Schizophrenia Research

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

Background and Hypothesis Negative symptoms in schizophrenia spectrum disorder (SSD) are associated with poor functional outcomes and reduced quality of life; however, effective treatments remain limited. A better understanding of the underlying brain mechanisms is needed to develop better treatments. Neuroimaging studies implicate multiple brain networks in negative symptoms, though findings remain heterogeneous, potentially reflecting the multidimensionality of both symptoms and brain networks. Larger, more systematic dissections are required to identify the key hub(s) underlying negative symptoms. Study Design Structural MRI data from 394 participants (210 SSD, 184 healthy controls [HC]) were analyzed to identify cortical thickness and subcortical volume demonstrating both SSD-HC differences and associations with negative symptoms measured by the Brief Negative Symptom Scale (BNSS). Regions meeting both criteria were selected as seeds for resting-state functional connectivity analyses in 143 SSD patients to examine association with negative symptoms and their subdomains. Study Results The thalamus was the only region demonstrating significant structural abnormalities both in SSD and an association with BNSS total score (p-FDR<0.05). Functional-network-defined thalamic subregions were subsequently examined. Several thalamic hypoconnectivities were significantly corresponded with negative symptoms, involving thalamic subregions associated with the cortical default mode, somatosensory, medial temporal, and dorsal attention networks (p=0.001, corrected<0.05). Blunted affect showed the most extensive thalamic connectivity alterations, involving the striatum, cerebellum, and temporoparietal junction/superior temporal sulcus (TPJ-STS). Thalamic hypoconnectivity with TPJ-STS was also associated with overall negative symptoms and anhedonia. Conclusions This study identifies the thalamus as a central hub of negative symptom-related dysfunction in SSD and highlights specific thalamic subnetworks as potential targets for circuit-based interventions.

Background: Auditory verbal hallucinations (AVH) are among the most disabling symptoms of schizophrenia, yet the network-level mechanisms linking auditory dysfunction to hallucination severity remain poorly characterized, limiting targeted therapeutic development. Methods: Using resting-state fMRI and high-resolution surface-based parcellation (HCP-MMP), we examined auditory-language functional connectivity and mesoscale network organization in 56 patients with schizophrenia and 22 healthy controls (primary dataset, N=78). Pairwise auditory-language connectivity associations with hallucination severity (PANSS P3) were examined alongside auditory network community structure, assortativity, hub organization, and routing efficiency. To further characterize these parcel-level findings at the vertex level, we applied a region-growing approach to identify auditory-frontal connectivity patterns maximally associated with severity. In silico perturbation analyses tested the causal role of belt cortex connectivity. Key findings were independently replicated in 93 patients from the Human Connectome Project for Early Psychosis (HCP-EP), for a combined total of 171 participants. Results: Auditory-language connectivity disruptions were concentrated in belt cortex and specifically implicated ventral what-stream connections, with a vertex-wise analysis converging on the same anatomy. Auditory network segregation scaled with hallucination severity, with belt cortex emerging as the primary integrative hub governing auditory-to-language routing efficiency. Perturbation analyses showed that strengthening earlier hierarchy auditory regions reduced network segregation more than strengthening later-hierarchy regions. Reduced belt cortex coupling and elevated network segregation replicated independently in the HCP-EP sample. Conclusions: Auditory network disorganization scales with hallucination severity and replicates across independent samples, with belt cortex as the critical locus of connectivity disruption and network integration failure, identifying it as a candidate neuromodulatory target.

