Schizophrenia Bulletin

Background and HypothesisClozapine is the only medication with proven efficacy for treatment-resistant schizophrenia, yet many patients experience delays of several years before initiation. Our aim was to develop and validate a dynamic prediction model for clozapine initiation among patients with schizophrenia trained solely on electronic health record (EHR) data from routine clinical practice. Study DesignEHR data from all adults ([≥] 18 years) with a schizophrenia (ICD10: F20) or schizoaffective disorder (ICD10: F25) diagnosis who had been in contact with the Psychiatric Services of the Central Denmark Region between 1 January 2013 and 1 June 2024 were retrieved. 179 structured predictors were engineered (covering, e.g.,diagnoses, medications, coercive measures) and 750 predictors derived from clinical notes. At every psychiatric hospital visit, we predicted if an incident clozapine prescription occured within the next 365 days. XGBoost and logistic regression models were trained on 85% of the data with 5-fold stratified cross-validation. Performance was evaluated on the remaining 15% of the data (held out) using the area under the receiver operating characteristic curve (AUROC). Study ResultsThe training/test set comprised of 194,234/35,527 hospital visits, distributed on 4928/878 unique patients. In the test set, the best XGBoost model achieved an AUROC of 0.81, sensitivity of 32%, positive predictive value of 23% at a 7.5% predicted positive rate. ConclusionsA dynamic prediction model based solely on EHR data predicts clozapine initiation with high discrimination. If implemented as a clinical decision support tool, this model may guide clinicians towards more timely initiation of clozapine treatment.

Schizophrenia frequently follows a chronic relapsing-remitting course, comprising alternating episodes with and without psychotic symptoms (hereafter: psychosis and psychotic remission). One potential neurobiological correlate of this course is aberrant dopamine synthesis and storage (DSS) in the striatum, which can be estimated by 18F-DOPA positron emission tomography (PET). We hypothesised that striatal DSS in patients with schizophrenia decreases from psychosis to psychotic remission, with lower striatal DSS in patients during psychotic remission compared to healthy subjects. Additionally, we explored whether striatal DSS is associated with psychotic relapse after remission. 18F-DOPA PET scans and clinical assessments were conducted in 28 patients with schizophrenia at two timepoints, first during psychosis and second during early psychotic remission 6 weeks to 12 months after the first timepoint, as well as in 21 healthy controls, assessed twice in a comparable time interval. The averaged influx constant kicer as proxy for DSS was calculated for striatal subregions (i.e., nucleus accumbens, caudate, and putamen) using voxel-wise Patlak modelling with a cerebellar reference region. Mixed-effects models and post hoc analyses were used to test for longitudinal changes in kicer and cross-sectional group differences. An exploratory clinical follow-up 12 months after the second scan was conducted to assess psychotic relapse, and post hoc ANCOVAs were used to test for differences in kicer at each session between relapsing and non-relapsing patients. Kicer in both caudate and nucleus accumbens significantly changed from psychosis to psychotic remission compared to healthy controls, with a significant longitudinal decrease of caudate kicer in patients. Furthermore, kicer in both caudate and accumbens was significantly lower in patients during early psychotic remission compared to controls. At the exploratory clinical follow-up, 32% of patients had experienced a psychotic relapse; they showed higher caudate kicer compared to non-relapsing patients during psychosis, with no difference during psychotic remission. These findings provide evidence for the link between striatal, particularly caudate, DSS and the relapsing-remitting course of psychotic symptoms in schizophrenia, with lower caudate DSS during early psychotic remission. Data suggest altered striatal dopamine synthesis together with impaired DSS dynamics along the course of psychotic symptoms in schizophrenia.

