Schizophrenia

Background Cognitive impairment is a core feature of schizophrenia and a major determinant of functional disability. Executive deficits affect approximately 85% of patients and are associated with reduced activity in the prefrontal cortex (hypofrontality). Current pharmacological treatments show limited efficacy in improving cognition, highlighting the need for alternative therapeutic approaches. Combining non-invasive brain stimulation with cognitive remediation may enhance neuroplasticity and improve cognitive outcomes. Methods This prospective, randomized, double-blind, sham-controlled, parallel-group superiority clinical trial. A total of 120 adults aged 18-65 years with clinically stable schizophrenia diagnosed according to DSM-5 criteria will be enrolled at a single clinical center. Participants will be randomly assigned in a 1:1 ratio to receive either active transcranial direct current stimulation (tDCS) targeting the dorsolateral prefrontal cortex followed by cognitive remediation therapy (CRT) using the RehaCom system, or sham stimulation followed by the same cognitive training. Assessments will be conducted at three time points: prior to the intervention (V1), immediately after the intervention (V2), and during the follow-up visit 8 weeks after the intervention (V3). The primary outcome is change in cognitive performance measured with the CANTAB battery. Secondary outcomes include symptom severity assessed with the PANSS, global clinical status (CGI-S), and neurophysiological changes measured by EEG. Written informed consent will be obtained from all participants, and the study has received ethics committee approval. Discussion This trial will evaluate whether tDCS administered prior to cognitive training enhances cognitive improvement compared with cognitive training alone. The findings may inform the development of more effective interventions targeting cognitive deficits in schizophrenia. Trial registration ClinicalTrials.gov Identifier: NCT07273175. Registered on 25 November 2025.

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.

ObjectiveTobacco use is a leading cause of mortality in schizophrenia, but treatments are partially effective. Default mode network (DMN) pathology is linked to tobacco use in schizophrenia, and transcranial magnetic stimulation (TMS) applied to the DMN affects craving in schizophrenia. To advance TMS therapeutics for tobacco use in schizophrenia, we used TMS experiments to 1) determine optimal stimulation parameters then 2) compare our optimal parameters against a well-established, effective TMS intervention for craving. MethodsIn Protocol Optimization TMS, nicotine-using individuals with schizophrenia (n=10) received single sessions of DMN-targeted TMS with pre/post neuroimaging and craving assessment. Neuroimaging analysis revealed bilateral parietal DMN connectivity was associated with craving change. In Comparative Effectiveness TMS (n=62), nicotine-using individuals with schizophrenia and non-psychosis controls participated in a crossover study comparing DMN-targeted and left dorsolateral prefrontal cortex (DLFPC)-targeted TMS with pre/post neuroimaging and craving assessment. Mixed effects models were used to determine effects of target, group, and relationship between craving change and connectivity change. ResultsIn Protocol Optimization TMS, increased craving was associated with increased bilateral parietal DMN connectivity (mean pFDR<0.012, r=0.60). In Comparative Effectiveness TMS, both interventions reduced craving (DLPFC: p=0.0015; DMN: p=0.0054) and bilateral parietal DMN connectivity (DLPFC: p=0.024; DMN: p=0.022). There was an interaction of bilateral parietal DMN connectivity change, group, and age (p=0.001) where connectivity change was associated with craving change in older individuals with schizophrenia (p=0.041) but not other groups. ConclusionsBilateral parietal DMN connectivity is a novel mechanism underlying craving in schizophrenia that can be engaged for therapeutic benefit.