Schizophrenia spectrum disorders (SSD) have been linked to immune dysregulation and altered intestinal barrier function, although findings across studies remain inconsistent. The present study investigated circulating markers of intestinal permeability and immune activation in individuals with early-stage SSD and healthy controls and examined their associations with clinical outcomes. Serum concentrations of intestinal fatty acid-binding protein (iFABP), zonulin, soluble CD14 (sCD14), bactericidal/permeability-increasing protein (BPI), and lipopolysaccharide-binding protein (LBP) were measured in 36 patients with SSD at baseline and one-year follow-up and in 36 matched healthy controls. Linear mixed-effects models adjusted for age, sex, and body mass index (BMI) were used to evaluate group differences and longitudinal changes. No biomarker differences between patients and controls, and no longitudinal changes within patients, remained statistically significant after correction for multiple testing. Similarly, biomarker concentrations were not associated with symptom severity, global functioning, or neutrophil-to-lymphocyte ratio (NLR). Exploratory analyses identified a robust positive association between BMI and zonulin concentrations and additional associations among iFABP, LBP, and sCD14. Exploratory mixed-effects models identified a negative non-significant association between iFABP and sCD14 after adjustment for age, sex, and BMI. Overall, the findings do not support a generalized alteration of gut permeability or immune activation markers in SSD. Instead, they suggest that variation in gut-related biomarkers may be more strongly influenced by metabolic and individual factors than by diagnosis or current symptom severity.

Schizophrenia may involve a fundamental disruption in the ability to construct a shared understanding of social reality, yet conventional neuroimaging studies have largely examined social cognition using simplified and highly structured paradigms that may not capture how individuals interpret complex and ambiguous interpersonal events in everyday life. Using an ecologically valid naturalistic fMRI paradigm, we examined shared and paranoia-related neural representations during ambiguous social narrative processing in 38 patients with schizophrenia and 46 healthy controls. Intersubject correlation was used to quantify neural convergence across individuals, whereas intersubject representational similarity analysis was used to examine how individual differences in paranoid ideation were reflected in neural representations. Compared with healthy controls, patients with schizophrenia showed reduced neural convergence within distributed systems supporting social inference, contextual integration, and salience attribution, including temporoparietal, temporal, insular, and inferior frontal regions. Furthermore, paranoid ideation was associated with altered neural representational structure. In healthy controls, higher paranoia was linked to reduced neural similarity across social-cognitive and affective regions, suggesting reduced convergence toward shared interpretations of ambiguous social information. In schizophrenia, paranoia-related representations showed sparse within-group associations but elevated patient-control differences across a distributed social-affective circuit, indicating a reorganization rather than a simple amplification of paranoia-related processing. Together, these findings demonstrate that schizophrenia involves both impaired alignment of neural responses during shared social meaning construction and organization of paranoia-related representations, providing an ecologically grounded framework for understanding abnormal social inference in psychosis.

Background: Approximately 25% of individuals with 22q11.2 deletion syndrome (22q11DS) develop a psychotic disorder, and the syndrome shares key neurodevelopmental features with psychosis in the general population. The olfactory system develops early in utero, providing a window into gestational disruptions relevant to psychosis risk. We hypothesized that 22q11DS would show impairments in olfactory function and structural anomalies of the olfactory system relative to psychosis spectrum (PS) youth without a known genetic syndrome and typically developing controls (TD). Methods: Participants included individuals with 22q11DS (n=101), PS (n=56), and TD (n=52). Sinonasal symptoms, odor identification, and discrimination (Sniffin' Sticks) behaviorally. Structural 3T MRI measured olfactory bulb volume, sulcus depth, and sulcus length. Sample sizes vary per analysis. Results: Relative to TD, 22q11DS showed elevated sinonasal burden (p<.001), lower odor identification (p<.001), and lower odor discrimination (p<.001). PS showed elevated sinonasal burden (p<.001) and marginally lower odor identification (p=.06), but no discrimination deficit. Olfactory bulb volume was significantly smaller in 22q11DS versus TD (p=.007, r=.39); PS showed a non-significant trend (p=.07). Olfactory sulcus depth (p=.52) and length (p=.82) did not differ across groups. Conclusions: 22q11DS is associated with elevated sinonasal burden, robust olfactory identification and discrimination deficits exceeding those of PS and reduced olfactory bulb volume. The co-occurrence of functional deficits and reduced bulb volume without sulcal anomalies may distinguish the 22q11DS olfactory phenotype from that of PS. These hypothesis-generating findings are consistent with partially dissociable neurodevelopmental mechanisms and support the utility of 22q11DS as a genetic model for psychosis risk.

