The British Journal of Psychiatry

Background: A comprehensive overview of how premature mortality in severe mental illness varies by socioeconomic position and healthcare utilization is lacking. Methods: We followed all Norwegian residents aged 30-79 years on January 1, 2008, through December 31, 2023. Nationwide registry linkage provided data on mental illness in primary and specialist care, educational attainment, and cause of death. We estimated the mortality gap as excess life-years lost from age 30 for depression, bipolar disorder, and schizophrenia compared with the general population, stratified by sex, healthcare utilization, and educational attainment. All-cause, external-cause, and natural cause mortality were assessed using competing risks. Results: The cohort comprised 2,486,836 individuals, including 483,933 with depression, 40,125 with bipolar disorder, and 21,963 with schizophrenia. Among men, the mortality gap ranged from 1.50 year (95% CI 0.36-3.34) among those with depression, non-inpatient care utilization, and university education to 19.86 years (18.34-21.36) among those with schizophrenia, inpatient care utilization, and less than high school education. Among women, the corresponding range was no gap to 18.16 years (17.03-19.53). Mortality gaps were generally larger with lower educational attainment and inpatient care utilization and increased from depression to bipolar disorder to schizophrenia. This pattern was consistent across sexes, diagnoses, healthcare utilization levels, and educational attainment levels and was most pronounced for natural-cause mortality. Conclusions: Premature mortality among people with severe mental illness forms a continuum across socioeconomic disadvantage, healthcare utilization, and diagnosis. Combining these measures can identify subgroups with the greatest mortality burden and may help target preventive interventions.

Brain-imaging models predicting psychiatric outcomes are rarely tested where they would be used. Clinical high risk for psychosis is a demanding test case because services differ in whom they recruit and how they record transition. We re-estimated a published structural magnetic resonance imaging (MRI) risk model and applied it unchanged to four independent cohorts (685 participants, 106 transitions). Discrimination was weak (area under the curve, 0.56) and near chance in the two cohorts not previously used to evaluate the model (0.53 and 0.56). Predicted risks did not transfer (calibration slope, 0.17). Exploratory performance landscapes, which map local discrimination across participant characteristics, showed that discrimination varied with negative-symptom severity, also in external cohorts, whereas apparent age- and brain-age-related variation depended on single cohorts; no global test survived multiple-testing correction. Reporting where a model works, not only its average accuracy, can reveal when one diagnostic label hides several prediction problems.

Early detection of individuals at clinical high risk for psychosis (CHR-P) improves access to preventive care. We developed and internally validated the E-DetectioN Tool for Emerging mental disoRders (ENTER), a multimodal digital screener designed to improve community identification of CHR-P compared with an established approach (PQ-16 cut-off). Participants aged 12-35 years from the UK and Italy completed the online ENTER screener, assessing attenuated psychotic symptoms, processing speed and environmental risk factors. Participants above the PQ-16 cut-off and a random subset below were assessed with the Comprehensive Assessment of At Risk Mental States (CAARMS). PQ-16 cut-off and ENTER models were developed using (penalised) logistic regression, random forest and extreme gradient boosting (XGBoost) within a repeated nested cross-validation framework with semi-supervised learning incorporating unlabelled data. Models were evaluated by discrimination, calibration and clinical utility. 2,522 participants completed the ENTER screener. 495 underwent CAARMS assessments. 124 (25.1%) met CHR-P criteria; 2,027 participants were not assessed with the CAARMS (unlabelled). ENTER showed improved discrimination (C=0.744, 95%CI: 0.697-0.790) compared to the PQ-16 cut-off (C=0.625, 95%CI: 0.570-0.682, p=0.003) and similar calibration (ENTER: slope=1.02, 95%CI: 0.78-1.32; PQ-16 cut-off: slope=0.39, 95%CI: 0.19-0.52, p=0.074). At a clinically relevant threshold, ENTER identified approximately 2 additional CHR-P individuals per 100 assessments compared with the PQ-16 cut-off. Compared with established PQ-16 cut-off pre-screening, ENTER showed higher performance for community identification of CHR-P individuals. Multimodal digital screening might support more informative community triage before specialist assessment. External validation and implementation studies are required to establish real-world clinical utility.

