搜索结果：Schizophrenia (Heidelberg, Germany)

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.

Schizophrenia is a heterogeneous disorder, with subpopulations showing a relatively higher heritable predisposition based on many common genetic variants with minimal effects, whereas other subpopulations likely have alternative pathogenic backgrounds, including rare genetic variants with large effects. These heterogeneities may hinder the identification of molecular profiles related to the disorder's pathogenesis. Therefore, this study aimed to identify transcriptional profiles specific to patients with schizophrenia with high heritable predisposition, indicated by high polygenic risk scores (PRS), and an alternative subgroup with low PRS. RNA-seq-based transcriptome data of the prefrontal cortices were compared among subgroups of patients with high PRS (PRS at or above the median; n = 12), low PRS (PRS below the median; n = 11), and controls (n = 21). Gene-category enrichment analysis of 584 differentially expressed genes (DEGs) identified 8 DEGs associated with DNA repair. Additionally, the expression levels of these DNA repair-related genes were associated with the general psychopathology scale, raising the hypothesis that oxidative stress accumulation, indicated by superoxide dismutase 2 expression may contribute to DNA repair activation. Furthermore, the expression levels of six DNA repair-related genes were significantly linked to the severity of the general psychopathology scale, suggesting that DNA repair might affect the clinical phenotypes of schizophrenia. This study used PRS to stratify patients with schizophrenia, highlighting the potential role of DNA repair-related pathways to the heterogeneity of schizophrenia. Understanding the role of DNA repair could lead to personalized treatments that target oxidative stress-related molecules.

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 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&#xa0;<&#xa0;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&#xa0;=&#xa0;0.27, p&#xa0;<&#xa0;0.001) and network loadings (r&#xa0;=&#xa0;-0.29, p&#xa0;<&#xa0;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.

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.

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.

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-na&#xef;ve 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&#x2009;=&#x2009;0.742, 95%CI: 0.667-0.817), and the four-biomarker model further improved discrimination (AUC&#x2009;=&#x2009;0.839, 95%CI: 0.781-0.897; 10-fold cross-validated AUC&#x2009;=&#x2009;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-na&#xef;ve schizophrenia from controls in a case-control sample; external validation and potential recalibration in real-world cohorts are warranted.

Cognitive remediation therapy (CRT) is an evidence-based behavioral intervention that enhances functional outcomes in schizophrenia patients by improving cognition. However, not all patients benefit equally from CRT, and predictors of real-world functional improvement are poorly understood. This study aimed to identify patient-related baseline predictors of functional improvement by evaluating two distinct CRT approaches targeting different types of cognition: social cognition (Integrated Social Cognition and Social Skills Training, ISST) and neurocognition (Neurocognitive Remediation Therapy, NCRT). This secondary analysis used data from a large, multicenter randomized controlled trial. Participants with schizophrenia (N&#xa0;=&#xa0;174) were randomly assigned to ISST or NCRT for six months. Multiple linear regression analyses were performed to determine whether baseline demographic, cognitive, clinical, or functional characteristics predicted changes in real-world functioning, as measured by the Social and Occupational Functioning Assessment Scale. The Digit Symbol Substitution Test was the strongest and most consistent predictor of functional improvement. Lower baseline functioning also predicted greater gains, although only in multivariable models. Domain-specific predictors were identified for each intervention: better affect recognition predicted better outcomes in ISST, whereas verbal memory did so in NCRT. The CRT approaches studied here appear to be most effective for individuals with a more preserved baseline level of cognitive performance, especially in terms of processing speed. These findings support the use of brief cognitive assessments to guide CRT implementation and suggest that tailoring interventions to individual cognitive profiles may enhance treatment efficacy.

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&#x2009;=&#x2009;"strongly disagree"; 9&#x2009;=&#x2009;"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.

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, &#x3b1;&#x2009;=&#x2009;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&#x2009;<&#x2009;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.

Schizophrenia (SCZ) is a complex psychiatric disorder, and its pathogenic mechanisms are not yet fully understood. The identification of reliable blood biomarkers and molecular subtypes for early diagnosis and effective therapy remains a significant challenge. To address this issue, we utilized a combination of bioinformatics and machine learning (ML) to identify potential biomarkers for SCZ. Our approach involved the integration of 12 different ML algorithms to develop a diagnostic signature based on data from several datasets, including GSE18312, GSE27383, GSE38485, GSE54913, and GSE165604. A nomogram was constructed using these datasets for potential clinical applications. In addition, clustering analysis was performed on SCZ patients using consensus clustering and non-negative matrix factorization (NMF) algorithms. We further evaluated subtype differences in biological functions and immune cells through various methods, such as gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), Proteomaps, and IOBR analyses. Our results identified a diagnostic signature composed of 16 genes (APBB2, CLCN1, SYDE1, PAX5, SNAI1, DAZL, UNC93B1, PLAGL2, HS3ST1, ITPKB, PILRA, BTLA, SWAP70, AZI2, ADM, and AVPR2), which demonstrated robust performance in diagnosing SCZ across eight different datasets. A nomogram based on these genes was created, providing clinical benefits for SCZ patients. Among the identified genes, AZI2 was found to be the most critical, influencing inflammation and immunity. We also identified potential chemical compounds that could target these 16 genes. Unsupervised clustering and NMF algorithms revealed two distinct subtypes of SCZ, each associated with unique immune cell profiles, biological functions, and protein expression levels. In conclusion, this study not only developed a diagnostic signature and a novel nomogram for SCZ but also provided new insights into the subtypes of SCZ. These findings may pave the way for personalized diagnosis and treatment strategies for SCZ patients.