Background: Interoception refers to the processing, integration, interpretation, and regulation of bodily signals by the brain. It is crucial to motivational and affective functioning such as subjective experience of arousal (i.e., intensity of emotion). Previous studies found altered self- report of arousal in people with schizophrenia, but the underlying biological mechanism is unclear. This study aimed to investigate interoceptive processing and emotional experience in schizophrenia by triangulating self-report, cardiac dynamics, and heartbeat-evoked potential (HEP; an event-related potential that reflects cortical processing of heartbeats). Methods: A total of 39 participants with schizophrenia spectrum disorders (SZ; 36% female) and 31 healthy controls (HC; 35% female) reported subjective arousal level when viewing images of varying emotional intensity while electroencephalogram and electrocardiogram were being recorded. Results: We found that intense images led to larger heartrate decelerations and higher subjective arousal ratings in HC, but did not modulate heartrate changes in SZ and were less predictive of their subjective ratings. Subjective ratings were predictive of cardiac dynamics in HC, but not in SZ. SZ showed a less negative HEP amplitude than HC when viewing less intense images. Lastly, SZ with less severe positive and negative symptoms exhibited cardiac dynamics more similar to those of HC. Conclusions: These findings suggest both reduced cardiac reactivity to emotional stimuli and a disconnect between interoceptive afferent signals and cortical processing, leading to different subjective emotional experience in people with schizophrenia. Studying interoception using a multimodal approach may reveal important insights into the underlying mechanisms of altered emotional experience in schizophrenia.

Objective: Cognitive models of psychosis implicate maladaptive core schemas in the development and emergence of psychotic symptoms, but no study has tested temporal dynamics between schemas and psychotic symptoms in a large sample of clinical high-risk (CHR) youth. Given their sizable role in cognitive behavioral therapies, the first-line treatment for CHR youth, core schemas may be key to both symptom development and treatment in this population. Methods: Participants were 578 CHR individuals from the second North American Prodrome Longitudinal Study (NAPLS-2) assessed across five timepoints. Time-lagged mixed-effects models tested forward and reverse paths for each Brief Core Schema Scales subscale with both psychotic symptom and functioning changes, controlling for autoregressive effects, time-varying depression, and linear time. Results: Twenty of 36 schema outcome pairs showed significant prospective associations. Negative-other schemas were prospectively associated with worsening across nearly all psychosis symptom and functioning domains. Suspiciousness exhibited bidirectional associations with all four schema subscales. Grandiose ideas were uniquely prospectively associated with positive-self and negative-other schemas. Positive schemas were prospectively associated with decreases in suspiciousness, negative symptoms, and improvements in functioning. Effects were largely independent of depressive symptoms and robust across sensitivity analyses, with partial attenuation of self-schema effects on suspiciousness. Conclusions: Core schemas were prospectively associated with psychosis symptom and functioning change in CHR youth, with symptom-domain specificity and bidirectionality. These findings extend cognitive models of psychosis into CHR syndromes and highlight schemas as potentially modifiable treatment targets to improve outcomes in this population.

We conducted an open-label pilot study of bilateral nucleus accumbens-anterior limb of the internal capsule (NAc-ALIC) deep brain stimulation (DBS) in three patients with treatment-resistant schizophrenia (TRS). Clinical symptoms, global functioning, cognition, stimulation parameters and intracranial local field potential (LFP) were assessed over 24 weeks. Two patients met the prespecified clinical response criterion, defined as a [&ge;]40% reduction in Positive and Negative Syndrome Scale (PANSS) total score, by week 8 and showed PANSS reductions of 69.0% and 69.4%, respectively, at week 24. The third patient showed a 18.7% reduction at week 24. Responders showed improvements in global functioning and selected cognitive domains. Longitudinal LFP recordings revealed increased gamma-band relative power and reduced theta-band activity in responders, whereas these changes were less consistent in the non-responder. DBS was generally well tolerated, with transient stimulation-related adverse effects resolving after reprogramming. These findings provide preliminary clinical evidence supporting further investigation of NAc-ALIC DBS in TRS and suggest that individualized programming and intracranial physiological measures may contribute to the identification of treatment-response signatures.