Background: The highly influential predictive processing theory of psychosis posits that symptoms arise from imbalances in the weighting of predictions (priors) and sensory evidence. Despite this theory's increasing prominence, studies often present conflicting results. This is particularly problematic as findings from single tasks with modest sample sizes are frequently used to advance a theory for a generalised altered reliance on priors in psychosis. Methods: This study presents a random-effects, multi-level meta-analysis (PROSPERO CRD42024574379) evaluating evidence for aberrant reliance on priors in psychosis across perceptual tasks. The search identified articles in Embase, MEDLINE, APA PsycINFO, and APA PsycArticles published between 1st January 2005 and 31st October 2024, with risk of bias assessed using the Newcastle-Ottawa Scale. Included articles (34 results from 27 studies) compared adults with schizophrenia-spectrum psychosis (SZ; n = 904) to healthy controls (n = 1,039) on behavioural measures representing reliance on priors. Results: Results provided no evidence for atypical reliance on priors in psychosis (g = .03, 95% CI [-0.27, 0.34]; p = .818) or associations with delusions (6 results; SZ = 183; r = -.16, 95% CI [-0.51, 0.19]; p = .293) or hallucinations (10 results; SZ = 370; r = .04, 95% CI [-0.28, 0.36]; p = .780). In contrast with the theory that psychosis may differentially affect priors at different levels of the cognitive hierarchy, a sub-group analysis indicated that a two-level hierarchical model of priors did not account for conflicting results (F(1,32) = 0.1, p = .758). Conclusion: These findings do not suggest that psychosis is associated with a generalised predictive processing deficit spanning multiple aspects of perception. Key words: psychosis, schizophrenia, predictive processing, prior expectations, perception

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 ([&ge;] 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.

BackgroundPsychosis has been conceptualised as a continuum extending from healthy individuals with psychotic-like experiences to clinical populations with schizophrenia. It is unclear which biological mechanisms found in chronic schizophrenia extend across the psychosis continuum to healthy individuals with high positive schizotypy (HS). In this study, we used computational modeling to test whether changes in effective connectivity and excitation/inhibition (E/I) balance reported in schizophrenia are also found in HS. MethodsA total of 2425 individuals from the general population were screened for HS. A subset (N=141) was invited for in-depth phenotyping. Resting-state functional magnetic resonance imaging (rsfMRI) and proton magnetic resonance spectroscopy (1H-MRS) were recorded in n=69 HS individuals and n=72 group-matched controls with low schizotypy (LS). We used dynamic causal modeling to estimate effective connectivity between bilateral primary auditory cortex (A1), superior temporal gyrus (STG), and inferior frontal gyrus (IFG). ResultsBilateral backward connectivity from IFG to STG was significantly reduced in HS compared to LS. Widespread cortical disinhibition in the auditory cortex-IFG network correlated with more severe positive schizotypy scores and impulsive nonconformity. Reduced excitability in the same network was correlated with stronger cognitive disorganisation. ConclusionsOur results favour a psychosis-continuum hypothesis, suggesting that reduced top-down drive from frontal cortex and compensatory allostatic upregulation of cortical excitability, as observed in chronic schizophrenia, also extend to groups with sub-clinical psychotic symptoms. Frontal cortex dysfunction may serve as a biologically interpretable biomarker of psychosis risk and a target for preventative interventions.

Schizophrenia is a serious mental disorder that changes the way people think, perceive, and manage daily life. Getting the diagnosis right is critical for proper treatment, but in practice it is often difficult. Current evaluations depend mostly on a clinicians judgment, and the overlap of symptoms with bipolar disorder or major depression makes the task even harder. EEG offers a safe and noninvasive way to study brain activity, yet no single EEG feature has been reliable enough to stand on its own. This makes it important to look at integrative approaches that bring together different aspects of brain dynamics. In this study, we analyzed EEG features to distinguish patients with schizophrenia from healthy controls. Spectral power was measured across {delta}, {theta}, , {beta}, and {gamma} bands. Temporal irregularity was quantified with Multiscale Permutation Entropy (MPE), which to our knowledge represents the first application of MPE to EEG in schizophrenia. Functional connectivity was estimated with the weighted Phase Lag Index in {theta}, , and {beta} bands, followed by extraction of graph measures including global efficiency, clustering coefficient, characteristic path length, and mean strength. These features were used to train Random Forest, Multi-Layer Perceptron, and Support Vector Machine classifiers. Among the models, Random Forest achieved the most reliable performance, reaching 99.7% accuracy under stratified 5-fold validation and 99.6% under leave-one-subject-out validation. Feature analysis showed that connectivity in {theta} and bands contributed most strongly to classification. Topographic maps of {theta}, , and {beta} activity also revealed regional group differences. Overall, the results suggest that combining spectral, entropy, and connectivity measures offers a promising framework for EEG-based detection of schizophrenia. Nevertheless, these findings are preliminary given the limited sample size (N=28), and replication in larger and more diverse cohorts is required before clinical translation.

