American Journal of Psychiatry

Objective: Autistic individuals may face elevated risk for PTSD, yet the degree to which this risk differs by sex remains unknown. We examined the association between autism and incident PTSD, characterized sex differences in risk, identified high-risk subgroups, and described post-diagnosis clinical trajectories. Method: We conducted a population-based matched cohort study using Swedish national registers. Individuals born 1990 through 2010 were followed from age 6 years through December 31, 2017. Autistic individuals (N=42,862) were matched 1:10 to controls (N=412,251) on sex and birth year. Cox proportional hazards regression estimated hazard ratios (HRs) for incident PTSD. Among those who developed PTSD, we compared care utilization, hospitalization rates, and persistence of care contacts. Results: During mean follow-up of 5.1 years, 401 autistic individuals (0.9%) and 903 controls (0.2%) developed PTSD (incidence rates: 18.3 vs 4.2 per 10,000 person-years). Autism was associated with 4.4-fold increased PTSD risk (HR=4.37; 95% CI, 3.93-4.86). Risk was higher among females (HR=4.79) than males (HR=3.39; P interaction=.006). Among autistic individuals, comorbid ADHD conferred additional risk (HR=1.38; 95% CI, 1.14-1.68). Ten-year cumulative incidence reached 6.0% among autistic females with ADHD. Autistic individuals with PTSD had higher care utilization (mean visits: 5.0 vs 3.9; P<.001), more psychiatric hospitalizations (27.9% vs 19.8%; P=.002), and more persistent courses (24.8% vs 12.3% with contacts in all 3 post-diagnosis years; P=.001). Conclusion: Autism is associated with substantially elevated PTSD risk, particularly among females with comorbid ADHD. When PTSD occurs, autistic individuals experience more severe and persistent clinical courses, supporting targeted screening and sustained follow-up.

ObjectiveObsessive-compulsive disorder (OCD) frequently co-occurs with bipolar disorder (BD) or schizophrenia (SCZ), and, importantly, can often precede their onset. However, the genetic architecture and directionality underlying these relationships remain unclear. We leveraged large-scale genome-wide association study (GWAS) data to examine shared genetic architecture and directional relationships among OCD, BD and SCZ, and used major depressive disorder (MDD) as a comparator. MethodsUsing linkage disequilibrium score regression (LDSC), MiXeR, and Generalized Summary-data-based Mendelian Randomization (GSMR) as well as complementary Mendelian randomization approaches, we characterized genetic correlations, polygenic overlap (Dice coefficient), and effect direction concordance ({rho}{beta}) across disorders. ResultsWe observed substantial genetic correlations between OCD and BD (rg=0.37), BD type 2 (BD2) (rg=0.54), and SCZ (rg=0.39), with a large proportion of shared causal variants between OCD and both BD (Dice=0.85) and SCZ (Dice=0.84). MiXeR analyses indicated that OCD and BD2 share a smaller proportion of causal variants (Dice=0.57) but there is a high concordance of effect directions amongst these causal variants ({rho}{beta}=0.96), whereas OCD and MDD showed minimal overlap but strong concordance among shared variants (Dice=0.09, {rho}{beta}=1). Directional GSMR and complementary TwoSampleMR analyses supported a causal effect of genetic risk to OCD on liability to BD (b=0.20, p=1.5x10{square}{square}), SCZ (b=0.52, p=9.5x10{square}{superscript 2}{superscript 1}), and MDD (b=0.24, p=1.06x10{square}{square}), with little evidence for reverse causal effects. ConclusionsTogether, these findings indicate that genetic liability to OCD can represent an early component of transdiagnostic psychiatric risk, with implications for understanding and potentially predicting the emergence of broader psychopathology across the life course.

