Schizophrenia Bulletin

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.

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.

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

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.

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.

Genetic risk for schizophrenia (SCZ) has been linked to cognitive performance before the onset age. We examined how SCZ-related polygenic risk and resilience variants, and their co-expression patterns in the human brain, were associated with cognitive abilities across development in 16,520 non-psychiatric European and African ancestry children and adults. SCZ risk showed significant negative associations with spatial, verbal, and working memory across ancestries (all t<-2, pFDR<0.05). In Europeans, risk and resilience variants had opposing effects on attention, working and spatial memory ({Delta}t>4, pFDR<0.05). Polygenic scores filtered through perinatal co-expression networks showed stronger links with cognition than adult ({Delta}AIC>5.75, p=0.02) or juvenile ({Delta}AIC>5.8, p=0.03) networks. Cross-ancestry correlations (R=0.52, p<0.01) highlight replicability. These findings support the neurodevelopmental basis of SCZ, suggesting that risk and resilience variants influence cognition from early life, independent of symptoms and elucidate biological pathways through which SCZ risk may influence early cognitive development.

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 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.

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.

BackgroundNegative symptoms are core features of schizophrenia that relate strongly to functional impairment, yet interventions targeting these symptoms remain largely ineffective. Emerging theoretical work highlights how environmental factors may shape and maintain negative symptoms. Although racial disparities in schizophrenia diagnosis among Black Americans are well documented and linked to racial stress and psychosis, the impact of racial stress on negative symptoms has not been examined. This study provides an initial test of a novel theory proposing that racial stress - here measured by racial discrimination - influences negative symptom severity through exacerbation of negative cognitions about the self, particularly defeatist performance beliefs (DPB). Study DesignParticipants diagnosed with schizophrenia-spectrum disorder (SSD) (N = 208; 80 Black, 128 White) completed the Positive and Negative Syndrome Scale (PANSS), the Defeatist Beliefs Scale, and self-report measures of subjective racial and ethnic discrimination (Racial and Ethnic Minority Scale and General Ethnic Discrimination Scale). Relationships among variables were tested using linear regression and mediation analysis. Study ResultsBlack participants exhibited significantly greater total and experiential negative symptoms than White participants with no group difference in DPB. Racial discrimination explained 46% of the relationship between race and negative symptoms. Among Black participants, higher DPB were associated with greater negative symptom severity. Discrimination was positively related to both DPB and negative symptoms. DPB partially mediated the relationship between discrimination and negative symptoms. ConclusionsFindings suggest that racial stress contributes to negative symptom severity via defeatist beliefs among Black individuals, highlighting potential targets for culturally informed interventions.

0.Clozapine is the gold-standard for treatment-resistant schizophrenia despite its severe metabolic complications, including metabolic syndrome (MetS) and type 2 diabetes (T2D) risk. A better understanding of the genetic factors influencing clozapine pharmacokinetics and their relationship to metabolic risk could help inform precision medicine approaches to clozapine prescribing. Using a series of genetic-epidemiological approaches, we aimed to identify candidate biomarkers associated with clozapine-induced metabolic dysfunction. We first used two-sample Mendelian randomization (MR) leveraging genome-wide association summary data to investigate evidence of causal relationships between clozapine metabolism and cardiometabolic traits. These analyses indicated that higher plasma clozapine levels and a higher clozapine-norclozapine ratio were both associated with a higher risk of T2D and higher blood pressure. We then applied a Phenome-scan-colocalization-MR pipeline to identify traits influenced by clozapine-metabolism loci that might serve as biomarkers of cardiometabolic risk. This pipeline identified 28 colocalizing candidate biomarkers associated with clozapine metabolising genetic loci. Subsequent MR highlighted associations for 16 of these 28 biomarker candidates with cardiometabolic outcomes, which included haematological markers and excretory traits (e.g. gamma-glutamyl transferase, red cell distribution width, and urea). These findings may inform the development of biomarker-guided monitoring approaches for risk stratification and early intervention, enabling a shift from reactive monitoring to predictive approaches in managing clozapine-induced metabolic dysfunction with appropriate clinical validation. These findings may also help to mitigate the risk of metabolic dysfunction associated with other antipsychotic medications.

The most recent Psychiatric Genomics Consortium (PGC) genome-wide association study of schizophrenia used the statistical fine-mapping tool FINEMAP to identify 70 genes that were likely to mediate common genetic variant associations with the disorder. Here, we extended that study by using two fine-mapping methods, SuSiE and FINEMAP, applying the methods to loci whose causal variant structure was considered too complex by the PGC, and optimising the proportion of posterior probability required by credible sets of causal SNPs for gene prioritisation. Prioritised gene sets were validated for schizophrenia relevance by testing for enrichment of loss-of-function mutation intolerance (LoFI), and for enrichment of rare deleterious coding variants associated with generalised cognition in UK Biobank, both known characteristics of schizophrenia associated genes. Concordance between FINEMAP and SuSiE was high, with most prioritised genes supported by both methods. Genes prioritised by both methods using a relaxed 80% posterior probability (PP) threshold for defining credible sets (N=98) were as enriched for LoFI and for rare deleterious missense variants associated with generalised cognition as genes prioritised using a more conservative 95% PP threshold (N=87). Loosening the credible set threshold combined with the joint application of SuSiE and FINEMAP increased the yield of prioritised genes by 40%, without reducing the orthogonal evidence for validity. Newly prioritised genes included calcium channel genes, CACNA1I and CACNB2, a glutamate receptor gene, GRM3, and TCF4, which has been previously implicated in schizophrenia.

