individuals from the Swedish Medical Birth Register, born in Sweden between January 1, 1982, to December 31, 1990, and followed for a diagnosis of CTD through December 31, 2013. ResultsWe identified 6,227 (0.25%) individuals in the birth cohort diagnosed with CTD. Using generalized linear mixed models, we estimated 4.7% (95% CrI, 4.4%-4.8%) genetic maternal effects, 0.5% (95% CrI, 0.2%-7%) environmental maternal effects, and 61% (95% CrI, 59%-63%) direct additive genetic effects. Around 1% of genetic maternal effects were due to maternal effects from the individual with comorbid obsessive-compulsive disorder. ConclusionsOur results demonstrate genetic maternal effects contributing to the risk of CTD in offspring and also highlight new sources of overlapping risk between CTD and obsessive-compulsive disorder.

BackgroundA common feature of Cannabis use disorder (CUD) is an intense reactivity to cannabis cues, which are becoming increasingly visible due to growth in the decriminalization, accessibility and marketing of cannabis products. The brains automatic reactivity to cannabis cues can trigger craving and subsequent use. This study aimed to test neural activity during cannabis cue-induced craving in non-treatment seeking individuals with moderate-to-severe CUD, with past attempts to cut down/quit. MethodsThe study examined 65 individuals with moderate-to-severe CUD and 43 controls, with a fMRI cannabis cue-induced craving task and assessment of mental health, substance use, and cognitive testing. Group differences in neural cue-induced craving were examined, adjusting for age and sex; correlations with cannabis use characteristics were assessed, accounting for recent substance use. ResultsIndividuals with a CUD relative to controls showed greater brain activity during cannabis cue-induced craving in the superior/middle occipital, medial/lateral OFC, anterior/posterior cingulate, cerebellar, hippocampus, middle temporal and lateral parietal cortices (p < .05; cluster k > 10, FWE-corrected). Greater occipital/cerebellar activity correlated with greater subjective arousal towards cannabis images and cannabis withdrawal scores, while anterior cingulate/inferior parietal activity negatively correlated with urinary level of 11-Nor-9-carboxy-{Delta}9-tetrahydrocannabinol:creatinine (ps<.05). ConclusionsExposure to cannabis cues can elicit greater activity within salience evaluation/attention, motivation and disinhibition pathways of addiction neurocircuitry in people with moderate-to-severe CUD, consistent with prominent neuroscientific theories of addiction and findings with other substances. Interventions which can suppress brain activity in salience and attention circuits during cannabis-induced craving may help reduce craving and subsequent use.

AimsWe performed a latent class analysis (LCA) in a sample ascertained for addiction phenotypes to investigate cocaine use disorder (CoUD) subgroups related to polysubstance addiction (PSA) patterns and characterized their differences with respect to psychiatric and somatic comorbidities. DesignCross-sectional study SettingUnited States ParticipantsAdult participants aged 18-76, 39% female, 47% African American, 36% European American with a lifetime DSM-5 diagnosis of CoUD (N=7,989) enrolled in the Yale-Penn cohort. The control group included 2,952 Yale-Penn participants who did not meet for alcohol, cannabis, cocaine, opioid, or tobacco use disorders. MeasurementsPsychiatric disorders and related traits were assessed via the Semi-structured Assessment for Drug Dependence and Alcoholism. These features included substance use disorders (SUD), family history of substance use, sociodemographic information, traumatic events, suicidal behaviors, psychopathology, and medical history. LCA was conducted using diagnoses and diagnostic criteria of alcohol, cannabis, opioid, and tobacco use disorders. FindingsOur LCA identified three subgroups of PSA (i.e., low, 17%; intermediate, 38%; high, 45%) among 7,989 CoUD participants. While these subgroups varied by age, sex, and racial-ethnic distribution (p<0.001), there was no difference on education or income (p>0.05). After accounting for sex, age, and race-ethnicity, the CoUD subgroup with high PSA had higher odds of antisocial personality disorder (OR=21.96 vs. 6.39, difference-p=8.08x10-6), agoraphobia (OR=4.58 vs. 2.05, difference-p=7.04x10-4), mixed bipolar episode (OR=10.36 vs. 2.61, difference-p=7.04x10-4), posttraumatic stress disorder (OR=11.54 vs. 5.86, difference-p=2.67x10-4), antidepressant medication use (OR=13.49 vs. 8.02, difference-p=1.42x10-4), and sexually transmitted diseases (OR=5.92 vs. 3.38, difference-p=1.81x10-5) than the low-PSA CoUD subgroup. ConclusionsWe found different patterns of PSA in association with psychiatric and somatic comorbidities among CoUD cases within the Yale-Penn cohort. These findings underscore the importance of modeling PSA severity and comorbidities when examining the clinical, molecular, and neuroimaging correlates of CoUD.

