Schizophrenia Bulletin

BackgroundPeople with schizophrenia exhibit notable difficulties in the use of everyday language. This directly impacts ones ability to complete education and secure employment. An impairment in the ability to understand and generate the correct grammatical structures (syntax) has been suggested as a key contributor; but studies have been underpowered, often with conflicting findings. It is also unclear if syntactic deficits are restricted to a subgroup of patients, or generalized across the broad spectrum of patients irrespective of symptom profiles, age, sex, and illness severity. MethodsWe conducted a systematic review and meta-analysis, registered on OSF, adhering to PRISMA guidelines, searching multiple databases up to May 1, 2024. We extracted effect sizes (Cohens d) and variance differences (log coefficient of variation ratio) across 6 domains: 2 in comprehension (understanding complex syntax, detection of syntactic errors) and 4 in production (global complexity, phrasal/clausal complexity, utterance length, and integrity) in patient-control comparisons. Study quality/bias was assessed using a modified Newcastle-Ottawa Scale. Bayesian meta-analysis was used to estimate domain-specific effects and variance differences. We tested for potential moderators with sufficient data (age, sex, study quality, language spoken) using conventional meta-regression to estimate the sources of heterogeneity between studies. FindingsOverall, 45 studies (n=2960 unique participants, 64{middle dot}4% English, 79 case-control contrasts, weighted mean age(sd)=32{middle dot}3(5{middle dot}6)) were included. Of the patient samples, only 29{middle dot}2% were women. Bayesian meta-analysis revealed extreme evidence for all syntactic domains to be affected in schizophrenia with a large-sized effect (model-averaged d=0{middle dot}65 to 1{middle dot}01, with overall random effects d=0{middle dot}86, 95% CrI [0{middle dot}67-1{middle dot}03]). Syntactic comprehension was the most affected domain. There was notable heterogeneity between studies in global complexity (moderated by the age), production integrity (moderated by study quality), and production length. Robust BMA revealed weak evidence for publication bias. Patients had a small-to-medium-sized excess of inter-individual variability than healthy controls in understanding complex syntax, and in producing long utterances and complex phrases (overall random effects lnCVR=0{middle dot}21, 95% CrI [0{middle dot}07-0{middle dot}36]), hinting at the possible presence of subgroups with diverging syntactic performance. InterpretationThere is robust evidence for the presence of grammatical impairment in comprehension and production in schizophrenia. This knowledge will improve the measurement of communication disturbances in schizophrenia and aid in developing distinct interventions focussed on syntax - a rule-based feature that is potentially amenable to cognitive, educational, and linguistic interventions. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSPrior studies have documented significant language deficits among individuals with psychosis across multiple levels. However, syntactic divergence--those affecting sentence structure and grammar--have not been consistently quantified or systematically reviewed. An initial review of the literature indicated that the specific nature and severity of syntactic divergence, as well as their impact on narrative speech production, symptom burden, and daily functioning, remain poorly defined. We conducted a comprehensive search of the literature up to May 1, 2024, using databases such as PubMed, PsycINFO, Scopus, Google Scholar, and Web of Science. Our search terms combined psychosis, schizophrenia, language production, comprehension, syntax, and grammar, and we identified a scarcity of meta-analytic studies focusing specifically on syntactic comprehension and production divergence in psychosis. Added value of this studyThis systematic review and meta-analysis is the first to quantitatively assess syntactic comprehension and production divergence in individuals with psychosis. This study provides estimated effect sizes associated with syntactic impairments as well as a quantification of the variance within patient groups for each domain of impairment. Besides a detailed examination of this under-researched domain, we also identify critical research gaps that need to be addressed to derive benefits for patients from knowledge generated in this domain. Implications of all the available evidenceThis study provides robust evidence of grammatical impairments in individuals with schizophrenia, particularly in syntactic comprehension and production. These findings can enhance early detection approaches via speech/text readouts and lead to the development of targeted cognitive, educational, and linguistic interventions. By highlighting the variability in linguistic deficits, the study offers valuable insights for future therapeutic trials. It also supports the creation of personalized formats of information and educational plans aimed at improving the effectiveness of any therapeutic intervention offered to patients with schizophrenia via verbal medium.