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&#x2248;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 (&#x3b2;&#x2248;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.

While schizophrenia (SZ) etiology remains unclear, accumulating evidence implicates mitochondrial dysfunction, particularly complex-I of the respiratory chain and its essential free-electron scavenger subunit, NDUFV2, as a contributor to neuronal and behavioral impairments observed in SZ. Our recent studies suggest a potential role for the NDUFV2 pseudogene (NDUFV2P1) in NDUFV2 deficits. Here, we describe a mechanism by which NDUFV2P1 negatively controls NDUFV2 mRNA transport and its protein levels in SZ-derived lymphocyte cell lines (SZ-LCLs). We found increased NDUFV2P1 transcript levels in SZ frontal cortex postmortem specimens (SZ-FCX) and across all studied SZ-LCLs subcellular fractions. However, NDUFV2 levels were reduced in SZ-FCX and in all cell compartments, except for the nucleus, as compared to healthy subjects-derived LCLs (CTL-LCLs), suggesting its impaired nuclear export. Concomitantly, we observed increased NDUFV2P1, yet decreased NDUFV2 mRNA binding to NXF1, a key player in nuclear mRNA export. Overexpression of NDUFV2P1 in CTL-LCLs mimicked the SZ-state, reducing NDUFV2 levels and its binding to NXF1. The interactome of both mRNAs revealed an opposite binding profile for most RNA-binding proteins (RBPs) in SZ-LCLs compared to CTL-LCLs. Pathway enrichment analysis of the differentially bound RBPs to both transcripts revealed additional potential interference sites for NDUFV2 and NDUFV2P1, including ribosomal-, spliceosome-, and RNA transport-related RBPs. This study uncovers a new mechanism in which NDUFV2P1 interferes with RBPs involved in regulating NDUFV2 transport from the nucleus to mitochondrial-bound ribosomes. While further validation is necessary to substantiate this mechanism, the findings highlight NDUFV2P1 potential as a means for regulating mitochondrial function and consequently energy metabolism in SZ.

Free D-serine (D-Ser) and D-aspartate (D-Asp) are increasingly recognized as key modulators of glutamatergic NMDA receptor-dependent neurotransmission, whose dysfunction has been implicated in neuropsychiatric conditions, including schizophrenia (SCZ) and autism spectrum disorder (ASD). The metabolism of these D-amino acids is tightly regulated by specific enzymes: serine racemase (SR) for D-Ser synthesis and degradation, and D-amino acid oxidase (DAAO) and D-aspartate oxidase (DASPO) for D-Ser and D-Asp degradation, respectively. The primate-specific protein pLG72 further modulates the activity of DAAO and DASPO. In this multicenter study, we employed a mass spectrometry (MS)-based approach to quantify SR, DAAO, DASPO, and pLG72 levels in serum samples from SCZ and ASD patients, along with matched non-psychiatric controls. Enzymatic activity and D-amino acid serum concentrations were also assessed. We identified distinct, disorder-specific alterations in these proteins. In SCZ patients, SR protein levels were elevated despite unchanged activity, while DAAO and pLG72 levels were decreased. Conversely, increased DASPO levels were associated with reduced D-Asp, indicating enhanced catabolism of this endogenous NMDA receptor ligand in SCZ. ASD patients exhibited elevated DAAO and DASPO, with reduced SR levels. Notably, positive correlations between pLG72 and both DAAO and DASPO flavoenzymes were observed in both disorders. These findings highlight the potential of D-amino acid metabolism-related enzymes as biomarkers for SCZ and ASD and provide new insights for future diagnostic and mechanistic investigations in neurodevelopmental disorders.

