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.

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.

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 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.

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 [≥]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.

Background: Biological risk scores provide objective markers of bipolar disorder (BD) liability. Large-scale genome-wide association studies (GWASs) have led to polygenic risk scores (PRSs) that capture genetic liability to BD at the individual level. We lack a comparable large-scale effort to leverage a brain-wide association study (BWAS) to create an imaging risk score (IRS) that captures brain structural liability to BD at the individual-level. Here, we conduct the largest multivariate BWAS of BD and develop a BD IRS. We compare the BD IRS to the PRS and assess their combined predictive performance in multimodal risk score (MRS) models. Methods: Our multivariate BD BWAS used 153 structural neuroimaging features from 3902 cases and 6855 controls (mean age (sd)=35.47 years (13.42), 56.70% female) in a cross-validated machine learning approach. Using the resulting model coefficients, we constructed an IRS. We then evaluated the out-of-sample performance of the IRS, PRS derived from the largest GWAS to date, and combined MRS model using logistic regression in a subset of individuals with imaging and genetic data (nBD=486, ncontrols=1701, age (sd)=33.10 (12.02), 56.47% female). We also performed stratified analyses for demographic and BD clinical groups. Prediction performance was quantified using the area under the receiver operating characteristic curve (AUC). Subsequent analyses examined associations between each risk score and BD relevant symptoms in developing youth. Outcomes: In predicting case status, the BD BWAS model achieved a mean AUCBD of 0.62 (sdBD=0.08) and in stratified analyses, had higher prediction than subgroup-specific BWAS models. The BD type II BWAS was the only exception (AUCBDII=0.60, sdBDII=0.07 vs AUCBD=0.58, sdBD=0.09). The BD PRS had an AUCBD of 0.65 (CI95%=0.63-0.68) and a higher AUC than subtype-specific PRS in stratified analyses. The PRS typically attained a higher AUC than the IRS. Notably, the IRS and PRS were uncorrelated (r=0.03, p=0.11). MRS models outperformed the prediction of individual PRS and IRS with the strongest prediction for BD type I (AUCBD=0.74, CI95%=0.70-0.78). The IRS had the strongest associations with BD-related symptoms in developing youth including increased energy (OR=1.21, pfdr=0.03) and distress from psychotic-like experiences (OR=1.23, pfdr=0.04). Interpretation: Our BD IRS is a novel biological indicator of BD risk. The lack of correlation between the IRS and PRS along with improved MRS prediction suggests the two risk scores capture some orthogonal liability to BD. We show that integrating imaging and genetics is useful for biological characterization of BD and should be considered for the development of clinically relevant prediction models.

Background: Approximately 25% of individuals with 22q11.2 deletion syndrome (22q11DS) develop a psychotic disorder, and the syndrome shares key neurodevelopmental features with psychosis in the general population. The olfactory system develops early in utero, providing a window into gestational disruptions relevant to psychosis risk. We hypothesized that 22q11DS would show impairments in olfactory function and structural anomalies of the olfactory system relative to psychosis spectrum (PS) youth without a known genetic syndrome and typically developing controls (TD). Methods: Participants included individuals with 22q11DS (n=101), PS (n=56), and TD (n=52). Sinonasal symptoms, odor identification, and discrimination (Sniffin' Sticks) behaviorally. Structural 3T MRI measured olfactory bulb volume, sulcus depth, and sulcus length. Sample sizes vary per analysis. Results: Relative to TD, 22q11DS showed elevated sinonasal burden (p<.001), lower odor identification (p<.001), and lower odor discrimination (p<.001). PS showed elevated sinonasal burden (p<.001) and marginally lower odor identification (p=.06), but no discrimination deficit. Olfactory bulb volume was significantly smaller in 22q11DS versus TD (p=.007, r=.39); PS showed a non-significant trend (p=.07). Olfactory sulcus depth (p=.52) and length (p=.82) did not differ across groups. Conclusions: 22q11DS is associated with elevated sinonasal burden, robust olfactory identification and discrimination deficits exceeding those of PS and reduced olfactory bulb volume. The co-occurrence of functional deficits and reduced bulb volume without sulcal anomalies may distinguish the 22q11DS olfactory phenotype from that of PS. These hypothesis-generating findings are consistent with partially dissociable neurodevelopmental mechanisms and support the utility of 22q11DS as a genetic model for psychosis risk.