BackgroundSchizophrenia is associated with widespread cognitive impairments. Several early risk factors for schizophrenia have been identified, and some studies suggest associations between these early risk factors and cognition, yet the literature is sparse in psychosis. MethodsClinical cohorts of child/adolescent and adult patients with first-episode psychosis (FEP) and healthy controls (HC) were linked with register-based information (N=276). Gestational age, Apgar scores, birth weight and length, parental age, and season of birth were extracted from the Danish medical birth registry. Cognition was assessed at time of diagnosis using BACS, CANTAB, and WAIS-III/WISC-IV. Missing data was imputed using MICE. Canonical correlation analysis (CCA) was used to examine patterns of associations. Post hoc analyses explored group differences according to diagnosis, age, and sex. ResultsCCA resulted in two significant patterns of associations. CCA1 was stable across imputations (r=0.44, p=.036, pmin= .017, pmax= .055), and constituted by a risk profile of lower maternal age, lower birth length, being small for gestational age, and lower birth weight and a cognitive profile of lower estimated IQ and poorer working memory, mental flexibility, processing speed, verbal fluency, and motor latency. The pattern was more expressed in FEP compared to HC and in adults compared to children. CCA2 was more unstable across imputations (r=0.38, p=.033, pmin=.003, pmax=.168) and constituted by a broad pattern of minor loadings. ConclusionCognitive functioning later in life is associated with multiple early risk factors, underscoring the complexity of developmental processes and the importance of the early developmental context in shaping cognitive trajectories.

BACKGROUND: Predicting long-term outcomes in first-episode schizophrenia (FES) remains difficult, despite being especially important early in the illness, when timely intervention is most critical. Many potential predictors have been studied, but few are reliable enough to guide early treatment decisions. It also remains unclear how much data from the initial phase of illness is required to improve prognostic accuracy. METHODS: We analysed 68 patients with first-episode schizophrenia (FES) assessed at baseline (V1; mean 0.5 years post-onset, YPO), one-year follow-up (V2; mean 1.2 YPO), and outcome (V3; mean 4.9 YPO). We trained elastic-net models to predict three V3 outcomes-negative symptoms (PANSS Negative factor; Wallwork/Fortgang), global functioning (GAF), and quality of life (WHOQOL-BREF psychological domain)-using either 23 V1 predictors alone or V1 predictors plus V2 data (43 predictors). Performance was evaluated with nested cross-validation on held-out data. RESULTS: Using predictors from the first year (V1+V2), we achieved statistically significant out-of-sample prediction for all three V3 outcomes: PANSS Negative factor (Wallwork/Fortgang) R2=0.22 driven mainly by log(DUP), PANSS Negative at V1/V2, and PANSS Disorganized at V2; WHOQOL-BREF Psychological Health R2=0.22 driven mainly by WHOQOL Psychological Health at V2 and GAF at V2; and GAF R2=0.14 driven mainly by GAF at V2, PANSS Positive at V2, WHOQOL Psychological Health at V2, and hospitalization burden (before V1 and between V1-V2). With baseline-only predictors (V1), only PANSS Negative showed meaningful predictive power (R2=0.15); GAF and WHOQOL-BREF did not outperform the intercept-only baseline. CONCLUSION: In FES, long-term functioning (GAF) and quality of life (WHOQOL-BREF) can not be predicted well from first-episode (V1) measures; at least an additional 1 year of follow-up is needed, implying these outcomes are driven by changes after onset that V1 misses. Negative symptoms differ: they are comparatively stable after initial antipsychotic treatment, and duration of untreated psychosis is their strongest predictor beyond baseline severity-consistent with early biology and treatment timing shaping their level and persistence. These contrasting patterns indicate different outcome phenotypes.

