Schizophrenia is a complex psychiatric disorder with significant genetic and clinical heterogeneity. Although numerous rare copy number variations (CNVs) with high risk for schizophrenia have been identified, they show no obvious overlap in gene content or function. We hypothesized that the downstream effects of schizophrenia-associated CNVs converge on shared molecular pathways. To test this, we profiled the prefrontal cortex of five schizophrenia-associated CNV mouse models - 15q13.3del, 3q29del, 1q21.1del, 22q11.2del, and 16p11.2dup - using single-cell RNA sequencing across two developmental stages: adolescence and adulthood. From 292,943 high-quality single-cell transcriptomes, we identified distinct age- and cell type-specific patterns of differential gene expression and biological pathway perturbations in each model. Rather than converging on a shared molecular mechanism, each CNV affected unique cellular pathways in a developmentally dynamic manner. Notably, genes dysregulated in deep-layer corticothalamic projection neurons from 15q13.3del and 16p11.2dup models, and intratelencephalic neurons from adult 22q11.2del mice, showed enrichment for schizophrenia-SNP heritability. These results support a model in which rare CNVs contribute to schizophrenia genetic risk through developmentally dynamic, distinct pathways rather than through a shared molecular mechanism.
Blunted affect is a transdiagnostic feature that impairs social functioning across psychiatric conditions, including schizophrenia and autism. We quantified facial expression patterns and subjective emotional experience during standardized social interaction in 38 individuals with schizophrenia, 16 autistic adults, and 39 neurotypical adults using automated facial expression analysis. During social interaction, individuals with schizophrenia displayed more neutral expressions and reduced valence and arousal compared to neurotypical adults, whereas autistic adults showed typical facial expressions but subjectively experienced lower positive affect. These findings highlight distinct emotional profiles in schizophrenia and autism within social interactions, with blunted facial affect characterizing schizophrenia and reduced subjective positive affect characterizing autism.
Cognitive impairment is a core feature of schizophrenia, yet the biological basis has not been established. Redox dysregulation has been implicated in cognitive impairment of patients with schizophrenia but evidence in early-stage, drug-naïve patients is limited and inconsistent. Herein we examined glutathione-related redox markers and the associations with cognition in 96 drug-naïve, first-episode schizophrenia patients and 94 matched controls. Patients with schizophrenia exhibited a systemic redox imbalance that was characterized by increased glutathione (GSH) and glutathione disulfide (GSSG) levels with a reduced GSH-to-GSSG ratio, while glutathione reductase activity remained unchanged. Marked cognitive deficits were observed across all domains. Among redox markers, GSSG showed robust and consistent negative associations with global cognition and multiple domains, and emerged as an independent predictor after covariate adjustment. In contrast, GSH and the GSH-to-GSSG ratio had weaker and less stable associations. No reliable relationships were demonstrated between redox markers and clinical symptoms after correction for multiple comparisons. These findings are the basis for a functionally asymmetric redox dysregulation model, in which increased oxidative load, indexed by GSSG, has a central role in early cognitive impairment, relatively independent of antioxidant capacity. These findings highlight GSSG as a candidate biomarker for early cognitive impairment and suggest redox-targeted interventions as a potential therapeutic strategy in schizophrenia.