Background. Population-representative evidence on social inequalities in youth mental health from an intersectional perspective is limited. We investigated inequalities across multiple mental health outcomes among young adults and examined whether measures operated equivalently across social and intersectional groups. Methods. Cross-sectional analyses were conducted with 9,675 participants aged 23 years from the nationally representative UK Millennium Cohort Study (born 2000-2002). Self-reported outcomes included psychological distress (Kessler-6), probable serious psychological distress/'caseness' (Kessler-6 score [≥]13), psychological wellbeing (Short Warwick-Edinburgh Mental Well-Being Scale; SWEMWBS), past-year self-harm, and lifetime suicide attempts. Measurement invariance analyses assessed comparability of the Kessler-6 and SWEMWBS across groups. Intersectional MAIHDA examined inequalities by sex assigned at birth, ethnic identity/background, sexual identity, and childhood poverty. Young people with lived experience of mental ill-health and/or social discrimination contributed to study design, interpretation, and reporting. Findings. Large inequalities were observed across all outcomes, with the largest disparities by sexual identity, followed by sex assigned at birth, childhood poverty history, and ethnic identity/background. Across intersectional strata, predicted psychological distress ranged from -0.27 to 1.32 SDs, and psychological wellbeing from -0.54 to 0.11 SDs. Predicted prevalence varied 6.99-fold (9.81% to 68.55%) for psychological distress 'caseness', 6.84-fold (8.60% to 58.79%) for self-harm, and 22.10-fold (1.96% to 43.32%) for suicide attempts. Young people at the intersection of sexual minority status, female birth sex, childhood poverty, and some ethnic minority identities/backgrounds experienced particularly poor outcomes. Most inequalities showed cumulative patterns consistent with additive expectations, although some intersectional groups experienced better or worse outcomes than expected. Accounting for measurement differences revealed inequalities that were otherwise undetected. Interpretation. Findings highlight the large extent of mental health inequalities when multiple dimensions of social (dis)advantage are considered, and the need to address both the social conditions generating these inequalities and the methodological assumptions shaping how they are measured and understood.

Those leaving military service frequently present with complex psychosocial problems, but military veterans are often reluctant to engage with statutory healthcare provision. Specialist mental health services have recently been established in the UK to specifically support military veterans with their psychological and social wellbeing. We explored the treatment and support provided by the London branch of a military veterans mental health and wellbeing service (Op COURAGE) from the perspectives of the multidisciplinary service team and their partner organisations and collaborators. We conducted semi-structured interviews with multidisciplinary service staff and members of their partner organisations and external agencies. Qualitative data were analysed using framework analysis.?A total of 16 professionals participated in this study, comprising five service staff, eight collaborators and three partner agency participants. Five themes with subthemes were identified, including (1) blended networks, (2) staff inclusivity and sensitivity, (3) spectrum of psychosocial interventions and holistic support, (4) referral mechanisms, and (5) (in)visibility of the service and advertising. Our evaluation highlighted the advantages of a multidisciplinary team and collaborative partnerships to meet the psychosocial needs of veteran and their significant others. We have proposed that service improvement could include increasing advertisement about this specialist service, deepening knowledge about veterans among staff and further involving veterans and key stakeholders in service decisions.

Background: Autistic people experience substantially higher rates of mental health conditions and are overrepresented in mental health services. However, most interventions and service models have been developed for non-autistic people, and evidence is needed as to whether there are disparities in outcomes. This systematic review aimed to compare outcomes between autistic and non-autistic people receiving the same mental health interventions or services. Methods: We conducted a systematic review following PRISMA guidelines (PROSPERO: CRD420251021068). We searched academic databases (MEDLINE, Embase, PsycINFO, PubMed, CINAHL), a grey literature database (HMIC), a trial registry (ISRCTN), preprint servers (medRxiv and PsyArXiv), Google, and Google Scholar, to identify relevant papers published 01/01/1992-30/04/2026. We conducted backwards and forwards citation searching and contacted experts. Study quality was assessed using a modified Critical Appraisal Skills Programme Cohort Study Checklist and the Autism-Inclusive Research Assessment (AIRA). Data were synthesised narratively, with random effects meta-analyses where appropriate. Results: Thirty-nine studies were included, comprising 4787730 participants, assessing outcomes of psychological therapies (n = 17) and multi-component or service-level approaches (n = 22). Nearly half (46.2%) were UK-based, and under a quarter (23.1%) included people with intellectual disabilities. Ten studies (25.6%) were rated low quality, twenty-two (56.4%) medium quality, and seven (17.9%) high quality. AIRA ratings highlighted concerns about research inclusiveness for autistic people, including limited involvement of autistic people and lack of validated or adapted outcome measures. Findings varied by intervention: for some, multiple large, higher-quality studies showed less favourable outcomes for autistic people (e.g., less improvement in symptoms or functioning, or higher rates of restrictive practices or acute service use). For other interventions, comparable or mixed outcomes were found across studies, with interpretation often limited by small samples. Conclusions: Mental health treatment outcomes for autistic versus non-autistic people varied across interventions and outcome types. Where significant differences were observed, these usually showed poorer outcomes for autistic people, although they generally reflected smaller improvements rather than a lack of benefit. Action is needed to improve the accessibility and appropriateness of mental health care for autistic people, supported by more high-quality, co-produced research across a broader range of countries and service contexts.

