Structural connectivity in schizophrenia and bipolar disorder: Effects of chronicity and antipsychotic treatment

Abnormal Structural Network Communication Reflects Cognitive Deficits in Schizophrenia

Schizophrenia has long been thought to be a disconnection syndrome and several previous studies have reported widespread abnormalities in white matter tracts in individuals with schizophrenia. Furthermore, reductions in structural connectivity may also impair communication between anatomically unconnected pairs of brain regions, potentially impacting global signal traffic in the brain. Therefore, we used different communication models to examine direct and indirect structural connections (polysynaptic) communication in large-scale brain networks in schizophrenia. Diffusion-weighted magnetic resonance imaging scans were acquired from 62 patients diagnosed with schizophrenia and 35 controls. In this study, we used five network communication models including, shortest paths, navigation, diffusion, search information and communicability to examine polysynaptic communication in large-scale brain networks in schizophrenia. We showed less efficient communication between spatially widespread brain regions particulary encompassing cortico-subcortical basal ganglia network in schizophrenia group relative to controls. Then, we also examined whether reduced communication efficiency was related to clinical symptoms in schizophrenia group. Among different measures of communication efficiency, only navigation efficiency was associated with global cognitive impairment across multiple cognitive domains including verbal learning, processing speed, executive functions and working memory, in individuals with schizophrenia. We did not find any association between communication efficiency measures and positive or negative symptoms within the schizophrenia group. Our findings are important for improving our mechanistic understanding of neurobiological process underlying cognitive symptoms in schizophrenia.

The whole-brain connectome landscape in patients with schizophrenia: a systematic review and meta-analysis of graph theoretical characteristics

The alterations of connectome in schizophrenia have been reported, but the results remain inconsistent. We conducted a systematic review and random-effects meta-analysis on structural or functional connectome MRI studies comparing global graph theoretical characteristics between schizophrenia and healthy controls. Meta-regression and subgroup analyses were performed to examine confounding effects. Based on the included 48 studies, Structural connectome in schizophrenia showed a significant decrease in segregation (lower clustering coefficient and local efficiency, Hedge's g= -0.352 and -0.864, respectively) and integration (higher characteristic path length and lower global efficiency, Hedge's g= 0.532 and -0.577 respectively). The functional connectome showed no difference between groups except γ. Moderator analysis indicated that clinical and methodological factors exerted a potential effect on the graph theoretical characteristics. Our analysis revealed a weaker small-worldization trend in structural connectome of schizophrenia. For the relatively unchanged functional connectome, more homogenous and high-quality studies are warranted to elucidate whether the change was blurred by heterogeneity or the presentation of pathophysiological reconfiguration.

Negative symptoms are associated with modularity and thalamic connectivity in schizophrenia

Negative symptoms, including avolition, anhedonia, asociality, blunted affect and alogia are associated with poor long-term outcome and functioning. However, treatment options for negative symptoms are limited and neurobiological mechanisms underlying negative symptoms in schizophrenia are still poorly understood. Diffusion-weighted magnetic resonance imaging scans were acquired from 64 patients diagnosed with schizophrenia and 35 controls. Global and regional network properties and rich club organization were investigated using graph analytical methods. We found that the schizophrenia group had higher modularity, clustering coefficient and characteristic path length, and lower rich connections compared to controls, suggesting highly connected nodes within modules but less integrated with nodes in other modules in schizophrenia. We also found a lower nodal degree in the left thalamus and left putamen in schizophrenia relative to the control group. Importantly, higher modularity was associated with greater negative symptoms but not with cognitive deficits in patients diagnosed with schizophrenia suggesting an alteration in modularity might be specific to overall negative symptoms. The nodal degree of the left thalamus was associated with both negative and cognitive symptoms. Our findings are important for improving our understanding of abnormal white-matter network topology underlying negative symptoms in schizophrenia.