Schizophrenia has been associated with disturbances in perceiving affordances, i.e. action possibilities offered by the environment. However, empirical research has largely relied on static laboratory tasks that poorly capture the dynamic perception-action loops of everyday environments. In this exploratory study, we used immersive virtual reality (VR) to examine environmental exploration and interaction in patients with schizophrenia and healthy controls (n = 19 each). Participants completed baseline questionnaires including self-report measures of anomalous world experience and were exposed to natural and urban 360° video environments and an interactive VR game. Their field of view was recorded and manually coded using a predefined coding scheme. Subjective affect, stress, and presence were assessed before and after VR exposure. Patients with schizophrenia showed reduced visual exploration of the environments, reflected by fewer gaze shifts per minute compared with controls, particularly in urban scenes. In the interactive VR game, overall object interaction patterns were comparable, although patients showed a tendency toward longer latencies before initiating social interaction with a virtual non-player character. Reduced fixation of the character's face was strongly associated with domains of anomalous world experience related to other persons, language, and atmosphere. Qualitative observations further suggested that immersive environments could interact with the sense-making of psychotic experiences in a few participants. Although preliminary given the limited sample size, these findings indicate subtle alterations in how patients with schizophrenia explore their surroundings, while basic object interaction remains preserved. Immersive VR paradigms may provide a promising experimental platform to investigate altered subject-world relations in psychosis.
Cognitive deficits are a core feature of schizophrenia, emerging early and strongly influencing functional outcomes. However, the role of the nitric oxide (NO) signaling pathway in drug-naïve, first-episode schizophrenia remains unclear. To investigate the relationship between the nitric oxide synthase (NOS) system and cognitive function, we studied 98 first-episode, drug-naïve schizophrenia patients and 96 matched healthy controls. Plasma levels of inducible NOS (iNOS), total NOS (TNOS), the iNOS/TNOS ratio, malondialdehyde (MDA), and hydrogen peroxide (H₂O₂) were measured. Psychopathological symptoms and cognitive performance were assessed using the Positive and Negative Syndrome Scale (PANSS) and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), respectively. Group differences and associations among NOS markers, cognitive domains, and symptom severity were examined. Patients exhibited marked NOS system dysfunction, characterized by reduced iNOS and TNOS levels, a lower iNOS/TNOS ratio, elevated MDA levels, and reduced H₂O₂ concentrations. TNOS levels were positively associated with RBANS total score and multiple cognitive domains, independent of PANSS total score, whereas iNOS levels were associated only with immediate memory. The iNOS/TNOS ratio showed no independent association with cognition. In addition, TNOS levels were correlated with PANSS total score, suggesting that overall NOS function reflects disease burden. These findings indicate that early schizophrenia is characterized by NOS system dysfunction. Overall NOS activity, rather than relative NOS subtype expression, is closely linked to multidimensional cognitive impairment and is partly independent of symptom severity.
The cerebellum has been implicated in schizophrenia-related structural and functional deficits, with posterior Crus I and II most consistently affected. Source-based morphometry (SBM) involves applying independent component analysis to gray matter volume to identify spatially distinct structural networks that covary across individuals. We applied SBM and voxel-based morphometry (VBM) to cerebellar structural imaging data to identify patterns of gray matter differences across individuals with schizophrenia (SZ), bipolar disorder with psychotic features (BDwP), and healthy controls (HC). Data were drawn from the Psychosis Human Connectome Project (P-HCP) and included 168 participants: 85 with SZ, 36 with BDwP, and 47 HC. T1-weighted images were processed using the ENIGMA Cerebellum Volumetrics Pipeline, and ICA decompositions were performed using the SBM module of the GIFT Toolbox. One independent component (IC) showed a significant diagnostic group effect (p < 0.05, Bonferroni-corrected), differentiating SZ from HC and BDwP. This cerebellar network included vermis VIIIa, bilateral Crus I, and right lobule IX with positive loadings, and bilateral Crus I and lobule IX with negative loadings. Voxel-based morphometry showed reduced GM volume in negatively loaded regions in SZ. Composite cognitive performance correlated with GM volume (r = 0.27, p < 0.001) and network loadings (r = -0.29, p < 0.001). Mediation analyses showed a strong direct diagnostic effect on IC loadings (-0.42), with small, nonsignificant indirect effects via cognition. These findings identify a cerebellar structural network that differentiates schizophrenia from bipolar disorder and controls, underscoring the cerebellum's unique contribution to the neurobiology of schizophrenia.
