American Journal of Psychiatry

Alcohol use disorder (AUD) remains a major public health problem, with few effective medications and suboptimal adherence. L-type calcium channel blockers (LTCCBs) have genetic and preclinical support as potential treatments for AUD. We evaluated whether brain penetrant (BP)-LTCCBs are associated with reduced alcohol consumption by conducting two preregistered (https://osf.io/huawv) observational cohort studies using electronic health records (EHRs) from the US Department of Veterans Affairs (VA) and Kaiser Permanente Northern California (KPNC). New users of BP-LTCCBs (nifedipine or felodipine) were compared with new users of a non-BP-LTCCB (amlodipine) and with unexposed patients sampled from the same clinics, following a 180-day washout and requiring at least 60 days supply. Propensity score matching was conducted separately for BP-LTCCB versus unexposed, non-BP-LTCCB versus unexposed, and BP-versus non-BP-LTCCB. The primary outcome was change in drinks per week from the most recent pre-index screen to end of follow-up, estimated using difference-in-differences (DiD) models. Prespecified subgroup analyses were conducted by AUD diagnosis, baseline drinking level, and sex. Across both health systems, BP-LTCCB initiation was not associated with greater reductions in drinks per week than either comparator, with broadly consistent findings across all subgroups. In two large, preregistered EHR-based cohorts with rigorous confounding control, BP-LTCCBs were not associated with reduced drinking relative to comparators. Despite compelling genetic and preclinical evidence, these results do not support repurposing BP-LTCCBs for AUD, highlighting the need to prioritize alternative pharmacologic targets, potentially within etiologically informed subgroups.

IntroductionMaternal mental health conditions, comprising maternal suicide and drug overdose, are currently the leading cause of maternal mortality in the United States. However, the relationship between suicidality and drug use behavior in the perinatal period is not well understood. We examined the association between suicidality and drug use behavior among perinatal individuals. Given the racial disparities in both drug use and suicide rates in the U.S., we also examined any differences in suicidality and drug use behavior by race. MethodsParticipants were recruited from a High-Risk Obstetric & Gynecological Clinic in the Midwestern U.S that specializes in providing obstetric care to perinatal individuals who have histories or current use of opioids and other illicit drugs. Participants (N = 66) were a sub-sample of a larger cohort enrolled in an mHealth intervention to support recovery from opioid and stimulant use disorders. We performed chi-square tests and t-tests to examine any significant associations between lifetime suicidality and drug use behavior during the perinatal period. ResultsThe final analytic sample included participants who had responded to the suicidality survey questions (n=43). Nearly 40% (n=16) of our sample endorsed a lifetime history of suicidal thoughts and behaviors (SITB). Of those, 87% (n=15) reported a previous suicide attempt. SITB was significantly associated with cravings for opioids during the perinatal period (p = .01) as well as comorbidities with perinatal anxiety symptoms? ( p < .05), depression symptoms? (p < .05), and bipolar disorder (p < .05). A higher proportion of recent cannabis use was found among mothers with SITB, compared to those without SITB (p=0.04). Mothers with SITB also had a strong positive correlation between preconception and postnatal nicotine use compared to mothers without SITB (p < .01). Finally, while white mothers endorsed more lifetime overdoses (p= 0.01), Black mothers endorsed higher cravings for opioids during pregnancy (p = 0.03). ConclusionsA history of SITB is a distinct risk factor for both illicit and recreational drug use behavior in the perinatal period, and frequently co-occurs with other perinatal mental health conditions. Further research is needed to better understand the directionality of this relationship and the complex interplay between high risk drug use behavior and suicidality.

Alcohol use disorder (AUD) is a chronic, relapsing condition and a major public health problem. However, few medications are approved to treat AUD, and those available show limited efficacy. Drug repurposing is a cost-effective strategy to identify novel therapeutic uses for existing medications. Here, we describe a pipeline that integrates genetic and electronic health record (EHR) data to identify and evaluate drugs to be repurposed for treating AUD. Our approach comprises 1) alcohol-associated gene identification and biological network generation; 2) mapping drugs to target proteins; 3) filtering promising repurposing candidates; and 4) an exemplar pharmacoepidemiologic analysis of the effect of an identified drug (i.e., baclofen) on alcohol consumption. Linking loci to genes from a genome-wide association study (GWAS) of problematic alcohol use identified 94 genes, which we expanded to 327 alcohol-related genes through network-based analyses. Across these analyses, 52 genes were linked to 195 FDA-approved drugs, including four already approved or used off-label to treat AUD. After filtering for safety, relevance, and data availability, 26 candidate drugs, including baclofen, were selected for further evaluation. An evaluation of the real-world effectiveness of baclofen using national EHR data from the United States Department of Veterans Affairs provided evidence that baclofen-exposed patients reduced alcohol consumption more than propensity-score-matched unexposed patients. This approach, which aligns genomic findings with real-world clinical data, provides an efficient method for identifying promising drug repurposing candidates and prioritizing those that merit evaluation in randomized trials to ultimately advance pharmacotherapies for AUD.