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

Objective. NMDA-receptor hypofunction has been implicated as a core pathophysiological mechanism in schizophrenia, but conflicting evidence exists regarding the locus of the hypofunction--i.e. predominantly affecting receptors on pyramidal neurons or interneurons. To investigate the locus of NMDA-receptor hypofunction we integrated imaging data from humans and mice with biophysical model simulations. Methods. Translational imaging measures--intrinsic neural timescales (INT) and spontaneous co-activation pattern similarity--were investigated in three schizophrenia-relevant mouse models (chronic ketamine administration, n=6; Df(16)A+/-, n=7; and SETD1A+/-, n=9) and matched control mice (n=5; n=7; and n=8, respectively) using two-photon calcium imaging, and individuals with schizophrenia (n=127) and matched non-clinical controls (n=152) using functional MRI. The stabilized supralinear network biophysical model was used to simulate NMDA-receptor hypofunction and its impact on the translational imaging measures. Results. We identified convergent neural phenotypes of shorter intrinsic neural timescales (INT) and reduced spontaneous co-activation pattern similarity in both the schizophrenia-relevant mouse models and the individuals with schizophrenia compared to matched controls. In silico simulations using the stabilized supralinear network biophysical model recapitulated the convergent neural phenotypes through reduced excitatory-to-excitatory connection strength (i.e. NMDA-receptor hypofunction on pyramidal neurons) and predicted that INT and pattern similarity are correlated; this prediction was confirmed in both the mouse and human data. Conclusions. These results identify NMDA-receptor hypofunction on pyramidal neurons as a general and translationally valid mechanism for NMDA-receptor hypofunction in schizophrenia. These convergent translational findings suggest prioritizing the development of treatments for schizophrenia that increase recurrent excitation.

The potential role of the cerebellum in the pathophysiology of schizophrenia (SCZ) has received relatively insufficient attention. Prior studies characterized cerebellar abnormalities mainly at the group level, without fully considering the heterogeneity of the disease. Here, we applied a machine learning approach (Subtype and Stage Inference, SuStaIn) to cross-sectional 3D volumetric MRIs of the cerebellum, including 1,588 individuals with SCZ (638 females; mean age: 31.9 +/- 12.0 years) and 2,341 healthy controls (HC) (1,041 females; mean age: 33.3 +/- 13.6 years), from 17 sites worldwide. SuStaIn identified three distinct spatiotemporal trajectories in cerebellar gray matter volume (GMV) reduction, respectively originating in lobule X (subtype 1), lobule III (subtype 2) and lobule VIIb (subtype 3), with subtypes 1 and 3 corresponding to the posterior lobe and subtype 2 to the anterior lobe. These cross-sectionally inferred trajectories were replicated in two independent samples of 1,334 and 530 patients, respectively. Multimodal analyses using neuroimaging, transcriptomic and behavioral data revealed subtype-specific biological characteristics in brain morphological patterns, cerebellar-cortical connectivity, gene expression and clinical symptoms. Specifically, subtype-related genes were enriched in metabolism-related processes and immunity-related processes, respectively, in subtype 1 and subtype 2; subtype 3 showed more severe brain abnormalities and worse cognitive symptoms. Treatment data from 381 patients, with up to 12 months of follow-up, revealed poorer response to antipsychotic medications (APM) in subtype 2 and subtype 3, but better response to transcranial magnetic stimulation (TMS) in subtype 1, which also had worse emotion-related symptoms. Together, our findings offer a comprehensive characterization of the heterogeneity of cerebellar pathophysiological progresses in SCZ, which may help in developing future clinical stratification and targeted intervention strategies.