BackgroundThe severity of positive psychotic symptoms largely defines emerging psychosis syndromes. However, depressive and negative symptoms are strongly psychologically and biologically interlinked. A transdiagnostic exploration of symptom severity across early illness syndromes could enhance the understanding of shared common factors and future trajectories of mental illness. We aimed to identify subgroups based on the severity of positive, negative, and depressive symptoms and assess relationships with: 1) premorbid functioning, 2) longitudinal illness course, 3) genetic risk, and 4) brain volume differences. MethodsWe analysed 749 participants from a multisite, naturalistic, longitudinal (18 months) cohort study of: clinical high risk for psychosis (n=147), recent onset psychosis (n=161), and healthy controls (n=286), and recent onset depression (n=155). Participants were stratified into subgroups based on severity of baseline positive, negative, and depression symptoms. Baseline and longitudinal differences between groups for clinical, functioning, and polygenic risk scores (schizophrenia, depression, cross-disorder) were assessed with ANOVAs and linear mixed models. Voxel-based morphometry was used to examine whole-brain grey matter volume differences. Discovery findings were replicated in a held-out sample (n=610). ResultsParticipants were stratified into no (n=241), mild (n=50), moderate (n=182), and severe symptom (n=254) subgroups. The mean (SD) age was 25.3 (6.0) and 344 (47.3%) were male. Symptom severity was associated with poorer premorbid functioning and illness trajectory, greater genetic risk, and lower brain volume. Findings were not confounded by the original study groups or symptoms and were largely replicated. Conclusions and relevanceTransdiagnostic symptom severity is linked to shared aetiologies, prognoses, and biological markers across diagnoses and illness stages. Such commonalities could guide therapeutic selection and future research aiming to detect unique contributions to specific psychopathologies.

Catatonia is a severe psychomotor syndrome that occurs across psychiatric diagnoses and is increasingly conceptualized as reflecting neurodevelopmental vulnerability. The anterior cingulate cortex (ACC) plays a central role in motor initiation and cognitive-affective integration and displays substantial interindividual variability in its sulcal morphology, which is established prenatally and remains stable across life. In this MRI study, we examined whether ACC sulcal patterns represent a structural trait marker of catatonia. We analyzed high-resolution T1-weighted images from a hospital-based cohort comprising patients with catatonia (N = 109), psychiatric patients without catatonia (N = 323), and healthy controls (N = 91). The presence of the paracingulate sulcus (PCS) in each hemisphere was determined through blinded visual inspection, and regression analyses tested associations with diagnostic group, adjusting for age, sex, scanner type, intracranial volume, and benzodiazepine and antipsychotic exposure. Patients with catatonia exhibited a significantly reduced prevalence of the left PCS and diminished hemispheric asymmetry compared with both non-catatonic patients and healthy controls. These effects were independent of whether catatonia occurred within psychotic or mood disorders. PCS size did not differ across groups, and sulcal pattern did not correlate with catatonia severity among affected individuals. The findings demonstrate that ACC sulcal deviations are specifically associated with catatonia across diagnostic categories, supporting a neurodevelopmental etiology and reinforcing ACC involvement in its pathophysiology. Early-determined sulcal morphology may represent a trait-level marker contributing to vulnerability for catatonia, with implications for early identification, risk stratification, and targeted intervention strategies.