Background and AimsCertain symptoms of problematic alcohol use (PAU) show associations with comorbid internalizing and externalizing disorders even after controlling for their common PAU factor. Outsized associations between PAU indicators and comorbid psychopathology may reflect distinct etiologic pathways or measurement characteristics that, if unaccounted for, could bias comorbidity estimates with PAU. Although these issues could represent a source of bias in estimates of genetic correlation with PAU, no studies have yet extended this work using genomic data. DesignGenomic structural equation modeling and the Qtrait function identified PAU indicators that showed appreciable residual genetic correlations with eleven comorbid psychiatric disorders and whose associations did not operate strictly through the latent PAU factor. SettingGenome-wide association studies (GWAS) were conducted in a variety of international locations. ParticipantsGWAS used in this study were conducted on 86,979 to 425,166 individuals of European ancestry. MeasurementsThe primary measurements were GWAS summary statistics for various forms of internalizing, externalizing, and neurodevelopmental psychiatric disorders and nine indicators from the Alcohol Use Disorder Identification Test. FindingsPAU indicators assessing alcohol-related consequences (i.e., Injuries, Failed expectations, Guilt/Remorse) each showed appreciable and positive residual genetic associations with multiple comorbid psychiatric conditions spanning various disorder spectra. Alcohol Quantity, 6+ Frequency, Blackouts, and Others concerned did not show direct genetic relationships with comorbid disorders. ConclusionsAlcohol-related consequences share unique genetic underpinnings with multiple psychiatric conditions apart from what is shared with their latent problematic alcohol use factor. Thus, alcohol-related consequences may unduly reflect dysfunction from comorbid psychiatric conditions or related third variables.

ObjectivesObsessive-compulsive disorder (OCD) is a common psychiatric disorder, with two-thirds of affected individuals reporting severe impairment. Despite its substantial burden and moderate heritability, its etiology remains poorly understood, and treatments are often suboptimal. While recent genome-wide association studies (GWAS) have identified some risk loci, yet OCD remains in the linear phase of sample collection to variant association, with many more OCD-associated variants left to discover. This study aimed to develop and validate an electronic health record (EHR)-based algorithm to identify OCD cases and facilitate large-scale genetic studies. MethodsWe leveraged EHR-linked biobank data from two large hospital systems, namely Vanderbilt University Medical Center (VUMC) and Mass General Brigham (MGB), to develop a high-throughput phenotyping algorithm integrating diagnostic codes, medication records, and natural language processing (NLP) of clinical notes. Algorithm performance was evaluated through expert chart review, and genetic validation was performed using OCD polygenic risk scores (PRS). ResultsExpert chart reviews found that our algorithm combining both ICD codes and NLP achieved higher positive predictive values (PPV) for OCD cases (0.84 at VUMC and 0.91 at MGB) compared to using either ICD codes or NLP alone, albeit with a lower case yield. Furthermore, at both sites, algorithm-determined cases exhibited significantly elevated PRS derived from the latest OCD GWAS, providing genetic validation of our phenotyping approach. ConclusionOur study demonstrates a scalable and cost-efficient approach for EHR-based ascertainment of OCD cases, facilitating large-scale genetic studies and advancing understanding of the disorders complex etiology.