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.

BackgroundPsychotic-like experiences (PLEs) have been shown to increase the risk for mental health problems in later life, especially psychosis. Following previously raised methodological concerns about the assessment of PLEs in adolescents, this study sought to differentiate subtypes of PLEs and to explore their trajectories. MethodsLongitudinally matched data of 671 German adolescents from three surveys over the time span of one year were analysed. Four trajectories were identified, including persisting, subsiding, and emerging highly indicative PLEs (HIPs), and non-highly indicative PLEs (non-HIPs), and longitudinally compared in terms of associated distress, psychopathology, and substance use. A differentiated never PLEs group was considered as a control. ResultsThe persisting HIPs group reported greater distress than the non-HIP group over time and was consistently associated with higher rates of internalising symptoms. The subsiding HIP group showed significant reductions in distress and internalising symptoms over time, but no significant changes regarding externalising symptoms and substance use. There was no difference in the extent of substance use between the groups. ConclusionsScreenings of PLEs should be mindful of different subtypes of PLEs that indicate a greater associated risk of poor mental health. PLE screening should not stop at whether PLEs are present but ask which ones.

Background: Risk of recurrent overdose is elevated following non-fatal overdose (NFOD) survival; timely interventions may reduce this risk. The specific role of mental health care in reducing recurrence is relatively underexplored, and post-overdose care has seldom been examined for sex differences. This study examined sex differences in the association between mental health-related primary care contacts following NFOD and overdose recurrence risk among people in British Columbia (BC) with a documented depression diagnosis history. Methods: This was a nested case-control study using linked administrative health data from the Provincial Health Services Authority Platform for Analytics and Data. The source cohort (n=7,022) comprised BC residents with a history of a documented depression diagnosis between 2010-2014 and at least one NFOD between 2015-2024. Cases experienced a recurrent overdose within one year of their index overdose; controls were selected using incidence density sampling. Exposures were the presence and number of mental health related primary care contacts in the 30- or 90-day window following the index overdose. Conditional logistic regression models were used to estimate adjusted incidence rate ratios (aIRRs) and confidence intervals (CI), overall and by sex. Secondary analyses were conducted using psychiatrist contacts. Results: Mental-health related primary care contact rates were low, with only 16.3% and 28.1% of the cohort with any contact within 30 and 90 days, respectively. Mental health-related primary care contacts were more strongly associated with reduced recurrence risk in the 30-day window (any contact aIRR: 0.57 [CI: 0.46-0.71]) than in the 90-day window (aIRR: 0.78 [CI: 0.65-0.94]). Any contact within 30 days was more strongly associated with lower recurrence risk among males (aIRR: 0.53 [CI: 0.39-0.72]) than among females (aIRR: 0.67 [CI: 0.50-0.91]), whereas associations between the number of contacts and recurrence risk were similar for males and females. Any psychiatrist contact within 30 days was more strongly associated with lower recurrence risk among females (aIRR: 0.50 [CI: 0.34-0.73]) than males (aIRR: 0.70 [0.52-0.95]). Discussion: Mental health-related care contacts shortly following NFOD were associated with lower overdose recurrence risk among people with a documented depression diagnosis history, with modest sex differences that varied by provider type. Low rates of contacts overall suggest gaps in access to care following NFOD, particularly among males. Further research on sex differences in post-overdose care are warranted.

