In different stages of schizophrenia (SZ), alterations in gray matter volume (GMV) of patients are normally regulated by various pathological mechanisms. Instead of analyzing stage-specific changes, this study employed a multivariate structural covariance model and sliding-window approach to investigate the illness duration-related developmental trajectory of GMV in SZ. The trajectory is defined as a sequence of brain regions activated by illness duration, represented as a sparsely directed matrix. By applying this approach to structural magnetic resonance imaging data from 145 patients with SZ, we observed a continuous developmental trajectory of GMV from cortical to subcortical regions, with an average change occurring every 0.208 years, covering a time window of 20.176 years. The starting points were widely distributed across all networks, except for the ventral attention network. These findings provide insights into the neuropathological mechanism of SZ with a neuroprogressive model and facilitate the development of process for aided diagnosis and intervention with the starting points.
Humans ; Schizophrenia/pathology* ; Gray Matter/pathology* ; Magnetic Resonance Imaging ; Disease Progression ; Male ; Female ; Brain/pathology* ; Cerebral Cortex/pathology* ; Adult

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

BACKGROUND: Patients with schizophrenia (SCZ) and major depressive disorder (MDD) share significant clinical overlap, although it remains unknown to what extent this overlap reflects shared neural profiles. To identify the shared and specific abnormalities in SCZ and MDD, we performed a whole-brain voxel-based meta-analysis using magnetization transfer imaging, a technique that characterizes the macromolecular structural integrity of brain tissue in terms of the magnetization transfer ratio (MTR). METHODS: A systematic search based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was conducted in PubMed, EMBASE, International Scientific Index (ISI) Web of Science, and MEDLINE for relevant studies up to March 2022. Two researchers independently screened the articles. Rigorous scrutiny and data extraction were performed for the studies that met the inclusion criteria. Voxel-wise meta-analyses were conducted using anisotropic effect size-signed differential mapping with a unified template. Meta-regression was used to explore the potential effects of demographic and clinical characteristics. RESULTS: A total of 15 studies with 17 datasets describing 365 SCZ patients, 224 MDD patients, and 550 healthy controls (HCs) were identified. The conjunction analysis showed that both disorders shared higher MTR than HC in the left cerebellum ( P =0.0006) and left fusiform gyrus ( P =0.0004). Additionally, SCZ patients showed disorder-specific lower MTR in the anterior cingulate/paracingulate gyrus, right superior temporal gyrus, and right superior frontal gyrus, and higher MTR in the left thalamus, precuneus/cuneus, posterior cingulate gyrus, and paracentral lobule; and MDD patients showed higher MTR in the left middle occipital region. Meta-regression showed no statistical significance in either group. CONCLUSIONS The results revealed a structural neural basis shared between SCZ and MDD patients, emphasizing the importance of shared neural substrates across psychopathology. Meanwhile, distinct disease-specific characteristics could have implications for future differential diagnosis and targeted treatment.
Humans ; Depressive Disorder, Major/drug therapy* ; Schizophrenia/pathology* ; Brain/pathology* ; Prefrontal Cortex ; Frontal Lobe ; Magnetic Resonance Imaging/methods*

Adolescent ; Adult ; Brain ; abnormalities ; pathology ; physiopathology ; Child ; Female ; Humans ; Image Processing, Computer-Assisted ; Male ; Nerve Net ; pathology ; physiopathology ; Schizophrenia ; etiology ; physiopathology ; Schizophrenic Psychology