ObjectiveDespite recommendations that young people at clinical high risk (CHR) for psychosis receive stepped treatment, few programs have published details of their clinical models or outcomes. This study describes the preliminary effectiveness of a risk calculator-informed stepped care model used at the Yale PRIME Clinic, a specialized outpatient clinic for young people at CHR. MethodsSeventy-one individuals (ages 12-25) at CHR enrolled in Yales PRIME Clinic during the first four years of the treatment program. Participants completed clinical assessments at six timepoints over two years of treatment within a care model informed by an empirically grounded psychosis risk calculator. Linear mixed-effect models were fit to examine changes in clinical symptoms over time, and sensitivity analyses evaluated differences in clinical trajectories between completers and non-completers. ResultsIndividuals engaged in treatment demonstrated significant and sustained improvements in positive, negative, general, disorganized, and depressive symptoms. Improvements in positive symptoms emerged by 6 months and continued to improve across most subsequent timepoints (6, 12, and 24 months). Pattern mixture analyses suggested that clinical trajectories did not significantly differ between completers and non-completers, though non-completers possessed more heterogeneous trajectories. ConclusionsA stepped care model informed by individualized risk calculator scores was feasible for delivery in a specialized outpatient setting, and was associated with broad symptom improvement for young people at CHR. Further controlled studies with blinded raters are needed to further confirm the efficacy of stepped care models and isolate the active components of treatment. HighlightsO_LIParticipants at clinical high risk for psychosis experienced significant reductions in attenuated psychotic symptoms and improvements in mood while enrolled in a risk-calculator-informed stepped care treatment model. C_LIO_LIParticipants who disengaged from treatment did not have significantly different clinical trajectories than those who remained in care. C_LIO_LIThe results suggest preliminary evidence for the feasibility of implementing a risk-calculator-informed stepped care model. C_LI

BackgroundAttention deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by attentional deficits, hyperactivity and impulsivity that often persists into adulthood. While dysfunction of dopaminergic neurotransmitter systems has been observed, underlying mechanisms remain incompletely understood. Current treatments with methylphenidate and amphetamines show limited long-term effectiveness and do not address broader clinical needs. The endocannabinoid system represents a promising therapeutic target. Cannabinoid type 1 (CB1) receptors are highly concentrated in the prefrontal cortex and striatum, brain regions central to ADHD pathophysiology. The "dual pathway model of ADHD" describes deficits in inhibition-related executive functions and reward-related functions, both mediated by fronto-striatal networks. Striatal CB1 receptor availability correlates negatively with impulsivity. Given the interaction between dopaminergic and endocannabinoid systems, CB1 receptors may play a key role in ADHD pathogenesis. MethodsThis controlled study will investigate CB1 receptor availability in ADHD using positron emission tomography (PET) with the CB1-selective radiotracer [18F]MK-9470. The primary outcome is the CB1 receptor distribution volume (VT) in the striatum. Secondary outcomes include CB1 receptor availability in prefrontal cortex and other ADHD-relevant brain regions, plasma concentrations of endocannabinoids (anandamide, 2-arachidonoylglycerol), and validated neuropsychological assessments of attention and impulsivity. We will compare three groups (n=34 each): medication-naive participants with ADHD, methylphenidate-treated participants with ADHD, and healthy controls. Statistical analysis will employ ANOVA with post-hoc comparisons and correlation analyses between neuroimaging and behavioral measures. DiscussionThis first investigation of the endocannabinoid system in ADHD will provide crucial insights into disease mechanisms and identify potential therapeutic targets. Results may inform development of novel cannabinoid-based treatments and improve evidence-based therapeutic strategies for ADHD management. Trial registration: German Clinical Trials Register (DRKS-ID: DRKS00037526, Registration date: 25 September 2025)

BackgroundBipolar disorder (BIP) frequently co-occurs with heightened substance use (SU) and substance use disorders (SUDs). Although the strong co-occurrence of these heritable traits points to shared genetic susceptibility, the extent to which there are differences in how SU and SUD overlap with BIP genetic architecture remains unclear. MethodsWe quantified the polygenic overlap between BIP and SUDs (alcohol, cannabis, opioid, and tobacco), and BIP and SU traits (drinks per week, lifetime cannabis use, prescription_opioid use, and smoking initiation) using GWAS summary statistics and trivariate MiXeR. We then isolated the general and unique genetic contributions of SUD and SU using GWAS-by-subtraction via GenomicSEM. Next, we tested associations between polygenic risk scores (PRSs) derived from these latent factors and diagnostic and behavioral outcomes in the Norwegian Mother, Father and Child Cohort Study. Finally, we applied GSA-MiXeR to explore pleiotropic pathway enrichment shared between the latent factors and BIP. ResultsWe found extensive polygenic overlap between traits, with SUDs being more genetically correlated with BIP than SU traits. The unique SUD factor correlated positively with psychiatric disorders, whereas unique SU correlated negatively. PRSs for BIP, shared SUD/SU, and unique SUD were significantly associated with BIP, SUD, and comorbid SUD-BIP; PRS for unique SU was only associated with self-reported lifetime SU. GSA-MiXeR revealed richer gene-set enrichment for SUD/BIP than SU/BIP implicating dopamine signaling and interneuron function. ConclusionBy dissecting the genetic liability to SUD and SU and investigating their relationship with BIP we find a genetic link driven by substance dependence but not substance use more broadly.

