Biomarkers , Magnetic Resonance Imaging , Melanins , Schizophrenia , Humans , Schizophrenia/metabolism , Schizophrenia/diagnostic imaging , Magnetic Resonance Imaging/methods , Melanins/metabolism , Biomarkers/metabolism , Antipsychotic Agents/therapeutic use , Drug Resistance , Brain/diagnostic imaging , Brain/metabolism
Advanced methods such as REACT have allowed the integration of fMRI with the brain's receptor landscape, providing novel insights transcending the multiscale organisation of the brain. Similarly, normative modelling has allowed translational neuroscience to move beyond group-average differences and characterise deviations from health at an individual level. Here, we bring these methods together for the first time. We used REACT to create functional networks enriched with the main modulatory, inhibitory, and excitatory neurotransmitter systems and generated normative models of these networks to capture functional connectivity deviations in patients with schizophrenia, bipolar disorder (BPD), and ADHD. Substantial overlap was seen in symptomatology and deviations from normality across groups, but these could be mapped into a common space linking constellations of symptoms through to underlying neurobiology transdiagnostically. This work provides impetus for developing novel biomarkers that characterise molecular- and systems-level dysfunction at the individual level, facilitating the transition towards mechanistically targeted treatments.
Magnetic Resonance Imaging , Schizophrenia , Humans , Schizophrenia/physiopathology , Schizophrenia/diagnostic imaging , Adult , Male , Brain/physiopathology , Brain/diagnostic imaging , Female , Bipolar Disorder/physiopathology , Attention Deficit Disorder with Hyperactivity/physiopathology , Attention Deficit Disorder with Hyperactivity/diagnostic imaging , Mental Disorders/physiopathology , Mental Disorders/diagnostic imaging , Young Adult , Models, Neurological , Middle Aged , Nerve Net/physiopathology , Nerve Net/diagnostic imaging
Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.
Bipolar Disorder , Magnetic Resonance Imaging , Obesity , Principal Component Analysis , Humans , Bipolar Disorder/diagnostic imaging , Bipolar Disorder/drug therapy , Bipolar Disorder/pathology , Adult , Female , Male , Magnetic Resonance Imaging/methods , Middle Aged , Obesity/diagnostic imaging , Schizophrenia/diagnostic imaging , Schizophrenia/pathology , Schizophrenia/drug therapy , Schizophrenia/physiopathology , Cerebral Cortex/diagnostic imaging , Cerebral Cortex/pathology , Cluster Analysis , Young Adult , Brain/diagnostic imaging , Brain/pathology
There is a lack of knowledge regarding the relationship between proneness to dimensional psychopathological syndromes and the underlying pathogenesis across major psychiatric disorders, i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizoaffective Disorder (SZA), and Schizophrenia (SZ). Lifetime psychopathology was assessed using the OPerational CRITeria (OPCRIT) system in 1,038 patients meeting DSM-IV-TR criteria for MDD, BD, SZ, or SZA. The cohort was split into two samples for exploratory and confirmatory factor analyses. All patients were scanned with 3-T MRI, and data was analyzed with the CAT-12 toolbox in SPM12. Psychopathological factor scores were correlated with gray matter volume (GMV) and cortical thickness (CT). Finally, factor scores were used for exploratory genetic analyses including genome-wide association studies (GWAS) and polygenic risk score (PRS) association analyses. Three factors (paranoid-hallucinatory syndrome, PHS; mania, MA; depression, DEP) were identified and cross-validated. PHS was negatively correlated with four GMV clusters comprising parts of the hippocampus, amygdala, angular, middle occipital, and middle frontal gyri. PHS was also negatively associated with the bilateral superior temporal, left parietal operculum, and right angular gyrus CT. No significant brain correlates were observed for the two other psychopathological factors. We identified genome-wide significant associations for MA and DEP. PRS for MDD and SZ showed a positive effect on PHS, while PRS for BD showed a positive effect on all three factors. This study investigated the relationship of lifetime psychopathological factors and brain morphometric and genetic markers. Results highlight the need for dimensional approaches, overcoming the limitations of the current psychiatric nosology.
