American Journal of Psychiatry

Importance: Preventing substance use disorder (SUD) is a top public health priority, but clinical practice currently lacks validated prognostic tools to identify risk before the onset of heavy use/problems. Objective: To determine whether models can predict SUD using genetic, behavioral, and environmental factors and to evaluate performance across substance types (alcohol, cannabis, tobacco), sex, and genetic similarity groups. Design: This prognostic study developed and validated a multi-domain risk model using data from four longitudinal cohorts (The National Longitudinal Study of Adolescent to Adult Health, Avon Longitudinal Study of Parents and Children, The Collaborative Study on the Genetics of Alcoholism, and FinnTwin12) with follow-up from early adolescence into young adulthood. Setting: Population-based and family-based samples from the United States, United Kingdom, and Finland. Participants: The analysis included participants with available genomic and behavioral data. The cohorts represented a spectrum of risk, ranging from nationally representative community samples to high-risk populations. Exposure(s) (for observational studies): Predictors included polygenic scores for substance use-related phenotypes and 10 established early-life behavioral and environmental risk factors. Main Outcome(s) and Measure(s): The outcomes were a diagnosis of moderate-to-severe SUD based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and positive and negative predictive value. Results: A total of 16,362 participants were included in the study (54.7% female; mean [SD] age 26.73 [3.36]). Genetic similarity group composition was 70.4% European, 16.8% African, 9.8% admixed American, 2.2% East Asian, and 0.7% South Asian. SUD prevalence was 22.0%. The integrated model achieved an AUC of 0.78 for predicting any SUD, with a sensitivity of 69% and a positive predictive value of 45%. Performance was comparable for specific substances (AUC range 0.74-0.82) and across genetic similarity groups (AUC range 0.61-0.82). The model demonstrated higher AUC in females compared with males. Conclusions and Relevance: Findings highlight the potential utility of an SUD prediction model to inform clinicians and patients about risk for developing a SUD.

Genome-wide association studies (GWAS) have identified numerous loci associated with substance use disorders (SUDs). To connect common genetic variation to cell type- and region-specific gene expression and chromatin accessibility, we examined the enrichment of genetic liability for several SUDs (alcohol, cannabis, tobacco, and opioid use disorders) and substance consumption phenotypes (drinks per week, cannabis ever-use, and cigarettes per day) in available single-nucleus RNAseq data spanning 10 brain regions and snATACseq data spanning 42 brain regions. Significant cell-type enrichment after multiple testing corrections was observed only for drinks per week and tobacco use disorder in the snRNAseq data and for cannabis use disorder and problematic alcohol use in snATACseq data. Across both transcriptomic and chromatin accessibility annotations, enrichment patterns were concentrated in excitatory neuronal populations, particularly upper layer intratelencephalic neurons, amygdala excitatory neurons, and regionally resolved striatal medium spiny neuron subtypes. Drinks per week, problematic alcohol use, and cannabis use disorder showed enrichment values that were significantly correlated within cell-type across snRNAseq and snATACseq, suggesting convergent biological signals across independent single-nucleus modalities. These findings implicate chromatin-mediated expression differences in specific excitatory neuronal populations as potential mediators of SUD genetic liability and highlight the value of integrating transcriptomic and chromatin accessibility data for characterising the neurobiology of addiction.

