Basal ganglia volume in unmedicated patients with schizophrenia is associated with treatment response to antipsychotic medication

Neural correlates of prediction error in patients with schizophrenia: evidence from an fMRI meta-analysis

Abnormal processes of learning from prediction errors, i.e. the discrepancies between expectations and outcomes, are thought to underlie motivational impairments in schizophrenia. Although dopaminergic abnormalities in the mesocorticolimbic reward circuit have been found in patients with schizophrenia, the pathway through which prediction error signals are processed in schizophrenia has yet to be elucidated. To determine the neural correlates of prediction error processing in schizophrenia, we conducted a meta-analysis of whole-brain neuroimaging studies that investigated prediction error signal processing in schizophrenia patients and healthy controls. A total of 14 studies (324 schizophrenia patients and 348 healthy controls) using the reinforcement learning paradigm were included. Our meta-analysis showed that, relative to healthy controls, schizophrenia patients showed increased activity in the precentral gyrus and middle frontal gyrus and reduced activity in the mesolimbic circuit, including the striatum, thalamus, amygdala, hippocampus, anterior cingulate cortex, insula, superior temporal gyrus, and cerebellum, when processing prediction errors. We also found hyperactivity in frontal areas and hypoactivity in mesolimbic areas when encoding prediction error signals in schizophrenia patients, potentially indicating abnormal dopamine signaling of reward prediction error and suggesting failure to represent the value of alternative responses during prediction error learning and decision making.

Decreased basal ganglia and thalamic iron in early psychotic spectrum disorders are associated with increased psychotic and schizotypal symptoms

Iron deficits have been reported as a risk factor for psychotic spectrum disorders (PSD). However, examinations of brain iron in PSD remain limited. The current study employed quantitative MRI to examine iron content in several iron-rich subcortical structures in 49 young adult individuals with PSD (15 schizophrenia, 17 schizoaffective disorder, and 17 bipolar disorder with psychotic features) compared with 35 age-matched healthy controls (HC). A parametric approach based on a two-pool magnetization transfer model was applied to estimate longitudinal relaxation rate (R₁), which reflects both iron and myelin, and macromolecular proton fraction (MPF), which is specific to myelin. To describe iron content, a synthetic effective transverse relaxation rate (R₂*) was modeled using a linear fitting of R₁ and MPF. PSD patients compared to HC showed significantly reduced R₁ and synthetic R₂* across examined regions including the pallidum, ventral diencephalon, thalamus, and putamen areas. This finding was primarily driven by decreases in the subgroup with schizophrenia, followed by schizoaffective disorder. No significant group differences were noted for MPF between PSD and HC while for regional volume, significant reductions in patients were only observed in bilateral caudate, suggesting that R₁ and synthetic R₂* reductions in schizophrenia and schizoaffective patients likely reflect iron deficits that either occur independently or precede structural and myelin changes. Subcortical R₁ and synthetic R₂* were also found to be inversely related to positive symptoms within the PSD group and to schizotypal traits across the whole sample. These findings that decreased iron in subcortical regions are associated with PSD risk and symptomatology suggest that brain iron deficiencies may play a role in PSD pathology and warrant further study.

Ultrastructural evidence for glutamatergic dysregulation in schizophrenia

The aim of this paper is to summarize ultrastructural evidence for glutamatergic dysregulation in several linked regions in postmortem schizophrenia brain. Following a brief summary of glutamate circuitry and how synapses are identified at the electron microscopic (EM) level, we will review EM pathology in the cortex and basal ganglia. We will include the effects of antipsychotic drugs and the relation of treatment response. We will discuss how these findings support or confirm other postmortem findings as well as imaging results. Briefly, synaptic and mitochondrial density in anterior cingulate cortex was decreased in schizophrenia, versus normal controls (NCs), in a selective layer specific pattern. In dorsal striatum, increases in excitatory synaptic density were detected in caudate matrix, a compartment associated with cognitive and motor function, and in the putamen patches, a region associated with limbic function and in the core of the nucleus accumbens. Patients who were treatment resistant or untreated had significantly elevated numbers of excitatory synapses in limbic striatal areas in comparison to NCs and responders. Protein levels of vGLUT2, found in subcortical glutamatergic neurons, were increased in the nucleus accumbens in schizophrenia. At the EM level, schizophrenia subjects had an increase in density of excitatory synapses in several areas of the basal ganglia. In the substantia nigra, the protein levels of vGLUT2 were elevated in untreated patients compared to NCs. The density of inhibitory synapses was decreased in schizophrenia versus NCs. In schizophrenia, glutamatergic synapses are differentially affected depending on the brain region, treatment status, and treatment response.

