Altered thalamic volumes and functional connectivity in the recovered patients with psychosis.

BACKGROUND: Investigating neural correlates in recovered patients with psychosis is important in terms of identifying biological markers associated with recovery status or predicting a possible future relapse. We sought to examine thalamic nuclei volumes and thalamus-centered functional connectivity (FC) in recovered patients with psychosis who discontinued their medication. METHODS: Thirty patients with psychosis who satisfied the criteria for full recovery and 50 healthy controls (HC) matched for age, sex, and education underwent magnetic resonance imaging and clinical evaluation. The recovered patients were divided into the maintained and relapsed subjects according to their clinical status on the follow-ups. Thalamic nuclei volumes and thalamus-centered FC were measured between the recovered patients and HC. Correlations between the thalamic nuclei or altered FC, and clinical symptoms and cognitive functioning were explored. RESULTS: Modest cognitive impairments and reduced thalamic nuclei volumes were evident in the recovered patients. Moreover, we found altered thalamo-cortical connectivity and its associations with negative symptoms and cognitive functioning in the recovered patients compared with HC. CONCLUSION: These findings suggest that there are still cognitive impairments, and aberrant neuronal changes in the recovered patients. The implication of differential FC patterns between the maintained and the relapsed patients remain to be further explored.

Deep Learning-based Brain Age Prediction in Patients With Schizophrenia Spectrum Disorders.

BACKGROUND AND HYPOTHESIS: The brain-predicted age difference (brain-PAD) may serve as a biomarker for neurodegeneration. We investigated the brain-PAD in patients with schizophrenia (SCZ), first-episode schizophrenia spectrum disorders (FE-SSDs), and treatment-resistant schizophrenia (TRS) using structural magnetic resonance imaging (sMRI). STUDY DESIGN: We employed a convolutional network-based regression (SFCNR), and compared its performance with models based on three machine learning (ML) algorithms. We pretrained the SFCNR with sMRI data of 7590 healthy controls (HCs) selected from the UK Biobank. The parameters of the pretrained model were transferred to the next training phase with a new set of HCs (n = 541). The brain-PAD was analyzed in independent HCs (n = 209) and patients (n = 233). Correlations between the brain-PAD and clinical measures were investigated. STUDY RESULTS: The SFCNR model outperformed three commonly used ML models. Advanced brain aging was observed in patients with SCZ, FE-SSDs, and TRS compared to HCs. A significant difference in brain-PAD was observed between FE-SSDs and TRS with ridge regression but not with the SFCNR model. Chlorpromazine equivalent dose and cognitive function were correlated with the brain-PAD in SCZ and FE-SSDs. CONCLUSIONS: Our findings indicate that there is advanced brain aging in patients with SCZ and higher brain-PAD in SCZ can be used as a surrogate marker for cognitive dysfunction. These findings warrant further investigations on the causes of advanced brain age in SCZ. In addition, possible psychosocial and pharmacological interventions targeting brain health should be considered in early-stage SCZ patients with advanced brain age.

Network biomarkers in recovered psychosis patients who discontinued antipsychotics.

There are no studies investigating topological properties of resting-state fMRI (rs-fMRI) in patients who have recovered from psychosis and discontinued medication (hereafter, recovered patients [RP]). This study aimed to explore topological organization of the functional brain connectome in the RP using graph theory approach. We recruited 30 RP and 50 age and sex-matched healthy controls (HC). The RP were further divided into the subjects who were relapsed after discontinuation of antipsychotics (RP-R) and who maintained recovered state without relapse (RP-M). Using graph-based network analysis of rs-fMRI signals, global and local metrics and hub information were obtained. The robustness of the network was tested with random failure and targeted attack. As an ancillary analysis, Network-Based Statistic (NBS) was performed. Association of significant findings with psychopathology and cognitive functioning was also explored. The RP showed intact network properties in terms of global and local metrics. However, higher global functional connectivity strength and hyperconnectivity in the interconnected component were observed in the RP compared to HC. In the subgroup analysis, the RP-R were found to have lower global efficiency, longer characteristic path length and lower robustness whereas no such abnormalities were identified in the RP-M. Associations of the degree centrality of some hubs with cognitive functioning were identified in the RP-M. Even though network properties of the RP were intact, subgroup analysis revealed more altered topological organizations in the RP-R. The findings in the RP-R and RP-M may serve as network biomarkers for predicting relapse or maintained recovery after the discontinuation of antipsychotics.