Key PointsO_ST_ABSQuestionC_ST_ABSIs variation in global functioning among people with schizophrenia associated with genetic differences? FindingsIn this genetic association study of 5991 adults with schizophrenia and 59,795 hospitalizations, polygenic scores for schizophrenia and educational attainment predicted global functioning at psychiatric admission and discharge, as well as the magnitude of functional improvement during hospitalization. Higher polygenic burden for schizophrenia was consistently associated with worse functional outcomes, including less functional improvement during hospitalization, while educational attainment polygenic score showed a more complex pattern of associations. MeaningPolygenic scores may help disentangle heterogeneity in schizophrenia functioning and course. ImportanceSchizophrenia is characterized by heterogeneity in disease outcomes and course. The extent to which this heterogeneity is associated with genetic variation is unclear. ObjectiveTo investigate whether polygenic scores (PGS) for schizophrenia and educational attainment are associated with global functioning during inpatient psychiatric hospitalization among patients with schizophrenia. Design, Setting, and ParticipantsAdults with schizophrenia were recruited nationwide for the SUPER-Finland Study between 2015 and 2018. Global functioning scores recorded during hospitalizations between 1994 and 2019 were extracted from a complete, longitudinal register. Data for the current genetic association study were analyzed between May 2024 and April 2025. We used linear mixed-effects models to examine associations among PGS and global functioning at admission and discharge, as well as functional change during hospitalization. ExposuresPsychiatric hospitalization and PGS for schizophrenia and educational attainment. Main Outcomes and MeasuresAdmission global functioning, discharge global functioning, and functional change during hospitalization. ResultsWe analyzed 117,810 global functioning scores from 59,795 hospitalizations and 5991 participants (2733 [45.62%] female, median [IQR] age = 47 [20] years). Higher schizophrenia PGS predicted lower admission global functioning ({beta} = -0.20; 95% CI, -0.40 to 0.00; P = .05) and discharge global functioning ({beta} = -0.36; 95% CI,-0.56 to -0.17; P < .001), and less functional improvement ({beta} = -0.31; 95% CI, -0.49 to -0.14; P < .001). Higher educational attainment PGS predicted greater functional improvement ({beta} = 0.20; 95% CI, 0.03 to 0.37; P = .02) but worse admission global functioning ({beta} = -0.23; 95% CI, -0.43 to -0.04; P = .02). Conclusions and RelevanceHigher genetic liability for schizophrenia is associated with worse global functioning across psychiatric hospitalization, including less functional improvement. Integrating PGS and clinically relevant, longitudinal disease outcomes may help parse heterogeneity in schizophrenia prognosis and course.

IntroductionMeditation is widely used to support mental well-being, and recent randomized trials suggest benefits for persistent psychotic symptoms in schizophrenia. However, the magnitude and timing of causal treatment effects, response heterogeneity, and underlying neurobiological mechanisms over clinically meaningful timescales remain unclear. MethodsWe analyzed data from an eight-month, parallel-group randomized clinical trial (ChiCTR1800014913) of 64 male inpatients with chronic schizophrenia, randomized to daily clinician-guided meditation plus rehabilitation or rehabilitation alone. Prespecified outcomes were PANSS percentage decrease rate and RBANS increase rate. Linear mixed-effects models estimated time-specific causal average treatment effects. Cross-lagged panel models examined temporal relations between symptom and cognitive benefits; latent-class mixed models characterized treatment-response heterogeneity. Resting-state fMRI at baseline, 3, and 8 months yielded functional components, their complexity indices, and functional-connectivity predictors of clinical benefit. ResultsMeditation produced progressive symptom improvement (average treatment effects on PANSS decrease rate: 11.8% after 3 months; 20.8% after 8 months) and an early cognitive gain (7.6% after 3 months) that plateaued. Early cognitive improvement predicted, but did not mediate, later symptom relief. Response trajectories were heterogeneous; marital status and lower antipsychotic burden characterized high responders. Neuroimaging revealed a biphasic pattern: higher baseline default-mode-cerebellar complexity predicted short-term benefit, whereas greater 3-month action-mode-sensorimotor-executive complexity predicted longer-term gains; functional-connectivity models converged on these findings. ConclusionsClinician-guided meditation, added to rehabilitation, yields robust causal treatment effects on symptoms in schizophrenia. A biphasic shift from default-mode-cerebellar involvement to action-mode engagement provides phase-specific, information-based indicators to guide personalized meditation in severe mental illness.