Increased subcortical region volume induced by electroconvulsive therapy in patients with schizophrenia

Electroconvulsive therapy (ECT) has been widely used to treat patients with schizophrenia. However, the underlying mechanisms of ECT remain unknown. In the present study, the treatment effects of ECT on brain structure in patients with schizophrenia were explored. Seventy patients with schizophrenia were scanned using structural magnetic resonance imaging. Patients in the drug group were scanned at baseline (time 1) and follow-up (time 2, 6 weeks of treatment). Patients in the ECT group were scanned before ECT treatment (baseline, time 1) and 10-12 h after the last ECT treatment (time 2). Voxel-based morphometry was applied to analyze the imaging data. Patients in the ECT group showed significantly increased gray matter volume (GMV) in the bilateral hippocampus/amygdala and left superior temporal gyrus (STG)/middle temporal gyrus (MTG) after ECT combined with antipsychotic therapy at time 2. In contrast, patients in the drug group showed decreased GMV in widespread brain regions. Correlation analysis results showed significantly negative correlations between the increased GMV in the bilateral hippocampus/amygdala and PANSS scores at baseline in the ECT group. ECT may modulate brain structure in patients with schizophrenia. The GMV in distinct subcortical regions was related to the individual therapeutic response in patients with schizophrenia.

Increased Homotopic Connectivity in the Prefrontal Cortex Modulated by Olanzapine Predicts Therapeutic Efficacy in Patients with Schizophrenia

Background

Previous studies have revealed the abnormalities in homotopic connectivity in schizophrenia. However, the relationship of these deficits to antipsychotic treatment in schizophrenia remains unclear. This study explored the effects of antipsychotic therapy on brain homotopic connectivity and whether the homotopic connectivity of these regions might predict individual treatment response in schizophrenic patients.

Methods

A total of 21 schizophrenic patients and 20 healthy controls were scanned by the resting-state functional magnetic resonance imaging. The patients received olanzapine treatment and were scanned at two time points. Voxel-mirrored homotopic connectivity (VMHC) and pattern classification techniques were applied to analyze the imaging data.

Results

Schizophrenic patients presented significantly decreased VMHC in the temporal and inferior frontal gyri, medial prefrontal cortex (MPFC), and motor and low-level sensory processing regions (including the fusiform gyrus and cerebellum lobule VI) relative to healthy controls. The VMHC in the superior/middle MPFC was significantly increased in the patients after eight weeks of treatment. Support vector regression (SVR) analyses revealed that VMHC in the superior/middle MPFC at baseline can predict the symptomatic improvement of the positive and negative syndrome scale after eight weeks of treatment.

Conclusions

This study demonstrated that olanzapine treatment may normalize decreased homotopic connectivity in the superior/middle MPFC in schizophrenic patients. The VMHC in the superior/middle MPFC may predict individual response for antipsychotic therapy. The findings of this study conduce to the comprehension of the therapy effects of antipsychotic medications on homotopic connectivity in schizophrenia.

Thalamus Radiomics-Based Disease Identification and Prediction of Early Treatment Response for Schizophrenia

Background

Emerging evidence suggests structural and functional disruptions of the thalamus in schizophrenia, but whether thalamus abnormalities are able to be used for disease identification and prediction of early treatment response in schizophrenia remains to be determined. This study aims at developing and validating a method of disease identification and prediction of treatment response by multi-dimensional thalamic features derived from magnetic resonance imaging in schizophrenia patients using radiomics approaches.