Bipolar Disorder , Depressive Disorder, Major , Genome-Wide Association Study , Gray Matter , Magnetic Resonance Imaging , Psychotic Disorders , Schizophrenia , Humans , Male , Female , Adult , Bipolar Disorder/genetics , Bipolar Disorder/pathology , Bipolar Disorder/diagnostic imaging , Depressive Disorder, Major/genetics , Depressive Disorder, Major/diagnostic imaging , Depressive Disorder, Major/pathology , Schizophrenia/genetics , Schizophrenia/pathology , Schizophrenia/diagnostic imaging , Psychotic Disorders/genetics , Psychotic Disorders/diagnostic imaging , Psychotic Disorders/pathology , Gray Matter/pathology , Gray Matter/diagnostic imaging , Middle Aged , Factor Analysis, Statistical , Brain/pathology , Brain/diagnostic imaging , Psychopathology , Multifactorial Inheritance/genetics , Cerebral Cortex/pathology , Cerebral Cortex/diagnostic imaging
Importance: In vivo imaging studies of reactive astrocytes are crucial for understanding the pathophysiology of schizophrenia because astrocytes play a critical role in glutamate imbalance and neuroinflammation. Objective: To investigate in vivo reactive astrocytes in patients with schizophrenia associated with positive symptoms using monoamine oxidase B (MAO-B)-binding fluorine 18 ([18F])-labeled THK5351 positron emission tomography (PET). Design, Setting, and Participants: In this case-control study, data were collected from October 1, 2021, to January 31, 2023, from the internet advertisement for the healthy control group and from the outpatient clinics of Seoul National University Hospital in Seoul, South Korea, for the schizophrenia group. Participants included patients with schizophrenia and age- and sex-matched healthy control individuals. Main Outcomes and Measures: Standardized uptake value ratios (SUVrs) of [18F]THK5351 in the anterior cingulate cortex (ACC) and hippocampus as primary regions of interest (ROIs), with other limbic regions as secondary ROIs, and the correlation between altered SUVrs and Positive and Negative Syndrome Scale (PANSS) positive symptom scores. Results: A total of 68 participants (mean [SD] age, 32.0 [7.0] years; 41 men [60.3%]) included 33 patients with schizophrenia (mean [SD] age, 32.3 [6.3] years; 22 men [66.7%]) and 35 healthy controls (mean [SD] age, 31.8 [7.6] years; 19 men [54.3%]) who underwent [18F]THK5351 PET scanning. Patients with schizophrenia showed significantly higher SUVrs in the bilateral ACC (left, F = 5.767 [false discovery rate (FDR)-corrected P = .04]; right, F = 5.977 [FDR-corrected P = .04]) and left hippocampus (F = 4.834 [FDR-corrected P = .04]) than healthy controls. Trend-level group differences between the groups in the SUVrs were found in the secondary ROIs (eg, right parahippocampal gyrus, F = 3.387 [P = .07]). There were positive correlations between the SUVrs in the bilateral ACC and the PANSS positive symptom scores (left, r = 0.423 [FDR-corrected P = .03]; right, r = 0.406 [FDR-corrected P = .03]) in patients with schizophrenia. Conclusions and Relevance: This case-control study provides novel in vivo imaging evidence of reactive astrocyte involvement in the pathophysiology of schizophrenia. Reactive astrocytes in the ACC may be a future target for the treatment of symptoms of schizophrenia, especially positive symptoms.
Astrocytes , Fluorine Radioisotopes , Positron-Emission Tomography , Schizophrenia , Humans , Schizophrenia/diagnostic imaging , Schizophrenia/metabolism , Male , Female , Adult , Astrocytes/metabolism , Case-Control Studies , Positron-Emission Tomography/methods , Gyrus Cinguli/diagnostic imaging , Hippocampus/diagnostic imaging
Schizophrenia (SZ) is a debilitating mental illness characterized by adolescence or early adulthood onset of psychosis, positive and negative symptoms, as well as cognitive impairments. Despite a plethora of studies leveraging functional connectivity (FC) from functional magnetic resonance imaging (fMRI) to predict symptoms and cognitive impairments of SZ, the findings have exhibited great heterogeneity. We aimed to identify congruous and replicable connectivity patterns capable of predicting positive and negative symptoms as well as cognitive impairments in SZ. Predictable functional connections (FCs) were identified by employing an individualized prediction model, whose replicability was further evaluated across three independent cohorts (BSNIP, SZ = 174; COBRE, SZ = 100; FBIRN, SZ = 161). Across cohorts, we observed that altered FCs in frontal-temporal-cingulate-thalamic network were replicable in prediction of positive symptoms, while sensorimotor network was predictive of negative symptoms. Temporal-parahippocampal network was consistently identified to be associated with reduced cognitive function. These replicable 23 FCs effectively distinguished SZ from healthy controls (HC) across three cohorts (82.7%, 90.2%, and 86.1%). Furthermore, models built using these replicable FCs showed comparable accuracies to those built using the whole-brain features in predicting symptoms/cognition of SZ across the three cohorts (r = .17-.33, p < .05). Overall, our findings provide new insights into the neural underpinnings of SZ symptoms/cognition and offer potential targets for further research and possible clinical interventions.