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.

In the past two decades, the focus on genome-wide association studies in large samples of unrelated patients has overshadowed family genetic studies. Therefore, little is still known about the levels and effects of the transmission of polygenic risk scores (PRS) among familial cases of schizophrenia (SZ) or bipolar disorder (BD) and their unaffected relatives. Prior research has shown that PRS are elevated in both patients and young individuals at familial risk for BD and SZ. We sought to study the transmission of PRS in affected multigenerational families and non-affected adult relatives (NAARs) with or without other non-mood nonpsychotic DSM-IV diagnoses and unrelated non-affected individuals from the same population. We genotyped 1,117 participants divided in 48 families from the Eastern Quebec Schizophrenia and Bipolar Disorder Kindreds. PRSs for both SZ and BD were computed using Multivariate Lassosum. For both SZ PRS and BD PRS, SZ and BD cases present higher PRS compared to controls, replicating previous findings. Regardless of a diagnosis of other non-psychotic and non-mood conditions, NAARs presented higher PRS than the unrelated cohort. Crucially, a subset of families presented consistently low PRS transmission profiles across generations, falling below expectations from our polygenic inheritance model. When the effect of individual PRs is accounted for, we observed sex-specific associations between familial PRS and patients' symptom dimensions. Our results clearly demonstrate that polygenic inheritance alone does not adequately explain disease transmission in families. Such an approach may also clarify why some families exhibit dense clustering of cases despite minimal polygenic burden.

Cognitive deficits are a core feature of schizophrenia, yet their neural mechanisms remain poorly understood. Network switching, a measure of how frequently brain networks change their interactions over time, has been linked to cognitive performance in healthy individuals and has been reported to be altered in schizophrenia. Recent evidence further suggests that the relationship between network switching and cognition depends on arousal, which is itself disrupted in schizophrenia. However, whether arousal-related alterations in network switching contribute to cognitive impairment in schizophrenia remains unclear. Here, we used concurrent resting-state functional MRI (fMRI) and pulse oximetry data from 39 healthy controls (HC), 27 psychiatric controls (PC), and 39 individuals with schizophrenia spectrum disorders (SSD) to examine whether network switching relates to indices of autonomic arousal. Additionally, in HC and SSD participants, we tested whether arousal moderated the association between network switching and performance on an attention task. We observed no group differences in autonomic arousal. However, PC exhibited higher dorsal default mode and anterior salience network switching rates compared to SSD participants. Additionally, autonomic arousal significantly moderated the relationship between network switching and cognitive performance in HC, an effect that was absent in SSD. Notably, these findings implicate network switching as a potential neural biomarker that differentiates PC from SSD. They also suggest that disrupted coupling between arousal state and network switching, rather than switching alone, may underlie cognitive dysfunction in SSD.

Background. Something in discourse with a person experiencing psychosis often "feels off" before formal assessment is completed, yet this disturbance has not been quantified at the level of ongoing dyadic conversation. Prior work has largely treated patient speech in isolation, limiting our capacity to measure how communicative disruption emerges within clinical exchange. Methods. We applied a three-level decomposition of conversational alignment in 109 patients with psychotic disorders (26 female) and 60 healthy controls (22 female) at baseline and 12 months (n = 115). Register divergence (dAUCnorm) captured lexical distance between interviewer and patient; embedding-based synchrony (rembed) measured semantic trajectory coupling; within-speaker coherence was computed separately for each speaker. We used linear mixed-effects models adjusted for timepoint and participant clustering. Results. Patients showed significantly greater lexical-semantic divergence from the interviewer (d = 0.48, p < .001) and reduced embedding-based synchrony (d = -0.59, p < .001), both effects replicating at each time point. Critically, the interviewer's within-speaker coherence was reduced during conversations with patients (d = -0.33, p = .016), indicating that the disruption extends beyond the patient to the interaction itself. Register divergence tracked impoverished thinking and synchrony tracked disorganized thinking (both FDR-corrected q = .038). Group differences were persistent at 12 months, indicating a partially stable profile. Conclusions. Conversational alignment in psychosis reveals a dyadic failure of semantic coordination that destabilizes the interviewing clinician's coherence even when patient narrative continuity is preserved. These transcript-derived alignment metrics offer a scalable approach to quantifying interpersonal communicative function from routine clinical encounters.