Background: Alcohol use disorder (AUD) is associated with increased dementia risk, but its long-term relationship with dementia, variation by age and subtype, and how this risk compares with that associated with alcohol consumption remain poorly characterised. We investigated these questions in a large prospective cohort of UK women. Methods: We analysed Million Women Study participants recruited aged 50-64 years and followed for more than 20 years through linked health records. Women with hospital-recorded AUD were matched to up to five controls. Cox models estimated associations between time-varying AUD and incident dementia overall, by subtype and attained age, with exposure lags of up to 15 years and competing-risk analyses. Self-reported alcohol consumption was analysed separately. Findings: Among 1,288,359 women, 20,070 with AUD were matched to 100,339 controls. Dementia occurred in 3,774 women with AUD and 8,239 matched controls. AUD was associated with all-cause dementia (HR=3.73 [95% CI 3.52-3.95]), with strongest associations for mixed (5.03 [3.88-6.51]), unspecified (4.29 [3.92-4.70]), and vascular dementia (3.96 [3.44-4.56]). Associations were substantially stronger before age 70 years (10.68 [9.02-12.63]) than at ages 70-79 years (3.75 [3.47-4.04]) or 80 years or older (2.34 [2.11-2.60]). Risk remained elevated with a 15-year lag (2.16 [1.81-2.58]) and after accounting for competing mortality. Associations with self-reported alcohol consumption were substantially weaker. Interpretation: Clinically recognised AUD identifies women at markedly increased and prolonged dementia risk, particularly at younger ages and for vascular and mixed dementia, not captured by drinking quantity alone. People with AUD should be considered a priority population for earlier dementia prevention and risk reduction. Funding: Wellcome Trust Career Development Award to AT (306069/Z/23/Z); NIH grants P50AA012870 and R01DA054869 (JG). The Million Women Study is supported by the UK Medical Research Council (grant number UKRI1464).

Background People diagnosed with severe mental illnesses (SMI) including bipolar disorder, schizophrenia and psychosis are disproportionately exposed to adverse social determinants of health, contributing to premature morbidity and mortality. Social prescribing aims to address social risk factors for poor health by linking patients in primary care to community activities. However, whether people with SMI access social prescribing through primary care remains unexplored. Aims To describe prevalence of, and sociodemographic characteristics associated with, social prescribing consultations in patients with SMI in primary care. Methods Using the UK Clinical Practice Research Datalink, we identified patients aged 18+ with a diagnosis of SMI between 2004-2019. We calculated the percentage of patients with SMI who received a social prescribing consultation between 2019-2023 and used logistic regression to examine associations between sociodemographic, health-related factors and social prescribing consultations and refusals. We used fixed effects analysis to determine whether a new diagnosis of SMI made between 2019-2023 was associated with an increased odds of receiving a social prescribing consultation. Results Among 112,334 patients with SMI, 0.8% received a social prescribing consultation in 2019 increasing to 9.5% in 2023. Between 2020-2023, older age (OR=1.18-2.34), being female (OR=1.16-1.31) and living in more deprived areas (OR=1.14-1.49) were associated with higher odds of receiving a social prescribing consultation amongst patients with SMI. Across all years, patients with SMI and depression (OR=1.32-1.92), diabetes (OR=1.19-1.35) or obesity (OR=1.17-1.54) also had increased odds. In 140,514 patients with time-varying SMI status, a new diagnosis of SMI was associated with higher odds of receiving a social prescribing consultation (OR=1.39, 95% CI 1.26-1.53). Conclusion Since 2019, social prescribing consultations among patients with SMI in primary care have increased and are reaching those in areas of higher deprivation and with greater health needs. Strategies to remove barriers to consultations among younger adults and males are still needed

Background: Cognitive impairment is a major determinant of functional outcome in psychotic disorders, yet the contribution of psychotropic medication is incompletely understood. This study aimed to determine whether personalised receptor-engagement profiles derived from prescribed psychotropic medications are associated with cognitive performance in individuals with psychotic disorders. Methods: We performed a cross-sectional study using clinical, cognitive, and medication data from the Bipolar-Schizophrenia Network on Intermediate Phenotypes studies. In 1,067 (51.5% female) individuals with psychotic disorders, we estimated personalised receptor-engagement profiles based on the prescribed dose and known pharmacological properties of 49 psychotropic medications across 32 drug targets. Correlated receptor-target modulation profiles were summarized into seven pharmacological clusters. Extreme gradient boosting models were trained using repeated nested cross-validation, with the contribution of pharmacological profiles to predicted cognition quantified using out-of-sample SHapley Additive exPlanations (SHAP) values. Overall pharmacological contribution was tested using within-diagnosis permutation testing. Results: Estimated receptor-engagement profiles were significantly associated with cognitive performance independent of diagnosis. A receptor profile involving alpha2-adrenergic, dopaminergic (DRD4, DRD5) and several serotonergic receptors was associated with poorer cognitive performance, whereas dopamine transporter (SLC6A3) engagement was associated with better cognitive performance. Muscarinic receptor modulation was additionally associated with poorer verbal memory and motor speed, while the DRD2-containing receptor profile was not associated with cognitive performance after correction for multiple testing. Conclusions: Modelling psychotropic medications according to receptor pharmacology identified receptor-engagement profiles associated with cognitive performance in psychotic disorders. This framework may help identify receptor systems for future investigation as potential targets for cognition-enhancing therapies and support the development of personalised prescribing strategies.