BackgroundSchizophrenia genome-wide association studies (GWASes) have identified >250 significant loci and prioritized >100 disease-related genes. However, gene prioritization efforts have mostly been restricted to locus-based methods that ignore information from the rest of the genome. MethodsTo more accurately characterize genes involved in schizophrenia etiology, we applied a combination of highly-predictive tools to a published GWAS of 67,390 schizophrenia cases and 94,015 controls. We combined both locus-based methods (fine-mapped coding variants, distance to GWAS signals) and genome-wide methods (PoPS, MAGMA, ultra-rare coding variant burden tests). To validate our findings, we compared them with previous prioritization efforts, known neurodevelopmental genes, and results from the PsyOPS tool. ResultsWe prioritized 62 schizophrenia genes, 41 of which were also highlighted by our validation methods. In addition to DRD2, the principal target of antipsychotics, we prioritized 9 genes that are targeted by approved or investigational drugs. These included drugs targeting glutamatergic receptors (GRIN2A and GRM3), calcium channels (CACNA1C and CACNB2), and GABAB receptor (GABBR2). These also included genes in loci that are shared with an addiction GWAS (e.g. PDE4B and VRK2). ConclusionsWe curated a high-quality list of 62 genes that likely play a role in the development of schizophrenia. Developing or repurposing drugs that target these genes may lead to a new generation of schizophrenia therapies. Rodent models of addiction more closely resemble the human disorder than rodent models of schizophrenia. As such, genes prioritized for both disorders could be explored in rodent addiction models, potentially facilitating drug development.

BackgroundSubtyping schizophrenia can disentangle heterogeneity and help with treatment decision- making. However, current schizophrenia subtypes have not demonstrated adequate clinical utility, limited by sample size, suboptimal clustering methods, and choice of clustering input. Polygenic scores (PGS) reflect the genetic risk of phenotypes including comorbidities and are available before treatment, making them candidate clustering input. MethodsWe derived PGS for schizophrenia, autism spectrum disorder, bipolar disorder type-1, depression, and intelligence in 4,915 schizophrenia cases with register linkage. We randomly divided the sample into discovery and replication partitions and applied a novel clustering workflow on both: preprocessing PGS, feature extraction with uniform manifold approximation and projection (UMAP), and clustering with density-based spatial clustering of applications with noise (DBSCAN). After replication, we re-performed clustering on the entire sample and evaluated treatment-relevant variables of medication and hospitalization (extracted from registers) across clusters. OutcomesWe identified five well-replicated PGS clusters. Cluster 1 (26% of entire sample) with generally lower PGS, had the least use of antipsychotics (including clozapine), and fewer outpatient visits. Cluster 2 (48%) with generally higher PGS, especially schizophrenia PGS, had more prescriptions of antipsychotics including clozapine and longer treatment with clozapine. Each featured by specific PGS, clusters 3 (high IQ-PGS, 11%), 4 (high ASD-PGS, 8%), 5 (high BIP-PGS, 7%) showed sub-threshold level significance in the corresponding phenotypic measures but did not differ significantly in the treatment-relevant variables. Solely categorizing the patients with SCZ-PGS did not generate any significant patterns in the phenotypic and treatment-relevant variables. InterpretationThe results suggest that combinations of PGS of brain disorders and traits can provide clinically relevant clusters, offering a direction for future research on schizophrenia subtyping. Future replications in independent samples are required. The workflow can be generalized to other disorders and with mechanism-informed PGS.

