Annarita Barone

Background: Although most individuals with schizophrenia do not show aggressive behavior, rates are higher than in the general population. Identifying the neurobiological correlates of aggression may inform prevention. Methods: We included 2260 individuals with schizophrenia spectrum disorders and 3058 healthy controls (HC) from 26 sites in the ENIGMA-Schizophrenia Working Group. The former were classified as showing at least moderate aggression (SZ+A; N = 231) or not (SZ−A; N = 2029) based on symptom rating scales. Structural covariance networks were constructed from cortical and subcortical volumes. We examined global and nodal network topology, as well as density within six large-scale brain networks and between each network and the rest of the brain. Metrics were summarized as the area under the curve (AUC) across a prespecified range of densities ( K = 0.10–0.25, Δ K = 0.01). Group differences were assessed using pairwise permutation tests with Benjamini–Hochberg correction for multiple comparisons. Results: Global and nodal network topology did not differ significantly between SZ+A and HC. Network–rest density of the salience network (SN) was higher in SZ+A than in HC, although this difference did not survive multiple-comparison correction (ΔAUC = 0.018, p _BH = .083). In exploratory subgroup analyses, higher SN network–rest density was observed only in SZ+A with high delusion severity (ΔAUC = 0.021, p = .007). By contrast, SZ−A demonstrated extensive alterations in global network topology compared with SZ+A and HC, alongside selective alterations in nodal topology and large-scale network density compared with HC. Results were broadly consistent across sensitivity analyses using alternative definitions of aggression and adjusting for current antipsychotic dose. Conclusions: SZ+A was characterized by fewer—not more—abnormalities in structural covariance network organization than SZ−A, which may reflect etiological heterogeneity. In SZ+A with high delusion severity, higher network–rest density of the SN may point to aberrant salience processing in aggressive behavior.

Treatment-resistant schizophrenia (TRS) affects almost 30% of patients with the disorder. This condition is associated with functional impairment and has been suggested to have a putatively different neurobiology compared to non-treatment-resistant schizophrenia. One striking feature of TRS is the presence of relevant cognitive deficits, which, in many cases, align with a Mild Cognitive Impairment (MCI)‑like clinical profile without implying amyloid-β (Aβ) pathology. Conversely, aspects of MCI partially overlap with the trajectory of schizophrenia, motivating investigation of putative common factors of convergence. Despite its relevance, in vivo data directly addressing this question are lacking. We used ¹⁸(F)-Flutemetamol Positron Emission Tomography (PET) to investigate regional cortical Aβ deposition and its potential association with clinical symptoms in patients with TRS with MCI‑like cognitive impairment (TRS-MCI). TRS-MCI ( n = 12) underwent a PET scan and clinical evaluation, including the Positive and Negative Syndrome Scale (PANSS) and the Brief Assessment of Cognition in Schizophrenia (BACS). PET image analysis was performed using the Diagnosis ORIented ANalysis software, which provides different semiquantitative indices of regional cortical Aβ PET measures. PET data obtained in TRS-MCI were compared with those of amyloid-negative cognitively impaired patients (Aβ- CI) without psychiatric disorders ( n = 12). Group‑level comparisons using expert visual assessment and semi‑automated quantification showed no significant differences. Exploratory correlation within TRS‑MCI revealed a negative association between the regional Aβ composite scores in the Right Parietal Cortex and the PANSS Positive score ( P ≤ 0.01). This pilot study found no evidence of increased cortical Aβ deposition in TRS patients; nevertheless, regional variation in Parietal Cortex ( ¹⁸ F)‑Flutemetamol PET signal within the Aβ‑negative range was associated with positive symptoms, warranting confirmation in larger, longitudinal cohorts.

Fear is a transdiagnostic construct implicated in multiple psychiatric disorders, reflecting a partial dissociation between clinical phenotypes and underlying neurobiological mechanisms. Converging evidence suggests that aberrant fear processing plays a central role in cognitive and psychopathological models of psychosis. In this narrative review, we synthesize evidence on the neurobiological mechanisms of aberrant fear modulation in schizophrenia from a translational perspective, integrating findings from neuroimaging, preclinical models, pharmacological interventions, and psychotherapy. Schizophrenia is characterized by aberrant emotional processing and inappropriate neural responses to stimuli with reduced or absent objective salience, reflecting impaired discrimination of relevant environmental information. At the system level, evidence implicates dysregulation of cortico-limbic and salience-processing networks in altered fear learning, threat appraisal, and emotional prediction. Neurochemical findings indicate that dopamine–glutamate dysregulation and associated intracellular signaling pathways act as upstream modulatory mechanisms contributing to these network-level abnormalities. Therapeutic interventions, including antipsychotic drugs and psychotherapeutic approaches, partially modulate these systems, although effects remain heterogeneous. Overall, the evidence supports a hierarchical model in which aberrant fear processing in schizophrenia arises from disrupted salience attribution and impaired integration across cognitive, affective, and neurobiological levels. This intermediate dysfunction links molecular alterations to large-scale network disturbances and clinical symptom expression, providing a framework for more mechanism-based therapeutic strategies.