Cognitive Dysfunction , Connectome , Magnetic Resonance Imaging , Nerve Net , Schizophrenia , Humans , Schizophrenia/diagnostic imaging , Schizophrenia/physiopathology , Male , Adult , Female , Connectome/methods , Cognitive Dysfunction/diagnostic imaging , Cognitive Dysfunction/physiopathology , Cohort Studies , Nerve Net/diagnostic imaging , Nerve Net/physiopathology , Young Adult , Middle Aged
Schizophrenia has been considered to exhibit sex-related clinical differences that might be associated with distinctly abnormal brain asymmetries between sexes. One hundred and thirty-two antipsychotic-naïve first-episode patients with schizophrenia and 150 healthy participants were recruited in this study to investigate whether cortical asymmetry would exhibit sex-related abnormalities in schizophrenia. After a 1-yr follow-up, patients were rescanned to obtain the effect of antipsychotic treatment on cortical asymmetry. Male patients were found to show increased lateralization index while female patients were found to exhibit decreased lateralization index in widespread regions when compared with healthy participants of the corresponding sex. Specifically, the cortical asymmetry of male and female patients showed contrary trends in the cingulate, orbitofrontal, parietal, temporal, occipital, and insular cortices. This result suggested male patients showed a leftward shift of asymmetry while female patients showed a rightward shift of asymmetry in these above regions that related to language, vision, emotion, and cognition. Notably, abnormal lateralization indices remained stable after antipsychotic treatment. The contrary trends in asymmetry between female and male patients with schizophrenia together with the persistent abnormalities after antipsychotic treatment suggested the altered brain asymmetries in schizophrenia might be sex-related disturbances, intrinsic, and resistant to the effect of antipsychotic therapy.
Antipsychotic Agents , Cerebral Cortex , Functional Laterality , Magnetic Resonance Imaging , Schizophrenia , Sex Characteristics , Humans , Female , Male , Schizophrenia/drug therapy , Schizophrenia/pathology , Schizophrenia/diagnostic imaging , Schizophrenia/physiopathology , Adult , Cerebral Cortex/diagnostic imaging , Young Adult , Antipsychotic Agents/therapeutic use , Functional Laterality/physiology , Adolescent , Brain Mapping
BACKGROUND: Previous investigations have revealed substantial differences in neuroimaging characteristics between healthy controls (HCs) and individuals diagnosed with schizophrenia (SCZ). However, we are not entirely sure how brain activity links to symptoms in schizophrenia, and there is a need for reliable brain imaging markers for treatment prediction. METHODS: In this longitudinal study, we examined 56 individuals diagnosed with 56 SCZ and 51 HCs. The SCZ patients underwent a three-month course of antipsychotic treatment. We employed resting-state functional magnetic resonance imaging (fMRI) along with fractional Amplitude of Low Frequency Fluctuations (fALFF) and support vector regression (SVR) methods for data acquisition and subsequent analysis. RESULTS: In this study, we initially noted lower fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, coupled with higher fALFF values in the left hippocampus and right putamen in SCZ patients compared to the HCs at baseline. However, when comparing fALFF values in brain regions with abnormal baseline fALFF values for SCZ patients who completed the follow-up, no significant differences in fALFF values were observed after 3 months of treatment compared to baseline data. The fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, and the left postcentral gyrus were useful in predicting treatment effects. CONCLUSION: Our findings suggest that reduced fALFF values in the sensory-motor networks and increased fALFF values in the limbic system may constitute distinctive neurobiological features in SCZ patients. These findings may serve as potential neuroimaging markers for the prognosis of SCZ patients.
Antipsychotic Agents , Limbic System , Magnetic Resonance Imaging , Schizophrenia , Humans , Schizophrenia/physiopathology , Schizophrenia/diagnostic imaging , Schizophrenia/drug therapy , Male , Female , Adult , Antipsychotic Agents/pharmacology , Limbic System/diagnostic imaging , Limbic System/physiopathology , Longitudinal Studies , Young Adult , Treatment Outcome , Outcome Assessment, Health Care , Middle Aged , Support Vector Machine
In neuroimaging studies, combining data collected from multiple study sites or scanners is becoming common to increase the reproducibility of scientific discoveries. At the same time, unwanted variations arise by using different scanners (inter-scanner biases), which need to be corrected before downstream analyses to facilitate replicable research and prevent spurious findings. While statistical harmonization methods such as ComBat have become popular in mitigating inter-scanner biases in neuroimaging, recent methodological advances have shown that harmonizing heterogeneous covariances results in higher data quality. In vertex-level cortical thickness data, heterogeneity in spatial autocorrelation is a critical factor that affects covariance heterogeneity. Our work proposes a new statistical harmonization method called spatial autocorrelation normalization (SAN) that preserves homogeneous covariance vertex-level cortical thickness data across different scanners. We use an explicit Gaussian process to characterize scanner-invariant and scanner-specific variations to reconstruct spatially homogeneous data across scanners. SAN is computationally feasible, and it easily allows the integration of existing harmonization methods. We demonstrate the utility of the proposed method using cortical thickness data from the Social Processes Initiative in the Neurobiology of the Schizophrenia(s) (SPINS) study. SAN is publicly available as an R package.