ImportanceBlood-based biomarkers hold promise for psychiatric diagnosis and prognosis, yet clinical translation is constrained by poor reproducibility. Psychiatric biomarker studies are typically small, and demographic, behavioral, and temporal covariates often go undetected or cannot be adequately modeled. This may lead to residual confounding and unstable associations. ObservationsLeveraging UK Biobank data (N=~500,000), we systematically quantified how technical, demographic, behavioral, and temporal covariates influence 29 blood biomarkers commonly measured in research studies in psychiatry. Variance analyses showed substantial differences across biomarkers. Technical factors explained 1-6% and demographic factors explained 5-15% of the variance, with pronounced age-by-sex interactions for lipids and sex hormones. Behavioral covariates, particularly body mass index (BMI) and smoking, strongly influenced inflammatory markers. Temporal factors introduced systematic confounding. Chronotype was associated with blood collection time, multiple biomarkers exhibited marked diurnal rhythms (including testosterone, triglycerides, and immune markers), and inflammatory markers showed seasonal peaks in winter. In association analysis of biomarkers with major depression, bipolar disorder and schizophrenia, covariate adjustments attenuated or eliminated a substantial proportion of the biomarker-disorder associations, with BMI emerging as the dominant confounder. These findings demonstrate that such confounding structures exist and can be characterized in large cohorts, though specific biomarker-disorder relationships require validation in clinical samples. Conclusions and RelevancePoor reproducibility of biomarkers may not only stem from insufficient biological signal but also from inconsistent handling of confounders. We propose a systematic framework distinguishing technical factors (to be removed), demographic factors (addressed through adjustment or stratification), temporal factors (ideally controlled at design stages), and behavioral factors (requiring explicit causal reasoning). Associations robust to multiple adjustment strategies should be prioritized for clinical biomarker development. Standardized collection protocols, comprehensive covariate measurement, and transparent reporting across models are essential to improve reproducibility and identify biomarkers that reflect genuine illness-related pathophysiology.

The 7-nicotinic acetylcholine receptor (7nAChR) has driven extensive research over the past three decades for its pro-cognitive potential. It is the leading druggable target for the cognitive deficits associated with schizophrenia and has motivated major pharmaceutical and clinical efforts to ameliorate similar impairments in other neurological disorders, such as Alzheimers disease (AD). Yet, a systematic evaluation of the role played by 7nAChR in cognition, and its mechanistic underpinnings, is still lacking. Here we report that 7nAChRs on principal and inhibitory forebrain neurons are largely inconsequential to mouse behavior, including in domains that are most sensitive to schizophrenia-related cognitive impairments. By contrast, loss of 7nAChR from astrocytes produces profound behavioral alterations that are cognitive domain-specific, are time-of-day dependent, coincide with reduced levels of the N-methyl D-aspartate receptor (NMDAR) co-agonist D-serine, and are fully restored by D-serine supplementation. Further, an 7nAChR partial agonist previously evaluated in Phase III trials for cognitive enhancement in schizophrenia and AD fails to augment behavior in mice lacking astrocytic 7nAChRs. Together, these findings identify astrocytes and D-serine/NMDAR signaling as a central mechanism through which 7nAChR, a major drug target, promotes cognitive behavior.

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.

Progress in pharmacological treatment development for neurodevelopmental disorders is hindered by a misalignment between targeted mechanisms, outcome measures, and trial designs. This study was initiated as a post-trial access pathway for bumetanide and later expanded with treatment-naive participants. Within this framework, we implemented a parent-cocreated sensory outcome measure set (PROMset) in an unmasked, multiple-baseline single-case experimental design with randomized baseline periods of 2-12 weeks, followed by 6 months of bumetanide treatment (up to 1.5 mg twice daily). Participants (7-19 years) had atypical sensory reactivity and a diagnosis of ASD, ADHD, epilepsy, or TSC. The primary outcome was a PROMset comprising seven PROMIS item banks assessing anxiety, depressive symptoms, sleep disturbance, fatigue, sleep-related impairment, cognitive function, and peer relationships. Secondary outcomes included SSP, SRS-2, RBS-R, and ABC. Of 113 enrolled participants (mean age 13.2 [SD 2.7], 64% male), 102 completed the trial and 95 had analyzable PROMsets. At baseline, PROMset scores showed substantial impairment across domains (mean deviation =9.0 T-score points, p<.001) and correlated with sensory reactivity (SSP; r=-0.40, p<.001). Individual-level analyses showed improvement in 24-41% of participants per PROM domain, most frequently in anxiety and depressive symptoms (41% and 38%; mean across-case Cohen's d=-1). Overall, 83% improved on at least one domain. Group-level analyses showed improvement across all secondary outcomes (p<.001), with superiority over historic placebo for RBS-R and SSP. Integrating PROMsets with individualized trial designs can reveal clinically meaningful changes, supporting a more sensitive and patient-centered framework for treatment evaluation in heterogeneous populations.