Schizophrenia is a complex neuropsychiatric disorder manifesting with diverse positive and negative symptoms as well as cognitive impairments. Current antipsychotics primarily address positive symptoms and frequently cause substantial side effects, highlighting the need for novel therapeutics targeting alternative pathomechanisms. Animal models are widely used to investigate schizophrenia's neurobiology and guide drug discovery, yet their clinical relevance for proof-of-concept (PoC) studies remains controversial. This Current Opinion critically examines the key limitations of animal models in schizophrenia research from a clinical perspective. The disorder's multifaceted nature, involving genetic, environmental, and neurodevelopmental factors, makes accurate replication in animals challenging. Additionally, core human-specific symptoms, like hallucinations and thought disorders, cannot directly be modeled, although some underlying cross-species constructs can be operationalized. We argue that animal models are most informative when used to test specific, well-defined mechanistic hypotheses and when readouts are anchored to human-relevant biomarkers and neurophysiology, rather than interpreted as proxies for diagnostic categories. Accordingly, translational utility is not uniform: predictive performance depends on the induction paradigm, the construct validity of behavioral and neurophysiological readouts, and the clinical endpoint being modeled. We advocate for close collaboration between preclinical and clinical researchers to refine existing models, establish new and translationally relevant paradigms, and clearly define their interpretive scope. Integrating complementary advanced in vitro and in silico models may enhance mechanistic understanding and help prioritize hypotheses and candidates. Still, these approaches should be viewed as adjuncts, not superior replacements, because they cannot yet capture the circuit- and systems-level dynamics relevant to schizophrenia.
Schizophrenia is often conceptualized as a brain network disorder, yet the organizational principles and heterogeneity underlying widespread cortical abnormalities remain poorly understood. Leveraging multisite MRI data from 3,958 individuals diagnosed with schizophrenia and 5,489 neurotypical individuals, we studied the cortical organization and its subtyping by analyzing individualized cortical network similarity. We used eigenvector decompositions to study spatial patterning of the gradients and graph theory to study small-world topology. Individuals with schizophrenia showed widespread alterations of gradient loadings, which followed inferior-superior and frontal-temporal axes. Alterations in small-world topology were localized in key network hubs, including the insula and anterior cingulate cortex. Brain-symptom association analyses identified a latent dimension linking disorganization symptoms to topological alterations. Finally, clustering cortical alterations identified two robust subtypes, characterized by divergent anterior cingulate (S1) versus temporoparietal (S2) thickness differences aligned with the intrinsic gradient-topology patterns. Both subtypes were present early in the illness and stable across disease stages and age groups. These findings reveal systematic disruptions of cortical organization in schizophrenia, providing a network-level framework for macroscale brain organization and inter-individual heterogeneity.
Tardive dyskinesia (TD) is a persistent, iatrogenic movement disorder arising from long-term use of dopamine receptor antagonists, particularly antipsychotics; however, its clinical and economic impact among adults with schizophrenia remains poorly characterized in real-world settings. This retrospective, matched-cohort analysis used two large U.S. claims databases (PharMetrics Plus and MarketScan Medicaid) to evaluate treatment patterns, healthcare resource utilization (HCRU), and costs among adults with schizophrenia with and without TD. Patients were propensity score matched 1:5 for age, sex, index year, and comorbidity burden. TD was identified in 2.2-2.6% of records, with affected patients being older, more often female, and exhibiting greater medical complexity than those without TD. Following matching, TD was associated with greater use of higher-risk antipsychotic regimens, including nearly double the use of first-generation agents and long-acting injectables, and a twofold to fourfold greater anticholinergic burden. Adherence to antipsychotic therapy was comparable between groups. Across both databases, patients with TD demonstrated substantially greater HCRU and costs, with all-cause expenditures elevated by 56-66% and schizophrenia-related costs by 49-103% versus patients without TD. Approximately one in five individuals with TD received a vesicular monoamine transporter 2 inhibitor, with these patients exhibiting the highest HCRU and costs, suggesting greater disease burden and treatment intensity. TD imposes a considerable clinical and economic burden in schizophrenia underscoring the need for earlier recognition, evidence-based treatment, and preventative strategies, including rational antipsychotic selection and proactive monitoring, to mitigate the long-term impact of TD.