Cerebral Cortex , Magnetic Resonance Imaging , Schizophrenia , Humans , Magnetic Resonance Imaging/standards , Magnetic Resonance Imaging/methods , Schizophrenia/diagnostic imaging , Schizophrenia/pathology , Cerebral Cortex/diagnostic imaging , Cerebral Cortex/anatomy & histology , Neuroimaging/methods , Neuroimaging/standards , Image Processing, Computer-Assisted/methods , Image Processing, Computer-Assisted/standards , Male , Female , Adult , Normal Distribution , Brain Cortical Thickness
Resting-state functional magnetic resonance imaging (rs-fMRI) has increasingly been used to study both Alzheimer's disease (AD) and schizophrenia (SZ). While most rs-fMRI studies being conducted in AD and SZ compare patients to healthy controls, it is also of interest to directly compare AD and SZ patients with each other to identify potential biomarkers shared between the disorders. However, comparing patient groups collected in different studies can be challenging due to potential confounds, such as differences in the patient's age, scan protocols, etc. In this study, we compared and contrasted resting-state functional network connectivity (rs-FNC) of 162 patients with AD and late mild cognitive impairment (LMCI), 181 schizophrenia patients, and 315 cognitively normal (CN) subjects. We used confounder-controlled rs-FNC and applied machine learning algorithms (including support vector machine, logistic regression, random forest, and k-nearest neighbor) and deep learning models (i.e., fully-connected neural networks) to classify subjects in binary and three-class categories according to their diagnosis labels (e.g., AD, SZ, and CN). Our statistical analysis revealed that FNC between the following network pairs is stronger in AD compared to SZ: subcortical-cerebellum, subcortical-cognitive control, cognitive control-cerebellum, and visual-sensory motor networks. On the other hand, FNC is stronger in SZ than AD for the following network pairs: subcortical-visual, subcortical-auditory, subcortical-sensory motor, cerebellum-visual, sensory motor-cognitive control, and within the cerebellum networks. Furthermore, we observed that while AD and SZ disorders each have unique FNC abnormalities, they also share some common functional abnormalities that can be due to similar neurobiological mechanisms or genetic factors contributing to these disorders' development. Moreover, we achieved an accuracy of 85% in classifying subjects into AD and SZ where default mode, visual, and subcortical networks contributed the most to the classification and accuracy of 68% in classifying subjects into AD, SZ, and CN with the subcortical domain appearing as the most contributing features to the three-way classification. Finally, our findings indicated that for all classification tasks, except AD vs. SZ, males are more predictable than females.
Alzheimer Disease , Machine Learning , Magnetic Resonance Imaging , Schizophrenia , Humans , Alzheimer Disease/physiopathology , Alzheimer Disease/diagnostic imaging , Female , Schizophrenia/physiopathology , Schizophrenia/diagnostic imaging , Male , Magnetic Resonance Imaging/methods , Aged , Middle Aged , Cognitive Dysfunction/physiopathology , Cognitive Dysfunction/diagnostic imaging , Nerve Net/physiopathology , Nerve Net/diagnostic imaging , Brain/diagnostic imaging , Brain/physiopathology , Connectome/methods , Rest/physiology , Case-Control Studies
Cortical bone thickness is essential for the mechanical function of bone. Some factors including aging, sex, body size, hormone levels, behavior, and genetics lead to changes in cranial cortical robusticity. Moreover, the skull is one of the hardest and most durable structures in the human body. Schizophrenia is defined as a psychiatric disease characterized by delusions and hallucinations, and these patients have reduced brain volume; however, there is no study including cortical bone structure. For this reason, the aim of this study was to determine whether there is a difference in the skull cortical thickness of patients with schizophrenia and, compare it with healthy subjects. The cranial length, cranial width, anterior cortical thickness, right and left anterior cortical thickness, right and left lateral cortical thickness, right and left posterior lateral thickness, and posterior cortical thickness were measured with axial computed tomography images of 30 patients with schizophrenia and 132 healthy individuals aged between 18 and 69years. A statistically significant difference was found between the two groups in the measurements of right and left posterior lateral thickness, and posterior cortical thickness ( P = 0.006, P = 0.001, and P = 0.047, respectively). The sexes were compared, and it was found that the cranial width, anterior thickness, left anterior thickness, and right and left posterior thickness measurements of patients with schizophrenia showed a statistically significant difference compared with the control group ( P < 0.001, P = 0.003, P = 0.001, P < 0.001 and P < 0.001, respectively). The authors observed that skull cortical thickness may be different in schizophrenia. The results obtained from this study may be beneficial for evaluating these structures for clinical and pathological processes. Furthermore, knowledge about the skull cortical thickness in planning surgical procedures will increase the reliability and effectiveness of the surgical method, and this will minimize the risk of complications.