Methods

A total of 390 subjects, including patients with schizophrenia and healthy controls, participated in this study, among which 109 out of 191 patients had clinical characteristics of early outcome (61 responders and 48 non-responders). Thalamus-based radiomics features were extracted and selected. The diagnostic and predictive capacity of multi-dimensional thalamic features was evaluated using radiomics approach.

Results

Using radiomics features, the classifier accurately discriminated patients from healthy controls, with an accuracy of 68%. The features were further confirmed in prediction and random forest of treatment response, with an accuracy of 75%.

Conclusion

Our study demonstrates a radiomics approach by multiple thalamic features to identify schizophrenia and predict early treatment response. Thalamus-based classification could be promising to apply in schizophrenia definition and treatment selection.

Characteristics of Multimodal Brain Connectomics in Patients With Schizophrenia and the Unaffected First-Degree Relatives

OBJECTIVE

Increasing pieces of evidence suggest that abnormal brain connectivity plays an important role in the pathophysiology of schizophrenia. As an essential strategy in psychiatric neuroscience, the research of brain connectivity-based neuroimaging biomarkers has gained increasing attention. Most of previous studies focused on a single modality of the brain connectomics. Multimodal evidence will not only depict the full profile of the brain abnormalities of patients but also contribute to our understanding of the neurobiological mechanisms of this disease.

METHODS

In the current study, 99 schizophrenia patients, 69 sex- and education-matched healthy controls, and 42 unaffected first-degree relatives of patients were recruited and scanned. The brain was parcellated into 246 regions and multimodal network analyses were used to construct brain connectivity networks for each participant.

RESULTS

Using the brain connectomics from three modalities as the features, the multi-kernel support vector machine method yielded high discrimination accuracies for schizophrenia patients (94.86%) and for the first-degree relatives (95.33%) from healthy controls. Using an independent sample (49 patients and 122 healthy controls), we tested the model and achieved a classification accuracy of 64.57%. The convergent pattern within the basal ganglia and thalamus-cortex circuit exhibited high discriminative power during classification. Furthermore, substantial overlaps of the brain connectivity abnormality between patients and the unaffected first-degree relatives were observed compared to healthy controls.

CONCLUSION

The current findings demonstrate that decreased functional communications between the basal ganglia, thalamus, and the prefrontal cortex could serve as biomarkers and endophenotypes for schizophrenia.

Increased regional homogeneity modulated by metacognitive training predicts therapeutic efficacy in patients with schizophrenia

Previous studies have demonstrated the efficacy of metacognitive training (MCT) in schizophrenia. However, the underlying mechanisms related to therapeutic effect of MCT remain unknown. The present study explored the treatment effects of MCT on brain regional neural activity using regional homogeneity (ReHo) and whether these regions' activities could predict individual treatment response in schizophrenia. Forty-one patients with schizophrenia and 20 healthy controls were scanned using resting-state functional magnetic resonance imaging. Patients were randomly divided into drug therapy (DT) and drug plus psychotherapy (DPP) groups. The DT group received only olanzapine treatment, whereas the DPP group received olanzapine and MCT for 8 weeks. The results revealed that ReHo in the right precuneus, left superior medial prefrontal cortex (MPFC), right parahippocampal gyrus and left rectus was significantly increased in the DPP group after 8 weeks of treatment. Patients in the DT group showed significantly increased ReHo in the left ventral MPFC/anterior cingulate cortex (ACC), left superior MPFC/middle frontal gyrus (MFG), left precuneus, right rectus and left MFG, and significantly decreased ReHo in the bilateral cerebellum VIII and left inferior occipital gyrus (IOG) after treatment. Support vector regression analyses showed that high ReHo levels at baseline in the right precuneus and left superior MPFC could predict symptomatic improvement of Positive and Negative Syndrome Scale (PANSS) after 8 weeks of DPP treatment. Moreover, high ReHo levels at baseline and alterations of ReHo in the left ventral MPFC/ACC could predict symptomatic improvement of PANSS after 8 weeks of DT treatment. This study suggests that MCT is associated with the modulation of ReHo in schizophrenia. ReHo in the right precuneus and left superior MPFC may predict individual therapeutic response for MCT in patients with schizophrenia.