Sex differences are commonly observed in neuroimaging phenotypes and in the risk of brain diseases, yet the underlying genetic mechanisms remain poorly understood. We investigated sex differences in the genetic architecture of 805 neuroimaging phenotypes in 22,950 males and 22,950 females matched for sample size and covariates, and systematically compared sex-stratified with sex-combined genetic analyses. We found eight variant-trait associations with significant sex differences, 235 fine-mapped sex-dominant causal associations, 457 sex-dominant colocalizations with sex hormones, and 96 sex-dominant colocalizations with schizophrenia. Compared with sex-combined analysis, sex-stratified analysis identified 47 new genetic associations, 170 new fine-mapped causal associations, 1,019 new colocalizations with sex hormones, and 191 new colocalizations with schizophrenia. Additionally, sex-stratified analysis improved global heritability and genetic-correlation estimates and enhanced polygenic prediction for certain phenotypes. This work highlights the need to routinely perform sex-stratified genetic association analyses to elucidate sex-specific and sex-shared genetic control of neuroimaging phenotypes and related disorders.

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.

ImportanceSemaglutide, a glucagon-like peptide-1 receptor agonist (GLP-1RA), is a highly effective medication to treat type 2 diabetes and obesity. However, concerns about potential suicidality persist, creating clinical uncertainty about its neuropsychiatric safety. ObjectiveTo assess risks of suicidality after initiating semaglutide compared to initiating SGLT2i and by duration of continuous semaglutide treatment. DesignActive-comparator, new-user target trial emulation to estimate inverse probability-weighted marginal cause-specific hazard ratios (HRs). For duration-of-treatment analyses, we used clone-censor-weight methods to estimate exposure-adjusted effects. SettingVeterans Health Administration. ParticipantsU.S. Veterans with type 2 diabetes receiving care from March 1, 2018 to September 1, 2025. ExposureInitiation of semaglutide vs SGLT2i; duration of semaglutide use ([&le;]6, 7-12, >12 months). OutcomesIncident suicidal ideation; suicide attempt or death; and a composite outcome. ResultsA total of 102,361 Veterans met inclusion criteria, including 11,478 new initiators of semaglutide and 90,883 new initiators of an SGLT2i. After overlap weighting, baseline characteristics were well balanced between treatment groups (mean [SD] age, 60.1 [11.7] years; BMI, 37.8 [6.8] kg/m2; hemoglobin A1c, 7.0% [1.4]; 85.5% male; 61.9% non-Hispanic White). During a median follow-up of 2.2 years, 9077 incident suicidal ideation events and 696 suicide attempts or deaths occurred. The incidence rate of suicidal ideation was 56.3 and 37.7 per 1000 person-years among semaglutide initiators and SGLT2i initiators, respectively (hazard ratio [HR], 0.99; 95% CI, 0.93-1.06; P = 0.86). For suicide attempts or deaths, the incidence rates were 4.30 and 2.64 per 1000 person-years, respectively (HR, 1.05; 95% CI, 0.84-1.31; P = .86). In adherence-adjusted analyses, sustained semaglutide treatment for more than 12 months, compared with 6 or fewer months, was associated with a 74% lower risk of suicide attempts or deaths (HR, 0.27; 95% CI, 0.14-0.54; P<.001). ConclusionAmong U.S. Veterans with type 2 diabetes, initiators of semaglutide were not observed to have an increased risk of suicidality compared with initiators of SGLT2i. Those with longer semaglutide treatment (beyond 12 months) had decreased risk of suicide attempt or death, suggesting longer term treatment is safe and may protect against for those outcomes.