BackgroundTransdiagnostic genetic factor models organize shared liability across psychiatric disorders, but they may leave systematic pairwise genetic overlap unexplained. MethodsUsing publicly available PGC cross-disorder LD score regression genetic correlations and published five-factor genomic SEM parameters, we computed model-implied disorder correlations and derived edge-level residual genetic correlations (observed minus model-implied) for all disorder pairs. We summarized residual misfit by ranking the largest residual edges and by aggregating residual edges into disorder-level hub indices. As a parsimonious comparison, we constructed a p-factor-augmented baseline and repeated the residual mapping. Uncertainty was propagated via Monte Carlo sampling using reported standard errors. ResultsResidual structure was concentrated in a subset of disorders rather than being uniformly distributed. The largest positive residual edge was OCD-anxiety ([~]0.35), followed by prominent residual links including OCD-Tourette syndrome, ADHD-cannabis use disorder, and ASD-ADHD. At the node level, OCD emerged as the most consistent residual hub, with ADHD typically second. Under the p-factor baseline, the overall residual pattern persisted. Hub rankings did not map one-to-one onto disorder uniqueness, indicating complementary information captured by node-level and edge-level residuals. ConclusionsHigher-order genetic factors explain broad shared liability but leave meaningful, structured residual links between specific disorder pairs. OCD and ADHD are robust residual hubs, highlighting candidate cross-disorder connections for targeted phenotypic harmonization, cross-phenotype GWAS, and theory-guided model refinements.

Tobacco use disorder (TUD) remains a leading cause of preventable mortality, and existing pharmacotherapies yield 12-month abstinence rates below 30%. As cannabis legalization expands, approximately 18-22% of people who use tobacco report concurrent cannabis use, yet the impact of co-use on cessation outcomes and the therapeutic potential of endocannabinoid system (ECS) modulation remain unclear. We conducted a translational systematic review and meta-analysis following PRISMA 2020 guidelines, searching Ovid MEDLINE, Embase, APA PsycInfo, and Web of Science through January 2026 (PROSPERO: CRD420250652724). Three study categories were eligible: observational studies of cannabis co-use and cessation outcomes; preclinical studies of cannabinoid modulators on nicotine-related behaviors; and human experimental studies of ECS-targeted interventions. Of 4,869 records screened, 52 studies met inclusion criteria. Meta-analysis of 18 observational studies (N=229,630) revealed that cannabis use was associated with 35% lower odds of achieving tobacco smoking cessation (OR=0.65; 95% CI: 0.55-0.78; p<0.0001; I{superscript 2}=88.1%). Preclinical evidence (15 studies) demonstrated that CB1 receptor antagonists robustly reduced nicotine self-administration and reinstatement, while cannabidiol (CBD) attenuated both nicotine intake and withdrawal without affecting food reinforcement. Clinical translation of CB1 receptor inverse agonists failed due to psychiatric adverse effects, but CBD showed promise by reducing cigarette consumption by 40%, reversing attentional bias to smoking cues, and alleviating withdrawal severity. These findings distinguish naturalistic cannabis exposure from potentially beneficial targeted ECS modulation, and support CBD as a promising candidate for adequately powered tobacco cessation trials.

BackgroundGabapentin and pregabalin have potential utility for treating alcohol use disorder (AUD), but their comparative effectiveness in reducing alcohol consumption in real-world settings is unknown. We compared changes in alcohol consumption associated with gabapentin or pregabalin treatment with those of matched unexposed comparators. MethodsWe identified patients who were prescribed gabapentin or pregabalin for [&ge;]60 days for any indication between 1 January 2009 and 30 June 2022 using electronic health records from the Veterans Aging Cohort Study (VACS-National). Alcohol consumption was measured using routinely-collected Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) questionnaires. We used propensity score matching to balance baseline characteristics between groups. Three comparisons were conducted: gabapentin vs. unexposed, pregabalin vs. unexposed, and pregabalin vs. gabapentin. Changes in AUDIT-C scores were estimated using multivariable difference-in-difference linear regression models. Analyses were stratified by baseline AUD diagnosis and AUDIT-C categories (lower-risk, at-risk, hazardous/binge). ResultsWe identified 592,957 gabapentin initiators, 14,923 pregabalin initiators, and 2,959,006 eligible unexposed comparators who were eligible for matching. Compared to unexposed individuals, patients who received gabapentin (DiD: 0.09, 95% CI 0.06, 0.11, p<0.0001) or pregabalin (DiD: 0.14, 95% CI 0.02, 0.26, p=0.0279) reported greater reductions in AUDIT-C scores. When compared head-to-head, pregabalin initiators reported greater reductions in AUDIT-C scores than gabapentin initiators with the largest difference observed among those with AUD (DiD: 0.86, 95% CI 1.22, 0.50, p<0.0001) and those who report baseline hazardous/binge drinking (DiD: 1.74, 95% CI 2.21, 1.27, p<0.0001). DiscussionIn this large, nationwide cohort, treatment with gabapentin and pregabalin were associated with reductions in reported alcohol consumption, compared to matched unexposed comparators. Initiation of pregabalin was associated with greater reductions than with gabapentin, particularly among those with AUD and those with highest severity of alcohol use. Known safety concerns and risk of misuse should be considered when prescribing these medications. Randomized clinical trials directly comparing these medications are necessary to validate these findings.