Different patterns of white matter microstructural alterations between psychotic and non-psychotic bipolar disorder

This study aimed to investigate alterations in white matter (WM) microstructure in patients with psychotic and non-psychotic bipolar disorder (PBD and NPBD, respectively). We used 3T-magnetic resonance imaging to examine 29 PBD, 23 NPBD, and 65 healthy control (HC) subjects. Using tract-based spatial statistics for diffusion tensor imaging data, we compared fractional anisotropy (FA) and mean diffusion (MD) pairwise among the PBD, NPBD, and HC groups. We found several WM areas of decreased FA or increased MD in the PBD and NPBD groups compared to HC. PBD showed widespread FA decreases in the corpus callosum as well as the bilateral internal capsule and fornix. However, NPBD showed local FA decreases in a part of the corpus callosum body as well as in limited regions within the left cerebral hemisphere, including the anterior and posterior corona radiata and the cingulum. In addition, both PBD and NPBD shared widespread MD increases across the posterior corona radiata, cingulum, and sagittal stratum. These findings suggest that widespread WM microstructural alterations might be a common neuroanatomical characteristic of bipolar disorder, regardless of being psychotic or non-psychotic. Particularly, PBD might involve extensive inter-and intra-hemispheric WM connectivity disruptions.

Abnormal Network Properties and Fiber Connections of DMN across Major Mental Disorders: A Probability Tracing and Graph Theory Study

The default mode network (DMN) is related to brain functions and its abnormalities were associated with mental disorders' pathophysiology. To further understand the common and distinct DMN alterations across disorders, we capitalized on the probability tracing method and graph theory to analyze the role of DMN across three major mental disorders. A total of 399 participants (156 schizophrenia [SCZ], 90 bipolar disorder [BP], 58 major depression disorder [MDD], and 95 healthy controls [HC]) completed magnetic resonance imaging (MRI)-scanning, clinical, and cognitive assessment. The MRI preprocessing of diffusion-tensor-imaging was conducted in FMRIB Software Library and probabilistic fiber tracking was applied by PANDA. This study had three main findings. First, patient groups showed significantly lower cluster coefficient in whole-brain compared with HC. SCZ showed significantly longer characteristic path compared with HC. Second, patient groups showed inter-group specificity in abnormalities of DMN connections. Third, SCZ was sensitive to left_medial_superior_frontal_gyrus (L_SFGmed)-right_anterior_cingulate_gyrus (R_ACG) connection relating to positive symptoms; left_ACG-right_ACG connection was the mania's antagonistic factor in BP. This trans-diagnostic study found disorder-specific structural abnormalities in the fiber connection of R_SFGmed-L_SFGmed-R_ACG_L_ACG within DMN, where SCZ showed more disconnections compared with other disorders. And these connections are diagnosis-specifically correlated to phenotypes. The current study may provide further evidence of shared and distinct endo-phenotypes across psychopathology.

Aberrant Subnetwork and Hub Dysconnectivity in Adult Bipolar Disorder: A Multicenter Graph Theory Analysis

Neuroimaging evidence implicates structural network-level abnormalities in bipolar disorder (BD); however, there remain conflicting results in the current literature hampered by sample size limitations and clinical heterogeneity. Here, we set out to perform a multisite graph theory analysis to assess the extent of neuroanatomical dysconnectivity in a large representative study of individuals with BD. This cross-sectional multicenter international study assessed structural and diffusion-weighted magnetic resonance imaging data obtained from 109 subjects with BD type 1 and 103 psychiatrically healthy volunteers. Whole-brain metrics, permutation-based statistics, and connectivity of highly connected nodes were used to compare network-level connectivity patterns in individuals with BD compared with controls. The BD group displayed longer characteristic path length, a weakly connected left frontotemporal network, and increased rich-club dysconnectivity compared with healthy controls. Our multisite findings implicate emotion and reward networks dysconnectivity in bipolar illness and may guide larger scale global efforts in understanding how human brain architecture impacts mood regulation in BD.