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.

BackgroundSuicidal behaviour is commonly associated with major depression (MD) and substance use disorders (SUDs). However, there is a paucity of research on risk for suicide ideation among individuals with comorbid SUDs and MD in the general population. ObjectivesThis study investigated the associated risk of suicide ideation in comorbid SUDs - cannabis use disorder (CUD), alcohol use disorder (AUD), drug use disorder (DUD) with depression in a nationally representative sample. MethodsMultilevel logistic regression models were used to analyze the 2012 Canadian Community Health Survey (CCHS-MHC) data. This is a cross-sectional survey of nationally representative samples of Canadians (n = 25,113) aged 15 years and older residing in the ten Canadian provinces between January and December 2012. Diagnoses of MD episode, AUD, DUD, CUD, and suicide risk were based on the WHO-CIDI-3.0 derived from DSM-IV diagnostic criteria. ResultsComorbidity was found to be the strongest predictor of suicide ideation. Compared to those with no diagnosis, individuals with a comorbid diagnosis of AUD with MDE, CUD with MDE, or DUD with MDE were 9 to 16 times more likely to have suicide ideation. A diagnosis of MDE was a significant predictor of suicide ideation with about a 7-fold increased risk. ConclusionSuicide is a preventable public health issue. Our study found a significantly increased risk of suicide ideation among persons who have comorbid SUD with MD. Effective integration of mental health and addictions services could mitigate the risk of suicide and contribute to better outcomes.

Background: Adverse childhood events (ACEs) contribute to the development of mood and anxiety disorders and substance dependence. However, the extent to which these effects are direct or indirect and whether genetic risk moderates them is unclear. Methods: We examined associations among ACEs, mood/anxiety disorders, and substance dependence in 12,668 individuals (44.9% female, 42.5% African American/Black, 42.1% European American/White). We generated latent variables for each phenotype and modeled direct and indirect effects of ACEs on substance dependence, mediated by mood/anxiety disorders (forward or "self-medication" model) and of ACEs on mood/anxiety disorders, mediated by substance dependence (reverse or "substance-induced" model). In a sub-sample, we also generated polygenic scores for substance dependence and mood/anxiety disorder factors, which we tested as moderators in the mediation models. Results: Although there were significant indirect effects in both directions, mediation by mood/anxiety disorders (forward model) was greater than by substance dependence (reverse model). Greater genetic risk for substance dependence was associated with a weaker direct effect of ACEs on substance dependence in both the African- and European-ancestry groups (i.e., gene-environment interaction) and a weaker indirect effect in European-ancestry individuals (i.e., moderated mediation). Conclusion: We found greater evidence that substance dependence results from self-medication of mood/anxiety disorders than that mood/anxiety disorders are substance induced. Among individuals at higher genetic risk for substance dependence who are more likely to develop a dependence diagnosis, ACEs exert less of an effect in promoting that outcome. Following exposure to ACEs, multiple pathways lead to mood/anxiety disorders and substance dependence. Specification of these pathways could inform individually targeted prevention and treatment approaches.