Schizophrenia , Skull , Tomography, X-Ray Computed , Humans , Male , Female , Schizophrenia/diagnostic imaging , Schizophrenia/pathology , Adult , Middle Aged , Skull/diagnostic imaging , Tomography, X-Ray Computed/methods , Adolescent , Aged , Young Adult , Cortical Bone/diagnostic imaging , Cortical Bone/pathology , Case-Control Studies
BACKGROUND: The basal ganglia are important structures for the release of dopamine in the limbic circuits of the midbrain, and the striatum and globus pallidus are the major nuclei of the basal ganglia, and the dysfunction of these regions has been the basis of many models that have attempted to explain the underlying mechanisms of schizophrenia symptoms. The purpose of this study was to investigate the changes in the volume of the striatum subregion and globus pallidus in three different stages of schizophrenia, and to analyze whether these volume changes were related to antipsychotic drugs and schizophrenia symptoms. METHODS: In this study, we investigated the volume of the striatum and globus pallidus in patients with schizophrenia at three different stages. The study included 57 patients with first-episode schizophrenia (FSZ), 51 patients with early-stage schizophrenia (ESZ), 86 patients with chronic schizophrenia (CSZ), and 191 healthy controls (HC), all of whom underwent structured magnetic resonance imaging (MRI) scans. Covariance analysis was performed using SPSS 26.0 was used for covariance analysis to determine whether there were significant differences in striatal subregion and globus pallidus volume between groups, and stratified analysis was used to further eliminate the effect of age on brain volume. Finally, the correlation analysis between the region of interest and the cumulative dose of antipsychotic drugs and psychotic symptoms was performed. RESULTS: The comparison between the different stages of the illness showed significant volume differences in the left caudate nucleus (lCAU) (F = 2.665, adjusted p = 0.048), left putamen (lPUT) (F = 12.749, adjusted p < 0.001), left pallidum (lPAL) (F = 41.111, adjusted p < 0.001), and right pallidum (rPAL) (F = 14.479, adjusted p < 0.001). Post-hoc analysis with corrections showed that the volume differences in the lCAU subregion disappeared. Further stratified analysis controlling for age showed that compared with the HC, the lPAL (t = 4.347, p < 0.001) was initially significantly enlarged in the FSZ group, the lPUT (t = 4.493, p < 0.001), rPUT (t = 2.190, p = 0.031), lPAL (t = 7.894, p < 0.001), and rPAL (t = 4.983, p < 0.001) volumes were all significantly increased in the ESZ group, and the lPUT (t = 3.314, p = 0.002), lPAL (t = 6.334, p < 0.001), and rPAL (t = 3.604, p < 0.001) subregion volumes were also significantly increased in the CSZ group. Correlation analysis showed that lPUT and bilateral globus pallidus were associated with cumulative dose of antipsychotics, but were not associated with clinical symptoms in each subregion. CONCLUSION: The findings suggest that different subregions of the striatum and globus pallidus show significant volume differences at different stages of schizophrenia compared to HC. These volume differences may be strong radiographic evidence for schizophrenia. In addition, the lPAL was the only significantly different brain region observed in the FSZ group, suggesting that it may be a sensitive indicator of early brain structural changes in schizophrenia. Finally, our findings support the hypothesis that antipsychotic drugs have an effect on the volume of brain structures.
Antipsychotic Agents , Corpus Striatum , Globus Pallidus , Magnetic Resonance Imaging , Schizophrenia , Humans , Schizophrenia/pathology , Schizophrenia/diagnostic imaging , Globus Pallidus/diagnostic imaging , Globus Pallidus/pathology , Male , Female , Adult , Retrospective Studies , Corpus Striatum/diagnostic imaging , Corpus Striatum/pathology , Young Adult , Antipsychotic Agents/therapeutic use , Middle Aged , Disease Progression
BACKGROUND: Gamma-band activity has been the focus of considerable research in schizophrenia. Discrepancies exist regarding the integrity of the early auditory gamma-band response (EAGBR), a stimulus-evoked oscillation, and its relationship to symptoms in early disease. Variability in task design may play a role. This study examined sensitivity of the EAGBR to stimulus intensity and its relation to symptoms and functional impairments in the first-episode schizophrenia spectrum (FESz). METHOD: Magnetoencephalography was recorded from 35 FESz and 40 matched healthy controls (HC) during presentation of 3 tone intensities (75 dB, 80 dB, 85 dB). MRIs were collected to localize auditory cortex activity. Wavelet-transformed single trial epochs and trial averages were used to assess EAGBR intertrial phase coherence (ITPC) and evoked power, respectively. Symptoms were assessed using the Positive and Negative Syndrome Scale. RESULTS: Groups did not differ in overall EAGBR power or ITPC. While HC exhibited EAGBR enhancement to increasing intensity, FESz exhibited reduced power to the 80 dB tone and, relative to HC, increased power to the 75 dB tone. Larger power and ITPC were correlated with more severe negative, thought disorganization, and resistance symptoms. Stronger ITPC was associated with impaired social functioning. DISCUSSION: EAGBR showed no overall deficit at disease onset. Rather, FESz exhibited a differential response across tone intensity relative to HC, emphasizing the importance of stimulus characteristics in EAGBR studies. Associations between larger EAGBR and more severe symptoms suggest aberrant synchronization driving overinclusive perceptual binding that may relate to deficits in executive inhibition of initial sensory activity.