Background and AimsAlcohol use disorder (AUD) remains a major public health concern, with persistent disparities in access to evidence-based treatment. This study aimed to examine associations between perceived discrimination in healthcare settings (PDHS), patient-clinician communication (PCC), and receipt of treatment for AUD, and compared these with sociodemographic and insurance-related factors. DesignCross-sectional analysis using structural equation modeling (SEM), logistic and multinomial logistic regression, and machine learning approaches including SHapley Additive exPlanations (SHAP). SettingUnited States, using data from the National Institutes of Health All of Us Research Program. ParticipantsA total of 5,287 adults with AUD (mean age 61 years; 57% men), including 71.6% non-Hispanic White, 12.2% Black, and 8.6% Hispanic participants. Insurance coverage included 52% government (Medicaid/Medicare), 37% private, and 21% military with 19% reporting more than one type. MeasurementsPrimary outcomes were receipt of Food and Drug Administration-approved pharmacotherapy and/or psychotherapy for AUD, examined as binary and multinomial outcomes. The primary exposure was PDHS, measured using a 7-item scale (range 7-35), with higher scores indicating more frequent discrimination. PCC, assessed using a 2-item scale (range 2-8) with higher scores indicating poorer communication, was examined as a potential mediator. Models were adjusted for age group, sex at birth, race/ethnicity, insurance type (government, private, military), household income, and Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) scores (range 0-12). FindingsPDHS was associated with poorer PCC ({beta} = 0.209, p < 0.001), although communication was not independently associated with treatment receipt. The indirect pathway from discrimination to treatment via communication was not supported. Military insurance was the strongest predictor of treatment receipt, with 6-7 times higher odds compared with other insurance types. Higher AUDIT-C scores and greater PDHS were also associated with increased likelihood of treatment. In analyses restricted to civilian participants, PDHS showed a stronger association with treatment receipt, while PCC demonstrated more modest effects. Machine learning models identified PDHS, AUDIT-C, and PCC as strong contributors, with the impact of poor communication most pronounced among individuals with lower income. ConclusionsAccess to treatment for alcohol use disorder is most strongly associated with insurance coverage, particularly military insurance. PDHS and PCC also contribute to treatment engagement, with differential effects across socioeconomic groups. These findings highlight the importance of addressing structural and interpersonal barriers to improve equitable access to evidence-based AUD treatment.

BackgroundForensic psychiatric services are expanding in many countries, and discharging patients from secure hospitals relies on accurate estimates of risk of adverse outcomes. Novel evidence-based tools for estimating one key risk, violent reoffending, have been developed in recent years. We aimed to externally validate one new tool, FoVOx, in forensic psychiatric patients sentenced to treatment, and to develop an updated model (FoVOx2), incorporating additional clinical predictors. MethodsUsing Swedish national registers, we conducted a temporal external validation of FoVOx by examining 767 patients discharged between 2014 and 2023. For the FoVOx2 cohort, 906 patients discharged between 2008 and 2023 were followed up, and additional predictors tested. The outcome was violent reconviction within 12 or 24 months. Model performance was evaluated using Harrells C-index, time-dependent AUCs, calibration, and classification metrics at predefined thresholds. ResultsIn temporal validation, FoVOx showed moderate discrimination (AUCs 0.69 and 0.71; C-index = 0.69) and acceptable overall accuracy (Brier <0.11). Calibration was generally good, with mild overestimation at the highest predicted risks (>20%) at 12 months and slight underprediction at 24 months. The updated FoVOx2 model newly incorporated clozapine treatment and additional diagnostic categories. It was associated with improved performance (AUCs 0.77; optimism-corrected C-index = 0.72; Brier 0.06 and 0.09) and achieved good calibration (intercept {approx} 0; slopes 1.03 and 1.05). ConclusionsUpdating risk assessment tools with additional clinical factors can lead to incremental improvement in model performance. Implementing tools should consider clinical utility and impact as next steps.