Elucidating the relationship between white matter structure, demographic, and clinical variables in schizophrenia-a multicenter harmonized diffusion tensor imaging study

White matter (WM) abnormalities are repeatedly demonstrated across the schizophrenia time-course. However, our understanding of how demographic and clinical variables interact, influence, or are dependent on WM pathologies is limited. The most well-known barriers to progress are heterogeneous findings due to small sample sizes and the confounding influence of age on WM. The present study leverages access to the harmonized diffusion magnetic-resonance-imaging data and standardized clinical data from 13 international sites (597 schizophrenia patients (SCZ)). Fractional anisotropy (FA) values for all major WM structures in patients were predicted based on FA models estimated from a healthy population (n = 492). We utilized the deviations between predicted and real FA values to answer three essential questions. (1) "Which clinical variables explain WM abnormalities?". (2) "Does the degree of WM abnormalities predict symptom severity?". (3) "Does sex influence any of those relationships?". Regression and mediator analyses revealed that a longer duration-of-illness is associated with more severe WM abnormalities in several tracts. In addition, they demonstrated that a higher antipsychotic medication dose is related to more severe corpus callosum abnormalities. A structural equation model revealed that patients with more WM abnormalities display higher symptom severity. Last, the results exhibited sex-specificity. Males showed a stronger association between duration-of-illness and WM abnormalities. Females presented a stronger association between WM abnormalities and symptom severity, with IQ impacting this relationship. Our findings provide clear evidence for the interaction of demographic, clinical, and behavioral variables with WM pathology in SCZ. Our results also point to the need for longitudinal studies, directly investigating the casualty and sex-specificity of these relationships, as well as the impact of cognitive resiliency on structure-function relationships.

White matter microstructure and structural networks in treatment-resistant schizophrenia patients after commencing clozapine treatment: A longitudinal diffusion imaging study

This study investigates changes on white matter microstructure and neural networks after 6 months of switching to clozapine in schizophrenia patients compared to controls, and whether any changes are related to clinical variables. T1 and diffusion-weighted MRI images were acquired at baseline before commencing clozapine and after 6 months of treatment for 22 patients with treatment-resistant schizophrenia and 23 controls. The Tract-based spatial statistics approach was used to compare changes over time between groups in fractional anisotropy (FA). Changes in structural network organisation weighted by FA and number of streamlines were assessed using graph theory. Patients displayed a significant reduction of FA over time (p<0.05) compared to controls in the genu and body of the corpus callosum and bilaterally in the anterior and superior corona radiata. There was no correlation between FA change in patients and changes in clinical variables or serum level of clozapine. There was no changes in structural network organisation between groups (F(7,280)=2.80;p = 0.187). This longitudinal study demonstrated progressive focal FA abnormalities in key anterior tracts, but preserved brain structural network organisation in patients. The FA reduction was independent of any clinical measures and may reflect progression of the underlying pathophysiology of this malignant form of schizophrenia illness.

Characteristics of White Matter Structural Networks in Chronic Schizophrenia Treated With Clozapine or Risperidone and Those Never Treated

BACKGROUND

Despite its benefits, a major concern regarding antipsychotic treatment is its possible impact on the brain's structure and function. This study sought to explore the characteristics of white matter structural networks in chronic never-treated schizophrenia and those treated with clozapine or risperidone, and its potential association with cognitive function.

METHODS

Diffusion tensor imaging was performed on a unique sample of 34 schizophrenia patients treated with antipsychotic monotherapy for over 5 years (17 treated with clozapine and 17 treated with risperidone), 17 never-treated schizophrenia patients with illness duration over 5 years, and 27 healthy control participants. Graph theory and network-based statistic approaches were employed.

RESULTS

We observed a disrupted organization of white matter structural networks as well as decreased nodal and connectivity characteristics across the schizophrenia groups, mainly involving thalamus, prefrontal, and occipital regions. Alterations in nodal and connectivity characteristics were relatively milder in risperidone-treated patients than clozapine-treated patients and never-treated patients. Altered global network measures were significantly associated with cognitive performance levels. Structural connectivity as reflected by network-based statistic mediated the difference in cognitive performance levels between clozapine-treated and risperidone-treated patients.

LIMITATIONS

These results are constrained by the lack of random assignment to different types of antipsychotic treatment.

CONCLUSION

These findings provide insight into the white matter structural network deficits in patients with chronic schizophrenia, either being treated or untreated, and suggest white matter structural networks supporting cognitive function may benefit from antipsychotic treatment, especially in those treated with risperidone.