ObjectivePsychosis - a complex and heterogeneous neuropsychiatric condition characterized by hallucinations and delusions - is a common feature of schizophrenia. There is evidence for altered DNA methylation (DNAm) associated with schizophrenia in both brain and peripheral tissues. We aimed to undertake a systematic analysis of variable DNAm associated with psychosis, schizophrenia, and treatment-resistant schizophrenia, also exploring measures of biological ageing, smoking, and blood cell composition derived from DNAm data to identify molecular biomarkers of disease. MethodsWe quantified DNAm across the genome in blood samples from 4,483 participants from seven case-control cohorts including patients with schizophrenia or first-episode psychosis. Measures of biological age, cellular composition and smoking status were derived from DNAm data using established algorithms. DNAm and derived measures were analyzed within each cohort and the results combined by meta-analysis. ResultsPsychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNAm data, with the largest differences seen in treatment-resistant schizophrenia patients. DNAm at 95 CpG sites was significantly different between psychosis cases and controls, with 1,048 differentially methylated positions (DMPs) identified between schizophrenia cases and controls. Schizophrenia-associated DMPs colocalize to regions identified in genetic association studies, with genes annotated to these sites enriched for pathways relevant to disease. Finally, a number of the schizophrenia associated differences were only present in the treatment-resistant schizophrenia subgroup. ConclusionsWe show that DNAm data can be leveraged to derive measures of blood cell counts and smoking that are strongly associated with psychosis. Our DNAm meta-analysis identified multiple DMPs associated with both psychosis and a more refined diagnosis of schizophrenia, with evidence for differential methylation associated with treatment-resistant schizophrenia that potentially reflects exposure to clozapine.

Background: Differences 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). Methods: For 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. Results: Genome-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. Conclusion: Findings 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.

Understanding factors that predict the course of schizophrenia remains essential for improving long-term clinical management. Rate and severity of symptom exacerbations vary widely across individuals, and although prior studies have examined potential predictors, findings have been inconsistent and often limited by small samples, infrequent assessments, and non-standardized measures. Using data from phase 1 of the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE), which includes a large cohort with monthly standardized evaluations, this study investigated whether baseline negative symptom severity predicts risk of symptom exacerbation over time. Participants were 1139 adults aged 18-65 years meeting DSM-IV criteria for schizophrenia. Symptoms worsening or exacerbation was defined as a [&ge;]12-point increase from baseline on the PANSS total score. Cox regression survival models examined the association between baseline PANSS negative symptom tertiles and time to exacerbation, adjusting for age, sex, PANSS positive and general psychopathology subscales, and CGI-Severity. Overall, 25.5% of participants experienced exacerbation over a 18-month period of follow-up. Survival curves demonstrated significant separation across negative symptom tertiles (p=0.047), with higher baseline negative symptoms associated with longer time to exacerbation. Compared with the lowest tertile, medium and high negative symptom groups showed reduced exacerbation risk (HR=0.73 and HR=0.69, respectively; both p=0.03). Findings indicate that greater baseline negative symptom severity is associated with a lower likelihood of short-term symptom worsening, suggesting a relatively stable illness course among individuals with more severe negative symptoms. These results have implications for prognosis and treatment planning, while underscoring the persistent functional burden imposed by negative symptoms despite lower exacerbation risk.

Metacognition is the set of reflexive processes allowing humans to evaluate the accuracy of their mental operations. Deficits in synthetic metacognition have been described in schizophrenia using mostly narrative assessment and linked to several key symptoms. Here, we assessed metacognitive performance by asking individuals with schizophrenia or schizoaffective disorder (N=20) and matched healthy participants (N = 21) to perform a visual discrimination task and subsequently report confidence in their performance. Metacognitive performance was defined as the adequacy between visual discrimination performance and confidence. Bayesian analyses revealed equivalent metacognitive performance in the two groups despite a weaker association between confidence and trajectory tracking during task execution among patients. These results were reproduced using a bounded evidence accumulation model which showed similar decisional processes in the two groups. The inability to accurately attune confidence to perceptual decisions in schizophrenia remains to be experimentally demonstrated, along with the way such impairments may underpin functional deficits.