Obsessive compulsive disorder (OCD) is significantly heritable, but only a fraction of the contributory genetic variation has been identified, and the molecular etiology involved remains obscure. Identifying rare contributory variants of large effect would be an important milestone in helping to elucidate the mechanisms involved. Analysis of densely affected pedigrees is a potentially useful strategy to bypass the sample size challenges of standard case-control approaches. Here we performed whole genome sequencing (WGS) of 25 individuals across two multiplex OCD pedigrees. We prioritised rare variants using a Bayesian inference approach which incorporates variant pathogenicity and co-segregation with OCD. In the first pedigree, we identified a highly deleterious missense variant in NPY5R, carried by the majority of affected individuals. This gene is brain-expressed and has previously been implicated in panic disorder and internet addiction GWAS studies. In the second pedigree, we identified a large deletion of DLGAP1 and a missense variant in MAPK8IP3, that perfectly co-segregated in a specific branch of the family: both genes have previously been implicated in OCD and autism. Both genes contribute to a protein interaction network including ERBB4 and RAPGEF1 which we had previously identified in a large Tourette Syndrome pedigree. Our analysis suggests that both energy homeostasis and downstream signalling from the post-synaptic density may both be important avenues for future research.

Background Major Depressive Disorder (MDD) is clinically and biologically heterogeneous. Here, we leveraged the genetics of individual depressive symptoms to dissect the disorder's underlying heterogeneity. Methods We utilized the BIObanks Netherlands Internet Collaboration (BIONIC). A series of genome-wide association studies (effective-N range: 14,407-47,110) compared controls (N=48,286) with partially different subsets of lifetime MDD cases (range: 3,892-15,577), each endorsing one of 12 individual DSM-based depressive symptoms. Results were combined in genetic correlations that informed factor analyses with Genomic Structural Equation Modeling, decomposing underlying MDD liability dimensions. The identified factors were assessed and further characterized using multivariate regression of neurodevelopmental/psychiatric and cardiometabolic traits. Results All symptoms demonstrated substantial SNP-based heritability (h2SNP:0.088-0.127). Despite high between-symptom genetic correlations, factor analyses yielded two highly correlated (rg=0.85) but still distinct latent factors: factor 1 (F1), capturing appetite/weight loss, insomnia, guilt/worthlessness, psychomotor slowing and suicidality, and factor 2 (F2), reflecting concentration problems, anhedonia, depressed mood, appetite/weight gain and fatigue. Overall, F1 had a stronger genetic overlap with neurodevelopmental/psychiatric phenotypes (e.g., autism: standardized estimate {beta}=0.45, p=4.49 x10-; schizophrenia: {beta}=0.40, p=1.73x10-), while F2 significantly overlapped with cardiometabolic traits (e.g., metabolic syndrome: {beta}=0.44, p=8.69x10-; coronary artery disease: {beta}=0.31, p=0.009). Conclusions We identified two genetic dimensions of MDD, each linked to partially distinct clinical manifestations and underlying biology, with one reflecting neurodevelopmental/psychiatric liabilities and the other capturing a strong cardiometabolic vulnerability. Disentangling such distinct dimensions may help guide patient stratification and targeted treatment, thereby advancing precision psychiatry.

Hoarding disorder (HD) affects approximately 2-3% of adults and is associated with substantial functional disability and limited access to evidence-based care. The aim of the current analysis was to examine the naturalistic effectiveness of therapist-delivered video cognitive-behavioral therapy (CBT) for HD in a large real-world sample, and to characterize individual-level treatment response, time-to-response, and moderators of outcome. This retrospective, observational analysis examined clinical data from 305 adults diagnosed with HD who received therapist-delivered video CBT through an online specialty therapy platform between September 2021 and February 2026. Hoarding symptom severity was assessed using the Hoarding Rating Scale-Self Report (HRS-SR). Linear mixed models examined symptom change from baseline to three timepoints: session 10, session 20, and each patient's final session. HRS-SR scores decreased from M = 22.4 (SD = 7.6) at baseline to M = 16.4 (SD = 8.2) at final session (Hedges' g = 0.81, 95% CI: 0.68-0.94). By the final session, median percent improvement was 25.0% [IQR: 3.0-46.7%]. A total of 39.3% of patients achieved [&ge;]35% HRS-SR reduction, 27.4% of patients who began above the clinical threshold achieved remission, 36.4% demonstrated reliable improvement, and 22.9% of eligible patients achieved clinically significant change. Among patients who achieved and maintained [&ge;]35% reduction through their final session (n = 120), median time to first response was session 9, with 54.2% responding within 10 sessions. Analyses of secondary outcomes showed significant improvements in clutter severity, depressive and anxiety symptoms, stress, quality of life, and functional disability (Hedges' g = 0.21-0.47). Greater baseline severity, more sessions, and longer treatment duration significantly moderated outcomes; prior OCD treatment history did not. Findings suggest that therapist-delivered video CBT for HD, delivered remotely in a real-world setting, produces outcomes consistent with controlled trials and may be a clinically effective and scalable approach for a condition historically underserved by mental health systems.