Neuronal signatures of anger and fear in patients with psychosis.

The present study investigated the functional neuroanatomy in response to sentence stimuli related to anger-provoking situations and fear of negative evaluation in patients with psychosis. The tasks consisted of four active conditions, Self-Anger (SA), Self-Fear, Other-Anger (OA), and Other-Fear (OF), and two neutral conditions, Neutral-Anger (NA) and Neutral-Fear (NF). Several relevant clinical measures were obtained. Under all contrasts, significantly higher activation in the left inferior parietal gyrus or superior parietal gyrus and the left middle occipital gyrus or superior occipital gyrus was observed in patients compared to healthy controls (HCs). However, we observed significantly lower activation in the left angular gyrus (AG) and left middle temporal gyrus (MTG) under the OA vs. NA contrast, as well as in the left precuneus and left posterior cingulate gyrus (PCG) under the OF vs. NF contrast in patients. The mean beta values for the significant regions under the SA vs. NA and OF vs. NF contrasts were significantly associated with the total PI and PANSS scores, respectively. These findings indicate that patients with psychosis exhibit hypoactivation in the AG, MTG, precuneus, and PCG compared to HCs. The findings suggest that patients with psychosis are less efficient at recruiting neural responses in those regions for semantic processing and social evaluation.

Differential effects of parental socioeconomic status on cortical thickness in patients with schizophrenia spectrum disorders and healthy controls.

OBJECTIVES: Widespread changes in cortical thickness (CT) have been repeatedly reported in schizophrenia (SZ). The nature of the pathophysiologic process underlying such changes remains to be elucidated. The aims of the present study were to measure the CT; evaluate parent socioeconomic status (pSES), childhood trauma (ChT) and premorbid adjustment (PA) in patients with schizophrenia spectrum disorders (SSDs); and investigate group differences in CT (i.e., SSD vs. healthy controls (HCs)), pSES, PA, and/or ChT, as well as the interactions among these factors. METHODS: 164 patients with SSD and 245 age-, sex- and education-matched healthy controls have participated. The pSES, ChT and PA were evaluated using Korean version of Polyenvironmental Risk Score, Early Trauma Inventory Self Report-Short Form and Premorbid Adjustment Scale, respectively. Vertex-wise measure of CT was estimated using the FreeSurfer. To investigate the main effects and interactions, multilevel regression was employed. RESULTS: We found widespread cortical thinning in patients with SSDs compared to HCs. The cortical thinning was associated with ChT, symptom severity and chlorpromazine equivalent dose and duration of illness in patients. In multilevel regression, main effects of group and pSES and interaction between group and pSES were found whereas a significant interaction between ChT and CPZ equivalent was found in patients. CONCLUSION: Our findings indicate that compared to HCs, patients with SSDs have cortical structural abnormalities, and that group and pSES interaction determines CT. Further studies are needed to explore the effects of psychosocial factors on brain structural and functional abnormalities in SZ.

Stage-Specific Brain Aging in First-Episode Schizophrenia and Treatment-Resistant Schizophrenia.

BACKGROUND: Brain age is a popular brain-based biomarker that offers a powerful strategy for using neuroscience in clinical practice. We investigated the brain-predicted age difference (PAD) in patients with schizophrenia (SCZ), first-episode schizophrenia spectrum disorders (FE-SSDs), and treatment-resistant schizophrenia (TRS) using structural magnetic resonance imaging data. The association between brain-PAD and clinical parameters was also assessed. METHODS: We developed brain age prediction models for the association between 77 average structural brain measures and age in a training sample of controls (HCs) using ridge regression, support vector regression, and relevance vector regression. The trained models in the controls were applied to the test samples of the controls and 3 patient groups to obtain brain-based age estimates. The correlations were tested between the brain PAD and clinical measures in the patient groups. RESULTS: Model performance indicated that, regardless of the type of regression metric, the best model was support vector regression and the worst model was relevance vector regression for the training HCs. Accelerated brain aging was identified in patients with SCZ, FE-SSDs, and TRS compared with the HCs. A significant difference in brain PAD was observed between FE-SSDs and TRS using the ridge regression algorithm. Symptom severity, the Social and Occupational Functioning Assessment Scale, chlorpromazine equivalents, and cognitive function were correlated with the brain PAD in the patient groups. CONCLUSIONS: These findings suggest additional progressive neuronal changes in the brain after SCZ onset. Therefore, pharmacological or psychosocial interventions targeting brain health should be developed and provided during the early course of SCZ.