BackgroundDifferences in age of psychosis onset (AOO) in schizophrenia (SCZ) are associated with different illness trajectories. Determining whether AOO differences can be explained by genome-wide or pathway-partitioned polygenic risk for SCZ (SCZ-PRS) may elucidate mechanisms underlying clinical variability. This study examined relationships between AOO, genome-wide SCZ-PRS, and pathway-partitioned SCZ-PRS in a harmonized, multi-ancestry North American dataset (SCZ-NA) and in UK Biobank (SCZ-UKBB). MethodsFor each cohort, we computed one genome-wide SCZ-PRS and 18 mutually-exclusive pathway-based PRS derived from previous published and validated neurodevelopmental gene-sets. We evaluated 13 SNP-to-gene mapping strategies, including comparing non-coding SNP-to-gene mappings informed by functional annotations versus distance-based windows. SCZ case-control prediction and AOO associations were tested using logistic and linear mixed models, respectively, controlling for sex, ancestry principal components, and genetic relatedness. ResultsGenome-wide SCZ-PRS robustly predicted SCZ case-control status in both cohorts but not AOO. In contrast, pathway-based analyses identified AOO associations for a fetal angiogenesis and a postnatal synaptic signaling and plasticity gene-set across both cohorts (p < .05), alongside nominal cohort-specific associations in other gene-sets. Associations depended on SNP-to-gene mapping definitions; experimentally informed strategies, particularly those incorporating brain expression Quantitative Trait Locus (eQTL) annotations performed best. ConclusionFindings suggest that neurovascular and postnatal synaptic signaling and refinement mechanisms contribute to AOO variation in SCZ, and that pathway-informed PRS, especially with brain-specific non-coding SNP-to-gene mappings, can help identify mechanisms contributing to variability in AOO. Replication in larger, prospectively phenotyped cohorts with harmonized AOO definitions will further clarify genetic mechanisms underlying clinical variability in SCZ.

Schizophrenia is a severe psychiatric disorder associated with altered dopaminergic signaling and hippocampal circuit dysfunction. Although antipsychotic medications remain the standard treatment, many are limited by incomplete efficacy and adverse effects. Cariprazine, a dopamine D2/D3 receptor partial agonist, has a favorable clinical profile, but its effects on neuronal excitability and network activity remain incompletely understood. Here, we integrated nationwide real-world clinical data with in vitro electrophysiology, computational modeling, and molecular analyses to define the neuronal actions of cariprazine. Among Hungarian patients diagnosed with schizophrenia and receiving index-drug monotherapy with one of the three prespecified D2/D3 targeting antipsychotics, haloperidol was associated with worse survival and a higher cumulative incidence of first registered suicide attempt than cariprazine or aripiprazole in matched observational cohorts. In primary mouse hippocampal cultures, multielectrode array recordings showed that acute cariprazine treatment moderately reduced spontaneous firing in a dose-dependent manner and prolonged burst intervals while largely preserving network synchronization. These effects were milder than those of haloperidol and aripiprazole. Whole-cell patch-clamp recordings revealed cell-type-dependent effects, with reduced intrinsic excitability and increased firing irregularity mainly in regular- and stuttering-type neurons. Conductance-based modeling identified enhanced Kv1-mediated D-type potassium currents as sufficient to reproduce these effects. Consistent with this mechanism, chronic cariprazine treatment altered Kv1.2 protein distribution without changing Kcna2/Kcna3 or Drd1/Drd2/Drd3 transcript expression. These findings identify modulation of intrinsic excitability via Kv1/D-type potassium currents as a candidate cellular mechanism of cariprazine and provide a translational link between real-world evidence and circuit-level drug effects.