Neuroimaging as a Window Into the Pathophysiological Mechanisms of Schizophrenia

Schizophrenia is a complex neuropsychiatric disorder with a diverse clinical phenotype that has a substantial personal and public health burden. To advance the mechanistic understanding of the illness, neuroimaging can be utilized to capture different aspects of brain pathology in vivo, including brain structural integrity deficits, functional dysconnectivity, and altered neurotransmitter systems. In this review, we consider a number of key scientific questions relevant in the context of neuroimaging studies aimed at unraveling the pathophysiology of schizophrenia and take the opportunity to reflect on our progress toward advancing the mechanistic understanding of the illness. Our data is congruent with the idea that the brain is fundamentally affected in the illness, where widespread structural gray and white matter involvement, functionally abnormal cortical and subcortical information processing, and neurometabolic dysregulation are present in patients. Importantly, certain brain circuits appear preferentially affected and subtle abnormalities are already evident in first episode psychosis patients. We also demonstrated that brain circuitry alterations are clinically relevant by showing that these pathological signatures can be leveraged for predicting subsequent response to antipsychotic treatment. Interestingly, dopamine D2 receptor blockers alleviate neural abnormalities to some extent. Taken together, it is highly unlikely that the pathogenesis of schizophrenia is uniform, it is more plausible that there may be multiple different etiologies that converge to the behavioral phenotype of schizophrenia. Our data underscore that mechanistically oriented neuroimaging studies must take non-specific factors such as antipsychotic drug exposure or illness chronicity into consideration when interpreting disease signatures, as a clear characterization of primary pathophysiological processes is an imperative prerequisite for rational drug development and for alleviating disease burden in our patients.

Numerical density of oligodendrocytes and oligodendrocyte clusters in the anterior putamen in major psychiatric disorders

There is increasing evidence to support the notion that oligodendrocyte and myelin abnormalities may contribute to the functional dysconnectivity found in the major psychiatric disorders. The putamen, which is an important hub in the cortico-striato-thalamo-cortical loop, has been implicated in a broad spectrum of psychiatric illnesses and is a central target of their treatments. Previously we reported a reduction in the numerical density of oligodendrocytes and oligodendrocyte clusters in the prefrontal and parietal cortex in schizophrenia. Oligodendrocyte clusters contain oligodendrocyte progenitors and are involved in functionally dependent myelination. We measured the numerical density (Nv) of oligodendrocytes and oligodendrocyte clusters in the putamen in schizophrenia, bipolar disorder (BPD) and major depressive disorder (MDD) as compared to healthy controls (15 cases per group). Optical disector was used to estimate the Nv of oligodendrocytes and oligodendrocyte clusters. A significant reduction in both the Nv of oligodendrocytes (- 34%; p < 0.01) and the Nv of oligodendrocyte clusters (- 41%; p < 0.05) was found in the schizophrenia group as compared to the control group. Sexual dimorphism for both measurements was found only within the control group. The Nv of oligodendrocytes was significantly lower in male schizophrenia cases as compared to the male control cases. However, the Nv of oligodendrocyte clusters was significantly lower in all male clinical cases as compared to the male control group. The data suggest that lowered density of oligodendrocytes and oligodendrocyte clusters may contribute to the altered functional connectivity in the putamen in subjects with schizophrenia.