Background: Predictive-processing accounts propose altered prediction-error signaling in psychosis. However, event-related potential (ERP) findings in first-episode psychosis (FEP) are inconsistent and focused predominantly on mismatch negativity (MMN). Examining anticipatory and later post-stimulus ERP responses alongside MMN within a single passive paradigm may broaden the assessment of predictive processing in FEP. Methods: 34 participants with non-affective FEP and 34 healthy controls (HC) underwent EEG during a passive auditory pattern-based paradigm. Mean amplitudes of contingent negative variation (CNV), MMN, and post-imperative negative variation (PINV) were quantified at five frontocentral electrodes. Exploratory analyses examined N1 and P2 mean amplitudes. Mixed models tested group, electrode, and group-by- electrode effects adjusting for age, sex and years of education. Regressions examined ERP associations with psychotic-like experiences, neurocognition, and social cognition across groups, and with symptoms, functioning, and antipsychotic dose within FEP. Results: FEP participants reported more psychotic-like experiences and showed poorer global and social cognition than HC (all p-FDR [&le;] .042). Standardized adjusted FEP-HC differences at FCz were nonsignificant for CNV ({beta} = -0.46), MMN ({beta} = -0.30), and PINV ({beta} = -0.10; all p-FDR [&ge;] .265). Exploratory analyses identified lower P2 amplitude in FEP at FCz ({beta} = -0.73; p-FDR = .019) and in the averaged frontocentral ROI ({beta} = -0.64; p-FDR = .027). No ERP-phenotype associations survived FDR correction. Conclusions: Despite phenotypic differences between FEP and HC, no significant differences emerged in the primary ERP indices of predictive processing examined. The exploratory P2 finding and its possible relationship to predictive processing and frontal dysfunction in FEP warrant further investigation.

Altered white matter microstructure, commonly indexed by fractional anisotropy (FA), has been reported in individuals at clinical high-risk of psychosis (CHR-P) across multiple white matter tracts. However, the relationship between these alterations and later transition to psychosis remains unclear. To address this gap, we investigated whether baseline and longitudinally updated FA measurements were associated with risk of transition to psychosis in a large cohort of individuals at CHR-P. We analysed diffusion tensor imaging data from N = 205 participants at CHR-P, 23 of whom developed psychosis within 3 years of follow-up. Data were collected at baseline, 6 months, and 12 months. Associations between global and tract-specific FA and transition risk were examined using Cox proportional hazards models of baseline data and longitudinally updated data. Point estimates were directionally consistent, with hazard ratios <1 for FA across all white matter tracts in both baseline and longitudinal models. Associations reached nominal significance in the hippocampal cingulum, anterior thalamic radiation, and forceps minor, but none of these remained significant after correcting for multiple comparisons (pcorr > .05). The directionally consistent estimates are compatible with small, distributed effects across multiple white matter pathways being associated with transition to psychosis, although this requires replication. Longitudinally updated FA measurements did not yield stronger associations than were available from baseline imaging data alone. Studies at an even larger scale are needed to establish whether these associations are robust and clinically meaningful.

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

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

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

BACKGROUND: Clinical high risk (CHR) for psychosis is characterized by substantial heterogeneity in symptoms, functioning, and outcomes. Although distributed resting-state functional connectivity (RSFC) abnormalities have been reported, it remains unclear whether this heterogeneity can be organized into consistent multivariate brain-symptom dimensions and clinically meaningful subgroups. METHODS: We analyzed RSFC and 34 clinical variables from 701 CHR participants in the Accelerating Medicines Partnership Schizophrenia Program (AMP SCZ). Partial least squares analysis identified latent brain-symptom dimensions, which were further examined using transcriptomic annotation, independent psychosocial and cognitive measures, hierarchical clustering, and Month 2 follow-up data. RESULTS: Two significant brain-symptom dimensions emerged. The first reflected general psychopathology and was associated with somatomotor-salience and higher-order connectivity, with enrichment for genes related to neuronal development. The second, capturing symptom differentiation, spanned negative/internalizing features with psychobehavioral overactivation and involved cerebellar-thalamic-somatomotor circuitry, with enrichment for genes related to synaptic signaling. These dimensions showed dissociable associations with broader psychosocial and cognitive measures, and their loading patterns were substantially reproducible at Month 2. Clustering based on these dimensions identified two biotypes with distinct clinical and connectivity profiles that remained broadly similar at Month 2 despite divergent short-term RSFC changes. CONCLUSIONS: These findings support complementary dimensional and categorical representations of CHR heterogeneity that link clinical variation with distributed brain connectivity and molecular signatures, while demonstrating short-term reproducibility of the identified dimensions and divergent RSFC changes across biotypes. This multilevel framework may help characterize biologically meaningful variation in psychosis risk.