Objective. Persistent, distressing psychotic-like experiences (PLEs) are associated with neurobiological alterations and increased psychosis risk. We combined individual-level neuroimaging measures with effect sizes from large neuroimaging studies to create a summary score ('Psychosis Neuroscore') reflecting neuroanatomic liability for psychosis, and examined its ability to predict PLE trajectories in young adolescents. Method. Using latent growth mixture models, we estimated PLE trajectories from four annual visits of the Adolescent Brain Cognitive Development Study (N=9584, ages 9-10 at baseline). Using baseline T1-weighted and diffusion-weighted imaging data, we calculated Psychosis Neuroscores, as well as Neuroscores for two psychiatric disorders with late adolescent/adult onset (Major Depressive Disorder, Bipolar Disorder). We compared Psychosis Neuroscores to i) other psychiatric Neuroscores, ii) modifiable risk factors, and iii) established risk factors in predicting trajectory membership. Results. We identified four trajectories of distressing PLEs: Persistent Elevated (N=1,968, 21%), Gradual Decreasing (N=3,424, 36%), Rapid Decreasing (N=1,593, 17%) and Low/No Distress (N=2,599, 27%). Adolescents with Persistent Elevated PLEs had significantly higher Multimodal (combined T1 and diffusion-weighted) and T1-weighted Psychosis Neuroscores than all other trajectories (Odds Ratios [ORs] 1.27-1.34,pFDR<.01). Bipolar Disorder Neuroscores showed a similar pattern (ORs 1.16-1.23,pFDR<.01). Psychosis Neuroscores showed comparable associations with established risk factors in predicting trajectory membership, but smaller associations than modifiable risk factors, including screen time, physical activity, and sleep disturbances. Conclusion. Psychosis Neuroscores differentiate youth with persistent PLEs from those with decreasing, remitting or low PLEs, demonstrating their potential utility for early risk stratification. Integration with established risk factors may enhance psychosis risk prediction in youth.

ObjectiveTobacco and cannabis are the most used substances among individuals at clinical high risk for psychosis (CHR-P), but it remains controversial whether substance use drives symptom exacerbation and psychosis transition, or vice versa. We investigated longitudinal dose-response relationships of tobacco and cannabis use with clinical presentation in a CHR-P population. MethodsData was obtained from the North American Prodrome Longitudinal Study (NAPLS2) CHR-P cohort (n=764). Participants were assessed every 6 months over two years. Substance use frequency, psychiatric symptoms (psychosis, depression, anxiety, and social anxiety), global social and role functioning, and neurocognitive performance were measured. Linear mixed effect models were used to model the relationship between substance use and clinical measurements across visits, and that between baseline use and trajectory of symptoms, functioning, and cognition. ResultsPsychiatric symptoms, functioning, and cognitive performance improved, while tobacco and cannabis use frequency did not change over two years for CHR-P individuals in NAPLS2. Heavier tobacco and cannabis use at current visit predicted worse anxiety at next visit (tobacco: {beta}=0.178, p=0.033; cannabis: {beta}=0.162, p=0.018). Better social functioning predicted heavier tobacco ({beta}=0.178, p<0.001) and cannabis: ({beta}=0.162, p<0.001) use at next visit. We observed a significant baseline cannabis-by-time interaction, where heavier baseline cannabis use predicted slower improvement of negative symptoms ({beta}=0.159, p=0.0017, FDRp=0.0067) and deterioration of role function ({beta}=-0.046, p=0.018). ConclusionsIn CHR-R, current tobacco and cannabis use predicted worse anxiety at future visits. Baseline cannabis use frequency predicts worse clinical trajectory, especially for negative symptoms.