**Importance** Average gray matter volume (GMV) loss in early psychosis may conceal clinically relevant differences in brain change. **Objective** To identify longitudinal GMV-change patterns, their cross-site correspondence, and clinical associations. **Design, Setting, and Participants** Prospective cohort with T1-weighted MRI acquired during 2011-2026 at 2 Czech sites; median follow-up, approximately 13 months. Participants were 222 patients with first-episode schizophrenia-spectrum psychosis and 178 healthy controls frequency-matched by site and baseline age. **Exposure** First-episode psychosis vs healthy control status. **Main Outcomes and Measures** Diagnosis-blind clustering by site of image-quality-corrected, subsequently annualized GMV change across 333 cortical parcels; longitudinal voxel-based morphometry (VBM); Global Assessment of Functioning and consensus 5-factor Positive and Negative Syndrome Scale negative-symptom scores. **Results** Among 400 participants (mean [SD] age, 28.2 [7.5] years), 208 (52.0%) were male. Each site independently yielded 3 clusters: C1 (near-stable GMV), C2 (pronounced decrease), and C3 (increase). Cross-site centroid correlations across 333 parcels were strong for C2 and C3 (Spearman rho = 0.865 and 0.861); C1 correlation was weak (rho = 0.138), as expected for near-zero profiles with little regional variation. C2/C3 correspondence supported pooling matched site-specific clusters for post hoc analyses. Pooled clusters contained 77 patients and 125 controls in C1, 66 patients and 16 controls in C2, and 79 patients and 37 controls in C3. Suffixes -P and -HC identify patient and control subgroups. To situate patient changes relative to controls, post hoc VBM revealed an unanticipated gradient of increasingly pronounced GMV reduction across C1-HC to C1-P to C2-P, prominently involving association cortex, and bilateral ventral temporal GMV increase in C3-P (familywise error-corrected P < .05). The opposite contrast along this ordering showed periventricular changes consistent with progressively greater ventricular enlargement. C2-P had the lowest mean follow-up functioning and highest mean negative-symptom severity (adjusted omnibus P = .005 and .02); clinical changes from baseline did not differ significantly among patient groups. **Conclusions and Relevance** Early GMV change in psychosis was not uniform but comprised two contrasting directions: a clinically relevant, control-anchored pattern of increasingly pronounced GMV loss involving default mode regions and a distinct, directionally opposing ventral temporal increase.

Background Diabetes is common in people with bipolar disorder, particularly men. Both type 2 diabetes and bipolar disorder are associated with evening chronotype, and men of working-age have later chronotypes than women. However, it is not known whether elevated rates of diabetes in bipolar are explained by evening chronotype, nor whether sex differences in chronotype contribute to higher rates of diabetes observed in men with bipolar disorder. Aim To determine whether evening chronotype increases the likelihood of comorbid type 2 diabetes in bipolar disorder, relative to those with no mental health problems. Additionally, to determine whether any effect differs between men and women. Methods Using data from the Our Future Health cohort, we estimated odds ratios for type 2 diabetes by bipolar disorder diagnosis, chronotype, and their interaction, adjusting for relevant covariates. Results A total of 1,136,694 participants (N = 6,846 with bipolar disorder) were included in the adjusted models. Type 2 diabetes was independently associated with bipolar disorder and evening chronotype. There were no significant differences in the interaction effects of chronotype on the odds of type 2 diabetes in bipolar across the whole sample or when stratified by sex. Conclusions The high prevalence of type 2 diabetes in people (and in men, specifically) with bipolar disorder may be independent of evening chronotype.