Glutamate metabotropic receptors (mGluRs) and their molecular partners at the postsynaptic density (PSD) represent a highly dynamic molecular hub that integrates multiple neurotransmitter signals and regulates synaptic plasticity and metaplasticity, which are putatively involved in the pathophysiology of psychiatric illnesses, including schizophrenia. Group I mGluRs (mGluR1 and mGluR5) interact with PSD adaptor and scaffolding proteins, such as Homer, Shank, Norbin, and PICK1, as well as intracellular downstream effectors, creating a molecular network that resembles a Lego-like structure, where modular protein interactions fine-tune glutamatergic transmission. Evidence from preclinical research indicates that dysregulation of mGluR expression and function, along with disrupted PSD protein expression, may contribute to the pathophysiology of schizophrenia by altering glutamatergic neurotransmission and synaptic stability. Antipsychotic mechanisms of action may involve, at least in part, the modulation of mGluR activity mediated through PSD proteins. Notably, novel agents that enhance spinogenesis by acting at the level of PSD proteins, such as SPG302, may open promising avenues for therapeutics aimed at restoring synaptic integrity. While Group I mGluRs dominate postsynaptic regulation, Group II (mGluR2/3) and III (mGluR4/6/7/8) receptors -primarily presynaptic- inhibit neurotransmitter release and plasticity, offering complementary therapeutic avenues. Emerging strategies, such as allosteric modulators of mGluRs, aim to rebalance synaptic signaling in treatment-resistant schizophrenia. This review synthesizes how PSD proteins and mGluRs interact in schizophrenia, exploring their potential as druggable targets for novel therapies.

Introduction: The corpus callosum (CC) is critical for inter-hemispheric integration, and its structural abnormalities have been implicated in the neurobiology of schizophrenia (SCZ). Approximately 20-35% of SCZ patients exhibit resistance to antipsychotics and are classified as treatment-resistant schizophrenia (TRS). To date, no studies have specifically analyzed CC morphology in TRS compared to healthy controls (HCs) and treatment-responsive SCZ patients (non-TRS). Methods: The study included 75 HCs and 97 SCZ patients (39 TRS and 58 non-TRS, including cannabis users and non-users). Participants underwent cross-sectional assessment using the Neurological Evaluation Scale (NES), the Brief Assessment of Cognition in Schizophrenia, and the Positive and Negative Syndrome Scale (PANSS). CC volume was measured via MRI and analyzed with a novel artificial intelligence program (MRI-AI) for single-subject assessment, with findings confirmed through group-level voxel-based morphometry (VBM). Results: TRS patients exhibited significantly higher total PANSS (p < 0.001) and NES (p < 0.001) scores and performed worse on working memory tasks compared to non-TRS patients. MRI-AI identified CC volume reduction in 55.88% of TRS patients (TRS CC: 3.02 mL vs. non-TRS with cannabis use: 3.69 mL; without cannabis use: 3.28 mL; p = 0.002). VBM confirmed significant CC volume reduction in TRS patients relative to HCs (p = 0.004). Cannabis use in non-TRS patients did not significantly affect CC volume or cognitive performance. Conclusions: TRS is associated with pronounced neurological, cognitive, and clinical dysfunctions. Aberrant CC volume may contribute to TRS pathogenesis and executive function deficits. MRI-AI provides a robust, single-subject approach for characterizing CC abnormalities in schizophrenia, offering potential for personalized clinical assessment. other: Future studies should explore longitudinal CC changes to evaluate whether they can be considered a potential biomarker for TRS. The potential of MRI-AI for single-subject analysis has provided encouraging results but should be further validated on larger samples.

Treatment-resistant schizophrenia (TRS) affects up to one in three individuals with schizophrenia and is associated with a significant clinical, social, and economic burden. Different from treatment-responsive forms, TRS appears to involve other biological mechanisms extending beyond dopaminergic dysfunctions. This review outlines current knowledge on the molecular and cellular basis of TRS, focusing on alterations in glutamate signaling, imbalances between excitatory and inhibitory activity, disruptions in D-amino acid metabolism, and evidence of neuroinflammation, oxidative stress, and mitochondrial or endoplasmic reticulum dysfunction. Data from genomics, proteomics, metabolomics, preclinical models, and postmortem studies suggest that TRS may have a peculiar neurobiological substrate. Further, multimodal brain imaging studies reveal differences in brain structure, white matter integrity, and network connectivity when compared to treatment-responsive individuals. Altogether, these findings support a shift from the traditional dopamine hypothesis toward a more comprehensive model that includes multiple immune, metabolic, and synaptic factors. Understanding the possible interplay of these complex mechanisms may lead to the identification of potential biomarkers that may help to predict antipsychotic response, as well as the development of more targeted treatments. Early recognition and a deeper biological insight into TRS are essential for improving care and guiding personalized therapeutic strategies.