Substance use disorders commonly co-occur with one another and with other psychiatric disorders. They share common features including high impulsivity, negative affect, and lower executive function. We tested whether a common genetic factor undergirds liability to problematic alcohol use (PAU), problematic tobacco use (PTU), cannabis use disorder (CUD), and opioid use disorder (OUD) by applying genomic structural equation modelling to genome-wide association study summary statistics for individuals of European ancestry (Total N = 1,019,521; substance specific Ns range: 82,707-435,563), while adjusting for the genetics of substance use (Ns = 184,765-632,802). We also tested whether shared liability across SUDs is associated with behavioral constructs (risk taking, executive function, neuroticism; Ns = 328,339-427,037) and non-substance use psychopathology (psychotic, compulsive, and early neurodevelopmental disorders). Shared genetic liability to PAU, PTU, CUD, and OUD was characterized by a unidimensional addiction risk factor (termed The Addiction-Risk-Factor, independent of substance use. OUD and CUD demonstrated the largest loadings, while problematic tobacco use showed the lowest loading. The Addiction-Risk-Factor was associated with risk taking, neuroticism, executive function, and non-substance psychopathology, but retained specific variance before and after accounting for genetics of substance use. Thus, a common genetic factor partly explains susceptibility for alcohol, tobacco, cannabis, and opioid use disorder. The Addiction-Risk-Factor has a unique genetic architecture that is not shared with normative substance use or non-substance psychopathology, suggesting that addiction is not the linear combination of substance use and psychopathology.

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.

BackgroundPolysubstance use (PSU), defined as the use of multiple psychoactive substances, often begins during adolescence. Since PSU is associated with heightened risk of subsequent health issues, including substance use disorders, understanding its antecedents could ultimately have significant public health impacts. We investigated how genetic susceptibility, and environmental exposures together influence the initiation of PSU in adolescents. MethodsWe analyzed data from 11,868 adolescents (aged 11-15 years) in the Adolescent Brain and Cognitive Development study. PSU was assessed through interviews and toxicology. We examined the associations of polygenic scores (PGSs) for addiction, derived from GenomicSEM analysis, environmental factors, and their interactions, with the initiation of PSU, while controlling for multiple covariates. OutcomesOur sample included 7,898 adolescents (mean age 12.9 [0.6] years; 4,150 [53%] male). Overall, 541 (6.8%) had initiated single substance use (SSU), and 162 (2.1%) reported PSU. PGSs for general addiction risk were significantly associated with PSU (Odds Ratios [OR]=1.62, 95% CI=1.30-2.01) but not with SSU. Key environmental risk factors for PSU included prenatal substance use and peer victimization, while planned pregnancy and positive family dynamics acted as protective factors. Notably, gene-environment interaction analyses showed that peer victimization (OR=2.4, 95% CI=1.4-4.2), prenatal substance use (OR=2.1, 95% CI=1.2-3.6), and substance availability (OR=2.3, 95% CI=1.3-3.9) increased PSU risk among adolescents with high genetic susceptibility but had negligible effects at low genetic risk levels (all p < 0.05 after multiple testing correction). InterpretationThis study provides the first evidence linking polygenic risk to PSU in early adolescence and demonstrates that PSU represents more severe manifestation of substance use liability, driven by heightened genetic vulnerability and adverse environmental exposures. This underscores the importance of studying PSU explicitly, identifying high-risk individuals early, and implementing tailored interventions to mitigate the risk of escalating substance use behaviors. FundingNational Institutes of Health. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe conducted a literature search on PubMed for research articles published in English from inception to August 30, 2024, using the search terms: ("polygenic risk" OR "polygenic score" OR "genetic risk") AND ("adolescents" OR "adolescence") AND ("polysubstance use" OR "multiple substance use" OR "number of substances"). This search yielded no studies examining the relationship between polygenic risk of substance use and polysubstance use (PSU) in adolescence, revealing a critical gap in the field. To investigate environmental factors, we searched PubMed using the terms: (("environmental risk" OR "environmental factor" OR "social determinants") AND ("adolescents" OR "adolescence") AND ("polysubstance use" OR "multiple substance use" OR "number of substances")). This search highlighted consistent associations between adolescent PSU and adverse social determinants, such as socioeconomic disadvantage, prenatal exposure, parental monitoring, peer influence, and trauma experience. However, evidence for interactions between genetic and environmental factors was limited to a small number of candidate gene studies, with largely inconclusive findings. Added value of this studyThis study offers several important contributions to the field. First, to our knowledge, it is the first population-based study in the U.S. to examine PSU in early adolescence within a large, diverse cohort, leveraging data from the Adolescent Brain Cognitive Development (ABCD) Study. The ABCD studys comprehensive and inclusive sampling enables analyses across socioeconomic and racial/ethnic backgrounds, strengthening the generalizability of findings. Second, our results reveal a previously unreported association between polygenic risk and PSU in adolescents. Specifically, we show that genetic risk shared across five adult substance use disorders (SUDs) including alcohol, nicotine, cannabis, cocaine, and opioid use disorders, significantly relates to PSU outcomes among adolescents aged 11-15 years. Third, the ABCD studys in-depth characterization of participants allows us to examine a wide array of contributory individual and socio-environmental factors. Finally, this study highlights specific environmental contexts--such as prenatal substance use, family dynamics, and peer relationships--that interact with genetic predisposition to shape PSU behaviors in adolescence. This integrative approach provides insights into gene-environment (GxE) interactions that contribute to PSU, offering a more nuanced understanding of the mechanisms underlying health disparities in adolescent substance use outcomes. Implications of All Available EvidenceOur study shows that integrating polygenic risk with assessments of environmental factors in adolescent population improves understanding of PSU risk. Adolescents exposed to adverse social determinants are particularly vulnerable to PSU, especially when they have a higher genetic predisposition to SUDs. These insights support more explicit study of PSU and targeted early prevention strategies addressing both genetic vulnerabilities and environmental stressors to reduce PSU risk in preadolescence.