Background: Schizophrenia Spectrum Disorders (SSD) is associated with spatially heterogeneous structural abnormalities across distributed brain systems, but the longitudinal evolution and neurochemical context of subcortical subregional changes remain poorly understood. We investigated longitudinal volume changes across thalamic, hippocampal, amygdalar, and brainstem subregions and their relationships with clinical characteristics and normative neurotransmitter distribution. Methods: A total of 357 SSD individuals with first-episode and 196 healthy controls were included. Clinical assessments were performed at baseline and at 1, 3, 5, 10, 15, and 20 years of follow-up. Using T1-weighted structural MRI, subregional volumes were quantified across the thalamus, hippocampus, amygdala, and brainstem. We examined baseline group differences, longitudinal volume changes, and associations with clinical variables, including symptom severity. Spatial patterns of regional associations were compared with normative maps of neurotransmitter receptor and transporter distributions. Results: Patients showed heterogeneous structural alterations across the examined subcortical subregions. The hippocampus showed prominent early volume deficits in specific subfields and demonstrated a strong association with antipsychotic medication doses. Amygdalar volumetric reductions were more widespread and were strongly associated with positive symptom severity. Localised structural abnormalities were also observed in the thalamus and brainstem, although these showed weak associations with clinical symptomatology. The spatial co-location of normative neurotransmitter maps with the structural and clinical associations revealed distinct overlapping with dopaminergic, GABAergic, glutamatergic, serotonergic and cholinergic systems. Conclusions: Longitudinal structural alterations in SSD showed marked anatomical heterogeneity across thalamic, limbic, and brainstem systems. Their spatial correspondence with normative neurochemical architecture suggests that regional and subregional structural vulnerability and clinical heterogeneity may be organized along distinct, partially overlapping neurotransmitter profiles.

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.

Importance. Suicide is a leading cause of mortality, yet its prevention remains a challenge. Suicide attempters exhibit disrupted decision-making, but the specific cognitive processes driving this impairment and their utility for risk stratification are unclear. Objective. To determine which computational decision-making mechanisms are disrupted in high-risk suicide attempters, and whether they distinguish attempters from depressed and healthy controls. Design. This cross-sectional study fit reinforcement-learning models to Iowa Gambling Task performance across two independent studies: SPAD (August 2017 to May 2020); SUICIDE-DECIDE (March 2021 to September 2023). Data was analyzed between January 2025 and July 2026. Setting. SPAD was conducted in Nimes (France). SUICIDE-DECIDE was a muticenter study across Jena (Germany) and Nimes. Clinical groups were recruited from academic inpatient psychiatry units and outpatient clinics, and healthy controls through local advertisement. Participants. SPAD included adults aged 60 years or older; SUICIDE-DECIDE middle-aged adults stratified by attempt means (violent/nonviolent). Consecutive participants were recruited into three groups: suicide attempters, patient controls, healthy controls. Main outcomes and measures. The primary outcomes were group differences on parameters reflecting learning from rewards and losses, sensitivity to win frequency, choice perseverance, and forgetting of past choices. We trained a multinomial logistic regression model in the SUICIDE-DECIDE study using self-reported depression and parameters that differentiated attempters from controls across studies, and evaluated its performance in the SPAD sample. Results. SPAD included 57 participants (40 females [70.2%]; mean [SD] age, 70.1 [8.2]). SUICIDE-DECIDE included 124 participants (77 females [62.1%]; 32.1 [11.0]). Suicide attempters forgot past choices faster than controls (SPAD: F(2,36) = 13.5; P < .001; SUICIDE-DECIDE: F(3,57) = 46.6; P < .001). No other parameter specifically differed in attempters across studies. In SUICIDE-DECIDE, greater forgetting of past choices was associated with attempter status only (RRR = 4.2, 95% CI [1.5, 11.5]). This parameter paired with depression severity correctly classified 87.2% of participants in SPAD (95% CI [74.3%, 95.2%], 41/47). Conclusions and relevance. Short-sighted decision-making may represent a cognitive phenotype associated with suicide in high-risk populations and a potential target for prevention and treatment.