Clinical decision support systems for psychiatric disorders such as schizophrenia can benefit from machine learning models based on neuroimaging data for objective diagnosis, prognosis, and effective treatment selection. Deep learning (DL) models promise to be suitable for this task since they can detect complex patterns in images without the need for prior information about candidate regions. Their downside, however, is the lack of transparency about the decision process. Explainable AI methods address this problem and might be helpful in the clinical translation of DL applications as well as potential biomarker indication. The current study qualitatively and quantitatively evaluates seven DL architectures frequently employed in medical image analyses with gradient-weighted class activation mapping (Grad-CAM) for plausibility and finds that only two of the seven models base their decisions in a schizophrenia classification task on plausible structural brain information, despite similar classification performance. Furthermore, we develop an approach to translate the saliency maps from the Grad-CAM into universally interpretable anatomical markers of schizophrenia and find candidate regions corresponding to known markers of schizophrenia. To conclude, this study demonstrates the necessity of using explainable methods alongside DL approaches and the feasibility to derive biomarkers with such methods.
Herbal medicine is widely used as an adjunctive treatment for schizophrenia, but evidence remains limited. To evaluate the effectiveness and safety of East Asian herbal medicine combined with antipsychotics in schizophrenia spectrum disorders. Ten sources including MEDLINE, EMBASE and CENTRAL were searched up to January 2025 for randomised controlled trials comparing East Asian herbal medicine combined with antipsychotics versus antipsychotics alone. Primary outcome was the overall symptom scores (PANSS/BPRS). Secondary outcomes included adverse events, negative and positive symptom scores, response rates, social function, quality of life, recurrence, and adherence. Risk of bias was assessed using the Cochrane RoB 2, and evidence certainty using GRADE. 270 studies comprising 26,053 participants were included. East Asian herbal medicine combined with standard-dose antipsychotics improved overall symptom (SMD - 1.38, 95% CI - 1.60 to -1.17; 181 studies, 18,569 participants; low-certainty evidence) and reduced adverse events (RR 0.56, 95% CI 0.51-0.62; 92 studies, 8983 participants; low-certainty evidence) versus antipsychotics alone. East Asian herbal medicine combined with low-dose antipsychotics versus standard-dose antipsychotics showed symptom improvement (SMD - 0.92, 95% CI - 1.54- - 0.29; 25 studies, 1907 participants; low-certainty evidence) and fewer adverse events (RR 0.44, 95% CI 0.34-0.58; 6 studies, 450 participants; low-certainty evidence). Low-certainty evidence suggests that East Asian herbal medicine as an adjunct to antipsychotics may improve symptoms and reduce adverse events in schizophrenia. However, most studies raised concerns regarding the risk of bias, and potential publication bias was suspected. Results require cautious interpretation and further high-quality studies are needed.