OBJECTIVES: Dopamine dysregulation has been regarded as one of the core pathologies in patients with schizophrenia. Since dopamine synthesis capacity has found to be inconsistent in patients with schizophrenia, current classification of patients based on clinical symptoms cannot reflect the neurochemical heterogeneity of the disease. Here we performed new subtyping of patients with first-episode psychosis (FEP) through biotype-based cluster analysis. We specifically suggested basal ganglia structural changes as a biotype, which deeply involves in the dopaminergic circuit. METHODS: Forty FEP and 40 demographically matched healthy participants underwent 3T T1 MRI. Whole brain parcellation was conducted, and volumes of total 6 regions of basal ganglia have been extracted as features for cluster analysis. We used K-means clustering, and external validation was conducted with Positive and Negative Syndrome Scale (PANSS). ResultsZZK-means clustering divided 40 FEP subjects into 2 clusters. Cluster 1 (n = 25) showed substantial volume decrease in 4 regions of basal ganglia compared to Cluster 2 (n = 15). Cluster 1 showed higher positive scales of PANSS compared with Cluster 2 (F = 2.333, p = 0.025). Compared to healthy controls, Cluster 1 showed smaller volumes in 4 regions, whereas Cluster 2 showed larger volumes in 3 regions. RESULTS: K-means clustering divided 40 FEP subjects into 2 clusters. Cluster 1 (n = 25) showed substantial volume decrease in 4 regions of basal ganglia compared to Cluster 2 (n = 15). Cluster 1 showed higher positive scales of PANSS compared with Cluster 2 (F = 2.333, p = 0.025). Compared to healthy controls, Cluster 1 showed smaller volumes in 4 regions, whereas Cluster 2 showed larger volumes in 3 regions. CONCLUSIONS: Two subgroups have been found by cluster analysis, which showed a distinct difference in volume patterns of basal ganglia structures and positive symptom severity. The result possibly reflects the neurobiological heterogeneity of schizophrenia. Thus, the current study supports the importance of paradigm shift toward biotype-based diagnosis, instead of phenotype, for future precision psychiatry.
Basal Ganglia* ; Brain ; Classification ; Cluster Analysis ; Diagnosis ; Dopamine ; Healthy Volunteers ; Humans ; Magnetic Resonance Imaging ; Pathology ; Phenotype ; Polytetrafluoroethylene ; Population Characteristics ; Psychotic Disorders* ; Schizophrenia ; Weights and Measures

Brain ; pathology ; Electroconvulsive Therapy ; adverse effects ; Humans ; Schizophrenia ; therapy

Early detection is a crucial milestone in the prevention and treatment of schizophrenia spectrum psychosis, which might alter the course of schizophrenia. Currently, there are two complementary approaches to characterizing the clinical-high risk state of psychosis : the ultra-high risk (UHR) and basic symptoms criteria. Individuals at UHR have two phase-specific problems : heightened risk for the potential pathology of schizophrenia spectrum psychosis and the symptoms, distress and psychosocial functional impairment, which make them seek help. The clinical characteristics of UHR are similar to those of overt psychotic disorders in terms of psychopathological symptoms dimensions, psychosocial disability, neurocognitive and socio-cognitive impairments, history of trauma and abuse experience, lack of protective factors and dysfunctional metacognitive beliefs, and the comorbidity of psychiatric illness. Regarding the risk, the pretest risk probability of a psychotic disorder in each high-risk clinic is considered an important factor for predicting the power of an early detection strategy. For the distress and psychosocial disability, the strategies of the therapeutic intervention will be a focus of clinical attention. On the follow-up, one of third of the UHR individuals have sufficient positive symptom to fulfil the at-risk criteria. Most of the UHR individuals have suffered from comorbid psychiatric illness at the times of both baseline and follow-up, and there is no improvement of psychosocial functioning. Currently, it is essential to optimize the early detection and intervention strategy according to the referring and recruitment characteristics of each high-risk clinic in Korean practice situations.
Comorbidity ; Diagnosis* ; Follow-Up Studies ; Pathology ; Protective Factors ; Psychotic Disorders* ; Schizophrenia