Importance. Anorexia nervosa (AN) is a severe metabo-psychiatric disorder with heterogeneous outcomes and elevated mortality. Characterizing severity trajectories may improve early risk stratification and targeted intervention. Objective. To identify AN severity trajectories using a register-based severity index (AN-RSI) and examine their associations with polygenic scores (PGS), preceding (prior to AN diagnosis) as well as subsequent (5 years post AN diagnosis) psychiatric and somatic disorders. Design. Population-based cohort study. Setting. Nationwide study in Denmark. Participants. Individuals born between 1969 and 2013 with diagnosed AN (N = 9,534 individuals). Genetic data were available in a subsample comprising 5,126 individuals. Exposures. Forty-one PGS indexing traits relevant to AN, and psychiatric and somatic disorders prior to AN diagnosis. Main Outcomes and Measures. The main outcomes of interest were the AN-RSI trajectories and psychiatric and somatic disorders 5 years post AN diagnosis. Results. Three trajectories were identified: "low and stable" (32.6%), "medium and stable" (53.5%), and "high increasing" (14.0%). The "low and stable" group was used as the comparison group for all analyses. Each 1 standard deviation (SD) increase in AN PGS corresponded with 13% greater odds of following the "high increasing" trajectory. Increases in BMI and attention-deficit/hyperactivity disorder PGS corresponded with 15% and 14% lower odds of following the "high increasing" trajectory, respectively. No preceding psychiatric or somatic disorders were significantly associated with trajectory assignment. In contrast, psychiatric and somatic disorders were more likely to occur subsequent to an AN diagnosis in those in the "high increasing" trajectory with odds ratios (OR) ranging between 1.73 and 3.81 for psychiatric disorders and between 1.61 and 5.38 for somatic disorders with a notable exception of obesity which showed a lower OR of 0.27. Conclusions and Relevance. Our findings hold significant clinical relevance by demonstrating that individuals with AN follow distinct severity trajectories that have different genetic risk as measured by PGS and clear differences in post-diagnosis morbidity patterns but no discernable differences in pre-diagnosis psychiatric or somatic morbidity. As the eating disorders genetics field progresses, incorporating PGS into comprehensive assessments at first presentation may aid in early identification, personalized intervention, and resource allocation for individuals at higher risk of developing a severe illness trajectory.

Food addiction (FA) has been proposed as a phenotype sharing features with substance use disorders. Despite increasing recognition of food addiction as a behavioral phenotype with features overlapping substance use disorders, little is known about its prevalence or clinical significance among individuals with alcohol use disorder (AUD). Objective: To examine the prevalence of FA and to evaluate demographic, psychological, and alcohol-related correlates in individuals with AUD. Design, Setting, and Participants: This cross-sectional analysis included 743 adults with AUD who were either treatment seeking (Tx) (n = 534) for AUD and were enrolled in an inpatient program at the National Institutes of Health Clinical Center or not treatment-seeking (non Tx) (n = 209). Main Outcomes and Measures: FA symptoms were assessed using the Yale Food Addiction Scale, with >=2 symptoms categorized as FA in this report. Multivariable logistic regression models adjusted for age, education, and income were conducted separately within each cohort. Results: Among 743 adults with AUD, 238 (32.1%) met criteria for FA symptoms, with similar prevalence among Tx (32.6%) and nonTx (30.6%) participants despite marked differences in clinical characteristics. Across both cohorts, FA was independently associated with higher body mass index, greater psychological distress, and greater alcohol dependence severity. Childhood trauma and poorer sleep quality were additionally associated with FA among treatment-seeking participants, whereas alcohol-related measures differed according to treatment status. Conclusions and Relevance: FA was common among adults with AUD and was associated with greater psychological, behavioral, and metabolic burden regardless of treatment-seeking status. These findings suggest that FA identifies a clinically meaningful subgroup of individuals with AUD who may benefit from more comprehensive assessment and integrated treatment approaches.

Background: Psychiatric disorders pose a significant public health burden, and their complex genetic architecture underlies multiple biological pathways, contributing to a lack of diagnostic biomarkers. Laboratory-Wide Association Studies (LabWAS) leverage electronic health record laboratory data as intermediary phenotypes to link genetic risk to physiology. Methods: Polygenic Scores (PGS) for 25 health-related, psychiatric, and substance use phenotypes were generated for individuals of African (AFR; N=10,473) and European (EUR, N=35,131) ancestry from the Penn Medicine Biobank. Laboratory data was prepared using the LabWAS pipeline, encompassing 78 laboratory tests and 6 vital signs. Linear regression models tested the association of each lab value with PGS adjusting for sex, age, and ten within-ancestry genetic principal components. Results: Four PGS were significantly associated with at least one laboratory value in AFR individuals and 22 PGS in EUR individuals. In EUR individuals, psychiatric PGS partitioned into three physiological profiles: anxiety, attention-deficit/hyperactivity disorder, major depressive disorder, and post-traumatic stress disorder shared a metabolic/inflammatory signature (higher BMI, glucose, and monocytes; lower high density lipoprotein cholesterol and oxygen saturation); anorexia nervosa, obsessive compulsive disorder, and schizophrenia were characterized by lower BMI; and bipolar disorder demonstrated a more circumscribed profile with lower electrolytes and renal makers. Substance use disorder PGS similarly clustered: tobacco use disorder and externalizing showed metabolic/inflammatory profiles; alcohol-related phenotypes showed lower red blood cell indices; and cannabis use disorder had a more circumscribed profile. Conclusions: LabWAS reveals physiologic signatures associated with genetic risk for psychiatric disorders, offering new biological insights into their pathology.