Cannabis and tobacco use are highly prevalent among people with psychosis and are associated with medical comorbidities and poor prognosis. Concurrent use of cannabis and tobacco ("co-use") is rising in the general population but has not been studied in psychosis. Given the devastating consequences of cannabis and tobacco use, it is critical to understand how their co-use affects psychiatric symptoms and the development of psychosis. We used the North American Prodrome Longitudinal Study 2, a multi-site prospective study of individuals at clinical high risk for psychosis (CHR) and healthy controls, to examine baseline differences in psychiatric symptoms and conversion to psychosis across substance groups: 1) CHR tobacco use, 2) CHR cannabis use, 3) CHR co-use, 4) CHR non-tobacco or cannabis substance use, 5) CHR without substance use, and 6) healthy controls. Among 1,014 participants (734 CHR, 280 controls), more frequent cannabis and tobacco use was linked to greater psychiatric symptom severity, including psychosis, anxiety, and depression. In survival analyses, co-use (HR = 2.53, 95% CI [1.44-4.45], p =.001), especially heavy co-use (HR = 3.63, 95% CI: 1.53-8.63, p = 0.003), was associated with increased risk of conversion to psychosis. Co-use of tobacco and cannabis was not associated with psychiatric symptom severity but did predict higher risk of conversion to psychosis. The combination of cannabis and tobacco use may exert a synergistic effect, amplifying conversion risk more than either substance alone, or may be a marker of an elevated underlying psychosis risk. These results highlight the need for early intervention strategies that address co-use in CHR populations to mitigate potential long-term psychiatric consequences.