Metabotropic glutamate 2/3 receptors (mGluR2/3) have been implicated in depression, anxiety, learning, and memory. However, their causal role in reward-related behaviors remains unclear. Here, we examined the effects of intraperitoneal administration of LY341495, a selective mGluR2/3 antagonist, on reward-related behaviors in mice. In a head-fixed temporal conditioning task, mice received a 10% sucrose solution every 10 seconds. After training, mice exhibited anticipatory licking and pupil dilation aligned with expected reward delivery, indicating successful reward prediction. LY341495 dose-dependently reduced licking behavior without disrupting temporal prediction, as normalization analyses revealed reduced gain but preserved timing. LY341495 also induced overall pupil dilation and attenuated reward-proximity pupillary responses. To determine whether reduced licking reflected general motor impairment, we assessed spontaneous locomotion in a freely moving open-field task. LY341495 did not affect locomotor activity or excretion, suggesting intact general motor and autonomic function. To further evaluate orofacial motor function, we measured ultrasonic vocalizations (USVs) during a social interaction task. LY341495 did not significantly alter USVs, indicating preserved mouth-related motor function independent of licking. In contrast, LY341495 dose-dependently reduced food intake in a freely moving feeding task. Moreover, social preference testing revealed that LY341495 reduced social interaction, suggesting impaired processing of non-food rewards. Together, these findings demonstrate that mGluR2/3 signaling regulates reward-seeking behaviors independently of general locomotor or orofacial motor function. These results provide new insights into glutamatergic mechanisms underlying reward processing and may have clinical implications for obesity, eating disorders, and psychiatric conditions involving motivational dysfunction.

The Mental Status Examination (MSE) is the cornerstone of the psychiatric evaluation, yet validating artificial intelligence (AI) against the inherent variance of clinical judgment remains a critical bottleneck. Here we introduce a multi-center framework to benchmark the open-weight multimodal foundation model Qwen3-Omni against independent expert panels at two sites, UTHealth and Yale. Evaluating 396 classifications across 10 MSE domains and three longitudinal timepoints of increasing symptom severity, we found that experts achieved substantial agreement (Gwets AC1 = 0.87), whereas the model achieved only moderate alignment (AC1 = 0.70-0.72). Even as the models overall pathology prediction rate approximated the experts, the aggregate equilibrium masked a profound "clinical reasoning gap". Specifically, the model systematically over-predicted observable signs (e.g., speech, affect) while notably failing in inferential domains requiring the interpretation of latent mental content (e.g., delusions, perceptions). A 4-bit quantization analysis of the model confirmed this mechanistically: reducing model capacity disproportionately degraded inferential reasoning while preserving perceptual feature extraction. Furthermore, model-to-expert agreement degraded linearly as clinical complexity intensified across longitudinal visits (Accuracy: T0 = 84.8-87%; T1 = 80-82%; T2 = 71-73%), whereas expert consensus remained robust. Notably, model errors increased 2.3-to-3.4 fold where human experts disagreed. These findings establish inter-expert variance as an essential measurable baseline for psychiatric AI, demonstrating that true clinical translation requires models to move beyond multimodal perceptual extraction to achieve higher-order diagnostic reasoning.