Subcortical Brain Volume Abnormalities in Individuals With an At-risk Mental State

Previous structural magnetic resonance imaging studies of psychotic disorders have demonstrated volumetric alterations in subcortical (ie, the basal ganglia, thalamus) and temporolimbic structures, which are involved in high-order cognition and emotional regulation. However, it remains unclear whether individuals at high risk for psychotic disorders with minimal confounding effects of medication exhibit volumetric changes in these regions. This multicenter magnetic resonance imaging study assessed regional volumes of the thalamus, caudate, putamen, nucleus accumbens, globus pallidus, hippocampus, and amygdala, as well as lateral ventricular volume using FreeSurfer software in 107 individuals with an at-risk mental state (ARMS) (of whom 21 [19.6%] later developed psychosis during clinical follow-up [mean = 4.9 years, SD = 2.6 years]) and 104 age- and gender-matched healthy controls recruited at 4 different sites. ARMS individuals as a whole demonstrated significantly larger volumes for the left caudate and bilateral lateral ventricles as well as a smaller volume for the right accumbens compared with controls. In male subjects only, the left globus pallidus was significantly larger in ARMS individuals. The ARMS group was also characterized by left-greater-than-right asymmetries of the lateral ventricle and caudate nucleus. There was no significant difference in the regional volumes between ARMS groups with and without later psychosis onset. The present study suggested that significant volume expansion of the lateral ventricle, caudate, and globus pallidus, as well as volume reduction of the accumbens, in ARMS subjects, which could not be explained only by medication effects, might be related to general vulnerability to psychopathology.

Socioeconomic disadvantage, brain morphometry, and attentional bias to threat in middle childhood

Socioeconomic disadvantage is associated with higher rates of psychopathology as well as hippocampus, amygdala and prefrontal cortex structure. However, little is known about how variations in brain morphometry are associated with socio-emotional risks for mood disorders in children growing up in families experiencing low income. In the current study, using structural magnetic resonance imaging, we examined the relationship between socioeconomic disadvantage and gray matter volume in the hippocampus, amygdala, and ventrolateral prefrontal cortex in a sample of children (n = 34) in middle childhood. Using an affective dot probe paradigm, we examined the association between gray matter volume in these regions and attentional bias to threat, a risk marker for mood disorders including anxiety disorders. We found that lower income-to-needs ratio was associated with lower bilateral hippocampal and right amygdala volume, but not prefrontal cortex volumes. Moreover, lower attentional bias to threat was associated with greater left hippocampal volume. We provide evidence of a relationship between income-related variations in brain structure and attentional bias to threat, a risk for mood disorders. Therefore, these findings support an environment-morphometry-behavior relationship that contributes to the understanding of income-related mental health disparities in childhood.

Indicated association between polygenic risk score and treatment-resistance in a naturalistic sample of patients with schizophrenia spectrum disorders

BACKGROUND

One third of people diagnosed with schizophrenia fail to respond adequately to antipsychotic medication, resulting in persisting disabling symptoms, higher rates of hospitalization and higher costs for society. In an effort to better understand the mechanisms behind resistance to antipsychotic treatment in schizophrenia, we investigated its potential relationship to the genetic architecture of the disorder.

METHODS

Patients diagnosed with a schizophrenia spectrum disorder (N = 321) were classified as either being treatment-resistant (N = 108) or non-treatment-resistant (N = 213) to antipsychotic medication using defined consensus criteria. A schizophrenia polygenic risk score based on genome-wide association studies (GWAS) was calculated for each patient and binary logistic regression was performed to investigate the association between polygenetic risk and treatment resistance. We adjusted for principal components, batch number, age and sex. Additional analyses were performed to investigate associations with demographic and clinical variables.

RESULTS

High levels of polygenic risk score for schizophrenia significantly predicted treatment resistance (p = 0.003). The positive predictive value of the model was 61.5% and the negative predictive value was 71.7%. The association was significant for one (p = 0.01) out of five tested SNP significance thresholds. Season of birth was able to predict treatment-resistance in the regression model (p = 0.05).

CONCLUSIONS

The study indicates that treatment-resistance to antipsychotic medication is associated with higher polygenetic risk of schizophrenia, suggesting a link between antipsychotics mechanism of action and the genetic underpinnings of the disorder.