Background: Neurodevelopmental copy number variants (ND-CNVs) are associated with diverse neuropsychiatric outcomes, but most evidence derives from clinically ascertained cohorts enriched for severe disease. Whether these associations generalize to large, heterogeneous population biobanks, and whether they reflect locus-specific or distributed genetic effects, remains unclear. Methods: We developed a scalable analytic pipeline within the All of Us Research Program to identify ND-CNV carriers from structural variant callsets and evaluate associations across neuropsychiatric phenotypes derived from electronic health records (EHRs). Logistic regression models estimated associations between carrier status and individual phenotypes, adjusting for age, healthcare utilization, observation time, and genetic ancestry principal components. Sensitivity analyses included exclusion of mosaic chromosomal alteration (mCA)-suspected events and leave-one-locus-out (LOLO) models. Phenotypes were further grouped into Research Domain Criteria (RDoC) domains to assess domain-level structure and cross-domain burden. Results: ND-CNV carrier status was associated with modest but consistent enrichment across neuropsychiatric phenotypes spanning affective, psychotic, neurodevelopmental, and trauma-related domains. Although no individual phenotype survived false discovery rate correction, global permutation analyses demonstrated directional enrichment exceeding expectations under randomized exposure assignment. Effects were distributed rather than driven by a single phenotype or locus, with deletion-overlapping carriers showing stronger associations than duplication-overlapping carriers. Associations remained stable after mCA exclusion and LOLO analyses. Domain-level analyses revealed correlated enrichment across RDoC systems, while cross-domain burden measures demonstrated strong interdependence but limited discriminative separation. Conclusions: ND-CNV carriers exhibit distributed, pleiotropic neuropsychiatric risk in a large biobank. These findings provide empirical support for a distributed model of ND-CNV-associated neuropsychiatric liability in which numerous modest, directionally concordant phenotype associations collectively contribute to pleiotropic risk across neuropsychiatric domains.

Supervised psilocybin services are expanding across the United States, yet how individuals accessing these programs compare with those using psilocybin in the general population is unknown. We conducted a cross-sectional descriptive comparison of Oregon Psilocybin Services (OPS) data from licensed service centers in 2025 (5,935 encounters) and the 2024 National Survey on Drug Use and Health (NSDUH) public-use file (1,822 of 47,299 adults reporting past-year psilocybin use), examining demographics, reasons for use, self-reported disability, and past-year psychiatric conditions and treatment. OPS clients were predominantly female (58.2%) and aged 35 or older (82.1%), whereas adults reporting psilocybin use nationally were predominantly male (64.0%) and younger than 35 (56.7%). Racial and ethnic minority representation was narrower in Oregon (0.9% Black, 2.5% Hispanic vs. 5.4% and 14.3% nationally). OPS clients reported higher incomes (58.5% earning >$95,000) and primarily cited wellness; self-reported disability was uncommon. Adults using psilocybin nationally had high past-year rates of major depressive episode (22.7%), serious psychological distress (36.8%), substance use disorder (61.7%), and mental health treatment receipt (42.9%). Oregon's open-access model selects higher-income, clinically stable, wellness-oriented adults, while millions with psychiatric and substance-use burden use psilocybin outside supervised channels; its safety and utilization data should not be generalized.

Psychiatric disorders are complex conditions characterized by substantial overlap in genetic risk and shared biological mechanisms. However, how individual risk genes contribute to shared disease mechanisms and disorder-specific phenotypes remains poorly understood. BRD1 has emerged as a chromatin-associated regulator with transdiagnostic relevance across psychiatric disorders and a central role in gene regulatory networks enriched for psychiatric risk genes. To investigate the biological consequences of reduced BRD1 function in a translationally relevant system, we generated a minipig model harboring a monoallelic deletion in BRD1 and performed longitudinal neuroimaging together with behavioral and multi-omics profiling. BRD1 haploinsufficient minipigs displayed normal growth and exploratory behavior but exhibited subtle age-dependent differences in motivational behavior. Despite the absence of overt developmental abnormalities, longitudinal neuroimaging revealed genotype-associated structural differences primarily involving the cerebral cortex and caudate nucleus, suggestive of altered neurodevelopmental trajectories. Integrated multi-omics analyses revealed striking convergence across transcriptomic and metabolomic datasets, identifying coordinated perturbations of mitochondrial function, redox regulation, and phospholipid metabolism across multiple brain regions. Notably, these molecular alterations were not restricted to the central nervous system, as peripheral multi-omics profiling revealed systemic metabolic alterations, including altered phospholipid composition and glucose metabolism. Together, these findings indicate that BRD1 haploinsufficiency is associated with coordinated neurodevelopmental and metabolic alterations across brain and peripheral tissues. More broadly, this study provides systems-level insight into how a psychiatric risk gene influences interconnected neurodevelopmental and metabolic processes across multiple levels of biological organization and highlights the value of large-animal multi-omics models for translational neuropsychiatric research.