AimAutistic children have a high but varied prevalence of internalizing and externalizing problems. This study aimed to identify the subtypes of internalizing and externalizing problems among autistic preschool children in Japan, examine their temporal stability, and investigate differences in participation in daily life and family outcomes across these subtypes. MethodsA prospective cohort study was conducted with 275 caregivers of autistic children aged 51-75 months. Internalizing and externalizing problems were assessed using the Strengths and Difficulties Questionnaire. ResultsLatent transition analysis identified five subtypes: Low-symptom, High-emotional, Externalizing, Comorbid, and Peer-difficulty groups. Membership in the High-emotional and Externalizing groups was relatively stable over time, whereas the Peer-difficulty group showed frequent transitions to subtypes with higher levels of internalizing or externalizing problems. Significant differences in participation in daily life and family outcomes were observed across subtypes, but these patterns were inconsistent with a simple gradient of symptom levels. ConclusionsThe novel findings that the temporal stability of subtype membership varied and that differences in participation in daily life and family outcomes were observed across the subtypes suggest that the heterogeneity of internalizing and externalizing problems may be associated with variations in childrens participation in daily life and family outcomes over time. Plain Language SummaryAutistic preschool children often experience emotional and behavioral difficulties, but the way these difficulties manifest varies widely across individuals. This study aimed to identify the patterns of these difficulties, examine how they change over time, and investigate how participation in daily life and family outcomes differ across autistic preschool children. We conducted a study with 275 caregivers of autistic children aged 4-6 years in Japan. From caregiver reports of childrens emotional and behavioral difficulties, five distinct patterns were identified: a group with mainly emotional difficulties, a group with mainly behavioral difficulties, a group with both types of difficulties, a group with relatively low levels of difficulties, and a group characterized primarily by peer-related difficulties. Our findings suggest that different patterns of emotional and behavioral difficulties are associated with differences in childrens participation in daily life and family outcomes. These differences could not be explained simply by the overall severity of difficulties but rather reflect distinct patterns based on the type of difficulty. The results indicate that autistic children face diverse difficulties that change over time.

The cerebellum rapidly integrates with cerebral networks during infancy and shows consistent structural and functional alterations in Autism Spectrum Disorder (ASD), suggesting that early cerebellar development may be consequential for later behavioral and psychiatric outcomes. Yet, little is known about the effect of ASD genetic liability on cerebello-cerebral functional connectivity in infancy or whether effects may differ by biological sex. Here, we leveraged neonatal functional magnetic resonance imaging, genetic, and behavioral follow-up data from the Developing Human Connectome Project (dHCP) to examine the relationship between ASD polygenic scores (PGS) and functional connectivity of cerebellar regions associated with sensorimotor and social-cognitive functions in 198 term-born neonates (mean age: 9.7 days). We report widespread sex differences in neonatal cerebello-cerebral connectivity that are regionally specific across cerebellar subdivisions. Across the full sample, elevated ASD PGS predicted alterations in cerebello-cerebral connectivity, with hemisphere-dependent differences in sensorimotor cerebellar connectivity with temporal cortex, and hyperconnectivity between the right social-cognitive seed and posterior cingulate. Notably, elevated ASD PGS predicted opposing patterns of cerebello-cerebral connectivity in males and females, including male hyperconnectivity between the right sensorimotor cerebellum and default mode areas, and female hyperconnectivity between the right social-cognitive seed and sensorimotor cortex. Connectivity associated with elevated ASD PGS showed nominal, sex-specific associations with 18-month language ability, attention problems, and emotional reactivity. Our findings show that ASD PGS influences the functional configuration of the cerebellum at birth and suggest that underlying cerebellar connectivity profiles associated with ASD may partially underlie distinct behavioral presentations in males and females.

Traumatic brain injuries (TBIs) are more than mere lesions and generate a persistent secondary pathology. This, combined with functional reorganization of circuits post-injury, may explain the increased risk for psychiatric disorders in patients with TBI. In the current studies, we demonstrate that frontal TBI changed the Pavlovian behavioral response to reinforcer-predicting cues and reduced the motivational value of cues. TBI also chronically impaired decision-making on a gambling-like task with reinforcer-paired cues. To investigate how these changes occur, we evaluated the nucleus accumbens (NAc) core. At a subacute time point (14 days), we confirmed reduced input to the NAc with optogenetics and evaluated electrophysiological and transcriptional changes. TBI increased neuronal excitability and the single nucleus RNA sequencing profile indicated a substantial stress and inflammatory response, but also high indicators of plasticity, particularly in D1- and D2-positive medium spiny neurons. To evaluate how these subacute changes transitioned to chronic NAc dysfunction, we measured immunohistochemical surrogates of activity post-mortem and recorded calcium activity from the NAc after TBI during Pavlovian conditioning. TBI reduced histological markers of activity and reduced cue-evoked calcium activity. Overall, these data indicate that substantial reorganization of the NAc occurs following frontal brain injury. A primary effect of this is to reduce the salience of environmental cues linked to outcomes. The inability to properly process outcomes could contribute to broader psychiatric symptoms after TBI, including impairments in decision-making, behavioral flexibility, and impulsivity but also presents a potential treatment target.