BackgroundAntipsychotic medications are recommended for managing schizophrenia spectrum disorders, yet their long-term effects on functional recovery remain unclear. Existing evidence is conflicting, often derived from between-subject comparisons vulnerable to confounding by indication. MethodsWe conducted a nationwide register-based cohort study of 65,630 individuals with incident schizophrenia spectrum disorders in Denmark (1998-2023). We modelled antipsychotic exposure against productive engagement (employment or education). We employed two distinct analytical approaches to separate causal from prognostic associations: (1) Within-subject stratified Cox models with time-varying covariates, where patients served as their own controls to eliminate time-invariant confounding; and (2) Fine-Gray competing risks models using a between-subject design with baseline exposure, accounting for mortality and emigration. FindingsOver 26.9 million person-weeks, the overall productive engagement rate was 48.2%. Integration of hospital pharmacy data revealed a 6.1% exposure misclassification bias in previous studies relying solely on community records. The primary within-subject analysis revealed significant temporal heterogeneity: medication use was associated with reduced engagement rates in the acute (0-2 years: HR 0.908) and consolidation phases (2-5 years: HR 0.946), but reversed to a positive association in the maintenance phase (5+ years: HR 1.019). In contrast, the between-subject Fine-Gray model yielded a null result (SHR 1.002, 95% CI 0.988-1.015), failing to detect these phase-specific dynamics. InterpretationWithin-subject modelling reveals that antipsychotic treatment involves a functional trade-off: it is associated with a transient reduction in engagement rates during the early consolidation phase (2-5 years), followed by stabilisation and potential benefit in the maintenance phase (5+ years). The null result in standard between-subject (Fine-Gray) analysis likely reflects residual confounding by indication and exposure misclassification, highlighting the necessity of within-person designs to unmask the true stage-specific impact of pharmacotherapy on vocational recovery. FundingNone directly for this study. Danmarks Nationalbank funded the research visit that facilitated this collaboration.

BackgroundPrediction of response to antipsychotic medications remains elusive, and a biomarker assisting in treatment selection would drastically improve prognosis. The 40 Hz auditory steady state response (ASSR) is an EEG biomarker, mirroring the GABA-glutamate signaling and the excitation/inhibition balance, consistently been reported to be impaired in schizophrenia, on, with inconsistent evidence of an association with specific symptoms. MethodsN=69 schizophrenia inpatients with an acute psychotic episode underwent an EEG recording to assess event related spectral perturbation (ERSP), intertrial phase coherence (ITC) and phase amplitude coupling (PAC) during the ASSR task, aimed to assess their relationship with response to antipsychotics and with positive, negative, disorganized, excited and depressive symptoms. Moreover, patients were compared with controls (N=36), to delineate schizophrenia acute phase ASSR dynamics. ResultsResponders to treatment showed a decreased 40 Hz ERSP in both the early (0-0.2s post-stimulus; P=0.0013; d=-0.936) and late (0-2-1.2s post-stimulus; P=0.0022; d=-0.932) time windows compared to non-responders. Using logistic regression and bootstrap optimism correction, ERSP classified the two groups with 70% accuracy. Responders but not non-responders showed a reduced ERSP compared to controls (P=0.0211; d=-0.558). Patients had reduced early ITPC (P=0.0001; d=-1.015) vs controls. responders compared to non-responders had increased PAC in the early (P=0.0215; d00.65) and in patients vs controls, in both the early (P=0.0002; d=0.57) and the late (P=0.0006; d=0.74) windows. No association emerged between ASSR metrics and symptoms severity. ConclusionsASSR is a candidate biomarker for antipsychotic treatment personalization. Only responders to treatment presented a significant gamma-band impairment, in line with previous literature on stabilized outpatients, but not non-responders, indicating that a distinct neurobiology could exist.