While medication for attention deficit hyperactivity disorder (ADHD) is effective, predictors of treatment response remain poorly understood. Given the use of polygenic scores (PGS) in psychiatric conditions, we investigate their potential to predict ADHD medication response. In this work, we recruited 309 participants aged 6-17 years from the Swedish ADHD medication and predictors of treatment outcome (ADAPT) study (ClinicalTrials.gov: NCT02136147; June 2015), and calculated their PGS. Compared with a reference cohort (N=780), ADAPT showed higher PGS for ADHD (p<2.22e-16), and lower PGS for autism (p=0.0051), educational attainment (EA) (p=8e-10), and intelligence (p=7e-08). To assess the association between genetic effects and changes in Swanson, Nolan, and Pelham ADHD Rating Scale-version IV (SNAP-IV) scores, linear mixed-effects models tested the interaction between each PGS and time (baseline, 3-months). PGS for ADHD was associated with higher SNAP-IV scores overall ({beta}=0.1419, p=0.0078, FDR=0.0293) but not with a change at follow-up; whereas, PGS for EA was associated with lower overall scores ({beta}=-0.1161, p=0.0256, FDR=0.0679) and smaller reductions at follow-up ({beta}=0.0946, p=0.0453, FDR=0.1130). Subgroup analyses indicated that these effects were more prominent in adolescents ([&ge;]13 years) and individuals classified as responders to treatment. We further explored machine learning models combining clinical and genetic information across 14 models with 49 features. Although models could not empirically generalize, estimated information-theoretic upper bounds for classification accuracy were 72% with PGS, 84% with clinical and demographic variables, and 92% when combined. This study highlights the potential of using PGS and combining genetic and clinical data to improve treatment stratification in ADHD.

Background: Psychopathy is a personality construct characterized by affective and interpersonal features coupled with severe antisocial behavior. While strongly associated with extreme behaviors such as violent crime, empirical work suggests that psychopathy exists as a dimensional trait in the general population. However, our understanding of the genetic structure of psychopathy remains limited, with genome-wide association studies (GWAS) having been restricted to broad measures of antisocial behavior. Methods: We perform the first large-scale GWAS of psychopathy, using total and factor scores from the Self-Report Psychopathy scale (SRP) in up to 10,558 participants enriched for mood disorder cases from the AFFECT study. LD score regression (LDSC) was used to characterize the heritability of SRP scores and estimate their genetic correlation (rG) with several externally-measured traits, using the Benjamini-Hochberg approach to perform multiple testing correction. Results: Psychopathy scores showed significant heritability, with 12-14% of phenotypic variance explained by common genetic variants. However, GWAS did not identify any genome-wide significant loci in this sample. The LDSC-estimated genetic correlation with antisocial behavior was only 0.54 (95%CI: 0.21-0.81), in line with prior twin research. Significant genetic correlations were found with a wide range of psychiatric disorders (rG's: 0.21 - 0.72), with the highest observed for borderline personality disorder (95% CI: 0.41-0.72) and substance use disorders (95% CI: 0.43-0.63). Psychopathy was also genetically correlated with lower life-satisfaction, poorer health outcomes, worse cognitive functioning, and lower educational attainment. Conclusions: In the first large-scale GWAS of self-reported psychopathy, we found significant SNP heritability and genetic overlap with risk for psychiatric disorders, and poorer behavioral, cognitive, and physical health outcomes. These findings provide important genetic support for differentiating psychopathy from antisocial behavior. Further, they inform our understanding of how genetic factors may contribute to poor health outcomes in psychopathy, and shed insight into the comorbidity between psychopathy and other disorders.