Background and AimsThe UK legalised medical cannabis in 2018, yet little is known about people accessing cannabis legally via prescription or those using cannabis for medical purposes without a prescription. This study aimed to estimate: 1) the percentage of people who use cannabis medically with and without a prescription; 2) the sources used to obtain cannabis; 3) the products used; and 4) the associations between monthly or more frequent (MMF) product use and medical cannabis use status. DesignNational repeat cross-sectional surveys conducted in September-November 2023 and 2024. SettingUK. ParticipantsPeople aged 16-65 who used cannabis in the past 12 months (n=4,414). MeasurementsInferential statistics compared outcomes by medical cannabis use status. Multivariable regression analyses estimated associations between MMF product use and medical cannabis use status. FindingsOverall, 13.0% of people reported receiving a medical cannabis prescription, 36.4% reported medical use without a prescription, and 50.6% reported no medical use. Cannabis was sourced through diverse routes; only 10.7% of people with prescriptions obtained all their cannabis from a legal medical prescription. People with a medical prescription had a higher probability of reporting MMF use of oils or liquid drops (aRR=3.51; 95% CI: 2.73-4.52), oil or liquid capsules (aRR=2.63; 1.99-3.47), vape oils (aRR=2.40; 2.03-2.84), edibles (aRR=2.41; 2.01-2.90), cannabis drinks (aRR=3.39; 2.69-4.26), solid concentrates (aRR=3.10; 2.29-4.21), hash or kief (aRR=1.82; 1.44-2.30), and topicals (aRR=3.42; 2.58-4.51) than people who did not report medical use, after adjusting for covariates. People who ever asked for a medical prescription and people with a medical prescription in the past year had a higher probability of screening positive for high-risk use. ConclusionOver one in ten people who use cannabis in the UK report a medical cannabis prescription, yet a third reported medical use without a prescription. With only a minority obtaining all their cannabis legally, many rely on illegal sources, suggesting prescriptions may not meet the needs of those reporting use for medical purposes. People with prescriptions show a higher probability of frequent use of processed, higher-potency products, and meeting a threshold for high-risk use. Healthcare encounters during medical cannabis prescribing should discuss risks related to potency, product type, and adverse effects such as cannabis use disorder.

Background At present, there are no approved pharmacological treatments for people at clinical high risk for psychosis (CHR-P). We sought to assess the acceptability of cannabidiol (CBD): a promising candidate treatment for this population. Methods CHR-P individuals completed a survey which assessed their views on the acceptability of CBD, its expected effectiveness and side effects, and on formulation preferences. Results The sample comprised 55 CHR-P individuals (24.3 years and 69% female). Most (91%) were familiar with CBD, and had previously used cannabis (64%), and around half (42%) had tried over-the-counter CBD. 75% were willing to take CBD as an intervention for mental health problems. Most participants anticipated fewer side effects with CBD than with existing medications, and preferred tablet or capsule formulations over liquids. Discussion CBD is perceived as a highly acceptable treatment among CHR-P individuals.

Psychotic-like experiences (PLEs) are common in youth and predict later mental health problems. Bullying victimization is a robust environmental risk factor for psychopathology including PLEs, but whether its association with PLEs reflects shared genetic liability, individual-specific putatively causal effects, or reciprocal processes is unclear. We analyzed seven waves of longitudinal data from the Adolescent Brain Cognitive Development (ABCD) Study, examining associations across the sample in addition to leveraging within-family comparisons among twin and sibling pairs who were concordant or discordant for exposure to bullying victimization. Using linear mixed-effects and cross-lagged models, we found that youth reporting bullying victimization were more likely to endorse significantly distressing PLEs than non-victimized youth (caregiver-reported odds ratio=2.35; youth-reported odds ratio=4.10). Longitudinal analyses revealed bidirectional associations: prior bullying predicted subsequent increases in distressing PLEs, and prior PLEs predicted elevated risk of later bullying victimization. Genetically-informed within-family analyses indicated that both shared genetic influences and individual-specific factors contributed to these associations; critically, bullied youth exhibited higher odds of distressing PLEs than their non-exposed siblings (youth-reported odds ratio=6.67; 95%CI:4.96-8.96), consistent with an individual-specific effect of victimization. Together, these findings suggest that bullying and PLEs are linked through reciprocal developmental processes that are not fully explained by familial confounding. More broadly, our results highlight bullying prevention as a plausible leverage point for reducing early psychosis-spectrum risk and illustrate the value of integrating within-family designs to help disentangle genetic and environmental contributions to mental health outcomes in adolescence. Significance StatementUnderstanding how early adversity shapes mental health trajectories is important for science and public policy. Using nationally representative, longitudinal twin and sibling data, analyses show that bullying victimization and psychotic-like experiences in youth are linked through reciprocal processes that cannot be fully explained by shared genetics or family background. Bullied youth were more likely to endorse distressing psychotic-like experiences than their own non-bullied siblings, providing rare evidence for individual-specific effects of bullying victimization. Early psychotic-like experiences also increased subsequent risk of being bullied, suggesting a potential feedback loop that may compound risk. These findings demonstrate how social environments and mental health dynamically interact and point to bullying prevention as a population-level strategy with potential to reduce early psychopathology risk.