Social withdrawal is a key component of the negative symptom domain of schizophrenia, and pharmacological blockade of the N-methyl-D-aspartate receptor (NMDAR) is widely used to model schizophrenia-relevant phenotypes in animals. However, findings on social behaviour are inconsistent across paradigms and laboratories. We therefore conducted a systematic review and meta-analysis to synthesise the effects of dizocilpine, ketamine, and phencyclidine on social interaction and social preference, to evaluate whether clinically approved antipsychotics modify these outcomes, and to examine locomotor activity measured within the same social tests to aid interpretation. We searched Embase, PubMed and Web of Science without language or date restrictions. Controlled in vivo studies in laboratory animals administering an eligible NMDAR antagonist and reporting social interaction and/or social preference outcomes were included. Two reviewers independently screened records, extracted data and assessed risk of bias. Effect sizes were computed as standardised mean differences and synthesised using correlated multilevel random-effects models with cluster-robust variance estimation. In total, 264 studies met the inclusion criteria. Overall, NMDAR antagonists were associated with reduced social interaction and reduced social preference relative to controls, although the social preference literature appeared vulnerable to small-study effects and imprecision. Locomotor activity measured during social interaction tests tended to be higher following NMDAR antagonists, whereas during social preference no consistent overall change was observed. In animals exposed to NMDAR antagonists, antipsychotics increased social behaviour, but these changes commonly co-occurred with reduced locomotion during social interaction tests, suggesting that improvements in social measures may partly reflect altered behavioural competition and time allocation rather than selective restoration of social functioning. Taken together, the evidence supports an overall link between NMDAR antagonism and reduced social behaviour, but the strength and interpretability of this signal depend on the paradigm and are constrained by heterogeneity and limitations in reporting.

BackgroundSchizophrenia is a neurodevelopmental disorder shaped by immune-related mechanisms, particularly dysregulated complement-mediated synaptic pruning. Genome-wide association studies have identified CSMD1 as a major schizophrenia risk gene, an association robustly replicated across populations of diverse ancestries. As a complement regulator, CSMD1 further links genetic vulnerability to synaptic refinement processes. However, the transcriptional status of CSMD1 and its homolog CSMD2 in individuals with schizophrenia (SZ individuals) remains poorly characterized. We conducted a meta-analysis of gene-expression datasets to determine whether CSMD1 and CSMD2 are differentially expressed in brain and peripheral tissues, and to assess the concordance between central and peripheral transcriptional signals. MethodsTranscriptional data were obtained from gene expression omnibus. Random-effects meta-analyses were performed on CSMD1 and CSMD2 expression data from 854 postmortem brain samples derived from 348 SZ individuals and 346 healthy controls (HC), and 295 peripheral blood samples from 162 SZ individuals and 133 HC. Sex-stratified analyses and meta-regressions evaluated potential moderators. ResultsIn brain tissues, CSMD2 expression was significantly increased in SZ individuals vs. HC (SMD: 0.22 [0.05; 0.39], adj-p=0.026), whereas CSMD1 showed no differential expression. The female-only meta-analysis revealed nominal CSMD2 overexpression (p=0.037) in brain tissues, not surviving correction. No significant transcriptional differences were detected in peripheral blood. ConclusionIn schizophrenia, our findings point to a dissociation between genetic vulnerability and transcriptional activity within the CSMD gene family. Schizophrenia is associated with selective brain CSMD2 overexpression, contrasting with unchanged CSMD1 transcription and absent peripheral blood alterations. These findings support complement-related dysregulation as a central pathway in schizophrenia.