Schizophrenia is a chronic and severe psychiatric disorder affecting approximately 1% of the global population, characterized by disrupted synaptic plasticity and brain connectivity. While substantial evidence supports its classification as a neurodevelopmental disorder, non-canonical neurodegenerative features have also been reported, with increasing attention given to astrocytic dysfunction. Overall, in this study, we explore the role of astrocytes as a structural and functional link between neurodevelopment and neurodegeneration in schizophrenia. Specifically, we examine how astrocytes contribute to forming an aberrant substrate during early neurodevelopment, potentially predisposing individuals to later neurodegeneration. Astrocytes regulate neurotransmitter homeostasis and synaptic plasticity, influencing early vulnerability and disease progression through their involvement in Ca²⁺ signaling and dopamine–glutamate interaction—key pathways implicated in schizophrenia pathophysiology. Astrocytes differentiate via nuclear factor I-A, Sox9, and Notch pathways, occurring within a neuronal environment that may already be compromised in the early stages due to the genetic factors associated with the ‘two-hits’ model of schizophrenia. As a result, astrocytes may contribute to the development of an altered neural matrix, disrupting neuronal signaling, exacerbating the dopamine–glutamate imbalance, and causing excessive synaptic pruning and demyelination. These processes may underlie both the core symptoms of schizophrenia and the increased susceptibility to cognitive decline—clinically resembling neurodegeneration but driven by a distinct, poorly understood molecular substrate. Finally, astrocytes are emerging as potential pharmacological targets for antipsychotics such as clozapine, which may modulate their function by regulating glutamate clearance, redox balance, and synaptic remodeling.

Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal ‘trajectory’ of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Almost 25% of schizophrenia patients suffer from obsessive-compulsive symptoms (OCS) considered a transdiagnostic clinical continuum. The presence of symptoms pertaining to both schizophrenia and obsessive-compulsive disorder (OCD) may complicate pharmacological treatment and could contribute to lack or poor response to the therapy. Despite the clinical relevance, no reviews have been recently published on the possible neurobiological underpinnings of this comorbidity, which is still unclear. An integrative view exploring this topic should take into account the following aspects: (i) the implication for glutamate, dopamine, and serotonin neurotransmission as demonstrated by genetic findings; (ii) the growing neuroimaging evidence of the common brain regions and dysfunctional circuits involved in both diseases; (iii) the pharmacological modulation of dopaminergic, serotoninergic, and glutamatergic systems as current therapeutic strategies in schizophrenia OCS; (iv) the recent discovery of midbrain dopamine neurons and dopamine D1- and D2-like receptors as orchestrating hubs in repetitive and psychotic behaviors; (v) the contribution of N-methyl-D-aspartate receptor subunits to both psychosis and OCD neurobiology. Finally, we discuss the potential role of the postsynaptic density as a structural and functional hub for multiple molecular signaling both in schizophrenia and OCD pathophysiology.

Schizophrenia is a worldwide mental illness characterized by alterations at dopaminergic and glutamatergic synapses resulting in global dysconnectivity within and between brain networks. Impairments in inflammatory processes, mitochondrial functions, energy expenditure, and oxidative stress have been extensively associated with schizophrenia pathophysiology. Antipsychotics, the mainstay of schizophrenia pharmacological treatment and all sharing the common feature of dopamine D2 receptor occupancy, may affect antioxidant pathways as well as mitochondrial protein levels and gene expression. Here, we systematically reviewed the available evidence on antioxidants’ mechanisms in antipsychotic action and the impact of first- and second-generation compounds on mitochondrial functions and oxidative stress. We further focused on clinical trials addressing the efficacy and tolerability of antioxidants as an augmentation strategy of antipsychotic treatment. EMBASE, Scopus, and Medline/PubMed databases were interrogated. The selection process was conducted in respect of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. Several mitochondrial proteins involved in cell viability, energy metabolism, and regulation of oxidative systems were reported to be significantly modified by antipsychotic treatment with differences between first- and second-generation drugs. Finally, antioxidants may affect cognitive and psychotic symptoms in patients with schizophrenia, and although the evidence is only preliminary, the results indicate that further studies are warranted.