Tourette syndrome (TS) is a neurodevelopmental disorder characterized by symptoms that emerge in childhood and often improve or even disappear in adulthood, providing a model for understanding how altered brain development shapes neural structure and function. We investigate brain structural alterations in TS and Chronic Tic Disorders (TS/CTD) across development, presenting the largest structural neuroimaging analysis for TS/CTD to date (1,803 individuals from the ENIGMA-TS Working Group), and integrating with large-scale genomewide association studies. Nonlinear age effects were observed in cortical thickness across development and in thalamic volume in children, indicating altered trajectories of brain maturation . Pediatric and adult TS/CTD showed distinct structural patterns, with widespread alterations in childhood and more focal changes in adulthood. Children also showed the most prominent effects highlighting the involvement of orbitofrontal cortex and putamen, alongside additional regions such as frontal and paralimbic areas. Genetic pleiotropy analyses identified overlap between TS/CTD-associated genetic effects on brain structure and neuroanatomical differences. Cross-disorder comparisons revealed correlations with ADHD and OCD and age-related patterns. These findings demonstrate altered neurodevelopmental trajectories in TS/CTD and implicate systems underlying inhibitory control and urge regulation.

Polygenic risk scores (PRS) have shown increasing utility for risk stratification across complex diseases, but for psychiatric disorders such as bipolar disorder (BD), current PRS explain only a fraction of disorder liability (~1-9%), with predictive performance further diminished in non-European populations and real-world clinical cohorts. To explore the potential of integrating social and environmental risk factors alongside genetic liability to improve risk prediction, we evaluated the relationship between a PRS for BD (PRSBD) and six social risk measures - perceived stress, discrimination in medical settings, neighborhood social cohesion, perceived neighborhood disorder, cost-related medication nonadherence, and adverse childhood experiences - to BD case status in 115,275 participants (7,000 cases; 108,275 controls) from the All of Us Research Program. PRSBD was associated with BD case status across ancestry groups, though liability-scale variance explained was attenuated relative to what has been reported for curated research cohorts (R2 = 1.86% in European, 0.60% in African, 1.65% in Latino/Admixed American ancestries). Each social risk factor tested exhibited a larger effect size than PRSBD, with perceived stress (OR = 2.05 per SD) and adverse childhood experiences (OR = 2.68 for [&ge;]4 ACEs) demonstrating the strongest associations. Individuals in the lowest genetic risk decile with high social burden exhibited BD prevalence comparable to or exceeding those in the highest genetic risk decile with low social burden. These findings demonstrate the substantial explanatory power of social risk factors and support the development of integrated genetic-social risk frameworks for more accurate and equitable psychiatric risk prediction.

Alternative-splicing events (ASE) increase transcriptomic variability and play key roles in biological functions. The contribution of ASE to bipolar disorder (BD) remains largely unexplored. We performed a Transcriptome-Wide Alternative-Splicing Analysis (TWASA) to identify ASEs and genes potentially involved in BD. The study comprised 635 individuals: a discovery sample (DS) of 31 individuals from eight multiplex BD families (16 BD cases; 15 unaffected relatives), and a replication sample (RS) of 604 subjects (372 BD cases; 232 controls). Sequencing was conducted on RNA from lymphoblastoid cell lines (DS) and whole blood (RS). TWASA was performed using VAST-TOOLS (VT), rMATS (RM), and MAJIQ/MOCCASIN (MCC). Gene-set association analyses of genes containing ASEs were performed across six psychiatric disorders. Novel ASE (nASE) were investigated in the DS using FRASER. Limited gene overlap was observed across TWASA tools. MCC identified 2,031 complex ASEs involving 1,508 genes, showing the strongest genetic association with BD across psychiatric phenotypes. Prioritization of MCC-identified ASE genes yielded 441 candidates, including DOCK2 as top candidate from the DS. Replication was obtained for 98 genes, five with an identical ASE, and four (RBM26, QKI, ANKRD36, and TATDN2) showing a concordant percentage-spliced-in direction with the DS. Finally, 578 nASE were identified in the DS, with no evidence of familial segregation or differences in ASE types. This first TWASA in BD reveals tool-specific variability, complex ASE for genes specifically associated with BD, and novel candidate genes for BD. Alternative transcript isoform abundance may represent a mechanism contributing to BD pathophysiology.