Auditory Cortex , Evoked Potentials, Auditory , Gamma Rhythm , Magnetoencephalography , Schizophrenia , Humans , Schizophrenia/physiopathology , Schizophrenia/diagnostic imaging , Male , Female , Gamma Rhythm/physiology , Young Adult , Adult , Evoked Potentials, Auditory/physiology , Auditory Cortex/physiopathology , Auditory Cortex/diagnostic imaging , Magnetic Resonance Imaging , Acoustic Stimulation , Adolescent
BACKGROUND: Violence in schizophrenia (SCZ) is a phenomenon associated with neurobiological factors. However, the neural mechanisms of violence in patients with SCZ are not yet sufficiently understood. Thus, this study aimed to explore the structural changes associated with the high risk of violence and its association with impulsiveness in patients with SCZ to reveal the possible neurobiological basis. METHOD: The voxel-based morphometry approach and whole-brain analyses were used to measure the alteration of gray matter volume (GMV) for 45 schizophrenia patients with violence (VSC), 45 schizophrenia patients without violence (NSC), and 53 healthy controls (HC). Correlation analyses were used to examine the association of impulsiveness and brain regions associated with violence. RESULTS: The results demonstrated reduced GMV in the right insula within the VSC group compared with the NSC group, and decreased GMV in the right temporal pole and left orbital part of superior frontal gyrus only in the VSC group compared to the HC group. Spearman correlation analyses further revealed a positive correlation between impulsiveness and GMV of the left superior temporal gyrus, bilateral insula and left medial orbital part of the superior frontal gyrus in the VSC group. CONCLUSION: Our findings have provided further evidence for structural alterations in patients with SCZ who had engaged in severe violence, as well as the relationship between the specific brain alterations and impulsiveness. This work provides neural biomarkers and improves our insight into the neural underpinnings of violence in patients with SCZ.
Schizophrenia , Humans , Male , Schizophrenia/diagnostic imaging , Brain/diagnostic imaging , Gray Matter/diagnostic imaging , Prefrontal Cortex , Cerebral Cortex/diagnostic imaging , Magnetic Resonance Imaging/methods
BACKGROUND: Lateral ventricular enlargement represents a canonical morphometric finding in chronic patients with schizophrenia; however, longitudinal studies elucidating complex dynamic trajectories of ventricular volume change during critical early disease stages are sparse. METHODS: We measured lateral ventricular volumes in 113 first-episode schizophrenia patients (FES) at baseline visit (11.7 months after illness onset, SD = 12.3) and 128 age- and sex-matched healthy controls (HC) using 3T MRI. MRI was then repeated in both FES and HC one year later. RESULTS: Compared to controls, ventricular enlargement was identified in 18.6% of patients with FES (14.1% annual ventricular volume (VV) increase; 95%CI: 5.4; 33.1). The ventricular expansion correlated with the severity of PANSS-negative symptoms at one-year follow-up (p = 0.0078). Nevertheless, 16.8% of FES showed an opposite pattern of statistically significant ventricular shrinkage during ≈ one-year follow-up (-9.5% annual VV decrease; 95%CI: -23.7; -2.4). There were no differences in sex, illness duration, age of onset, duration of untreated psychosis, body mass index, the incidence of Schneiderian symptoms, or cumulative antipsychotic dose among the patient groups exhibiting ventricular enlargement, shrinkage, or no change in VV. CONCLUSION: Both enlargement and ventricular shrinkage are equally present in the early stages of schizophrenia. The newly discovered early reduction of VV in a subgroup of patients emphasizes the need for further research to understand its mechanisms.
Magnetic Resonance Imaging , Schizophrenia , Humans , Schizophrenia/diagnostic imaging , Schizophrenia/pathology , Schizophrenia/physiopathology , Male , Female , Longitudinal Studies , Adult , Young Adult , Cerebral Ventricles/diagnostic imaging , Cerebral Ventricles/pathology , Lateral Ventricles/diagnostic imaging , Lateral Ventricles/pathology , Disease Progression , Case-Control Studies , Adolescent
BACKGROUND: Distinguishing untreated major depressive disorder without medication (MDD) from schizophrenia with depressed mood (SZDM) poses a clinical challenge. This study aims to investigate differences in fractional amplitude of low-frequency fluctuations (fALFF) and cognition in untreated MDD and SZDM patients. METHODS: The study included 42 untreated MDD cases, 30 SZDM patients, and 46 healthy controls (HC). Cognitive assessment utilized the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Resting-state functional magnetic resonance imaging (rs-fMRI) scans were conducted, and data were processed using fALFF in slow-4 and slow-5 bands. RESULTS: Significant fALFF changes were observed in four brain regions across MDD, SZDM, and HC groups for both slow-4 and slow-5 fALFF. Compared to SZDM, the MDD group showed increased slow-5 fALFF in the right gyrus rectus (RGR). Relative to HC, SZDM exhibited decreased slow-5 fALFF in the left gyrus rectus (LGR) and increased slow-5 fALFF in the right putamen. Changes in slow-5 fALFF in both RGR and LGR were negatively correlated with RBANS scores. No significant correlations were found between remaining fALFF (slow-4 and slow-5 bands) and RBANS scores in MDD or SZDM groups. CONCLUSIONS: Alterations in slow-5 fALFF in RGR may serve as potential biomarkers for distinguishing MDD from SZDM, providing preliminary insights into the neural mechanisms of cognitive function in schizophrenia.