Background: Helsmoortel-Van der Aa syndrome, caused by pathogenic variants in ADNP, is characterised by substantial clinical heterogeneity, but how biological sex influences disease biology and treatment response remains an emerging area of investigation. Here, we investigated whether sex modifies the behavioural and molecular consequences of Adnp deficiency, the response to the investigational drug candidate davunetide (NAP), and the clinical phenotype of Helsmoortel-Van der Aa syndrome. Methods: We studied male and female Adnp heterozygous mice harbouring the p.Leu822Hisfs*6 variant and sex-matched wild-type littermates using continuous 24-h behavioural phenotyping, hippocampal genome-wide DNA methylation and bulk RNA sequencing. NAP effects on behaviour, hippocampal ADNP protein abundance, and epi-transcriptomic responses were assessed using genotype-by-treatment models. Four Core Genotypes mice were assessed to distinguish sex-chromosome and gonadal contributions to hippocampal Adnp transcript expression, and reproductive-tissue transcriptomes were analysed in Adnp mice to unravel a possible endocrine component of the disease. Findings were compared with clinical and developmental data from 129 individuals with Helsmoortel-Van der Aa syndrome. Findings: Adnp deficiency produced a shared overall behavioural phenotype in male and female mice, but through distinct patterns of behavioural disruption, indicating that sex modifies the implementation rather than the magnitude of the phenotype. This distinction was also evident at the molecular level: hippocampal DNA methylation was predominantly determined by genotype and showed convergence between sexes, whereas transcriptional responses diverged, with mitochondrial pathways predominating in males and chromatin, RNA processing, and cell-cycle pathways in females. NAP partially shifted behavioural abnormalities towards the wild-type state in both sexes and increased hippocampal ADNP protein abundance in heterozygous mice, without reversing the underlying methylation phenotype. Its transcriptional effects were markedly broader in males, indicating a sex-dependent molecular response to treatment. In reproductive tissues, Adnp deficiency was associated with convergent alterations in steroid hormone biosynthesis, despite no evidence for direct regulation of hippocampal Adnp expression by sex-chromosome complement or gonadal hormonal state. By contrast, sex was not associated with robust differences across the clinical and developmental features assessed in 129 individuals with Helsmoortel-Van der Aa syndrome after correction for multiple testing. Interpretation: Biological sex modifies how Adnp deficiency is expressed at behavioural and molecular levels, but these differences do not necessarily define distinct clinical phenotypes. The convergence of the methylation response alongside greater divergence in transcriptional and behavioural responses identifies sex as a modifier of disease biology rather than a determinant of the core phenotype. The sex-dependent response to NAP further indicates that biological sex may influence pharmacological responses even when treatment-associated behavioural improvement is observed in both sexes. These findings support consideration of biological sex as a prespecified variable in preclinical and clinical studies of Helsmoortel-Van der Aa syndrome and suggest that systematic investigation of sex-dependent biology may also be relevant to therapeutic development across rare diseases. Keywords: Helsmoortel-Van der Aa syndrome (HVDAS), Activity-Dependent Neuroprotective Protein (ADNP), autism spectrum disorder, intellectual disability, sex, mouse model, behaviour.