Conventional schizophrenia treatment guidelines do not adequately address all clinically important issues in routine practice. This study aimed to update the 2021 expert consensus of the Japanese Society of Clinical Neuropsychopharmacology (JSCNP) to reflect the current clinical landscape. A total of 154 board-certified psychiatrists from the JSCNP and the Japanese Society of Neuropsychopharmacology (JSNP) evaluated treatment options across 21 clinically relevant situations using a 9-point Likert scale (1 = "strongly disagree"; 9 = "strongly agree"); the response rate was 44%. First-line antipsychotics varied by predominant symptoms: risperidone, brexpiprazole, olanzapine, paliperidone, and blonanserin for positive symptoms; aripiprazole and brexpiprazole for negative symptoms and cognitive impairment; aripiprazole, brexpiprazole, lurasidone, olanzapine, and quetiapine for depression and anxiety; brexpiprazole, aripiprazole, and olanzapine for disorganized thinking; olanzapine and risperidone for excitement and aggression; and aripiprazole, brexpiprazole, and lurasidone for social integration. Brexpiprazole, quetiapine, and aripiprazole were first-line options for patients at high risk of extrapyramidal side effects or diabetes mellitus. Dose reduction or switching was the treatment of choice for tardive dyskinesia. Repeated recurrence, patient request, and poor medication adherence were indications for introducing long-acting injectable antipsychotics. Switching to clozapine was the treatment of choice for treatment-resistant schizophrenia. Adverse effects were the highest-rated factor for both dose reduction and simplification to antipsychotic monotherapy. Second-generation antipsychotics were rated as first- or second-line options in most situations, whereas first-generation antipsychotics were generally rated as third-line. These recommendations provide practical guidance for treatment selection and shared decision-making in clinically challenging situations not adequately addressed by existing evidence alone.
Neurological soft signs (NSS) are frequent in schizophrenia spectrum disorders (SSD) and have been linked to structural alterations in basal ganglia-thalamic (BGT) regions. We hypothesized that SSD patients would show BGT volume differences compared to healthy controls (HC) and that NSS severity would relate to BGT volume and surface morphology in a replicable pattern. Structural 3T T1-weighted MRI scans were obtained from 327 SSD patients and 134 matched HC in Mannheim (Germany) and Bern (Switzerland). NSS were assessed using the Heidelberg Scale and the Neurological Evaluation Scale (NES). BGT volumes were segmented using FSL-FIRST and compared across groups using general linear models adjusted for age, sex, intracranial volume, and daily antipsychotic medication. Associations with NSS scores were tested using regression analyses. High-NSS compared to low-NSS SSD patients showed reduced left accumbens volume in both cohorts, with a significant main effect in the Mannheim cohort (β = -43.73, p = .002 uncorrected, p = .019 corrected) and a partial replication in the Bern cohort (β = -53.06, uncorrected p = .03, p > .05, corrected). In contrast, IF-related effects on left accumbens and bilateral thalamic volumes were cohort specific. Daily antipsychotic medication and illness duration did not mediate or moderate these associations. This bicentric MRI study provides converging evidence that NSS severity in SSD is associated with BGT alterations, particularly reduced left nucleus accumbens volume. However, thalamic and surface-level findings were cohort specific, indicating partial rather than uniform reproducibility. Associations were not explained by daily dosage of antipsychotic medication or illness duration.
Converging evidence indicates that schizophrenia reshapes the embodied structure of subjectivity, profoundly altering how individuals experience their bodies and surrounding space. This Perspective proposes a neurodevelopmental framework linking measurable distortions of personal space (PS) and peripersonal space (PPS) to deeper phenomenological disruptions of lived spatiality. Experimental findings consistently show an enlarged PS and a contracted PPS, maybe reflecting an excessive feeling of overexposure as well as a diminished sense of possible spatial enactment of bodily capacities. These anomalies likely stem from early neurodevelopmental disturbances in multisensory integration and sensorimotor learning. Phenomenological psychopathology further reveals how such spatial disorganization manifests as instability in self-world boundaries and a pervasive sense of altered atmosphere. Integrating neurodevelopmental, cognitive, and experiential dimensions provides a unified account of how schizotaxic vulnerability unfolds into spatial and Self-disturbances. This approach reframes embodiment and spatiality as developmental interfaces between neural processes and subjective transformation in schizophrenia.