Depressive Disorder, Major , Magnetic Resonance Imaging , Schizophrenia , Humans , Depressive Disorder, Major/physiopathology , Depressive Disorder, Major/diagnostic imaging , Male , Female , Adult , Schizophrenia/physiopathology , Schizophrenia/diagnostic imaging , Schizophrenia/complications , Cognition/physiology , Brain/physiopathology , Brain/diagnostic imaging , Neuropsychological Tests/statistics & numerical data , Middle Aged , Young Adult , Cognitive Dysfunction/physiopathology , Cognitive Dysfunction/diagnostic imaging
Background and Objectives: Neuroimaging reveals a link between psychiatric conditions and brain structural-functional changes, prompting a paradigm shift in viewing schizophrenia as a neurodevelopmental disorder. This study aims to identify and compare structural brain changes found during the first schizophrenia episode with those found after more than 5 years of illness. Materials and Methods: This prospective study involved 149 participants enrolled between 1 January 2019 and 31 December 2021. The participants were categorized into three groups: the first comprises 51 individuals with an initial psychotic episode, the second consists of 49 patients diagnosed with schizophrenia for over 5 years, and a control group comprising 50 individuals without a diagnosis of schizophrenia or any other psychotic disorder. All participants underwent brain CT examinations. Results: The study examined all three groups: first-episode schizophrenia (FES), schizophrenia (SCZ), and the control group. The FES group had a mean age of 26.35 years and a mean duration of illness of 1.2 years. The SCZ group, with a mean age of 40.08 years, had been diagnosed with schizophrenia for an average of 15.12 years. The control group, with a mean age of 34.60 years, had no schizophrenia diagnosis. Structural measurements revealed widening of frontal horns and lateral ventricles in the SCZ group compared to FES and the FES group compared to the control group. Differences in the dimensions of the third ventricle were noted between SCZ and FES, while no distinction was observed between FES and the control group. The fourth ventricle had similar measurements in FES and SCZ groups, both exceeding those of the control group. Our results showed higher densities in the frontal lobe in schizophrenia patients compared to FES and the control group, with the control group consistently displaying the lowest densities. Conclusions: In summary, our comparative imaging analysis of schizophrenia patients, first-episode schizophrenia, and control patients revealed distinct ventricular patterns, with SCZ showing greater widening than FES and FES wider than the control group. Frontal lobe density, assessed via cerebral CT scans, indicated a higher density in the SCZ group in both anterior and posterior cortex portions compared to FES and the control group, while the left posterior cortex in FES had the highest density. These findings highlight unique neuroanatomical features across groups, shedding light on structural differences associated with different stages of schizophrenia.
Brain , Schizophrenia , Humans , Schizophrenia/diagnostic imaging , Schizophrenia/physiopathology , Schizophrenia/complications , Adult , Female , Male , Prospective Studies , Brain/diagnostic imaging , Brain/physiopathology , Tomography, X-Ray Computed/methods , Neuroimaging/methods , Middle Aged
The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effective use of this treatment option in patients with schizophrenia. This variability may be deciphered by leveraging predictive information in structural MRI, clinical, sociodemographic, and genetic data using artificial intelligence. We developed and cross-validated rTMS response prediction models in patients with schizophrenia drawn from the multisite RESIS trial. The models incorporated pre-treatment sMRI, clinical, sociodemographic, and polygenic risk score (PRS) data. Patients were randomly assigned to receive active (N = 45) or sham (N = 47) rTMS treatment. The prediction target was individual response, defined as ≥20% reduction in pre-treatment negative symptom sum scores of the Positive and Negative Syndrome Scale. Our multimodal sequential prediction workflow achieved a balanced accuracy (BAC) of 94% (non-responders: 92%, responders: 95%) in the active-treated group and 50% in the sham-treated group. The clinical, clinical + PRS, and sMRI-based classifiers yielded BACs of 65%, 76%, and 80%, respectively. Apparent sadness, inability to feel, educational attainment PRS, and unemployment were most predictive of non-response in the clinical + PRS model, while grey matter density reductions in the default mode, limbic networks, and the cerebellum were most predictive in the sMRI model. Our sequential modelling approach provided superior predictive performance while minimising the diagnostic burden in the clinical setting. Predictive patterns suggest that rTMS responders may have higher levels of brain grey matter in the default mode and salience networks which increases their likelihood of profiting from plasticity-inducing brain stimulation methods, such as rTMS. The future clinical implementation of our models requires findings to be replicated at the international scale using stratified clinical trial designs.