Approximately 30% of U.S. adolescents have consumed alcohol, and earlier onset is associated with faster escalation and greater risk of adult alcohol use disorder. Predicting not only who will initiate drinking but also when could enable more timely and targeted prevention. Existing machine-learning approaches have largely classified drinking status or predefined trajectory classes, requiring fully observed outcomes and often excluding adolescents who remain abstinent at last follow-up. Many also rely on neuroimaging or small, hand-selected feature sets, limiting scalability. We developed a stacked-encoder survival framework for predicting drinking-onset timing from baseline clinical data alone. The framework compresses 1,582 clinical features using an unsupervised denoising autoencoder and re-embeds them with FocalTab, a TabPFN encoder fine-tuned with focal loss; the encoders are then frozen for survival modeling using a neural Cox or random survival forest head. Among 661 NCANDA adolescents who were non-drinkers at baseline, 495 initiated drinking within six years. The stacked representation outperformed single-encoder and raw-feature models, achieving an Uno C-index of 0.7654 and time-dependent AUC of 0.8274. Focal-loss encoding outperformed cross-entropy encoding, while SHAP identified alcohol expectancies, substance access, and community prevention engagement among the most influential predictors. Unsupervised clustering further identified five biotypes with a monotonic gradient in mean time to onset (4.30 to 2.86 years) and differential limbic and thalamic neuroimaging phenotypes. These findings support the feasibility of scalable, clinically based prediction of drinking-onset timing and data-driven adolescent risk stratification.

Background: Dissociative identity disorder (DID) is associated with frequent psychiatric comorbidity. Its complex and overlapping symptom profile can complicate recognition of both DID and co-occurring psychiatric conditions, contributing to diagnostic uncertainty. Evidence regarding psychiatric comorbidity is limited and prevalence estimates vary across studies. Aims: This meta-analysis aimed to examine the prevalence of psychiatric comorbidities in DID and factors associated with variation in prevalence estimates. Methods: Eligible studies were identified through PubMed, Scopus, Embase, PsycINFO, and MEDLINE from 1980 to 25 April 2026 (PROSPERO, no. CRD420261335819). Studies reporting psychiatric comorbidity in adults with DID were independently screened by two reviewers. Risk of bias was assessed. Random-effects meta-analyses using logit-transformed prevalence estimates were conducted. Meta-regressions examined moderators, whilst influence and sensitivity analyses assessed robustness. Certainty was evaluated using the GRADE approach. Results: Twenty-four studies (N = 858) contributed to the meta-analysis across 23 psychiatric comorbidities. Among individuals with DID, posttraumatic stress disorder had the highest pooled prevalence (87.44%, 95% CI 71.79-94.96), followed by major depressive disorder (62.64%, 95% CI 33.45-84.84), and borderline personality disorder (47.05%, 95% CI 34.21-60.32). Substantial heterogeneity was noted across most estimates. Meta-regressions identified significant associations with participant characteristics, recruitment, study quality, and diagnostic method. Risk of bias and certainty of evidence were heterogenous. Conclusions: Psychiatric comorbidity in DID is substantial and spans multiple diagnostic categories, although considerable heterogeneity and methodological variation limit confidence in prevalence estimates. Standardised diagnostic assessment, more representative sampling, and longitudinal research are needed to clarify the extent and clinical significance of comorbidity in DID.