Most genetic variants associated with complex heritability phenotypes lie in non-coding regions and are thought to influence disease risk by regulating gene expression. However, most transcriptome-wide association approaches primarily model local (cis) genetic effects, leaving much of gene regulation unexplained. Here, we show that incorporating distal (trans) regulatory effects improves the prediction of gene expression and the identification of disease-associated genes. Using RNA sequencing data from six human post-mortem brain regions, we developed INGENE and MODULE, two models capturing the combined influence of candidate trans-acting variants within gene coexpression networks. Integrating these models with conventional cis-based predictors improved gene expression imputation (maximum likelihood estimation, α = 0.05) for 18,744 genes across regions. Applying this framework to Psychiatric Genomics Consortium wave 3 genotypes identified 766 genes associated with schizophrenia (PFDR < 0.01), including 641 not previously reported by transcriptome-wide analyses. These findings highlight the contribution of distal regulatory mechanisms and gene network interactions to schizophrenia risk.
Objective peripheral biomarkers for early-stage schizophrenia are needed to improve diagnostic accuracy and treatment planning. To identify potential biomarkers, we compared multiple serum factor concentrations between 90 first-episode drug-naïve patients and healthy matched controls, and further examined associations with symptom severity and cognitive functions among patients. Serum interleukin (IL)-8, vascular cell adhesion molecule (VCAM)-1, matrix metalloproteinase (MMP)-2, and MMP-7 concentrations were quantified by Luminex multiplex immunoassays, and log10-transformed values compared with adjustment for age, sex, years of education, body mass index, and smoking status. Associations with symptoms as assessed by the Positive and Negative Syndrome Scale (PANSS) and cognitive functions as assessed by the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) were examined by Pearson's correlation analysis. Multivariable logistic regression models were developed for case-control discrimination by receiver operating characteristic analysis with 10-fold cross-validation and calibration. Serum log10[IL-8] and log10[MMP-7] were higher while serum log10[MMP-2] and log10[VCAM-1] were lower in patients. Serum log10[MMP-2], log10[MMP-7], and log10[VCAM-1] were positively correlated among patients, whereas log10[IL-8] was not associated with this MMP/VCAM-1 axis. There were no stable linear associations with PANSS or RBANS scores. Serum log10[IL-8] demonstrated the highest single-marker discrimination (AUC = 0.742, 95%CI: 0.667-0.817), and the four-biomarker model further improved discrimination (AUC = 0.839, 95%CI: 0.781-0.897; 10-fold cross-validated AUC = 0.804). A Youden-derived threshold of 0.518 yielded 78.9% sensitivity and specificity for distinguishing cases. A serum inflammation-endothelium-extracellular matrix biomarker panel showed good discriminative performance in distinguishing first-episode drug-naïve schizophrenia from controls in a case-control sample; external validation and potential recalibration in real-world cohorts are warranted.
Neurotypical people are generally quite adept at interpreting social signals from dynamic bodies and faces. This ability prevents one from incurring high costs associated with ineffective and maladaptive social interactions. Individuals with mental disorders, such as schizophrenia (SZ), often exhibit deficits in nonverbal social cognition. It remains unclear whether reading the language of bodies and faces is affected by SZ, and if this is indeed the case, how these potential deficits are related to one another. In the present study, participants (28 males with SZ and 28 typically developing, TD, matched controls) were administered face-to-face computer tasks on inferring emotions from dynamic point-light body motion and faces. The outcome indicates that SZ patients exhibit global impairments in both body and face reading, albeit patients demonstrate a similar emotion recognition profile as TD controls. In SZ patients only, a positive link was found between accuracy of recognizing emotions expressed through faces and bodies, whereas processing speed of emotions conveyed through bodies and faces was tied to each other in both SZ and TD individuals. For SZ patients, inferring social signals from dynamic faces and bodies may be rather challenging in terms of neurocognitive mechanisms, which is reflected in the tight link in recognition accuracy. Along with previous data on inferring emotions in the eyes collected in the same cohort, this work provides novel insights into the specific global aberrations in social cognition in SZ and offers a blueprint for the development of strategies for the targeted treatment of gender-specific mental disorders.