Reduced density of oligodendrocytes and oligodendrocyte clusters in the caudate nucleus in major psychiatric illnesses

Functional dysconnectivity in schizophrenia and affective disorders may be associated with myelin and oligodendrocyte abnormalities. Altered network integration involving the caudate nucleus (CN) and metabolic abnormalities in fronto-striatal-thalamic white matter tracts have been reported in schizophrenia and impaired patterns of cortico-caudate functional connectivity have been found in both bipolar disorder (BPD) and schizophrenia compared to healthy controls. Postmortem studies have found ultrastructural dystrophy and degeneration of oligodendrocytes and dysmyelination in the CN in schizophrenia and BPD. We aimed to test the hypothesis that oligodendrocyte density may be reduced in the CN in major psychiatric disorders and may thereby form the cellular basis for the functional dysconnectivity observed in these disorders. Optical disector was used to estimate the numerical density (Nv) of oligodendrocytes and oligodendrocyte clusters (OLC) in the CN of cases with schizophrenia, BPD and major depressive disorder (MDD) and in normal controls (15 cases per group). A significant reduction in the Nv of oligodendrocytes was found in schizophrenia and BPD as compared to the control group (p < 0.05), and the Nv of OLC was significantly lowered in schizophrenia and BPD compared to controls (p < 0.05). There were no significant differences between MDD and control groups. The Nv of OLC was significantly decreased in the left hemisphere in schizophrenia as compared to the left hemisphere of the control group (-52%, p < 0.01). The data indicates that a decreased density of oligodendrocytes and OLC could contribute to the altered functional connectivity of the CN in subjects with severe mental illnesses.

Examining resting-state functional connectivity in first-episode schizophrenia with 7T fMRI and MEG

Schizophrenia is often characterized by dysconnections in the brain, which can be estimated via functional connectivity analyses. Commonly measured using resting-state functional magnetic resonance imaging (fMRI) in order to characterize the intrinsic or baseline function of the brain, fMRI functional connectivity has significantly contributed to the understanding of schizophrenia. However, these measures may not capture the full extent of functional connectivity abnormalities in schizophrenia as fMRI is temporally limited by the hemodynamic response. In order to extend fMRI functional connectivity findings, the complementary modality of magnetoencephalography (MEG) can be utilized to capture electrophysiological functional connectivity abnormalities in schizophrenia that are not obtainable with fMRI. Therefore, we implemented a multimodal functional connectivity analysis using resting-state 7 Tesla fMRI and MEG data in a sample of first-episode patients with schizophrenia (n = 19) and healthy controls (n = 24). fMRI and MEG data were decomposed into components reflecting resting state networks using a group spatial independent component analysis. Functional connectivity between resting-state networks was computed and group differences were observed. In fMRI, patients demonstrated hyperconnectivity between subcortical and auditory networks, as well as hypoconnectivity between interhemispheric homotopic sensorimotor network components. In MEG, patients demonstrated hypoconnectivity between sensorimotor and task positive networks in the delta frequency band. Results not only support the dysconnectivity hypothesis of schizophrenia, but also suggest the importance of jointly examining multimodal neuroimaging data as critical disorder-related information may not be detectable in a single modality alone.

Enhanced baseline activity in the left ventromedial putamen predicts individual treatment response in drug-naive, first-episode schizophrenia: Results from two independent study samples

Background

Antipsychotic medications are the common treatment for schizophrenia. However, reliable biomarkers that can predict individual treatment response are still lacking. The present study aimed to examine whether baseline putamen activity can predict individual treatment response in schizophrenia.

Methods

Two independent samples of patients with drug-naive, first-episode schizophrenia (32 patients in sample 1 and 44 in sample 2) and matched healthy controls underwent resting-state functional magnetic resonance imaging (fMRI) at baseline. Patients were treated with olanzapine for 8 weeks; symptom severity was assessed using the Positive and Negative Syndrome Scale (PANSS) at baseline and week 8. Fractional amplitude of low frequency fluctuation (fALFF) and pattern classification techniques were used to analyze the data.