Psychiatric disorders frequently co-occur with a broad range of non-psychiatric conditions, suggesting shared biological mechanisms that transcend traditional diagnostic boundaries. Although recent studies have demonstrated substantial genetic overlap between psychiatric and other medical disorders, the genomic architecture underlying these relationships and the extent to which shared genetic liability can be leveraged for psychiatric gene discovery remain incompletely understood. Here, we systematically investigated the shared genetic architecture between eleven major psychiatric disorders and thirty-nine non-psychiatric disorders spanning cardiovascular, metabolic, autoimmune, neurological, gastrointestinal, respiratory, and other disease categories. To maximize statistical power, we meta-analyzed genome-wide association study (GWAS) summary statistics from large biobanks and international consortia. Genome-wide analyses identified 298 significant genetic correlations between psychiatric and non-psychiatric disorders, revealing pervasive shared liability across disease domains. Local genetic correlation analyses identified 180 genomic regions contributing to cross-disorder risk, while colocalization analyses revealed 1,470 candidate shared variants. Several highly pleiotropic loci, including regions containing FURIN and TCF4, contributed to risk across multiple psychiatric and other medical conditions. Genomic structural equation modeling identified recurrent dimensions of shared liability, including cardiovascular-kidney-metabolic and neuroimmune-related dimensions, suggesting that psychiatric-medical comorbidity is organized into biologically coherent systems. Leveraging these shared genetic architectures through cross-trait analyses identified 1,569 significant loci, including 382 psychiatric risk loci not reported in the individual psychiatric GWAS used in our analyses. Integrative positional and functional gene-mapping approaches prioritized genes involved in neuronal development, synaptic organization, neurotrophic signaling, and cellular homeostasis, with LRFN5, MED19, PITPNM2, CTNND1, TMEM106B, GLYCTK, and PCLO as the top implicated genes. Pathway and tissue-enrichment analyses further demonstrated convergence on neurodevelopmental and synaptic processes and significant enrichment across multiple brain regions. Our results provide a comprehensive characterization of the genetic architecture underlying comorbidity between psychiatric and other medical disorders and demonstrate that leveraging genetically correlated medical conditions across domains can substantially increase power for psychiatric risk-locus discovery.

Importance: Obsessive-Compulsive Disorder (OCD) has a 2% global prevalence, but only about 50% of patients respond to conventional treatment, underscoring the need for additional effective interventions. Objective: To assess the feasibility, safety, and preliminary evidence for efficacy of repeated psilocybin administration in OCD patients who had previously attempted psychotherapy or pharmacotherapy. Design: Waitlist-controlled open label randomized clinical trial. Setting: Data were collected at the Johns Hopkins University School of Medicine. Participants: Data were analyzed from 30 participants (total randomized N=37, by age, sex and OCD severity) with a failed previous attempt at either pharmacotherapy or evidence-based psychotherapies such as exposure response prevention (ERP). Intervention: Participants received two psilocybin doses over two weeks (20 mg followed by 30 mg, if well-tolerated) under supportive conditions. The immediate-treatment arm received the drug within a month following enrollment, and the waitlist-control arm received identical support and dosing after an 8-week waiting period. Main Outcomes: Clinician-administered Y-BOCS scores was collected one week post each drug administration and one month post session 2. Self-assessed reports were collected for acute subjective effects (Mystical Experience Questionnaire (MEQ), Challenging Experience Questionnaire (CEQ), and 11-Dimensional Altered States of Consciousness (11D-ASC)), State-Trait Anxiety Inventory (STAI), Beck Depression Inventory-II (BDI-II), and Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q). Results: A total of 37 participants were enrolled in the study (age[SD] years:38.4[11.6] years; 21 [56.75%] female), with 30 [81.08%] completing the 1-month follow-up. We show that two successive doses of psilocybin over two weeks were well-tolerated, leading to improvements in OCD symptoms. Compared with the waitlist group (N=14), the immediate-treatment group (N=16) showed a greater reduction in the Y-BOCS scores (F(2,56)=16.17, p<0.001). After crossover, this improvement persisted one month after the second psilocybin dose for both groups (F(3,84)=29.91, p<0.001). Reductions in Y-BOCS score post sessions were correlated with several acute subjective effects measures, including total scores on MEQ, and individual factors on CEQ and 11D-ASC. Conclusions and Relevance: Repeated psilocybin administration is tolerable and potentially efficacious in reducing OCD symptoms. These results support further investigation of multidose psilocybin protocols as a viable therapeutic approach. Trial Registration: ClinicalTrials.gov Identifier NCT05546658