Problematic Sexual Behaviour (PSB) is defined as difficult to control recurrent sexual behaviours that continue despite adverse consequences, leading to social and functional impairment. There is debate whether PSB is a disorder of compulsion or addiction; PSB often co-occurs with neuropsychiatric disorders, but further elucidation regarding underlying biology is required. A deficiency in reward neurotransmitter systems (reward deficiency syndrome: RDS) may underlie a shared vulnerability to addiction. We conducted the first case-control genome wide association study (GWAS) of PSB in patients (n=448), and comparison participants with (n=196) and without PSB (n=1488). We used polygenic risk scores (PRS) to test genetic overlap with related psychiatric, behavioural and personality phenotypes. Three models were used: 1) All-PSB (patient + comparison) vs. controls, 2) Patient-PSB vs controls, and 3) RDS (yes/no). Results suggested genetic overlap of PSB with psychiatric conditions, with PRS for major depression, substance use, and others predicting PSB status. PRS for related behavioural phenotypes (e.g., externalizing, age at first sex, number of lifetime sexual partners) and personality traits also predicted PSB. The patient model showed stronger associations than the All-PSB model, and RDS had both shared and distinct genetics with PSB. As expected with the sample size, only suggestive hits were observed with single variant and gene-based tests. PSB may share genetic mechanisms with various conditions. Further research in larger cohorts is needed to better understand the underlying genetics and environmental factors involved, and to improve diagnostic classification, intervention and treatment prospects.

ImportanceSuicide is a leading cause of death in the United States with risk strongly influenced by Interpersonal trauma, contributing to treatment resistance and clinical complexity. ObjectiveTo assess clinical and genetic factors in individuals who died from suicide, with and without interpersonal trauma exposure. DesignIndividuals who died from suicide with and without trauma were compared in a retrospective case-case design. Prevalence of 19 broad clinical categories was assessed between groups. Results directed selection of 42 clinical subcategories, and 40 polygenic scores (PGS) for further assessment. Multivariable logistic regression models, adjusted for critical covariates and multiple tests, were formulated. Models were also stratified by age group (<26yo and [&ge;]26yo), sex, and age/sex. SettingA population-based evaluation of comorbidity and polygenic scoring in two suicide death subgroups. ParticipantsA total of 8 738 Utah Suicide Mortality Research Study individuals (23.9% female, average age = 42.6 yo) who died from suicide were evaluated, divided into trauma (N = 1 091) and non-trauma exposed (N = 7 647) individuals. A subset of unrelated European genotyped individuals was also assessed in PGS analyses (Trauma N = 491; Non-trauma N = 3 233). Exposures"Trauma" is here defined as interpersonal trauma exposure, including abuse, assault, and neglect from International Classification of Disease coding. Main Outcomes and MeasuresPrevalence of comorbid clinical sub/categories and PGS enrichment in trauma versus non-trauma exposed suicide deaths. ResultsOverall, trauma-exposed individuals died from suicide earlier (mean age of 38.1 yo versus 43.3 yo; P <0.0001) and were disproportionately female (38% versus 21%, OR = 3.3, CI = 2.9-3.8). Prevalence of asphyxiation and overdose methods, prior suicidality, psychiatric diagnoses, and substance use (OR range = 1.3-3.7) were elevated in trauma exposed individuals who died from suicide. Genetic PGS were also elevated in trauma-exposed individuals who died from suicide for depression, bipolar disorder, cannabis use, PTSD, insomnia, and schizophrenia (OR range = 1.1-1.4) with ADHD and opioid use showing uniquely elevated PGS in trauma exposed males (OR range = 1.2-1.4). Conclusions and RelevanceResults demonstrated multiple convergent lines of age- and sex-specific evidence differentiating trauma-exposed from non-trauma exposed suicide death. Such findings suggest unique biological backgrounds and may refine identification and treatment of this high-risk group.

BackgroundCognitive-behavioral therapy (CBT) is a widely used treatment for mental disorders, yet the biological mechanisms underlying its effects, and the factors contributing to response, remain poorly understood. DNA methylation, an epigenetic mechanism shaped by both genetic and environmental factors, may offer insights into individual differences in psychotherapy outcomes. MethodsSaliva samples were collected before treatment, after treatment, and three months post-treatment from individuals with OCD undergoing the Bergen 4-Day Treatment (n = 889). DNA methylation was measured using the Illumina EPIC v02 array, followed by epigenome-wide DNA methylation analyses of CBT response. ResultsWe identified ten differentially methylated regions (DMRs) associated with treatment response at baseline, 23 DMRs showing consistent associations with response across multiple time points, and three DMRs displaying longitudinal methylation changes associated with response. These loci were annotated to genes with roles in neuroplasticity, stress response, immune function, mitochondrial processes, and gene regulation. Baseline and stable methylation signals were largely influenced by genetic variation, whereas all longitudinal associations appeared to be confounded by psychoactive medication use and psychiatric comorbidities. In addition, changes in monocyte and CD4+T cell proportions were associated with treatment response. ConclusionsWe identified DNA methylation markers associated with CBT response in OCD at baseline. Stable methylation patterns associated with treatment response are likely driven by genetic factors. Longitudinal methylation analyses should be interpreted cautiously, as medication and comorbidities can exert substantial effects - even when they remain unchanged over time. Baseline methylation profiles may ultimately help predict treatment outcomes, thereby advancing precision psychiatry.