Background and Hypothesis Identifying which patients with schizophrenia will remain stable and which will relapse is relevant to both trial design and clinical practice. We hypothesized that higher negative and lower positive symptoms at baseline would predict longer time to relapse. Study Design This analysis pooled individual participant data on 557 patients with schizophrenia randomized to placebo from five placebo-controlled antipsychotic withdrawal relapse-prevention studies, each with a double-blind phase of at least 6 months. Relapse was defined as a [&ge;]12-point increase in Positive and Negative Syndrome Scale (PANSS) total score from double-blind baseline at any time during the double-blind phase. Cox regression analyses modeled time to relapse with the three PANSS subscales, age and sex. Study Results PANSS Negative and Positive symptom subscales predicted relapse in opposite directions and at almost equal magnitude in the pooled model. Higher negative symptoms predicted lower relapse risk (hazard ratio (HR)=0.94 per point, 95% confidence interval (CI)=0.90-0.99) and higher positive symptoms predicted higher relapse risk (HR=1.06, 95% CI=1.00-1.13). PANSS General Psychopathology did not predict relapse (HR=0.98, 95% CI=0.95-1.02). Based on the pooled estimates, a 4-point higher baseline PANSS Positive score corresponded to a 27% higher relapse risk, while a 4-point higher baseline PANSS Negative score corresponded to a 21% lower risk. Conclusions These results may help predict relapse risk in clinical care and in clinical trial samples but require prospective validation.

Circadian disruption is a transdiagnostic feature of psychiatric illness, particularly in bipolar disorder (BD), where evening chronotype is linked to greater symptom severity. The suprachiasmatic nucleus (SCN) times pineal gland (PG) melatonin synthesis through a well-described feedforward pathway. Moreover, melatonin can also phase-shift the SCN-pacemaker, consistent with a functional feedback limb. Directed effective connectivity between the SCN-containing hypothalamus and the PG has not been estimated in human neuroimaging, and it is unknown whether that directed coupling varies by psychiatric diagnosis or chronotype. We applied cross-spectral dynamic causal modeling (DCM) to resting-state fMRI data in 431 UK Biobank (healthy controls [HC, N=136], BD [N=78], major depressive disorder [MDD, N=154] and psychotic disorders [PY, N=63]). Random-effects Bayesian model selection compared a fully connected model with reduced archiature and, separately, feedforward-only (SCN[-&gt;]PG) vs feedback-only (PG[-&gt;]SCN) models. A per-subject log Bayes factor difference (dF) indexed directionality preference and was tested against diagnosis, chronotype and their interaction using ANCOVA. The fully connected model was strongly preferred (posterior probability=97.8%, protected exceedance probability [PXP]=1.00). Feedforward architecture dominated overall (70% vs 30%, PXP=1.00). Diagnosis did not predict dF (p=.403), but chronotype did (p=.036), and there was a significant diagnosis-by-chronotype interaction (p<.001). Feedforward dominance was strongest in evening chronotypes (p<.001). Model evidence favored a fully connected architecture with overall feedforward dominance. That preference varied by chronotype and, qualified by the interaction, was strongest in BD evening chronotypes. The pattern supports BD-evening chronotype as a high-risk subgroup and argues for routine chronotype assessment in BD care.

Background and Hypothesis: Although psychotic disorders are characterized by widespread cortical thinning, translating these findings into individualized biomarkers remains challenging. Regional Vulnerability Index (RVI) and Neuroscore are candidate individual-level biomarkers that quantify the similarity between an individual's structural brain pattern and generic psychosis-associated alterations. This study investigated cortical thickness (CT)-based RVI and Neuroscore, along with mean CT deviation from healthy individuals, across the psychosis spectrum. Study Design: Using structural 3T MRI data from 289 participants (clinical high risk for psychosis [CHR], n=39; first episode psychosis [FEP], n=44, chronic psychosis [CP], n=86; healthy controls [HC], n=120), RVI, Neuroscore, and mean CT deviation (z) scores were computed from region-wise CT measures quantified using FreeSurfer v7.2. Group differences and associations with symptoms were evaluated. Study Results: RVI and Neuroscore were significantly higher, and mean CT z-scores lower, in FEP and CP compared with CHR and HC, with moderate-to-large effect sizes (|Cohen's d| = 0.55-1.15). No differences were observed between FEP and CP or CHR and HC. Indices were not associated with psychosis-spectrum symptom severity in the CHR, FEP, or CP groups. RVI (r = -0.561, p < .001) and Neuroscore (r = -0.997, p < .001) were strongly negatively correlated with the mean CT z-score. Conclusions: CT-based RVI and Neuroscore appear to index established disease status but not risk status, while showing substantial overlap with mean CT deviation. These findings highlight the need to further refine these biomarkers through data-driven and multimodal approaches to improve their utility for risk and prognostic prediction.