BackgroundNumerous studies have reported associations between environmental exposures and ADHD. However, whether environmental effects are causal or due to confounding with other familial factors, such as genetic risk, is still unclear. A more complete understanding of which environmental risk factors are causal remains crucial. MethodsUsing one population (ABCD cohort, N=11646) and one case-control cohort (Oregon ADHD-1000, N=744), we conducted both full-cohort and sibling-control analyses (770 and 152 families in ABCD and Oregon ADHD-1000, respectively) to assess the association of family environment and perinatal risk factors with ADHD symptoms. Within-family effects were compared to effects estimated in the full cohorts. We also assessed the impact of gene-environment correlation using child polygenic risk scores and measures of maternal mental health. ResultsFor both cohorts, full-cohort analyses yielded significant associations between child ADHD symptoms and family conflict, perinatal health factors, and breastfeeding duration (p-values <0.001). These associations were non-significant after accounting for family-level confounds (e.g., genetic risk and shared family environment) in exposure-discordant sibling-control analyses. In the full cohorts, effect sizes were substantially reduced (an average 43.7% decrease in effect size across all exposures tested in the ABCD cohort; average 47.6% decrease in Oregon ADHD-1000) after adjusting for child ADHD polygenic risk and measures related to maternal mental health. ConclusionsThe full-cohort associations between child ADHD symptoms and environmental risks confirm associations from prior research, but current findings do not indicate direct causal effects. Instead, much or all of the observed risk appears due to confounding with family-level factors, likely including genetic factors. Our results underscore the importance of accounting for familial risk factors that may confound relationships between behavioral traits and environmental exposures by using multiple study designs. Key PointsO_LINumerous environmental risk factors are associated with ADHD, but whether these are important casual associations is insufficiently studied. C_LIO_LISignificant associations between child ADHD symptoms and features of the family environment and perinatal health were replicated in two independent cohorts, confirming prior work. C_LIO_LISibling-control analyses provided no consistent evidence of causal relationships for any of the risk factors studied. Furthermore, accounting for factors related to genetic risk and parental mental health substantially reduced the observed effect sizes in full-cohort analyses. C_LIO_LIFindings are consistent with previous studies on the effects of breastfeeding duration and some substance exposures (e.g., smoking during pregnancy), suggesting associations are largely due to confounding with unmeasured familial factors. C_LIO_LIFurther study is warranted regarding potential sex differences in exposure associations with ADHD symptoms, as well as more complex causal pathways (e.g., gene-environment or environment-environment interaction). C_LI

AimsEstimate trends in levels of cannabis use among adults with and without serious psychological distress (SPD) in the United States from 2009-2019, and to ascertain whether cannabis use among individuals with SPD was associated with inpatient psychiatric hospitalization and outpatient mental health care. DesignUsing multivariable logistic regression models and predictive margin methods, we estimated linear time trends in levels of cannabis use by year and SPD status and rates of psychiatric hospitalization and outpatient service use. SettingThe United States: National Survey on Drug Use and Health (NSDUH), an annual cross-sectional survey, 2009-19 public use files. Participants447,228 adults aged [&ge;] 18 years. MeasurementsIn the past year, self-report of any and greater-than-weekly cannabis use, any inpatient psychiatric hospitalization, and any outpatient mental health care. FindingsRates of any and weekly-plus cannabis use increased similarly among individuals with SPD compared to those without from 2009-2014 but more rapidly in SPD from 2015-2019 (p<0.001). Among individuals with SPD, probability of psychiatric hospitalization was greater among individuals with less than weekly (5.2%, 95% CI 4.4-5.9%, p=0.011), and weekly-plus cannabis use (5.4%, 95% CI 4.6-6.1, p=0.002) compared to no use (4.1%, 95% CI 3.8-4.4%). For outpatient mental health care, no use was associated with a 27.4% probability (95% CI 26.7-8.1%) of any outpatient care, significantly less than less than weekly use (32.7% probability, 95% CI 31.3-34.1% p<0.001) and weekly-plus use (29.9% probability, 95% CI 28.3-31.5% p=0.006). ConclusionsCannabis use is increasing more rapidly among individuals with SPD than the general population, and is associated with increased rates of psychiatric hospitalization as well as increased outpatient service use. These findings can inform policy makers looking to better tailor regulations on advertising for medical and adult use cannabis and develop public health messaging on the use of cannabis in people with mental illness.