Cross-sectional and longitudinal studies have identified widespread and progressive grey matter volume (GMV) reductions in schizophrenia, especially in the frontal lobe. In this study, we found a progressive GMV decrease in the rostral medial frontal cortex (rMFC, including the anterior cingulate cortex) in the patient group during a 6-week follow-up of 40 patients with schizophrenia and 31 healthy controls well-matched for age, gender, and education. The higher baseline GMV in the rMFC predicted better improvement in the positive score on the Positive and Negative Syndrome Scale (PANSS), and this might be related to the improved reality-monitoring. Besides, a higher baseline GMV in the posterior rMFC predicted better remission of general symptoms, and a lesser GMV reduction in this region was correlated with better remission of negative symptoms, probably associated with ameliorated self-referential processing and social cognition. Besides, a shorter disease course and higher educational level contributed to better improvement in the general psychopathological PANSS score, and a family history was negatively associated with improvement of the negative and total PANSS scores. These phenomena might be important for understanding the neuropathological mechanisms underlying the symptoms of schizophrenia and for making clinical decisions.
Adult ; Antipsychotic Agents ; therapeutic use ; Female ; Frontal Lobe ; diagnostic imaging ; drug effects ; pathology ; Genetic Predisposition to Disease ; Gray Matter ; diagnostic imaging ; drug effects ; pathology ; Humans ; Image Processing, Computer-Assisted ; Longitudinal Studies ; Magnetic Resonance Imaging ; Male ; Organ Size ; Psychiatric Status Rating Scales ; Regression Analysis ; Schizophrenia ; diagnostic imaging ; drug therapy ; genetics ; pathology ; Time Factors ; Treatment Outcome

OBJECTIVES: Social cognition plays an important role in psychiatric symptoms and prognosis in patients with schizophrenia. Diagnostic scales are predominantly text-based or intended for the evaluation of theoretical concepts, with limited usefulness in clinical settings. We therefore developed a video based social cognition scale. METHODS: Our scale consists of 20 video clips portraying frequently experienced social interactions in real life. Patients were asked which interactions were socially unnatural and the reasons for lies told by actors. Our scale was validated and social cognition and its relationship with symptoms was evaluated using item response theory. RESULTS: A total of 209 participants (schizophrenia, 101 ; bipolar disorder, 49 ; healthy controls 59) were enrolled. Our scale showed high reliability and concurrent validity compared with the order subtest of the short form of the Weschler Adult Intelligence scale. Internal validity also was high (Cronbach's alpha=0.904). Most items were easy to answer and highly discriminative. The test information curve showed our scale to be more informative in patients with low social cognition ability. CONCLUSION: Our scale may aid in the study of pathology and social cognition deficits in patients with schizophrenia.
Adult ; Bipolar Disorder ; Cognition* ; Humans ; Intelligence ; Interpersonal Relations ; Pathology ; Prognosis ; Schizophrenia* ; Theory of Mind ; Weights and Measures

BACKGROUNDAuditory verbal hallucinations (AVHs) of schizophrenia have been associated with structural and functional alterations of some brain regions. However, the brain regional homogeneity (ReHo) alterations specific to AVHs of schizophrenia remain unclear. In the current study, we aimed to investigate ReHo alterations specific to schizophrenic AVHs.

METHODSThirty-five schizophrenic patients with AVH, 41 schizophrenic patients without AVHs, and fifty healthy subjects underwent resting-state functional magnetic resonance imaging. ReHo differences across the three groups were tested using a voxel-wise analysis.

RESULTSCompared with the healthy control group, the two schizophrenia groups showed significantly increased ReHo in the right caudate and inferior temporal gyrus and decreased ReHo in the bilateral postcentral gyrus and thalamus and the right inferior occipital gyrus (false discovery rate corrected, P < 0.05). More importantly, the AVH group exhibited significantly increased ReHo in the left precuneus compared with the non-AVH group. However, using correlation analysis, we did not find any correlation between the auditory hallucination rating scale score and the ReHo of brain regions.

CONCLUSIONSOur results suggest that increased ReHo in the left precuneus may be a pathological feature exclusive to schizophrenic AVHs.

Adult ; Female ; Hallucinations ; pathology ; physiopathology ; Humans ; Magnetic Resonance Imaging ; Male ; Parietal Lobe ; physiopathology ; Schizophrenia ; pathology ; physiopathology