Background and HypothesisAntipsychotic medications are the first-line treatment for schizophrenia. However, around 40% of people with schizophrenia who are treated with antipsychotics could develop extrapyramidal side-effects (EPSE) including: 1) Dyskinesias, 2) Parkinsonism, 3) Akathisia, and 4) Dystonia. Study DesignWe conducted Genome-wide association (GWAS) and Epigenome-wide association (EWAS) meta-analysis of EPSE utilising data from previous schizophrenia case control studies. We integrated significant EWAS findings to an EPSE GWAS meta-analysis to enhance our understanding of the functional impact of common variants on EPSE. We also investigated whether polygenic risk scores (PRS) for schizophrenia, Parkinsons disease, and Lewy-body dementia could be predictive of EPSE development. Study ResultsThe top index SNP rs2709733 (A/G) from EPSE GWAS (p=2.214x10-7) mapped to a long intergenic non-protein coding RNA, LINC01162 with consistent effects across all cohorts. We identified 9 differentially methylated positions (DMPs) associated with EPSE when controlling for methylation age, sex, derived estimates of cell composition, smoking score, and schizophrenia PRS. Four of the DMPs cg14531564, cg20647656, cg12004641, cg22845912, and their affiliated genes (SDF4, ANKMY1, TNS1, SLA) were associated with the risk of developing EPSE and not with schizophrenia risk. Another DMP (cg12044923) which mapped to the STK32B gene, showed significant enrichment for association with risk of EPSE. ConclusionsOur study sheds new light on the potential biological mechanisms underlying EPSE development in schizophrenia, highlighting the importance of exploring both methylation shifts and common SNP associations. Further research with larger samples sizes and a focus on the role of STK32B are encouraged.

Formal thought disorder (FTD) is a key clinical factor in schizophrenia, but the neurobiological underpinnings remain unclear. In particular, relationship between FTD symptom dimensions and patterns of regional brain volume deficiencies in schizophrenia remain to be established in large cohorts. Even less is known about the cellular basis of FTD. Our study addresses these major obstacles based on a large multi-site cohort through the ENIGMA Schizophrenia Working Group (752 individuals with schizophrenia and 1256 controls), to unravel the neuroanatomy of positive, negative and total FTD in schizophrenia and their cellular bases. We used virtual histology tools to relate brain structural changes associated with FTD to cellular distributions in cortical regions. We identified distinct neural networks for positive and negative FTD. Both networks encompassed fronto-occipito-amygdalar brain regions, but negative FTD showed a relative sparing of orbitofrontal cortical thickness, while positive FTD also affected lateral temporal cortices. Virtual histology identified distinct transcriptomic fingerprints associated for both symptom dimensions. Negative FTD was linked to neuronal and astrocyte fingerprints, while positive FTD was also linked to microglial cell types. These findings relate different dimensions of FTD to distinct brain structural changes and their cellular underpinnings, improve our mechanistic understanding of these key psychotic symptoms.

BackgroundEfforts to define biologically grounded subtypes of schizophrenia have increasingly leveraged neuroimaging data and clustering algorithms. Such approaches aim to capture patient-level heterogeneity with potential clinical and mechanistic relevance. This review evaluates whether structural neuroimaging-derived subtypes can be robustly identified and meaningfully linked to clinical variation. MethodsA systematic review was conducted of peer-reviewed studies published between January 2015 and December 2024 that applied data-driven clustering algorithms to neuroimaging data to identify patient-level subtypes of individuals with schizophrenia or related spectrum disorders. Transdiagnostic studies and those focusing solely on case-control classification, or on feature-level clustering without individual-level subtype assignment, were excluded. ResultsEighteen studies met inclusion criteria. Most used structural MRI, but input features and clustering algorithms varied widely. Across studies, three broad neuroanatomical patterns were described: subtypes with widespread reductions in brain structure, those with regionally circumscribed abnormalities, and those with largely preserved profiles. However, the specific brain regions implicated within each category varied considerably between studies, and no subtype profile was consistently reproduced. Subtypes were not reliably associated with clinical features although there was a trend for higher clinical burden for the widespread subtypes. ConclusionsCurrent evidence is insufficient to determine whether macroscale neuroimaging features can define subtypes of schizophrenia that are biologically valid or clinically meaningful. Given the limited and inconsistent findings, the subtypes reported to date may reflect continuous variation within the disorder rather than discrete, biologically distinct entities. Advancing the field will require larger, harmonized datasets, standardized analytic pipelines, and rigorous external and longitudinal validation.