Suicidality phenotypes, including suicidal ideation (SI), non-fatal suicide attempt (SA), and suicide death (SD), are heritable and exhibit both shared and phenotype-specific genetic influences. Using genomic structural equation modelling, we estimated the shared genetic architecture across GWAS of SI (176,147 cases, 1,010,300 controls), SA (53,919 cases, 1,063,988 controls), and SD (7,584 cases, 652,070 controls) and conducted a multivariate GWAS of a latent suicidality factor capturing their shared liability. This analysis identified 36 genome-wide significant loci, including seven not previously reported in any suicidality GWAS. Follow-up analyses identified residual genetic variance specific to each phenotype, including three SD-specific genomic risk loci. Conditioning suicidality phenotypes on genetic liability to psychiatric disorders revealed significant residual genetic variance across SI, SA, SD, and the suicidality common factor. Together, these results suggest that suicidality reflects both shared genetic liability and phenotype-specific contributions.

Background: Schizophrenia, bipolar disorder, and depression share substantial genetic liability. However, the molecular mechanisms underlying this shared architecture remain poorly characterized. In particular, the role of circulating proteins as potential mediators and therapeutic targets is not well understood. Methods: Based on large-scale genome-wide association studies, we constructed a latent psychiatric common factor using genomic structural equation modeling. We then performed proteome-wide Mendelian randomization to estimate the associations between circulating proteins and this shared liability, based on four independent proteomic cohorts. Protein-psychiatric common factor associations were prioritized through comprehensive sensitivity analyses and colocalization. We additionally performed tissue- and single-cell expression enrichment analyses and a systematic druggability assessment. Results: We identified 36 circulating proteins with evidence of association with the psychiatric common factor that withstood multiple sensitivity analyses. Several proteins showed distinct tissue-specific expression patterns, with enrichment in brain, immune, or liver tissues, highlighting convergent neuroimmune and systemic pathways. For instance, genetically predicted higher levels of MAPK3, FES, MRE11A, HS6ST3, OLFM1, BTN3A1, BTN3A2 and BTN3A3 were associated with increased psychiatric risk, whereas higher levels of CD40, ITIH3, and ITIH4 were associated with decreased risk. Druggability assessment identified CD40, MAPK3, FES, MRE11A and BTN3A1 as established or potential therapeutic targets. Conclusions: By integrating genetic, proteomic, and transcriptomic data, this study identifies circulating proteins that associated with the shared genetic effects on three major psychiatric disorders. These findings provide biologically grounded candidates for therapeutic targeting and offer insights into shared disease mechanisms.

Individuals at clinical high risk for psychosis (CHR) are cognitively and neurobiologically heterogeneous, which encourages the use of a clustering approach to parse this heterogeneity. Multimodal approaches are assumed to be superior to unimodal approaches in identifying subgroups. With the success of the use of cognition and electrophysiological measures collectively in established psychotic disorders, and the lack of such an approach in CHR, we were motivated to address this gap. Using the North American Psychosis-Risk Longitudinal Study (NAPLS) 2 consortia (CHR (N=764)), we applied unsupervised cluster analysis on the combined cognitive and electrophysiology measures to identify CHR subgroups and assess their relationship with clinical and functional outcomes. A two-cluster solution with modest separability was found, which prompted the use of an alternative probabilistic, rather than discrete, clustering approach. Individuals who were more likely to be in Cluster 1 exhibited poorer cognitive performance, larger N100, mismatch negativity, and P300 amplitudes, and worse functioning, as well as a younger age of onset. These findings were largely replicated in NAPLS 3 (CHR (N=628)). Taken together, the results of our previous study of cognition-only clustering and the current study of combining cognition and electrophysiology indicate that multimodal clustering, if not developmentally informed, may obscure meaningful subtyping.