BackgroundEarly low-level alcohol use predicts subsequent alcohol use and problems. Impulsivity and poor inhibitory control also predict later problematic alcohol use. However, few studies prospectively examine early sipping in combination with modeling impulsivity and inhibitory control change over time as predictors of adolescent alcohol use. MethodsData Release 6.0 from the Adolescent Brain Cognitive Development (ABCD) Study was used (n=11,866; 48% Female). A series of linear mixed-effect models examined trajectories of non-religious sipping at baseline (ages 9-10) and self-reported impulsivity (UPPS-P) and task-based inhibitory control (Flanker task) over time as predictors of past year drinks and problematic alcohol use by ages 15-16. Predictors were run as separate models and a full model with all predictors together. Models were nested within the participant and study site. Interactions with age (to measure change over time from Baseline to Year 6) were included. Corrections for multiple comparisons were employed. ResultsIn individual models, four impulsivity interactions were significant: (1) negative urgency*age ({beta}=.04, FDR-p<.001), (2) positive urgency*age ({beta}=.04, FDR-p<.001), (3) lack of planning*age ({beta}=.04, FDR-p<.001), and (4) sensation seeking*age ({beta}=.04, FDR-p<.001), suggesting that as age increases, the relationship between impulsivity and alcohol use strengthens. Sipping*age ({beta}=.02, FDR-p<.001) interactions also predicted standard drinks. Regarding problematic use, there was a significant interaction in the full model: negative urgency*age ({beta}=-.07, p=.05), indicating that this relationship is more pronounced at earlier ages. ConclusionsTrait impulsivity and sipping in late childhood relate to future alcohol use, and the relationship strengthens with age. Our results found a negative interaction between negative urgency and age on problematic use, potentially indicating negative urgency as a phenotype of vulnerability to experiencing alcohol related problems at younger ages. Findings indicate the importance of understanding facets of impulsivity in the context of adolescent alcohol use for prevention and intervention efforts.

Substance use disorder (SUD) recovery typically requires transformative change and prioritizing long-term healthy goals. Unfortunately, successful recovery is threatened by relapse rates that often exceed 50% in the first year. We previously reported on an experiential virtual reality (VR) SUD recovery intervention using personalized future self-avatars that produced emotional engagement and positive behavioral change, ie, stronger connection with the future self and future rewards and reduced craving. Here, we used fMRI to identify brain engagement to a future self experience with divergent futures. Twenty adults (14 male, 33 years old) in early SUD recovery (<1 year) interacted with age-progressed versions of themselves in two different VR future realities: an SUD Future Self and a Recovery Future Self. Vivid lifelike visual and audio animation was augmented with a personalized narrative concerning future drug use and recovery. MRI immediately followed. Participants viewed videos of their future selves in the virtual environment and were directed to contemplate what they were seeing. Viewing and contemplating the future selves elicited activation in midline default mode regions (posterior cingulate and ventromedial prefrontal cortices), visual regions including the occipital and fusiform face areas, and left middle frontal gyrus. The Recovery Future Self produced significant left occipital face area activation compared with the SUD Future Self. Midline default mode activation correlated with VR-induced increases in delayed reward preference, and also with greater trait perseverance. Using digital selves as therapeutic agents reveals an entirely novel set of possible interventions and opens exciting new frontiers in behavior change methodology. Future studies targeting decision-making and future behavior could be informed by evaluating increased midline default mode engagement, with uniquely self-focused mechanisms signaled by executive network and face area coactivation. New hope for treatment-resistant mental health conditions is offered by the nearly limitless range of therapeutic experiences enabled by immersive digital therapeutics. Plain Language SummaryHigh relapse rates in early recovery remains a serious challenge. To promote better outcomes, our team recently developed a virtual reality experience where people interacted with future versions of themselves. We used magnetic resonance imaging (MRI) to understand how the brain activated to this experience, and what brain responses were linked to positive outcomes. We worked with 20 adults in early recovery. Each person used virtual reality to interact with two different future selves: one who had returned to substance use, and one who had stayed in recovery. These digital future selves looked and sounded like the participants and were paired with a personalized story about future drug use and recovery. Right after the virtual reality session, participants brains were scanned while they watched videos of these future selves and were asked to think about what they were seeing. When people viewed and reflected on their future selves, brain areas involved in self-reflection and imagining the future became more active, along with regions that process faces. The future selves triggered brain activation in "self-focused" brain networks and in face-processing regions. Activity in key "self-focused" brain regions was linked to choosing larger, delayed rewards over smaller, immediate ones, and to lower impulsivity. These findings suggest that lifelike digital versions of peoples future selves engage brain systems that support thinking ahead, persistence, and valuing long-term outcomes. This creates a promising new avenue for immersive digital therapeutic experiences to encourage lasting behavior change in early recovery from substance use disorder.