Altered functional connectivity in psychotic disorder not otherwise specified.

BACKGROUND: Few studies have investigated functional connectivity (FC) in patients with psychotic disorder not otherwise specified (PNOS). We sought to identify distinct FC differentiating PNOS from schizophrenia (SZ). METHODS: In total, 49 patients with PNOS, 42 with SZ, and 55 healthy controls (HC) matched for age, sex, and education underwent functional magnetic resonance imaging (fMRI) brain scans and clinical evaluation. Using six functional networks consisting of 40 regions of interest (ROIs), we conducted ROI to ROI and intra- and inter-network FC analyses using resting-state fMRI (rs-fMRI) data. Correlations of altered FC with symptomatology were explored. RESULTS: We found common brain connectomics in PNOS and SZ including thalamo-cortical (especially superior temporal gyrus) hyperconnectivity, thalamo-cerebellar hypoconnectivity, and reduced within-thalamic connectivity compared to HC. Additionally, features differentiating the two patient groups included hyperconnectivity between the thalamic subregion and anterior cingulate cortex in PNOS compared to SZ and hyperconnectivity of the thalamic subregions with the posterior cingulate cortex and precentral gyrus in SZ compared to PNOS. CONCLUSIONS: These findings suggest that PNOS and SZ exhibit both common and differentiating changes in neuronal connectivity. Furthermore, they may support the hypothesis that PNOS should be treated as a separate clinical syndrome with distinct neural connectomics.

Altered Neuroanatomical Signatures of Patients With Treatment-Resistant Schizophrenia Compared to Patients With Early-Stage Schizophrenia and Healthy Controls.

Background: The relationship between brain structural changes and cognitive dysfunction in schizophrenia is strong. However, few studies have investigated both neuroanatomical abnormalities and cognitive dysfunction in treatment-resistant schizophrenia (TRS). We examined neuroanatomical markers and cognitive function between patients with TRS or early-stage schizophrenia (ES-S) and healthy controls (HCs). Relationships between neuroanatomical markers and cognitive function in the patient groups were also investigated. Methods: A total of 46 and 45 patients with TRS and ES-S and 61 HCs underwent structural magnetic resonance imaging (MRI) brain scanning and comprehensive cognitive tests. MRI scans were analyzed using the FreeSurfer to investigate differences in cortical surface area (CSA), cortical thickness (CT), cortical volume (CV), and subcortical volume (SCV) among the groups. Four cognitive domains (attention, verbal memory, executive function, and language) were assessed. Comparisons of neuroanatomical and cognitive function results among the three groups were performed. Results: A widespread reduction in CT was observed in patients with TRS compared to HCs, but differences in cortical thinning between TRS and ES-S patients were mainly limited to the inferior frontal gyrus and insula. Several subcortical structures (accumbens, amygdala, hippocampus, putamen, thalamus and ventricles) were significantly altered in TRS patients compared to both ES-S patients and HCs. Performance in the verbal memory domain was significantly worse in TRS patients compared to ES-S patients. A positive relationship between the thickness of the left middle temporal gyrus and the composite score for language was identified in patients with ES-S. Conclusions: Our findings suggest significant cognitive impairment and reductions in CT and SCV in individuals with TRS compared to those with ES-S and HCs. These abnormalities could act as biomarkers for earlier identification of TRS.

Altered thalamic subregion functional networks in patients with treatment-resistant schizophrenia.