BackgroundSchizophrenia liability reflects both the aggregate effects of many common genetic variants and rare structural variation at recurrent neurodevelopmental copy-number variant (ND-CNV) loci. Although both components of genetic liability have been associated with schizophrenia and related phenotypes, it remains unclear whether they exhibit similar neuropsychiatric association profiles or show evidence of interaction when examined jointly. MethodsWe analyzed 71,992 participants from the All of Us Research Program Controlled Tier version 8 dataset, including 2,115 participants carrying structural variants overlapping curated recurrent ND-CNV loci. We integrated binary ND-CNV carrier status, an ancestry-adjusted and standardized reduced schizophrenia polygenic risk score (PRS), and longitudinal electronic health record-derived psychiatric and neurodevelopmental phenotypes. Logistic regression models evaluated pooled, deletion-overlapping, and duplication-overlapping carrier associations, schizophrenia PRS effects, and PRS x ND-CNV interactions. Dimensional analyses, confirmatory factor analysis (CFA), and structural equation modeling (SEM) provided complementary summaries of phenotype covariance and assessed the robustness of primary associations across alternative representations of the phenotype space. ResultsSchizophrenia PRS and ND-CNV carrier status showed distributed association profiles extending beyond schizophrenia diagnosis across psychosis-spectrum, neurodevelopmental, cognitive, and internalizing phenotypes. ND-CNV carriers had higher estimated odds of schizophrenia diagnosis than non-carriers (OR = 1.49, 95% CI 1.09-2.03), while each 1-SD increase in schizophrenia PRS was associated with higher odds of a broad psychosis-spectrum phenotype (OR per SD = 1.07, 95% CI 1.03-1.10). Deletion-overlapping carriers exhibited generally larger and more consistently positive association estimates than duplication-overlapping carriers. Psychosis-spectrum prevalence increased from 5.4% in the lowest PRS decile to 6.7% in the highest, while ND-CNV carriers maintained consistently higher prevalence than non-carriers across the PRS distribution. PRS x ND-CNV interaction estimates remained near the null, providing little evidence of widespread multiplicative interaction. Among tested covariance structures, bifactor models showed the lowest residual misfit and were therefore carried forward for SEM analyses. ConclusionsSchizophrenia-associated polygenic liability and structural variation overlapping recurrent ND-CNV loci exhibit distributed neuropsychiatric association profiles with limited evidence of widespread multiplicative interaction. Their joint evaluation in the large, ancestrally diverse All of Us cohort demonstrates that distinct forms of genomic liability can be examined within a shared, real-world phenotype space extending beyond schizophrenia diagnosis alone.

Substance use and psychiatric disorders frequently co-occur, but establishing causality of their relationships is difficult given the multifactorial nature of these traits. To assess these relationships, we applied two genetically informed methods using the largest available European-ancestry genome-wide association studies of six substance use behaviors and twelve psychiatric and personality phenotypes. Using Genomic Structural Equation Modelling, we modelled the latent genetic architecture of the psychiatric and personality traits and examined these factors' correlations with substance use traits. A structure with three factors fit the data best: F1 (PTSD, MDD, GAD, ADHD, agreeableness), F2 (BD, SCZ, OCD, openness), and F3 (OCD, GAD, extraversion, neuroticism), which showed differential correlations with substance use. Smoking correlated significantly which each factor, however, strongest with F1, alcohol use showed weak but significant correlations with F1 and F2, and cannabis use showed moderate correlations with F1 and F2, but strongest with F2. Using Mendelian Randomization, we examined bidirectional causal relationships. We found strong evidence that smoking continuation was causally associated with increased bipolar disorder risk, cigarettes per day with increased schizophrenia, and smoking initiation with increased extraversion and decreased agreeableness. Genetic liability to schizophrenia and PTSD were causally associated with increased risk of cannabis use, and schizophrenia with increased alcohol use. Liability to neuroticism, openness and agreeableness was causally linked to smoking behaviors, and extraversion to cannabis use. Most remaining associations showed weak causal evidence, largely due to heterogeneity and pleiotropy. Together, these findings provide evidence for both shared genetic liability and, for a subset of relationships, direct causal effects between substance use behaviors, psychiatric disorders, and personality traits, which can help inform future intervention and prevention research.