Machine Learning , Magnetic Resonance Imaging , Schizophrenia , Transcranial Magnetic Stimulation , Humans , Schizophrenia/therapy , Schizophrenia/diagnostic imaging , Schizophrenia/physiopathology , Transcranial Magnetic Stimulation/methods , Female , Male , Adult , Workflow , Treatment Outcome , Middle Aged , Young Adult
BACKGROUND: Previous studies have documented thalamic functional connectivity (FC) abnormalities in schizophrenia, typically examining the thalamus as a whole. The specific link between subregional thalamic FC and cognitive deficits in first-episode schizophrenia (FES) remains unexplored. METHODS: Using data from resting-state functional magnetic resonance imaging, we compared whole-brain FC with thalamic subregions between patients and HCs, and analyzed FC changes in drug-naïve patients separately. We then examined correlations between FC abnormalities with both cognitive impairment and clinical symptoms. RESULTS: A total of 33 FES patients (20 drug-naïve) and 32 age- and sex-matched healthy controls (HCs) were included. Compared to HCs, FES patients exhibited increased FC between specific thalamic subregions and cortical regions, particularly bilateral middle temporal lobe and cuneus gyrus, left medial superior frontal gyrus, and right inferior/superior occipital gyrus. Decreased FC was observed between certain thalamic subregions and the left inferior frontal triangle. These findings were largely consistent in drug-naïve patients. Notably, deficits in social cognition and visual learning in FES patients correlated with increased FC between certain thalamic subregions and cortical regions involving the right superior occipital gyrus and cuneus gyrus. The severity of negative symptoms was associated with increased FC between a thalamic subregion and the left middle temporal gyrus. CONCLUSION: Our findings suggest FC abnormalities between thalamic subregions and cortical areas in FES patients. Increased FC correlated with cognitive deficits and negative symptoms, highlighting the importance of thalamo-cortical connectivity in the pathophysiology of schizophrenia.
Cognitive Dysfunction , Magnetic Resonance Imaging , Schizophrenia , Thalamus , Humans , Schizophrenia/physiopathology , Schizophrenia/diagnostic imaging , Male , Female , Thalamus/physiopathology , Thalamus/diagnostic imaging , Adult , Cognitive Dysfunction/physiopathology , Cognitive Dysfunction/etiology , Cognitive Dysfunction/diagnostic imaging , Young Adult , Cerebral Cortex/physiopathology , Cerebral Cortex/diagnostic imaging , Connectome , Nerve Net/physiopathology , Nerve Net/diagnostic imaging
Schizophrenia is accompanied by aberrant interactions of intrinsic brain networks. However, the modulatory effect of electroencephalography (EEG) rhythms on the functional connectivity (FC) in schizophrenia remains unclear. This study aims to provide new insight into network communication in schizophrenia by integrating FC and EEG rhythm information. After collecting simultaneous resting-state EEG-functional magnetic resonance imaging data, the effect of rhythm modulations on FC was explored using what we term "dynamic rhythm information." We also investigated the synergistic relationships among three networks under rhythm modulation conditions, where this relationship presents the coupling between two brain networks with other networks as the center by the rhythm modulation. This study found FC between the thalamus and cortical network regions was rhythm-specific. Further, the effects of the thalamus on the default mode network (DMN) and salience network (SN) were less similar under alpha rhythm modulation in schizophrenia patients than in controls ([Formula: see text]). However, the similarity between the effects of the central executive network (CEN) on the DMN and SN under gamma modulation was greater ([Formula: see text]), and the degree of coupling was negatively correlated with the duration of disease ([Formula: see text], [Formula: see text]). Moreover, schizophrenia patients exhibited less coupling with the thalamus as the center and greater coupling with the CEN as the center. These results indicate that modulations in dynamic rhythms might contribute to the disordered functional interactions seen in schizophrenia.
Cerebral Cortex , Electroencephalography , Magnetic Resonance Imaging , Nerve Net , Schizophrenia , Thalamus , Humans , Schizophrenia/physiopathology , Schizophrenia/diagnostic imaging , Thalamus/physiopathology , Thalamus/diagnostic imaging , Cerebral Cortex/physiopathology , Cerebral Cortex/diagnostic imaging , Adult , Male , Female , Nerve Net/physiopathology , Nerve Net/diagnostic imaging , Brain Waves/physiology , Young Adult , Neural Pathways/physiopathology , Default Mode Network/physiopathology , Default Mode Network/diagnostic imaging , Connectome