Importance: Anhedonia, social withdrawal and executive deficits represent transdiagnostic symptoms in depression, schizophrenia and addition, yet transdiagnostic brain volumetric alterations and their contribution to these symptom domains have not been systematically characterized. Objective: To determine common and disorder-specific gray matter deficits in patients with schizophrenia (SZ), major depression disorder (MDD) and alcohol use disorder (AUD) compared to heathy controls. Data Sources: A comprehensive literature search using three databases including PubMed, Web of Science and PsycInfo (between January 2000 to March 2024) as well as searches on review articles. Study Selection: Studies had to be published in English, reporting whole-brain results, comparing patients and healthy controls. Data Extraction and Synthesis: This meta-analysis adhered to the PRISMA guidelines and was pre-registered (https://osf.io/s57uq) prior to data analysis. Data was independently extracted and verified by 3 contributors, and statistical brain maps were generated using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) random-effects model. 147 VBM studies encompassing 90 Schizophrenia, 44 MDD and 13 AUD studies were finally included. Main Outcomes and Measures: Statistical maps of common and disorder-specific gray matter deficits in patients versus healthy controls are presented. Statistical inference utilized permutation tests, with threshold at p < .0025 and cluster extent of 10 voxels. Heterogeneity was evaluated using the I2 statistic and publication bias using Eggers regression test. Results: Capitalizing on a coordinate-based meta-analysis involving n=13,041 participants, we found shared GMV alterations in the ventromedial prefrontal cortex, ventral anterior cingulate cortex, insula, superior temporal gyrus. On the network level, we found robust functional interactions of the identified shared regions with the cortical midline structures as well as social and theory of mind-related behavioral functions. Subsequent characterization analyses highlighted the involvement of dopaminergic and serotonergic neurotransmitters as well as associated genetic annotations. Conclusions and Relevance: Overall, the present meta-analysis found common as well as separate GMV abnormalities in schizophrenia, major depressive disorder and alcohol use disorder suggesting a common neurostructural substrate and treatment target for social withdrawal and anhedonia across these disorders. Keywords: alcohol-use disorder, depression, meta-analysis, schizophrenia, voxel-based morphometry

Background: Schizophrenia is characterized by widespread structural and functional brain abnormalities, yet it remains unclear whether these alterations converge across imaging modalities and whether such convergence is associated with underlying cellular distribution and evolution of the human cortex. Methods: We performed coordinate-based meta-analyses of seven whole-brain neuroimaging modalities, including cortical thickness, gyrification, voxel-based morphometry, amplitude of low-frequency fluctuations, regional homogeneity, regional cerebral blood flow (all based on magnetic resonance imaging), and glucose metabolism based on [18F]-Fluorodeoxyglucose positron emission tomography. The analyses included 200 studies (209 datasets) comprising 11,794 patients with schizophrenia and 10,342 healthy controls. After single-modality meta-analyses using seed-based d-mapping, the meta-analytic result maps were integrated using orthonormal projective non-negative matrix factorization. Finally, the resulting component maps were related to maps of cortical cell type-specific gene expression and human-specific cortical evolution. Results: Multimodal integration identified a robust convergence pattern centered in bilateral insular, mediofrontal, and lateral sensorimotor cortices, with the strongest contributions from regional homogeneity, cerebral blood flow, and amplitude of low-frequency fluctuations. The convergence pattern showed significant spatial correspondence with cortical gene expression profiles of astrocytes, microglia, and oligodendrocyte progenitor cells. In contrast, we found no evidence for a preferential localization to regions of human-specific cortical expansion or connectivity. Conclusions: Structural and functional brain abnormalities in schizophrenia converge on an insular-mediofrontal-sensorimotor pattern that aligns with glial gene expression profiles. These results support glia-related regional vulnerability as an organizing principle of multimodal brain abnormalities in schizophrenia.