Objective: The Genetic Risk for Serious Mental Illness and Development ("Paisa Kids") Study is establishing a longitudinal cohort of 3,000 youth enriched transdiagnostically for risk for serious mental illnesses (SMI; i.e., schizophrenia, bipolar disorder, and severe depression) from the Paisa region of Colombia. Its objective is to clarify the early clinical, neurobehavioral, genetic, and environmental profiles associated with later SMI and distinguish transdiagnostic from disorder-specific pathways. This paper describes the study infrastructure, recruitment streams, and baseline assessment battery, and characterizes the first two-thirds of the cohort. Method: Youth aged 6-15 years are being recruited. Youth recruited for high SMI risk either have a first or second degree adult relative with a SMI diagnosis or a psychiatric diagnosis themselves identified through electronic medical records (EMRs) associated with later SMI. Lower-risk youth have a relative without a SMI diagnosis. Baseline measures include psychiatric and developmental history, neurobehavioral functioning, environmental exposures, and genome-wide genotyping. Psychiatric EMRs provide longitudinal follow-up. Results: Among 2,384 participants enrolled thus far (mean age=11.2 years, 45.0% female), 2,211 were recruited for high SMI-risk and 173 for lower SMI-risk. Overall, 73.2% met criteria for a history of one or more psychiatric disorders. Logistic regression comparing rates of diagnoses and ACEs between recruitment streams showed elevated rates of depressive and anxiety disorders, attention-deficit/hyperactivity disorder, oppositional defiant disorder, and several ACEs among high versus lower SMI-risk youth. Conclusion: Integrating multidomain phenotyping, genomic data, and longitudinal EMR follow-up, the Paisa Kids cohort provides a unique resource for investigating pathways of risk and resilience to SMI.

Locomotor response to a novel environment is a heritable, addiction-relevant behavioral phenotype in rodents. We characterized its genetic basis in 9,341 male and female heterogeneous stock (HS) rats from eight studies. Locomotor activity was heritable across studies, while pairwise genetic correlations were positive but variable, indicating shared yet nonidentical genetic influences. Given nonuniform genetic architecture, we compared three complementary approaches to locus discovery that analyzed SNP effects 1) on a pooled locomotor phenotype (MEGA), 2) across studies under a fixed-effect model (METAL), or 3) on a shared genetic factor (Genomic SEM). To ensure comparability, all three locus-discovery approaches were applied to a common subset of seven studies. Together, these approaches identified 38 loci, with both convergence and method-specific discovery across analyses. Genomic SEM identified 31 loci, compared to 8 for MEGA and 13 for METAL. To interpret the loci, we integrated brain molecular QTLs, predicted coding and splice consequences, and open-field locomotor phenotypes from knockouts of orthologous mouse genes. Our results highlighted established neurobehavioral candidates spanning locomotor and reward-related biology (Negr1 and Lmo4), serotonergic signaling (Htr1b), and GABAergic signaling (Gabrg2), as well as relatively novel genes including Tcerg1l, Pcdh10, and Tmem132e. Our results illustrate how Genomic SEM can integrate genetically correlated yet heterogeneous behavioral measures and enable discovery of loci underlying their shared genetic architecture, highlighting its utility for complex-trait studies in rodents.

Objective: Cognitive models of psychosis implicate maladaptive core schemas in the development and emergence of psychotic symptoms, but no study has tested temporal dynamics between schemas and psychotic symptoms in a large sample of clinical high-risk (CHR) youth. Given their sizable role in cognitive behavioral therapies, the first-line treatment for CHR youth, core schemas may be key to both symptom development and treatment in this population. Methods: Participants were 578 CHR individuals from the second North American Prodrome Longitudinal Study (NAPLS-2) assessed across five timepoints. Time-lagged mixed-effects models tested forward and reverse paths for each Brief Core Schema Scales subscale with both psychotic symptom and functioning changes, controlling for autoregressive effects, time-varying depression, and linear time. Results: Twenty of 36 schema outcome pairs showed significant prospective associations. Negative-other schemas were prospectively associated with worsening across nearly all psychosis symptom and functioning domains. Suspiciousness exhibited bidirectional associations with all four schema subscales. Grandiose ideas were uniquely prospectively associated with positive-self and negative-other schemas. Positive schemas were prospectively associated with decreases in suspiciousness, negative symptoms, and improvements in functioning. Effects were largely independent of depressive symptoms and robust across sensitivity analyses, with partial attenuation of self-schema effects on suspiciousness. Conclusions: Core schemas were prospectively associated with psychosis symptom and functioning change in CHR youth, with symptom-domain specificity and bidirectionality. These findings extend cognitive models of psychosis into CHR syndromes and highlight schemas as potentially modifiable treatment targets to improve outcomes in this population.