Brain-age models use neuroimaging features to predict chronological age and thereby estimate normative lifespan patterns; the resulting brain-age gap (BAG) quantifies deviation from age-expected brain characteristics. Structural brain-age acceleration is well established in schizophrenia spectrum disorders (SSD), but the utility of resting-state functional connectivity (rs-FC)-based brain age remains unclear. Here, we trained rs-FC brain-age models on aggregated lifespan data from healthy controls (N≈2,200) and evaluated them in four independent SSD case-control cohorts. Across cohorts and atlases, SSD showed higher FC-based BAG than healthy controls (β≈0.4-0.6), indicating modest functional brain-age elevation at the group level. However, within SSD, more negative (delayed maturation) BAG was associated with poorer cognitive performance, longer duration of illness, and higher neurological soft signs (NSS). Over 12-24 weeks, increases in BAG accompanied reductions in NSS motor coordination and hard signs. Together, these findings suggest that rs-FC brain age captures both a small case-control shift and a clinically relevant dimension within SSD that is not well described by uniform "acceleration". FC-based BAG may therefore reflect heterogeneity in network-level development and reorganization, with younger-appearing functional profiles indexing greater neurodevelopmental burden.
Schizophrenia (SCZ) is a highly heritable and complex neuropsychiatric disorder. Emerging evidence implicates dysregulated brain iron, particularly in subcortical regions, in SCZ pathophysiology. Here, we systematically dissected the shared genetic architecture between SCZ and subcortical brain susceptibility phenotypes by integrating large-scale genome-wide association study (GWAS) data with quantitative susceptibility mapping (QSM) phenotypes across 16 subcortical regions. Using the MiXeR framework, we quantified the extent and pattern of shared genetic overlap between SCZ and each QSM phenotype, revealing the strongest overlap in the left and right nucleus accumbens. Conditional and conjunction false discovery rate analyses identified 666 unique shared SNPs. Functional annotation highlighted enrichment in pathways related to synaptic function and neuronal development, with pronounced expression in neurons. Additionally, we characterized their spatio-temporal expression patterns of shared genes and identified 89 significant expression-trait associations linked to SCZ-related phenotypes. Furthermore, the virtual drug screen identified 691 potential protein-drug pairs that may contribute to both iron regulation and SCZ. Our findings provide new insights into the complex interaction between subcortical brain susceptibility phenotypes and SCZ, highlighting pathways that may offer novel therapeutic strategies for SCZ and related brain susceptibility-associated conditions.
Akathisia is a severe psychomotor syndrome characterized by distressing subjective restlessness and observable repetitive, purposeless movements. Despite its substantial clinical impact, it remains underrecognized, and its neurobiological underpinnings are poorly understood. In this study, we examined clinical, cognitive, psychomotor, and structural brain correlates of akathisia across schizophrenia spectrum disorders (SSD) and mood disorders (MOD). A total of 308 patients (SSD: n = 215, MOD: n = 93) underwent structural magnetic resonance imaging (MRI) and deep clinical phenotyping. Akathisia was assessed using the Barnes Akathisia Rating Scale. In addition, different scales were used to assess psychopathology, global and cognitive functioning, and other psychomotor abnormalities. Structural 3T MRI data were processed using FreeSurfer version 7.4.1. Akathisia prevalence was 21.9% in SSD and 12.9% in MOD. In SSD, akathisia was associated with younger age, poorer global functioning, greater psychopathology, and more pronounced psychomotor abnormalities. In MOD, akathisia was linked to higher psychopathology and poorer cognitive performance. Neurobiologically, SSD patients with akathisia showed reduced cortical thickness in the paracentral lobule, primary motor cortex, and superior frontal gyrus, without differences in cortical surface area or basal ganglia structures. No structural MRI differences were observed in MOD. As the largest transdiagnostic structural MRI study of akathisia to date, our findings support its characterization as a distinct clinical and neurobiological phenotype, particularly in SSD.