In 2024, approximately 30% of U.S. adolescents reported having consumed alcohol at least once in their lifetime, with about 25% of these individuals engaging in binge drinking. Adolescent alcohol use is associated with neurodevelopmental impairments, elevated risk of later alcohol use, and mental health disorders. These findings underscore the importance of identifying the variables driving adolescent alcohol use and leveraging them for early identification and targeted intervention. Previous studies have typically developed machine-learning classification models that use neuroimaging data in combination with limited clinical measurements. Neuroimaging data are expensive and difficult to obtain at scale, whereas clinical measures are more practical for large-scale screening due to their low cost and widespread accessibility. However, clinical-only approaches for alcohol drinking classification remain largely underexplored. Furthermore, prior studies have often focused on adults, limiting generalizability to the broader adolescent population. Additionally, confounding factors such as age and substance use, which are strongly correlated with alcohol consumption, have often been inadequately addressed, potentially inflating classification performance. Finally, class imbalance remains a persistent challenge, with prior attempts yielding only limited improvements. To address these limitations, we propose FocalTab, a framework that integrates TabPFN with focal loss for robust generalization and effective mitigation of class imbalance. The approach also incorporates an initial preprocessing step to remove confounding factors to account for age and substance-use. We compare FocalTab against state-of-the-art methods across different variable selections and dataset settings. FocalTab achieves the highest accuracy (84.3%) and specificity (80.0%) in the most stringent setting, in which both age and substance use variables were excluded, whereas competing models drop to near-chance specificity (12-24%). We further applied SHapley Additive exPlanations (SHAP) analysis to identify key clinical predictors of drinker classification, supporting enhanced screening and early intervention.

BackgroundCannabis use is highly prevalent among people who use unregulated drugs. While daily cannabis use has been hypothesized to provide protective effects through substitution or tolerance mechanisms, the relationship between cannabis use frequency and overdose risk remains poorly understood, particularly for infrequent users. MethodsWe conducted a secondary analysis of cross-sectional interview data from people who use unregulated drugs in Vancouver, British Columbia, collected during the fentanyl crisis (November 2019-July 2021; n=657). Binary logistic regression examined associations between self-reported cannabis use frequency (five categories: less than monthly, 1-3 times per month, weekly, more than weekly and daily) and non-fatal overdose in the preceding six months. Daily use served as the reference category. Models adjusted for age, gender, ethnicity, homelessness, mental health, HIV status, incarceration and daily use of alcohol, opioids, fentanyl, cocaine and stimulants. ResultsAmong 657 participants, 95 (14.5%) reported non-fatal overdose in the past six months. In adjusted models with daily cannabis use as the reference, infrequent cannabis use was associated with significantly increased odds of overdose: use 1-3 times per month (aOR=3.17, 95% CI: 1.50-6.69, p=.002) and more than weekly use (aOR=3.13, 95% CI: 1.70-5.76, p<.001) showed approximately three-fold increased odds compared to daily use. Less frequent use showed non-significant trends in the same direction (less than monthly: aOR=1.73, 95% CI: 0.89-3.37, p=.109; weekly: aOR=1.44, 95% CI: 0.59-3.51, p=.421). Sensitivity analysis restricted to participants with daily stimulant or fentanyl use (n=148) revealed even stronger associations. ConclusionsInfrequent cannabis use was associated with substantially increased overdose risk compared to daily use. This frequency-dependent relationship, with infrequent users at highest risk, likely reflects tolerance differences: infrequent users lack tolerance to synergistic cannabis-opioid effects. These findings were completely obscured in preliminary analyses that dichotomized cannabis use as daily versus less-than-daily, demonstrating how analytical choices can mask critical public health insights. Current harm reduction approaches, including cannabis distribution programs, should incorporate frequency-dependent risk communication and develop strategies to protect infrequent users who may be at heightened overdose risk.

Despite decades of clinical implementation of medications for opioid use disorder (OUD), overdose mortality rates remain high, underscoring a critical gap in treatments that target brain mechanisms driving addiction. Mindfulness-Oriented Recovery Enhancement (MORE) has demonstrated efficacy in reducing opioid use and craving, hypothetically by restructuring the salience of drug and natural rewards. Yet, to date, MOREs neurobiological mechanisms remain unclear. In this first functional magnetic resonance imaging (fMRI) randomized controlled trial (RCT) of MORE for OUD (NCT04112186), we tested whether compared with an active psychoeducational supportive therapy (PST) control group, MORE rebalanced neural responses to drug and natural reward cues in inpatients with OUD receiving standard of care including medications. Compared with PST, eight weeks of MORE significantly reduced drug-biased activity in the dorsolateral prefrontal cortex (dlPFC) and posterior regions of the default mode network including the precuneus during downregulation of responses to drug cues relative to upregulation of responses to natural reward cues (even when controlling for passive cue viewing). The shift from drug to natural reward responses in the lateral and ventromedial PFC was associated with lower cue-induced craving exclusively in the MORE group. MORE also reduced medial PFC synchronization to naturalistic drug-related movie scenes and significantly extended abstinence duration at follow-up ([~]4 months post-treatment) relative to PST. Together, this neuroimaging RCT demonstrates that MORE normalizes function in PFC nodes of the reward, salience, and control systems, positioning MORE as a biologically-grounded adjunct to pharmacotherapy for OUD.