BackgroundA central goal in psychiatry is to move from symptom-defined diagnoses toward biologically interpretable and reliable phenotypes. In cocaine use disorder (CUD), many resting-state abnormalities have been reported, but few circuit-level findings have been explicitly screened for reliability. We tested whether prespecified thalamocortical features yield a reproducible phenotype in CUD and whether that phenotype reflects diagnosis, recent cocaine use, or longer-term illness history. MethodsDiscovery analyses used resting-state data from 105 participants (46 healthy controls, 59 CUD). From a 13-region thalamocortical circuit, we derived an HC-trained LEiDA state model, generated 11 prespecified features, and advanced only those meeting split-half reliability criteria (ICC[3,1] [&ge;]0.40). A separate paired TMS sample (n=44) was used for extension analyses. ResultsFive features survived reliability screening. Within CUD, longer duration since beginning cocaine use was associated with greater occupancy of a control-like state (standardized {beta}=0.37, q=0.005) and stronger whole-thalamus connectivity with control frontoparietal cortex (standardized {beta}=0.30, q=0.018). Neither days since last use nor CUD vs. healthy diagnosis were associated with any reliable feature after correction. Joint-history models indicated that the signal was better explained by longer-term use history than by recent use. Localization analyses indicated the connectivity effect was concentrated in dorsal thalamic regions. TMS-interaction and effective-connectivity follow-ups were null. ConclusionsReliability screening identified a thalamocortical control-network phenotype in CUD that tracks longer cocaine-use history rather than diagnosis or recent use. More broadly, this workflow offers a practical framework for screening candidate circuit-level psychiatric phenotypes for reliability.

Stimulant use disorder (StimUD) is a significant public health problem, but genetic studies have been limited by small sample sizes. We conducted genome-wide association studies (GWAS) of StimUD in the Million Veteran Program (MVP) and All of Us (AOU), followed by meta-analysis with FinnGen and 10 additional datasets, for a total of 709,369 individuals (Ncases=33,977, Ncontrols=675,392) in four broad ancestry groups: European (EUR) (Ncases=22,564, Ncontrols=624,672), African (AFR) (Ncases=7,574, Ncontrols=34,189), Admixed American (AMR) (Ncases=3,657, Ncontrols=15,698), and East Asian (EAS) (Ncases=182, Ncontrols=833). Population-specific SNP heritability was 6.1% in EUR and 2.4% in AFR. We discovered a total of 19 genome-wide-significant loci, six in EUR, including DRD2*rs5794864, P=7.32E-10, one in AFR, five in a multi-ancestry meta-analysis, including CHRNA5*rs55781567, P=3.27E-9, two in a male-only meta-analysis, including FTO*rs8057044, P=9.50E10-9, and five in a meta-analysis of sex-stratified results. In a hold-out AOU subsample (NEUR=18,841, NAFR=12,263, NAMR=9,739), ancestry-specific polygenic risk scores were significantly associated with StimUD in EUR (OR=3.28, 95% confidence interval (CI)=2.89-3.71) and AMR (OR=2.01, 95% CI=1.71-2.37). Transcriptome-wide association studies, fine-mapping, and colocalization analyses prioritized additional genes (e.g., GPX1, BSN). Genetic correlation, Mendelian randomization, and causal mixture analyses revealed relationships with other substance use and use disorder phenotypes, including cannabis use disorder (rg=0.94, P=5.43E-237) and opioid use disorder (rg=1.01, P=4.40E-107), and other psychiatric traits, including anxiety, depression, neuroticism, and attention-deficit/hyperactivity disorder. This is the first well-powered GWAS of StimUD, and it offers significant insights into disease biology.