Background and Hypothesis: Environmental exposures linked to schizophrenia may play a role in shaping long-term clinical outcomes among individuals with psychotic disorders. This study examined whether the Maudsley Environmental Risk Score (ERS), a cumulative measure of five established environmental risk factors, predicts trajectories of symptoms, cognition, and psychosocial functioning over 25 years following first hospitalization for psychosis. Study Design: Participants were drawn from the Suffolk County Mental Health Project, a longitudinal cohort of individuals with first-admission psychosis assessed six times over two decades. A total of 516 participants had sufficient ERS data and repeated assessments of symptoms (SAPS, SANS), cognitive ability, and functioning (GAF). Study Results: Linear mixed-effects models showed that higher ERS was significantly associated with lower global functioning ({beta} = -0.104, p = 0.008), an effect that remained consistent over time. ERS also predicted more severe and worsening reality distortion ({beta} = 0.082, p = 0.023 for intercept; {beta} = 0.005, p = 0.032 for slope of time). No significant associations were observed between ERS and cognitive ability, disorganization, or negative symptoms. Conclusions: These findings highlight the contribution of environmental risk to functional impairment and persistent positive symptoms across the course of psychotic illness. Incorporating ERS into clinical risk models may aid the identification of individuals likely to experience a more severe illness trajectory, and inform long-term treatment planning.

In treatment-resistant schizophrenia, clozapine treatment has been associated with longitudinal reductions in subcortical volumes, ventricular enlargement, and widespread cortical thinning. However, it is unknown how these structural changes relate to clozapines pharmacological profile and clinical efficacy. We combined five longitudinal datasets with MRI acquired before and on average 5 months after clozapine initiation in 143 individuals to quantify brain structural changes and their association with normative maps relating to neuroreceptor architecture and physiological systems, and improvement in symptom severity. Clozapine treatment was associated with grey matter volume reductions across multiple subcortical regions (including the amygdala, hippocampus, thalamus, caudate, putamen and nucleus accumbens), increases in pallidal volume, ventricular enlargement, and widespread cortical thinning. Cortical regions showing the greatest magnitude of thinning corresponded to areas with higher normative densities of serotonergic 5-HT1A, 5-HT2A and 5-HT4 receptors. Changes in subcortical volume or cortical thickness during clozapine treatment were not associated with changes in total or positive symptom severity. In addition, baseline subcortical volume, cortical thickness, or gyrification prior to starting clozapine did not predict subsequent symptom improvement. Cortical thinning may partly reflect clozapines activity at serotonergic receptors, which have been implicated in cortical network stabilisation and neuroplasticity, however structural remodelling during clozapine treatment may reflect a process independent from its clinical efficacy in improving core symptoms of psychosis.

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.

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 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.

IntroductionTotal and social cognition deficits independently predict functioning in psychosis, but targeting these in clinical trials are unsuccessful in improving function. The admixture of schizophrenia and affective psychoses (aff-P) cases could be a roadblock if these differ in cellular pathology. MethodsWe examined cognitive functioning (MATRICS) and hippocampal cellular pathologies based on metabolite biomarker concentrations (1H-MRSI), using categorical and transdiagnostic classifications in 80 participants: 22 non-psychotic affective disorder (NP-aff), 25 healthy controls (HC), and 33 with psychosis, including 20 schizophrenia and 13 aff-P cases. ResultsNP-aff and HC had similar total cognition (46.64{+/-}12.01 vs 41.10{+/-}17.88), both superior psychosis (28.34{+/-}12.34; ps<0.01). Metabolite concentrations were similar across all groups but showed significant within-group associations to cognitive tests. For HC, total cognition, working memory and reasoning deficits were associated with reduced neuronal integrity (-.414, -.422, -.433, ps<.05), although no biomarker predicted total cognition in the clinical groups. For NP-aff, elevated myelin/membrane concentrations accompanied cognitive deficits; significantly so for visual learning deficits (.446, p<.05), which were also associated with decreased glia (-.503, p<.05). In all psychotic cases only reduced myelin/membrane concentrations predicted deficits (-.514, p<.05); but separating schizophrenia from aff-P, respectively showed reduced glutamate/excitation in schizophrenia (-.673, p<.05) but higher myelin/membrane and neuronal integrity concentrations (.575, .581, ps<.05) in aff-P. ConclusionsSchizophrenia and aff-P significantly differed for biomarkers of cellular pathology related to social cognition. Distinctly different underpinnings for cognition were also identified for other groups, aligning with DSM-5 and ICD disorder based categories. These findings include support for heterogeneous, but not transdiagnostic, conceptualizations of cognition and psychosis.

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.