IntroductionFamily Constellation Therapy (FCT) has been widely disseminated in clinical, public health, and judicial settings despite persistent concerns regarding its theoretical basis, safety, and the limited availability of rigorous randomised evidence supporting its clinical use. ObjectiveThe aim of this systematic review is to assess the effects of FCT across all clinical conditions, explicitly considering both benefits and harms; and summarise the characteristics of studies and intervention settings used in randomised controlled trials of FCT. MethodsFollowing a prospectively registered protocol (CRD420251136190), we conducted a systematic search of seven databases (PubMed, EMBASE, APA PsycInfo, CENTRAL, BVS, Web of Science, and CINAHL) and grey literature (ICTRP and ProQuest database) without language or date restrictions to identify published and unpublished randomised controlled trials of FCT. Study selection, data extraction, risk of bias (RoB 2), and certainty of evidence (GRADE) were performed in duplicate. Statistical analyses followed a prospectively registered analysis plan with prespecified criteria for data pooling and for handling analytical limitations. ResultsNo reliable evidence was found to support the use of FCT for any condition across both clinical and non-clinical samples. All trials included were judged to be at high risk of bias and all comparisons were rated as very low-certainty evidence. Concerns regarding potential adverse effects were identified, and the available data was insufficient to establish the effectiveness of the intervention, precluding any clinical recommendation. ConclusionClinicians, policymakers, and consumers should reconsider adopting FCT while reliable evidence is not available.

BackgroundScalable, low-burden behavioral interventions are needed to address rising subclinical mental health symptoms. However, few randomized controlled trials have evaluated ultra-brief, remotely delivered, meditation using multimodal outcome assessment under real-world conditions. MethodsWe conducted a fully remote randomized controlled trial (ClinicalTrials.gov: NCT06014281) evaluating a focused-attention meditation intervention delivered via brief instructor training and independent daily practice. A total of 299 meditation-naive adults were randomized to immediate intervention or waitlist control in a delayed-intervention design. Participants practiced [&ge;]10 minutes daily for 8 weeks within a 16-week study. Outcomes included validated self-report measures, web-based cognitive tasks, and wearable-derived physiological metrics. ResultsAcross randomized and within-participant replication phases, the intervention was associated with significant reductions in anxiety and mind wandering, with effects remaining stable during 8-week follow-up. Improvements were greatest among participants with higher baseline symptom burden. Sleep disturbance improved selectively among individuals with poorer baseline sleep. Secondary outcomes, including rumination, perceived stress, social connectedness, and quality of life, also improved. Cognitive performance showed modest improvements primarily among lower-performing participants. Resting heart rate exhibited nominal reductions. ConclusionsAn ultra-brief, fully remote meditation intervention requiring 10 minutes per day was associated with sustained improvements in psychological functioning and smaller, baseline-dependent effects on cognition in a non-clinical population. These findings support digital delivery of low-dose meditation as a scalable preventive mental health strategy.