Background and HypothesisAuditory-verbal hallucinations (AVH), hearing voices without external speakers, are a core symptom of schizophrenia. A prominent account proposes that AVH reflect failures to recognize self-generated speech. Similar effects in hallucination-prone individuals suggest that these mechanisms span a continuum from subclinical to clinical manifestations. We used a self-other voice discrimination (SOVD) task, previously identified as a potential biomarker of self-disturbance, to assess self-recognition deficits in patients with (AVH+) and without (AVH-) a history of AVH, as well as in healthy individuals. Study Design41 schizophrenia patients (23 AVH+, 18 AVH-) and 40 healthy controls completed the SOVD task. In a follow-up experiment, 26 additional healthy participants performed a familiar-other voice discrimination task identical to SOVD, but without the self-voice. In patients, performance was tested in relation to symptom severity (PANSS), and in controls to hallucination proneness scores. Study ResultsSOVD performance was selectively impaired in AVH+ patients, while AVH- patients did not substantially differ from controls. Across groups, higher PANSS and hallucination proneness scores were specifically related to reduced self-voice recognition, with no impact on other-voice recognition. This effect did not extend to familiar-other voice discrimination. ConclusionsImpaired self-voice recognition is a promising selective marker of AVH occurrence in the acute phase of schizophrenia and extends to hallucination proneness in the general population. These findings support a dimensional view of hallucinations and point to deficits specific to self-voice processing rather than general voice perception. They also highlight SOVD as a promising cognitive biomarker of AVH, with direct implications for early identification and targeted interventions.

BackgroundAbout one in three persons with a schizophrenia related disorder (SRD) have elevated anti-gliadin IgG antibodies (AGA). This AGA positive (AGA+) subgroup of SRD clinically has a higher burden of negative symptoms and are symptoms associated with high functional impairments with a lack of effective therapeutics. Alterations in T cells have been demonstrated in SRD, and we have previously shown regulatory T cells (Tregs) are increased and correlate with fewer negative symptoms in persons with SRD compared with healthy controls. MethodsTo further elucidate the role of the immune system in AGA+ SRD pathology, we investigated the relationship of T cells and negative symptoms in 26 medicated and clinically stable persons with SRD. Participants had blood drawn; AGA-IgG measured by ELISA (AGA positive defined as [&ge;]20 U); had flow cytometry performed to quantify proportions of pan T cells (CD3+), helper T cells (CD3+CD4+), Tregs (CD3+CD4+CD25+Foxp3+), and activated Tregs (aTregs) (CD3+CD4+CD25+Foxp3+RA-); had serum cytokines measured; and completed the Scale for the Assessment of Negative Symptoms (SANS) to measure negative symptoms. Results46% of persons with SRD in this study were AGA+ and, in this group specifically, pan-T cells were correlated with worse SANS total, anhedonia, alogia, and avolition (p<0.05), while helper T cells and Tregs were correlated with less negative symptoms (respectively, SANS total and alogia; SANS total, anhedonia, alogia; P<0.05). AGA+ persons with SRD also had several elevated serum cytokines, corresponding with a broadly pro-inflammatory phenotype. ConclusionsThese hypothesis-generating findings highlight T cell dysfunction in AGA+ positive SRD, suggesting Tregs protecting against negative symptom severity but also an unidentified other T cell population to possibly be driving negative symptom severity.