Attention Deficit Hyperactivity Disorder (ADHD) frequently co-occurs with distinct personality profiles, but whether ADHD shapes personality (scar model) or personality influences the development of ADHD (vulnerability model) remains unclear. Leveraging genome-wide association study (GWAS) data, we examined directional associations between ADHD and the Big Five personality traits (Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness). We estimated genetic correlations and conducted bidirectional two-sample Mendelian Randomization (MR) analyses between ADHD and the Big Five. Robustness was evaluated using multiple sensitivity tests, including MR-CAUSE, which accounts for correlated and uncorrelated pleiotropy, and colocalization analyses on fine-mapped variants. Higher genetic liability to Neuroticism and Extraversion, alongside lower liability to Conscientiousness, increased ADHD risk, consistent with the vulnerability model. Conversely, ADHD genetic liability was associated with lower Agreeableness, supporting the scar model. Associations were generally robust across sensitivity analyses, with MR-CAUSE supporting the Neuroticism and Agreeableness associations and colocalization providing variant-level support for associations between ADHD and Neuroticism, Conscientiousness, and Agreeableness. These findings provide early, population-level insight into personality-related vulnerability to ADHD and motivate further work on the role of personality traits in ADHD risk.

Genetic studies of serious mental illness (SMI, including schizophrenia and bipolar disorder) have implicated two classes of risk variant: common variants1-3, each of small effect but collectively accounting for most population-level risk, and ultra-rare coding variants4,5 which confer large risk in a small number of individuals. Most such studies cannot directly assess the impact of specific variants on SMI, transdiagnostically, as the phenotypic information that they collect is focused on a single diagnosis. Here we report results of association analysis of predicted deleterious variants from exome sequencing of 21,958 cases (SMI and severe major depressive disorder) and 19,826 controls from the Mision Origen biobank in the Paisa genetic isolate of Colombia. We identified transdiagnostic associations to seven genes, three at an exome-wide and four at a false discovery rate significance threshold. Five of these genes have not previously been implicated in SMI (ADAP1, WIPI1, NFE2L1, FBXO10, and HLA-DPB1 ); for the first four of these the association is driven by variants enriched in the Paisa due to a founder effect, filling the gap between ultra-rare and common variants. The strongest association that we observe is to a frameshift variant (7:904169:T:TC) in ADAP1 that is genome-wide significant for SMI, schizophrenia, and bipolar disorder and increases risk for both diagnoses by more than threefold; it truncates ADAP1, a brain-enriched Arf6 GTPase-activating/scaffolding protein that has been mechanistically linked to post-mitotic neuronal morphogenesis and regulation of dendritic differentiation6. Variant carriers differ significantly from other SMI cases in Mision Origen for psychotic, manic, and cognitive item-level phenotypes assessed through analyses of electronic health records7-9 and displayed impaired executive function on neurocognitive testing. Variant carriers differ significantly from other SMI cases in Mision Origen for multiple item-level phenotypes (psychotic, manic, and cognitive) assigned through natural language processing of longitudinal electronic health records. Although the 7:904169:T:TC variant is not significantly associated with major depressive disorder, carriers compared to others with this diagnosis display a significant increase in symptoms typical of bipolar disorder. The variant's high allele frequency in Mision Origen (~0.4%) will enable population-level studies to stratify SMI based on causation and identify additional factors influencing risk and resilience.