BackgroundA high proportion of autistic people receive off-license antipsychotic medication, often in the absence of a mental illness, primarily for behaviours that challenge, which is a public health concern. Although meta-analyses have been published recently, there is a lack of a comprehensive network meta-analysis to inform clinicians about the relative efficacy and safety of antipsychotic medications. AimsTo conduct a network meta-analysis of available RCTs of antipsychotic medications involving autistic participants to assess the relative efficacy of different antipsychotics and their adverse effects. MethodWe searched seven databases and hand-searched ten relevant journals. Two authors independently screened titles, abstracts, and full papers, extracted data, and assessed their quality. ResultsWe analysed data from 22 RCTs involving 1562 autistic people. The largest mean difference with 95% confidence interval in the Aberrant Behaviour Checklist-Irritability (ABC-I) score compared with placebo was from the combined intervention with risperidone and parent training: -11.16 (-15.13, -7.18), followed by risperidone: -7.59 (-9.22, -5.95), and aripiprazole: -5.59 (-7.18, -4). The largest effect on Clinical Global Impression-Improvement (CGI-I) scores was from risperidone, 7.65 (2.17, 27.04), followed by aripiprazole, 7.02 (1.92, 25.72), compared with placebo. Risperidone (4; 1.57, 10.21) and aripiprazole (2.77; 1.20, 6.39) had significantly higher odds ratios for adverse effects, but aripiprazole showed the least weight gain. ConclusionsCombined parent training and risperidone followed by risperidone and aripiprazole showed the best effects on the ABC-I score, whereas risperidone and aripiprazole showed the greatest effect on the CGI-I score. However, risperidone and aripiprazole showed significantly increased adverse effects.

Schizophrenia spectrum disorders (SSDs) are clinically and neurobiologically heterogeneous. Normative modeling addresses heterogeneity of structural brain alterations by focusing on individual-level deviations, but their clinical relevance in SSDs remains controversial. We mapped the relationship between individual gray matter volume (GMV) deviations and schizophrenia diagnosis and symptoms. Normative models of GMV were established using cross-sectional, T1-weighted magnetic resonance imaging data from a large, multi-site, healthy reference cohort (N = 7957). Deviations were derived for SSD patients (n = 379) and healthy controls (n =149). Patients showed a significantly more negative average deviation compared to controls and regional deviations predicted diagnostic status with adequate performance (AUC = 0.79). A more negative deviation was associated with higher symptom severity and lower cognitive functioning in SSD. Negative deviations were scattered across the brain, with the largest alterations in the salience network. Our findings strengthen the potential of normative modeling to disentangle the heterogeneous underpinnings of SSD and provide further evidence for individualized structural deviations, particularly in the salience network, as promising markers of illness severity in SSDs.

Weak inhibition of mitochondrial complex I (mtCI) has been shown to have neuroprotective effects in cellular and animal models of Alzheimers and Huntingtons diseases, at least in part by enhancing mitochondrial biogenesis and function. Mitochondrial dysfunction has also been demonstrated in schizophrenia patients and mouse models of schizophrenia. We tested whether weak inhibition of mtCI would ameliorate mitochondrial and behavioral phenotypes in a mouse model of schizophrenia. In mice with four copies of the Gldc gene, 8 weeks of treatment with the weak mtCI inhibitor, the small-molecule tricyclic pyrone compound CP2, reversed spontaneous alternation deficits in the Y maze, startle habituation deficits, and social novelty deficits in the three-chamber social interaction test. Consistent with the mechanism of action, Western blots revealed that CP2 reverses the reduced expression of PGC-1, a master regulator of mitochondrial biogenesis, and of the VDAC1, a primary gatekeeper for the exchange of metabolites, ions, and ATP between mitochondria and the cytosol. These findings suggest that the improvement of mitochondrial function may represent a novel strategy to reverse pathophysiological and behavioral deficits in schizophrenia.