Background: Bipolar disorder (BIP) and obsessive-compulsive disorder (OCD) frequently co-occur and show evidence of genetic overlap, yet the specific pleiotropic loci and their functional mechanisms remain unclear. Methods: We conducted large-scale genetic analyses using GWAS summary statistics for BIP and OCD, excluding 23andMe data. We applied conjunctional FDR analysis to identify pleiotropic variants jointly associated with BIP and OCD, followed by integrative annotation through transcriptomic (eQTL, sQTL), epigenomic (mQTL, haQTL), and proteomic (pQTL, histone PTM) data. SMR analysis was used to prioritize putative regulatory effects, while AlphaGenome predictions and targeted histone proteomics were employed to evaluate allele-specific chromatin changes. Results: We observed a significant genetic correlation (rg = 0.38, P = 3.8 x 10-29) and extensive polygenic overlap between BIP and OCD. Bidirectional MR supported causal effects in both directions, with stronger evidence for BIP influencing OCD risk. ConjFDR analysis revealed 2,143 pleiotropic SNPs jointly associated with BIP and OCD, with convergent signals at the ITIH3/ITIH4 locus. Summary-data-based Mendelian randomization (SMR) and colocalization with multi-omic QTLs (eQTL, pQTL, mQTL, and haQTL) further prioritized the ITIH3/4 locus, where multiple SNPs (e.g., rs3774364) colocalized with H3K27ac histone acetylation QTLs in the prefrontal cortex (PP_H4 > 0.5). Integrated PBMC RNA-seq and complementary histone mass spectrometry linked immune--ECM transcriptional activity to exploratory global histone acetylation changes in BIP and OCS-BIP, with suggestive alterations in H3K27ac-containing peptides. Conclusions: Our multi-omic analysis highlights ITIH3/ITIH4 as a prioritized pleiotropic locus for BIP and OCD. Epigenetic regulation, particularly through histone acetylation, may underlie shared susceptibility and offers a novel mechanistic link between these psychiatric disorders.

Post-traumatic stress disorder (PTSD) has a significant genetic component (h2 = 24-72%). While the majority of prior studies have utilized common variants, recent research suggests rare variants also contribute to PTSD liability. Here, we examined the role of rare copy number variants (rCNVs; MAF < 1%) from multi-ancestry whole-genome sequencing data in the All of Us Research Program, using an electronic health record-defined PTSD phenotype. Genome-wide burden analyses utilizing all rCNV lengths revealed significant associations for deletion count across European-like (EUR-like; beta = 0.005, SE = 0.001, P = 5.99 x 10-6, FDR P = 3.59 x 10-5 ) and African-like (AFR-like; beta = 0.003, SE = 0.001, P = 0.005, FDR P =0.02) ancestries. We conducted rCNV burden analyses within and across EUR-like (N case = 1,179, N control = 33,689), AFR-like (N case = 504, N control = 12,216), and Admixed American (AMR-like) (N case = 418, N control = 11,935) ancestries using three separate domains of gene-sets previously implicated in neuropsychiatric disorders: neurodevelopmental disorders (NDD; N = 53), abnormal behavior mouse mutant-derived (N = 146), and PTSD (N = 5). Within-ancestry analyses across all three domains yielded one significant brain-expressed gene-set within the EUR-like cohort. Meta-analyzing across ancestries identified 11 NDD gene-sets enriched for rCNV count (FDR P < 0.05). rCNVs with lengths greater than 10kb were examined, but observed no significant signals. Future research using larger samples and detailed PTSD phenotypes, integrated with functional genomic data and brain-region-specific expression profiles, is needed to fully map the disorder's genetic landscape.

Background. Cord blood DNA methylation profile scores (MPSs) based on genetic and pre-/perinatal risk factors for neurodevelopmental conditions (NDCs) may capture downstream biological effects and help understand how combined exposure signals contribute to NDC risk. Methods. Using data from two longitudinal birth cohorts, Generation R (N-train = 1856, N-test = 476) and ALSPAC (N-validation= 832), we developed cord blood MPSs based on genetic and pre-/perinatal NDC risk factors. We assessed individual and combined predictive performance of risk factors and MPSs for eight childhood psychiatric outcomes (four broad, four specific), measured between ages 5 and 14 years. We also evaluated if the MPSs could be combined into a composite "transmission load" MPS. Results. We validated four novel MPSs: maternal age, birthweight, and genetic liability for ADHD and schizophrenia (r range = 0.08 to 0.29) and included two previously validated MPSs: maternal smoking and gestational age (r range = 0.42 to 0.63). Jointly modeling the six MPSs with their corresponding risk factors explained on average 3.3% of variance in outcomes, higher than that explained by risk factors (1.8%) or MPSs alone (1.6%), indicating complementary sources of risk. The "transmission load" MPS did not replicate due to heterogeneous contributions of the predictors across cohorts. Conclusions. The four novel MPSs based on genetic and pre-/perinatal risk factors can serve as valuable tools for future research. Integrating genetic and prenatal risk factors with DNA methylation at birth can provide insights into their individual and joint contributions to early psychiatric risk and may improve prediction.