AimsTo estimate polygenic and polygene x environment contributions to alcohol consumption and problems in the context of childhood maltreatment and lifetime trauma. DesignMain and interaction effects models predicting alcohol consumption and problems were estimated using multiple linear regression. Covariates included age, sex, education, employment status, and ancestral principal components. SettingUSA ParticipantsA sample of 2,114 Black adults (75% female; Mage=39.88, SD=13.92) recruited from the Grady Trauma Hospital in Atlanta, Georgia. MeasurementPolygenic scores (PGS) for trauma-related symptoms (re-experiencing: PGSREEX, avoidance: PGSAVOID, hyperarousal: PGSHYPER, PTSD symptom score: PGSPCL) and alcohol consumption (PGSAUDIT-C) and use disorder (AUD; PGSAUD) were derived using genome-wide association Million Veterans Program summary statistics with PRS-CS. FindingsChildhood maltreatment and lifetime trauma (excluding childhood abuse) were positively associated with alcohol consumption (AUDIT-C) ({beta}childhood-maltreatment=0.17, SE=0.02; {beta}lifetime-trauma=0.28, SE=0.02) and alcohol problems (AUDIT-P) ({beta}childhood-maltreatment=0.25, SE=0.02; {beta}lifetime-trauma=0.27, SE=0.02). None of the PGSs were associated with AUDIT-C, but both the PGSs for re-experiencing ({beta}=0.1, SE=0.03) and avoidance ({beta}=0.08, SE=0.03) were positively associated with AUDIT-P. Experiencing lifetime trauma and being at elevated genetic risk for AUD (interaction-{beta}Trauma_x_PGSAUD=0.17, SE=0.05) and hyperarousal (interaction-{beta}TraumaxPGSHYPER=0.11, SE=0.06) were associated with higher AUDIT-P scores; while more lifetime trauma and higher genetic risk for AUD were associated with higher AUDIT-C scores (interaction-{beta}Trauma_x_PGSAUD=0.12, SE=0.05). ConclusionsIndividuals with elevated genetic risk for AUD are more likely to consume alcohol and to develop worse alcohol problems in the context of lifetime trauma. Interventions focused on also minimizing the effects of trauma-exposure would be particularly beneficial among individuals at risk for AUD.

Neurodevelopmental disorder-risk CNVs (NDD CNVs) are associated with complex neuropsychiatric phenotypes. These CNVs also confer risk for a host of medical outcomes in adults yet the long-term health consequences in the context of comorbid psychiatric illness have not been well documented. Twenty-four psychiatric inpatients with treatment-resistant psychosis were identified as carriers of NDD CNVs as part of a larger Pennsylvania State Hospital genomics study. Comprehensive life course phenotyping was performed through review of medical records, specialized neurobehavioral evaluation, and synthesis of data using the Human Phenotype Ontology. Phenotypes were examined across the cohort and within sets of individuals with CNVs in common. Retrospective phenotyping indicated comorbid medical manifestations across multiple organ systems. Cardiovascular disorders were present in 96% of cases and motor disorders in 92%. All cases had multiple organ system involvement, and most organ systems (12/17 systems) were affected in 50% or more of cases culminating in a high degree of individual-level comorbidity. Potentially novel health outcomes are described for individual CNV loci. Our descriptive case series supports a complex and multidimensional course of illness. Thorough reporting on the long-term implications of these variants is the first step toward advancing clinical care for these complex psychiatric patients carrying NDD CNVs.