BACKGROUND: The thalamus plays a key role in filtering information and has extensive interconnectivity with other brain regions. A large body of evidence points to impaired functional connectivity (FC) of the thalamocortical pathway in schizophrenia. However, the functional network of the thalamic subregions has not been investigated in patients with treatment-resistant schizophrenia (TRS). AIM: To identify the neural mechanisms underlying TRS, we investigated FC of thalamic sub-regions with cortical networks and voxels, and the associations of this FC with clinical symptoms. We hypothesized that the FC of thalamic sub-regions with cortical networks and voxels would differ between TRS patients and HCs. METHODS: In total, 50 patients with TRS and 61 healthy controls (HCs) matched for age, sex, and education underwent resting-state functional magnetic resonance imaging (rs-fMRI) and clinical evaluation. Based on the rs-fMRI data, we conducted a FC analysis between thalamic subregions and cortical functional networks and voxels, and within thalamic subregions and cortical functional networks, in the patients with TRS. A functional parcellation atlas was used to segment the thalamus into nine subregions. Correlations between altered FC and TRS symptoms were explored. RESULTS: We found differences in FC within thalamic subregions and cortical functional networks between patients with TRS and HCs. In addition, increased FC was observed between thalamic subregions and the sensorimotor cortex, frontal medial cortex, and lingual gyrus. These abnormalities were associated with the pathophysiology of TRS. CONCLUSION: Our findings suggest that disrupted FC within thalamic subregions and cortical functional networks, and within the thalamocortical pathway, has potential as a marker for TRS. Our findings also improve our understanding of the relationship between the thalamocortical pathway and TRS symptoms.

Diagnosis of schizophrenia with functional connectome data: a graph-based convolutional neural network approach.

Previous deep learning methods have not captured graph or network representations of brain structural or functional connectome data. To address this, we developed the BrainNet-Global Covariance Pooling-Attention Convolutional Neural Network (BrainNet-GA CNN) by incorporating BrainNetCNN and global covariance pooling into the self-attention mechanism. Resting-state functional magnetic resonance imaging data were obtained from 171 patients with schizophrenia spectrum disorders (SSDs) and 161 healthy controls (HCs). We conducted an ablation analysis of the proposed BrainNet-GA CNN and quantitative performance comparisons with competing methods using the nested tenfold cross validation strategy. The performance of our model was compared with competing methods. Discriminative connections were visualized using the gradient-based explanation method and compared with the results obtained using functional connectivity analysis. The BrainNet-GA CNN showed an accuracy of 83.13%, outperforming other competing methods. Among the top 10 discriminative connections, some were associated with the default mode network and auditory network. Interestingly, these regions were also significant in the functional connectivity analysis. Our findings suggest that the proposed BrainNet-GA CNN can classify patients with SSDs and HCs with higher accuracy than other models. Visualization of salient regions provides important clinical information. These results highlight the potential use of the BrainNet-GA CNN in the diagnosis of schizophrenia.

Neuronal Signatures of Negative and Positive Schemas towards the Self and Others in Patients with Early Stage Schizophrenia.

OBJECTIVE: The present study investigated the functional neuroanatomy underlying negative and positive schemas towards the self and others in patients with early stage schizophrenia spectrum disorders (SSDs) using a task-based fMRI procedure. METHODS: This study included 50 patients with SSDs and 52 controls. The schema-evoking task consisted of four active conditions and neutral condition. Differences in brain activation were compared between the two groups. Correlation analysis was performed between task-related activation and psychopathology. RESULTS: The SSD patients exhibited higher activity of the left middle and inferior frontal gyri under the negative-others minus neutral contrast as well as greater activation of the left superior and middle frontal gyri and right medial superior frontal gyrus under the positive- self minus neutral and positive-others minus neutral contrasts. Under the positive-others minus neutral contrast, negative correlation was observed between activity of the right inferior parietal gyrus and right angular and total score of the Positive and Negative Syndrome Scale (PANSS), whereas positive correlation between activity of the left middle cingulate gyrus and left/right precuneus and positive-others score of the Brief Core Schema Scales (BCSS). CONCLUSION: The present findings suggest that the frontal brain regions of SSD patients are more sensitive to negative and positive schemas towards the self and/or others compared to those of controls.