Background Cocaine use disorder (CUD) is estimated to be 50% heritable, yet few genetic variants have been robustly associated with risk. During January 2021 to June 2024, cocaine was involved in 30% of U.S. overdose deaths. Identifying genetic contributors to CUD could inform diagnostics and treatments. The missing heritability may stem from small sample sizes, models that inadequately account for small-effect common variants, and the exclusion of large-effect structural variants like copy number changes. Epistasis likely contributes but remains challenging to detect genome-wide. Results We focused on epistasis and haplotypes rather than individual SNPs by applying the custom correlation coefficient in BlocBuster to construct allele networks from eQTL SNPs. Testing these regulatory haplotype networks for association with cocaine use in 7,826 individuals with opioid use disorder identified 12 significant associations across two ancestries. For one haplotype, raw genotyping array intensity data revealed a copy number increase at the CYP2D6 locus in individuals of European ancestry. In a subcohort of individuals who co-use cocaine and heroin (i.e., speedball), two haplotypes were also significantly associated with HIV infection. One of these involved GPR75, whose ligand, CCL5 (RANTES), is shared with CCR5, a coreceptor for HIV entry. Conclusions Our findings, integrated with long-read human pan-genomes, support a model in which non-functional copies of CYP2D6 disrupt dopaminergic, glutamatergic, and kynurenine pathways in the brain, contributing to cocaine use severity. The association of additional haplotypes with HIV status in speedball users highlights the genetic contribution to comorbid risk in high-exposure populations.

Background Youth involved in child protection systems are at increased risk of psychiatric disorders and are overrepresented in inpatient mental health services. However, few studies have directly compared the clinical characteristics and mental health service use of youth across different child protection pathways. Objective To compare clinical characteristics, psychosocial risk factors, clinical complexity, and mental health service use among psychiatrically hospitalised youth in foster care, adoption, and child welfare supervision. Participants and Setting This retrospective observational study included 236 children and adolescents across three child protection pathways admitted to a Child and Adolescent Inpatient Psychiatry Unit between 2018 and 2024. Methods Clinical, psychosocial, and service-use data were extracted from medical records and compared using univariate analyses, multilevel mixed-effects models, logistic regression, and time-to-event analyses. Results All groups showed high comorbidity and clinical severity, but distinct clinical profiles emerged. Youth in foster care more frequently presented with externalising disorders, trauma exposure, and substance use; adopted youth showed higher rates of neurodevelopmental and prenatal adversity-related conditions; and youth under child welfare supervision more often presented with affective symptoms and suicidal ideation. Post-discharge emergency department re-consultation differed significantly between groups (p = 0.007) and was most frequent among adopted youth, who also had higher odds of psychiatric readmission. Youth in foster care had the shortest median time to emergency re-consultation, although time-to-event differences were not significant (p = 0.476). Conclusions Distinct clinical and service-use profiles across child protection pathways support trauma-informed, placement-sensitive mental health care and stronger coordination between child protection and mental health services.

Objective To evaluate the association of early addiction consultation with withdrawal pharmacotherapy and complications in hospitalized patients with alcohol withdrawal. Methods Retrospective single-center cohort of adult hospitalizations with alcohol withdrawal (diagnosis code or CIWA-Ar [&ge;]10 within 24 hours) from July 2020 to January 2026. Exposure was an addiction consult service order within 24 hours of arrival, compared with no or later consultation. Primary outcomes were intensive care unit (ICU) transfer after the first 24 hours and delirium tremens or withdrawal seizure not present on admission. Process outcomes included phenobarbital and thiamine administration within 24 hours and benzodiazepine dose in the first 48 hours. Secondary outcomes included length of stay and 30-day death or return to hospital. Results Of 4,663 hospitalizations, 1,379 (29.6%) received early consultation. After adjustment, early consultation was associated with lower odds of ICU transfer (odds ratio [OR] 0.73; 95% CI 0.54-0.99) and fewer episodes of delirium tremens (risk difference -1.09 per 100; -1.45 to -0.73), with no significant difference in withdrawal seizure. Early consultation was associated with phenobarbital (OR 1.57; 1.32-1.86) and thiamine (OR 1.23; 1.07-1.41) within 24 hours, higher 48-hour lorazepam-equivalent dose (ratio of geometric means 1.44; 1.32-1.57), shorter stays (ratio 0.92; 0.88-0.97), and lower odds of 30-day death or return to hospital (OR 0.78; 0.66-0.91). Conclusions Early addiction consultation was associated with earlier, more intensive withdrawal pharmacotherapy, lower odds of ICU transfer, and fewer episodes of delirium tremens, although the complication associations were sensitive to cohort definition.