Schizophrenia-spectrum disorders (SSDs) and dissociative disorders (DDs) often co-occur, and both show emotion processing deficits. Alexithymia-comprising difficulty identifying feelings (DIF), difficulty describing feelings (DDF), and externally oriented thinking (EOT)-is considered a shared vulnerability factor, yet the relative prominence of each facet within and across these disorders remains uncertain. The current two meta-analyses synthesised severity of overall alexithymia and its facets in SSDs (Meta-analysis 1) or DDs (Meta-analysis 2) compared to psychiatrically healthy controls. A preregistered search of PsycINFO, PubMed, and Embase (1970-31 December 2024) identified adult case-control studies. Pooled Hedges' g values were estimated with random-effects meta-analysis models, then compared across diagnoses (moderator analyses) with mixed-effects meta-analysis models. Meta-analysis 1 pooled 27 SSD studies (1477 patients, 1249 controls). Meta-analysis 2 pooled 30 DD studies (842 patients, 796 controls). Both patient groups scored higher than controls on overall alexithymia and all facets. In SSDs, DIF showed the largest group effect (g&#x2009;=&#x2009;0.894; CI 0.667-1.122), whereas DDF (g&#x2009;=&#x2009;0.622; CI 0.468-0.775) and EOT (g&#x2009;=&#x2009;0.585; CI 0.400-0.770) showed moderate effects. In DDs, both DIF (g&#x2009;=&#x2009;1.311; CI 0.991-1.632) and DDF (g&#x2009;=&#x2009;0.954; CI 0.707-1.202) showed large effects, whereas EOT (g&#x2009;=&#x2009;0.427; CI 0.163-0.690) showed a small-to-moderate effect. Between the disorder groups, after removing extreme effects, DDs exhibited greater DIF and DDF than SSDs, whereas SSDs showed higher EOT. Heterogeneity was moderate-to-high, and publication bias was possible in SSD studies. Alexithymia is a significant transdiagnostic deficit, but its facet profiles differ between SSDs and DDs. Emotion-focused interventions should therefore target facet-specific deficits prominent to each disorder group.

Clozapine is an effective antipsychotic used in treatment-resistant schizophrenia, but high serum levels may increase side effects. This study aimed to examine the efficacy and tolerability profile of clozapine in a naturalistic setting. The impact of multiple factors, specifically CYP1A2 genotypes, smoking, and fluvoxamine coadministration, on CYP1A2 enzyme activity was assessed as a secondary exploratory end point. In this prospective, observational study, 32 patients receiving stable clozapine therapy were observed over a 24-hour period at the Central Institute for Mental Health, Mannheim. Clozapine blood levels were measured via liquid chromatography-mass spectrometry and the MyCare Clozapine Assay. Clozapine levels above 600 ng/mL were not associated with increased clinical efficacy but were linked to more side effects. Sleep quality was generally poor, and daytime sedation was frequent. While coadministration with the CYP1A2 inhibitor fluvoxamine led to a dose-corrected increase in clozapine levels of approximately 50%; smoking reduced clozapine (-36%) and norclozapine (-32%) levels. Clozapine levels above the therapeutic reference range may not provide additional benefits and could increase side effects. Therapeutic drug monitoring is an essential clinical practice tool, especially when using comedication or in smokers. Overall, these findings should be interpreted as exploratory and supportive of existing therapeutic guidance because of the small sample size and naturalistic study design.

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.

A consistent postmortem finding in schizophrenia (SCZ) is reduction in dendrites' size. However, neurons with larger dendritic trees have also been encountered. In vitro experiments with neurons and neuronal-like cells coming directly from patients with SCZ showed similar results, evidencing at times more extensions and at others less arborizations. The process of extending and retracting neuronal outgrowths depends on microtubules polymerization and depolymerization. The possibility that microtubule polymerization/depolymerization is related to defects in the neuronal structure comes from several microtubular anomalies reported in SCZ such as its abnormal distribution in the cytoplasm, irregular shape of microtubules and even absence of these cytoskeletal components in dendrites. Moreover, microtubules in olfactory neuroepithelial cells from patients with SCZ were resistant to depolymerization. But whether deficits in microtubules are associated with abnormalities in the neuronal structure has never been investigated in living cells coming directly from patients. Therefore, we studied dynamic neurostructural changes in Monocyte-Derived-Neuronal-like cells (MDNCs) from 12 controls and 13 patients with SCZ. First, we showed that human neuroprogenitor cells and MDNCs have comparable neurostructural plasticity. Then, we investigated whether colchicine, a microtubular stabilizing and depolymerizing agent, disrupts dynamic neurostructural changes. The lowest concentration of colchicine tested, stopped dynamic neurostructural changes in MDNCs from controls, while cells from patients with SCZ continued to extend and retract neuronal outgrowths. Following, we investigated if antipsychotics impact dynamic structural changes, but our results were inconclusive. Our data indicate that, under certain circumstances, neuronal-like cells from patients with SCZ evidenced hyperdynamic microtubule-based neurostructural changes and consequently, link deficits in microtubules with anomalies in the neuronal shape. While other potential confounders are unlikely to have influenced our results, the effects of medications cannot be excluded.