BackgroundParental genetics matters for childrens behavioural difficulties, but the extent to which this is due to direct genetic transmission versus environmentally mediated indirect genetic effects remains unclear. MethodsWe studied eight European birth cohorts with over 33,000 family-based trio samples. We analysed polygenic scores (PGSs) for 13 mental health and neurodevelopmental conditions and their composite indices (PC1 and mean) representing general neuropsychiatric liabilities, as well as educational attainment (EA) and alcohol and cigarette use, from children (PGSc), mothers (PGSm), and fathers. Child internalising, externalising, and total difficulties reported by mothers and/or fathers were examined at preschool and school ages. We then conducted multivariate meta-analyses to combine cohort-level results. FindingsWe observed several direct genetic effects on externalising difficulties, while indirect genetic influences were mainly identified for internalising difficulties. Specifically, child PGSs for attention-deficit/hyperactivity disorder (ADHD) and EA predicted higher and lower levels, respectively, of child externalising and total difficulties (all pFDR<0{middle dot}001; for school-aged externalising difficulties, PGSc-ADHD: {beta}=0{middle dot}121 [95% CI 0{middle dot}091 to 0{middle dot}151], pFDR<0{middle dot}0001; PGSc-EA: {beta}=-0{middle dot}095 [95% CI -0{middle dot}127 to -0{middle dot}063], pFDR<0{middle dot}0001), whereas maternal PGSs for major depressive disorder (MDD) and general neuropsychiatric liabilities were associated with internalising and total difficulties across parental raters and child ages (all pFDR<0{middle dot}05; for school-aged internalising difficulties, PGSm-MDD: {beta}=0{middle dot}049 [95% CI 0{middle dot}017 to 0{middle dot}081], pFDR=0{middle dot}016; PGSm-PC1: {beta}=0{middle dot}056 [95% CI 0{middle dot}022 to 0{middle dot}091], pFDR=0{middle dot}011). No statistically significant effects from paternal PGSs were identified. InterpretationIn this multi-cohort study, findings across multiple traits, raters, and ages supported several direct genetic effects of ADHD and EA on child externalising difficulties and indirect genetic effects on internalising difficulties, especially maternal depression and general neuropsychiatric liabilities. These suggest that child internalising difficulties are not solely driven by direct genetic transmission. More comprehensive research is needed to better understand the mechanisms involved, and ultimately how to ameliorate child behavioural difficulties. FundingEU, ERC, RCN, RCF, UKRI, SERI, DFG Research in contextO_ST_ABSEvidence before this studyC_ST_ABSIndirect genetic effects (IGEs) refer to the influence of parental genotypes on offspring outcomes beyond direct genetic effects (DGEs), for example via environmental pathways. While IGEs on offspring cognitive traits are well-established for educational attainment, evidence for IGEs of parental liabilities to mental health and neurodevelopmental conditions remains limited. To assess the current state of evidence, we conducted a systematic search of published studies applying trio-based polygenic score (PGS) designs to child and adolescent mental health outcomes. We identified 141 primary studies in MEDLINE, Embase, PsycInfo, and Web of Science, by 6 March 2025, after removing duplicates; following screening, 12 studies met inclusion criteria (see supplement for a full description including results). Ten out of the 12 studies focused on externalising outcomes, with little or inconsistent support for IGEs. When observed, IGEs were mainly driven by maternal liabilities to autism, educational attainment, and cognitive performance on child outcomes. The current evidence was too limited and heterogeneous to synthesize findings quantitatively, therefore a qualitative synthesis was conducted. Many studies were statistically underpowered, and the observed IGEs were in all cases sample-specific. There were no published multi-cohort studies. Added value of this studyWe integrated information across over 33,000 mother-father-child trios from eight European cohorts, investigating 18 PGSs from parents and children, using maternal and paternal ratings of offsprings internalising, externalising, and total difficulties as outcomes at both preschool and school age. We mainly observed DGEs on externalising difficulties, consistent with previous studies. Some evidence of IGEs was found for internalising and total difficulties. IGEs were often found to be maternally driven, with the most robust evidence across ages and raters emerging for maternal depression and general neuropsychiatric liabilities. Implications of all the available evidenceThe current evidence suggests that childrens behavioural difficulties, especially internalising difficulties, may be partly driven by the environment shaped by maternal neuropsychiatric liabilities. Ours and previous findings highlight a pressing need for more comprehensive studies across different cohorts, raters, outcomes, and time points to understand the true extent of IGEs in the intergenerational transmission of mental health.