Common gray and white matter abnormalities in schizophrenia and bipolar disorder

This study aimed to investigate abnormalities in the gray matter and white matter (GM and WM, respectively) that are shared between schizophrenia (SZ) and bipolar disorder (BD). We used 3T-magnetic resonance imaging to examine patients with SZ, BD, or healthy control (HC) subjects (aged 20–50 years, N = 65 in each group). We generated modulated GM maps through voxel-based morphometry (VBM) for T1-weighted images and skeletonized fractional anisotropy, mean diffusion, and radial diffusivity maps through tract-based special statistics (TBSS) methods for diffusion tensor imaging (DTI) data. These data were analyzed using a generalized linear model with pairwise comparisons between groups with a family-wise error corrected P < 0.017. The VBM analysis revealed widespread decreases in GM volume in SZ compared to HC, but patients with BD showed GM volume deficits limited to the right thalamus and left insular lobe. The TBSS analysis showed alterations of DTI parameters in widespread WM tracts both in SZ and BD patients compared to HC. The two disorders had WM alterations in the corpus callosum, superior longitudinal fasciculus, internal capsule, external capsule, posterior thalamic radiation, and fornix. However, we observed no differences in GM volume or WM integrity between SZ and BD. The study results suggest that GM volume deficits in the thalamus and insular lobe along with widespread disruptions of WM integrity might be the common neural mechanisms underlying the pathologies of SZ and BD.

Connectivity strength of the EEG functional network in schizophrenia and bipolar disorder

The application of graph theory measures in the study of functional brain networks allows for the description of their general properties and their alterations in mental illness. Among these measures, connectivity strength (CS) estimates the degree of functional connectivity of the whole network. Previous studies in schizophrenia patients have reported higher baseline CS values and modulation deficits in EEG spectral properties during cognitive activity. The specificity of these alterations and their relationships with pharmacological treatments remain unknown. Therefore, in the present study, we assessed functional CS on EEG-based brain networks in 79 schizophrenia and 29 bipolar patients in addition to 63 healthy controls. The subjects performed a P300 task during the EEG recordings from which the pre-stimulus and the task-related modulation CS values were computed in the global and theta bands. These values were compared between the groups and between the patients who had and had not received different treatments. The global band pre-stimulus CS was significantly higher in the schizophrenia group compared with the bipolar and control groups. Theta band CS modulation was decreased in schizophrenia and bipolar patients. Treatment with antipsychotics, lithium, benzodiazepines, and anticonvulsants did not significantly alter these CS values. The first-episode and chronic schizophrenia patients did not show significant differences in CS values. Higher global band pre-stimulus CS values were associated with worse general cognition in schizophrenia patients. These data support increased connectivity in the whole-brain network that is specific to schizophrenia and suggest a general hyper-synchronized basal state that might hamper cognition in this syndrome.

Social cognition in psychosis: Predictors and effects of META-cognitive training

Social cognition deficits are found in schizophrenia and bipolar disorder, but its neural underpinnings are poorly understood. Given the complexity of psychological functions underlying this kind of cognition, we hypothesized that alterations in global structural connectivity could contribute to those deficits. To test this hypothesis, we studied a group of schizophrenia and bipolar patients with connectomics based on diffusion magnetic resonance imaging and assessments of general and social cognition. The latter was assessed using the Mayer, Salovey and Caruso Emotional Intelligence Test (MSCEIT) for emotional intelligence and the Spanish Group for Schizophrenia Treatment Optimization (Grupo Español para la OPtimización del Tratamiento de la Esquizofrenia, GEOPTE) test for behavioral aspects of social cognition. Graph theory applied to fractional anisotropy for the connections among cortical regions was used to obtain the small-world (SW) index of the structural connectivity network. In addition, we assessed the possibility of predicting the response of social cognition deficits to Meta-cognitive Training based on their possible underpinnings in a subgroup of patients. Patients showed lower scores in emotional intelligence and behavioral social cognition. MSCEIT scores were associated with SW index and working memory, and GEOPTE scores were related to verbal memory. Improvement in social cognition after Meta-cognitive Training was associated with lower scores of the social cognition in the baseline, according to the GEOPTE scale. Our findings support structural connectivity as one of the factors underlying emotional intelligence in schizophrenia, and the use of Meta-cognitive Training to improve social cognition in patients with larger deficits.