ImportanceBlood neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) are entering clinical use in neurology as markers of neuroaxonal and astrocytic injury, but their utility in psychiatry is unclear. ObjectiveTo determine whether psychiatric diagnoses are associated with altered plasma NfL and GFAP levels. Design, Setting, and ParticipantsThis population-based study examined plasma NfL and GFAP among 47,495 participants from the UK Biobank (54.0% female; 93.5% White; mean [SD] age 56.8 [8.2] years) who provided blood samples and sociodemographic and clinical data between 2006 and 2010. Normative modeling was applied to assess associations between 7 lifetime psychiatric diagnostic categories and deviations from expected NfL and GFAP levels, while accounting for neurological diagnoses, cardiometabolic burden, and substance use. Data were analyzed between July 2025 and March 2026. Main Outcomes and MeasuresDeviations in plasma NfL and GFAP levels from normative predictions. ResultsRelative to the reference population, plasma NfL levels were higher among individuals with bipolar disorder (d=0.20; 95% CI, 0.03-0.37; p=0.03), recurrent depressive disorder (d=0.23; 95% CI, 0.07-0.38; p=0.009), and depressive episodes (d=0.06; 95% CI, 0.02-0.10; p=0.01), lower among individuals with anxiety disorders (d=-0.07; 95% CI, -0.12 to -0.02; p=0.008), but did not differ in schizophrenia spectrum, stress-related, or other psychiatric disorders. Plasma GFAP levels were not elevated in any psychiatric disorders. Variability in NfL levels was greater among individuals with schizophrenia spectrum disorders (variance ratio [VR]=1.30; p=0.005), depressive episodes (VR=1.06; p=0.006), and anxiety disorders (VR=1.08; p=0.005). Variability in GFAP levels was increased only in anxiety disorders (VR=1.08; p=0.01). Plasma NfL levels exceeding percentile-based normative thresholds were more common among individuals with schizophrenia spectrum disorders, bipolar disorder, recurrent depressive disorder, and depressive episodes. Neurological diagnoses, cardiometabolic burden, and substance use were associated with plasma NfL and GFAP levels. Conclusions and RelevanceThis study provides population-level evidence of plasma NfL elevation in bipolar and depressive disorders and increased variability in schizophrenia spectrum, bipolar and depressive disorders, supporting its potential as a biomarker in psychiatry and informing its ongoing neurological applications. Plasma GFAP levels, in contrast, were largely unaltered across psychiatric disorders. Key PointsO_ST_ABSQuestionC_ST_ABSAre plasma neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) levels altered in psychiatric disorders? FindingsIn this cohort study including 47,495 individuals, normative modeling revealed that plasma NfL levels were elevated in bipolar and depressive disorders, whereas plasma GFAP levels were not elevated in any psychiatric disorder. Plasma NfL levels also showed higher variability in schizophrenia spectrum, bipolar, and depressive disorders. MeaningPlasma NfL shows distinct alterations in schizophrenia spectrum and affective disorders, supporting its further investigation as a biomarker in clinical psychiatry and highlighting the need to consider psychiatric comorbidity in neurological applications.

Substance use disorders run in families, yet the mechanisms underlying intergenerational transmission remain unclear. We investigated indirect genetic effects, pathways through which parental genotypes influence offspring phenotypes via the family environment, for alcohol use disorder (AUD), nicotine dependence (ND), and related quantitative outcomes, and aimed to identify family environmental factors through which such effects may operate. Using transmitted and non-transmitted polygenic scores (PGS) constructed for problematic alcohol use, tobacco use disorder, and general addiction liability, we analyzed 5972 European-ancestry adult offspring with at least one genotyped parent from the population-based Lifelines cohort (Netherlands). Offspring outcomes included lifetime DSM-5 AUD diagnosis, AUD symptom count, maximum drinks in 24 hours, Fagerstrom Test for Nicotine Dependence score, and cigarettes per day. AUD findings were meta-analyzed with data from the Brisbane Longitudinal Twin Study (N = 1368; Australia). We also examined parent-of-origin effects and mediation by parental substance use and socioeconomic status using structural equation modeling. Transmitted PGS robustly predicted all AUD and ND outcomes ({beta} = 0.07-0.16; OR = 1.20 for AUD diagnosis). Non-transmitted PGS, indexing indirect genetic effects, were negligible for all clinical syndrome outcomes. The only significant indirect genetic effect was on cigarettes per day ({beta} = 0.03, p = 0.01), mediated by parental smoking behavior but not socioeconomic status. These findings indicate that intergenerational transmission of risk for AUD and ND is driven primarily by direct genetic effects, with modest indirect genetic effects on smoking quantity. Larger samples and cross-trait analyses are needed to further elucidate these mechanisms.