Background and HypothesisVoice atypicalities are potential markers of clinical features of schizophrenia (e.g., negative symptoms). A recent meta-analysis identified an acoustic profile associated with schizophrenia (reduced pitch variability and increased pauses), but also highlighted shortcomings in the field: small sample sizes, little attention to the heterogeneity of the disorder, and to generalizing findings to diverse samples and languages. Study DesignWe provide a critical cumulative approach to vocal atypicalities in schizophrenia, where we conceptually and statistically build on previous studies. We aim at identifying a cross-linguistically reliable acoustic profile of schizophrenia and assessing sources of heterogeneity (symptomatology, pharmacotherapy, clinical and social characteristics). We relied on previous meta-analysis to build and analyze a large cross-linguistic dataset of audio recordings of 231 patients with schizophrenia and 238 matched controls (>4.000 recordings in Danish, German, Mandarin and Japanese). We used multilevel Bayesian modeling, contrasting meta-analytically informed and skeptical inferences. Study ResultsWe found only a minimal generalizable acoustic profile of schizophrenia (reduced pitch variability), while duration atypicalities replicated only in some languages. We identified reliable associations between acoustic profile and individual differences in clinical ratings of negative symptoms, medication, age and gender. However, these associations vary across languages. ConclusionsThe findings indicate that a strong cross-linguistically reliable acoustic profile of schizophrenia is unlikely. Rather, if we are to devise effective clinical applications able to target different ranges of patients, we need first to establish larger and more diverse cross-linguistic datasets, focus on individual differences, and build self-critical cumulative approaches.

BackgroundLipidomic alterations have been reported across schizophrenia (SCZ) and bipolar disorder (BD), but findings are heterogeneous and often overlap across diagnoses, limiting diagnostic specificity. Associations between lipid profiles and illness severity have also been inconsistent when assessed using single symptom scales, raising the possibility that unidimensional measures fail to capture biologically relevant variation. Whether plasma lipidomic alterations relate to multidimensional psychosis severity, and how they relate to polygenic liability, remains unclear. MethodsWe examined associations among psychiatric and cognitive polygenic risk scores (PRS), plasma lipidomics (361 species across 16 classes), and a machine-learning-derived severe psychosis probability score in a transdiagnostic cohort of individuals with SCZ or BD (PRS n=1,320; lipid subset n=428). Regression and lipid class enrichment analyses tested severity associations. Mediation and canonical correlation analyses assessed integrated genetic-lipid-severity relationships. ResultsSCZ-PRS (positive), BD-PRS (negative), and educational attainment PRS (negative) showed modest associations ({beta} = |0.02|) with severe psychosis probability. Lipid class enrichment analysis identified nine classes associated with severity, including increased sphingolipids (dSM, dCer), phosphatidylcholines (PC), triacylglycerides (TAG), and phosphatidylethanolamine plasmalogens (PE-P), alongside decreased phosphatidylcholine plasmalogens (PC-P). Most lipid class associations were robust to adjustment for diagnosis and medication. No significant mediation or shared multivariate genetic-lipid structure was observed. ConclusionsPlasma lipidomic variation tracks multidimensional psychosis severity across diagnostic boundaries. These findings suggest that lipidomic alterations may reflect transdiagnostic biological processes linked to illness burden that are not fully captured by categorical diagnoses, single symptom scales, or common-variant polygenic risk.

Cognitive heterogeneity is a core feature of schizophrenia (SCZ). Conventional approaches examine this heterogeneity using domain-specific scores, which may not fully reflect the underlying cognitive structure. In this study, a norm-anchored cognitive structural deviation (NCSD) framework was developed to examine such heterogeneity from a structure-informed perspective. The HC-derived latent cognitive structure (N-LCS) captured performance across the assessed tasks and remained stable under external validation in an independent cohort. Patients with SCZ showed greater global deviation from the N-LCS, along with altered loading directions of Wisconsin Card Sorting Test (WCST)-derived executive indicators which were consistent across robustness analyses, and altered correlation patterns among cognitive measures relative to HC. These features were quantified using three NCSD-derived indices: the cognitive normative deviation index (CNDI), loading pattern divergence (LPD), and correlation structure discrepancy (CSD). CNDI discriminated SCZ from HC with stable performance under cross-validation. LPD and CSD were associated with anxiety ratings, with LPD also showing a trend-level association with positive symptoms. Exploratory clustering identified a three-cluster solution with clear separation and moderate stability. Together, these findings show that cognitive heterogeneity in SCZ involves both global deviation from the N-LCS and structural alteration. NCSD provides a refined framework to characterize such heterogeneity and may inform precision psychiatry and functional recovery.