BackgroundElevated rates of alcohol, tobacco, and cannabis use are observed in both patients with psychotic disorders and individuals at clinical high risk for psychosis (CHR-P), and strong genetic associations exist between substance use disorders and schizophrenia. While individuals with 22q11.2 deletion syndrome (22qDel) are at increased genetic risk for psychosis, initial evidence suggests that they have strikingly low rates of substance use. In the current study, we aimed to directly compare substance use patterns and their neurobehavioral correlates in genetic and clinical high-risk cohorts. MethodsData on substance use frequency and severity, clinical symptoms and neurobehavioral measures were collected at baseline and at 12-month follow-up visits in two prospective longitudinal cohorts: participants included 89 22qDel carriers and 65 age and sex-matched typically developing (TD) controls (40.67% male, Mage=19.26 {+/-} 7.84 years) and 1288 CHR-P youth and 371 matched TD controls from the North American Prodrome Longitudinal Study-2 and 3 (55.74% male; Mage=18.71 {+/-} 4.27 years). Data were analyzed both cross-sectionally and longitudinally using linear mixed models. ResultsControlling for age, sex, and site, CHR-P individuals had significantly elevated rates of tobacco, alcohol, and cannabis use relative to TD controls, whereas 22qDel had significantly lower rates. Increased substance use frequency and severity in CHR-P individuals was associated with increased positive psychosis symptom severity, dysphoric mood, social functioning, and IQ, while higher social anhedonia was associated with lower substance use frequency and severity, across all domains at baseline. These patterns persisted when we investigated these relationships longitudinally over one-year. CHR-P youth exhibited significantly increased positive psychosis symptoms, dysphoric mood, social anhedonia, and IQ compared to 22qDel carriers, and significantly higher social functioning and lower rates of autism spectrum disorder (ASD) compared to 22qDel carriers, both at baseline and at one year follow-up. ConclusionsIndividuals at genetic and clinical high risk for psychosis have strikingly different patterns of substance use. Factors such as increased neurodevelopmental symptoms (lower IQ, higher rates of ASD) and poorer social functioning in 22qDel may help explain this distinction from substance use patterns observed in CHR-P individuals.

ObjectivePersons with substance use disorders (SUD) often suffer from additional comorbidities. Researchers have explored this overlap via phenome wide association studies (PheWAS). However, PheWAS are largely cross-sectional, limiting our understanding of whether diagnoses predate development of an SUD. We characterize whether polygenic scores (PGS) are associated with time to comorbid diagnoses in electronic health records (EHR) after the first documented SUD diagnosis. MethodsUsing data from All of Us (N = 393,596), we explored: 1) whether social determinants of health (SDoH) are associated with lifetime risk of SUD (N cases = 42,568) and 2) within a subset those with a diagnosed SUD and available genetic data SUD (N = 21,357), whether PGS for alcohol use disorders, cannabis use disorders, depression, externalizing, post-traumatic stress disorder, and schizophrenia were associated with subsequent diagnoses via a phenome-wide survival analysis. ResultsMultiple SDoH were associated with lifetime SUD diagnosis, with annual household income having the largest overall associations (e.g., <$10K annually vs $100K-$150K annually: OR = 3.89, 95% CI = 3.66, 4.13). There were 101 phenome-wide significant PGS associations with subsequent diagnoses across various bodily systems. PGSs for alcohol use disorders, post-traumatic stress disorder, and schizophrenia were each associated with time to their respective diagnoses. ConclusionsSocial determinants, especially those related to income, have profound associations with lifetime SUD risk. Additionally, PGS for psychiatric conditions are associated with multiple post-SUD diagnoses within those with a SUD, suggesting PGS may capture information beyond lifetime risk, including timing and severity of comorbidities related to SUD.

Cannabis use disorder (CUD) affects [~]22M people globally and is characterised by difficulties in cutting down and quitting use, but the underlying neurobiology remains unclear. We examined resting-state functional connectivity (rsFC) between regions-of-interest (ROIs) of the addiction neurocircuitry and the rest of the brain in 65 individuals with moderate-to-severe CUD who reported attempts to cut down or quit, compared to 42 controls, and explored the association between rsFC and cannabis exposure and related problems, to elucidate potential drivers of rsFC alterations. The CUD group showed greater rsFC than controls between ROIs implicated in reward processing and habitual substance use (i.e., nucleus accumbens, putamen, pallidum) and occipito/parietal areas implicated in salience processing and disinhibition. Putamen-occipital rsFC correlated with levels of problematic cannabis use and depression symptoms. CUD appears to show neuroadaptations of the addiction neurocircuitry, previously demonstrated in other substance use disorders.