Background: The etiology and nosological status of seasonal affective disorder (SAD) as a specifier of depressive episodes versus a transdiagnostic disorder are the subject of debate. In this study, we investigated the underlying etiology of SAD and dimensional seasonality by examining their association with latitude and genetic risk for a range of traits, and investigated gene-environment interactions. Methods: This study included 12,460 adults aged 18-90 with a history of depression from the Australian Genetics of Depression Study. Regression models included predictors for latitude (distance from equator) and polygenic scores for eight traits; major depressive disorder, bipolar disorder, anxiety disorders, chronotype, sleep duration, body mass index, vitamin D levels, and educational attainment. Outcomes were SAD status and general seasonality score. Results: SAD was positively associated with latitude (OR[95%CI] = 1.05[1.03-1.06], padjusted<0.001), and there was nominal evidence of additive and multiplicative interactions between chronotype genetic risk and latitude (OR = 0.99[0.99-0.99], padjusted=0.381; OR=0.98[0.97-0.99], padjusted=0.489). General seasonality score was associated with latitude (IRR=1.01[1.01-1.01], padjusted 0.001) and genetic risk for major depressive disorder (IRR =1.02[1.01-1.03], padjusted<0.001), bipolar disorder (IRR=1.02[1.01-1.03], padjusted=0.001), anxiety disorders (IRR=1.03[1.01-1.04], padjusted<0.001), vitamin D levels (OR=0.89[0.80-0.95], padjusted=0.048), and educational attainment (IRR=0.97[0.96-0.99], padjusted<0.001). Conclusions: These findings enhance understanding of SAD etiology, highlighting contributions of psychiatric genetic risk and geographic measures on seasonal behavior, and support examining seasonality as a continuous dimension.

BackgroundEpidemiological studies show an inverse association between cigarette smoking and Parkinsons disease (PD), suggesting a potential protective effect of smoking on PD incidence, despite the well-established and overwhelming harms of smoking to human health. We integrated genomic and proteomic approaches to investigate the causality and molecular basis of this potential relationship. MethodsWe analyzed summary statistics from genome-wide association studies (GWAS) of smoking initiation (SmkInit), smoking intensity, and PD. Two-sample Mendelian randomization (MR) tested whether genetic liability to smoking behaviors causally influences PD risk. Shared genomic architecture was quantified using MiXeR, and conjunctional false discovery rate (conjFDR) analysis identified loci jointly associated with smoking and PD, which were then mapped to genes and tested for tissue enrichment. To identify mediating proteins, we integrated dorsolateral prefrontal cortex proteomic data with GWAS using proteome-wide association studies (PWAS), summary-based MR, heterogeneity in dependent instruments testing, and colocalization. Finally, the druggability of convergent genes was evaluated. ResultsMR analyses indicated a protective effect of genetic liability to SmkInit on PD risk (OR = 0.78, 95% CI: 0.67-0.91, P = 1.5 x 10-3), which was consistent across sensitivity analyses and not suggestive of directional pleiotropy. However, no significant effect of genetic liability to cigarettes per day (CigDay) on PD risk was found. MiXeR revealed modest polygenic overlap between SmkInit and PD (13.9%; genetic correlation rg = -0.16) and between CigDay and PD (22.9%; rg = -0.09). ConjFDR identified 95 shared loci for SmkInit-PD and 26 for CigDay-PD. SmkInit-PD loci mapped to genes involved in neurotrophic signaling, synaptic organization, microglial modulation, and mitochondrial stress responses, with expression enriched in substantia nigra, basal ganglia, and interconnected cortical regions. PWAS identified 11 proteins shared by PD and SmkInit and 5 shared with CigDay, several of which (AKT3, MAPT, RIT2, EXD2, and PPP3CC) were supported by both genomic and proteomic analyses. Druggability assessment highlighted six proteins with existing pharmacologic modulation potential, spanning neurotrophic, microglial, proteostatic, and ion-channel pathways. ConclusionsGenetic liability to smoking initiation appears to confer modest protection against PD. Integrative genomic and proteomic evidence converges on neurotrophic, synaptic, microglial, and mitochondrial pathways as shared mechanisms, identifying biologically coherent potential therapeutic targets for advancing smoke-free neuroprotective strategies in PD.