Importance: Excess mortality associated with mental disorders is well established, but estimates are largely based on specialist psychiatric populations. Whether they characterize mortality in the broader diagnosed population is uncertain. Objective: To characterize heterogeneity in excess mortality by diagnosis, psychiatric care setting, substance use disorder (SUD), and time since diagnosis. Design: Nationwide population-based cohort study with follow-up from January 1, 2011, through December 31, 2023. Setting: Primary and specialist health care and population registers in Finland. Participants: Residents aged 5 to 95 years without a recorded prevalent mental disorder at cohort entry. Exposures: Mental, behavioural, and neurodevelopmental disorders classified using ICD-11, with time-varying psychiatric care setting and SUD status. Main Outcomes and Measures: All-cause mortality, mortality rate ratios (MRRs), and 10-year differences in restricted mean survival time (RMST). Results: Among 5,526,599 individuals (2,784,897 [50.4%] women), 1,463,064 (26.5%) received a mental disorder diagnosis. Excess mortality varied substantially by diagnosis, clinical subgroup, and time since diagnosis. Among those aged 5 to 64 years with any mental disorder, adjusted MRRs across care setting and SUD strata ranged from 1.54 (95% CI, 1.39-1.71) to 8.97 (7.86-10.24). MRRs were highest immediately after first diagnosis and declined during the first 2 to 3 years. At 3 years, MRRs for depressive, anxiety or fear-related, and stress-related disorders among individuals without SUD treated outside specialist psychiatric care ranged from 0.88 (0.79-0.98) to 1.20 (1.12-1.29) in men and from 0.81 (0.73-0.89) to 1.13 (1.04-1.22) in women, whereas MRRs for schizophrenia and other primary psychotic disorders remained 1.84 (1.60-2.12) in men and 1.55 (1.37-1.75) in women. Ten-year survival loss across all mental disorders was 0.53 years (95% CI, 0.53-0.54) in men and 0.34 years (0.33-0.34) in women and was greater for natural than external causes. Conclusions and Relevance: Excess mortality varied markedly by diagnosis, clinical context, and time since diagnosis and was small in some common disorders outside specialist psychiatric care without SUD. Estimates derived from specialist psychiatric populations or averaged across follow-up may therefore provide an incomplete picture of mortality in the broader diagnosed population.

Addiction is a complex and heritable trait which progresses through several developmental stages, each of which is presumably influenced by multiple partially overlapping genetic factors. Cocaine initially produces rewarding effects, followed by aversive effects including anxiety, craving, anhedonia, and withdrawal. These aversive effects have been suggested to contribute to the etiology of cocaine use disorders (CUD), as repeated exposure is thought to desensitize the rewarding effects and sensitize the aversive effects through a process involving both aberrant reward-based learning and aberrant avoidance-based learning. We examined the genetic basis of aversion learning using both food-based and cocaine-based behavioral assays in outbred Heterogenous Stock (HS) rats. A total of 1,074 HS rats (35.3% male) underwent runway operant cocaine-seeking, food-based progressive ratio and punishment testing, and locomotion testing. These phenotypes were significantly heritable (with h2 estimates as high as 0.307) and identified significant (p < 0.05) genetic loci related to avoidance-based learning including from the punishment task on Chromosomes 2, 3, 5, and 6, and the cocaine-operant runway latency task on Chromosome X. 172 positional candidate genes were identified from significant and suggestive loci, including Cdh10, Cdh12, Cdh18 which have previously been associated with smoking initiation from human GWAS, Adcy3, Cfap206, and Drc1 which are associated with primary neuronal cilia, as well as SNPs associated with novelty-related and social interaction phenotypes in independent samples of HS rats. Our results suggest that these aversion learning phenotypes are themselves complex heritable traits influenced by multiple genetic loci, which may pleiotropically affect other aspects of addiction biology.