Findings

Univariate analysis shows an elevated pre-treatment fALFF in the left ventromedial putamen in both patient samples compared to healthy controls (p's < 0.001). The support vector regression (SVR) analysis suggests a positive relationship between baseline pre-treatment fALFF in the left ventromedial putamen and improvement in positive symptom at week 8 in each patient group using a cross-validated method (r = 0.452, p = .002; r = 0.511, p = .003, respectively).

Interpretation

Our study suggests that elevated pre-treatment mean fALFF in the left ventromedial putamen may predict individual therapeutic response to olanzapine treatment in drug-naive, first-episode patients with schizophrenia. Future studies are needed to confirm whether this finding is generalizable to patients with schizophrenia treated with other antipsychotic medications.

Fund

The National Key R&D Program of China and the National Natural Science Foundation of China.

Brain findings associated with risperidone in rhesus monkeys: magnetic resonance imaging and pathology perspectives

Brain changes associated with risperidone, a dopamine-2/serotonin-2 receptor antagonist, have been documented in rats and humans, but not in nonhuman primates. This study characterized brain changes associated with risperidone in nonhuman primates. Rhesus monkeys were orally administered risperidone in a dose-escalation paradigm up to a maximum tolerated dose of 0.5 mg/kg/day for 3 weeks, or 3 months followed by a 3-month recovery period. Transient and fully reversible neurological signs consistent with risperidone pharmacology were observed. The results of a magnetic resonance imaging evaluation after 3 months of treatment and at the end of the 3-month recovery period showed no meaningful changes in the brain. There were no risperidone-related brain weight changes or gross findings. Histomorphological evaluation of brain sections stained with hematoxylin and eosin, ionized calcium binding adaptor molecule 1 (Iba1), and luxol fast blue/cresyl violet double staining showed no notable differences between control and risperidone groups. However, evaluation of the brain after glial fibrillary acidic protein (GFAP) immunohistochemical staining revealed increased staining in the cell bodies and processes of astrocytes in the putamen without apparent alterations in numbers or distribution. The increase in GFAP staining was present after 3 weeks and 3 months of treatment, but no increase in staining was observed after the 3-month recovery period, demonstrating the reversibility of this finding. The reversible increase in GFAP expression was likely an adaptive, non-adverse response of astrocytes, associated with the pharmacology of risperidone. These observations are valuable considerations in the nonclinical risk assessment of new drug candidates for psychiatric disorders.

Prediction of early response to overall treatment for schizophrenia: A functional magnetic resonance imaging study

INTRODUCTION

Treatment response at an early stage of schizophrenia is of considerable value with regard to future management of the disorder; however, there are currently no biomarkers that can inform physicians about the likelihood of response.

OBJECTS

We aim to develop and validate regional brain activity derived from functional magnetic resonance imaging (fMRI) as a potential signature to predict early treatment response in schizophrenia.

METHODS

Amplitude of low-frequency fluctuation (ALFF) was measured at the start of the first/single episode resulting in hospitalization. Inpatients were included in a principal dataset (n = 79) and a replication dataset (n = 44). Two groups of healthy controls (n = 87; n = 106) were also recruited for each dataset. The clinical response was assessed at discharge from the hospital. The predictive capacity of normalized ALFF in patients by healthy controls, ALFF_ratio , was evaluated based on diagnostic tests and clinical correlates.

RESULTS

In the principal dataset, responders exhibited increased baseline ALFF in the left postcentral gyrus/inferior parietal lobule relative to non-responders. ALFF_ratio of responders before treatment was significantly higher than that of non-responders (p < 0.001). The area under the receiver operating characteristic curve was 0.746 for baseline ALFF_ratio to distinguish responders from non-responders, and the sensitivity, specificity, and accuracy were 72.7%, 68.6%, and 70.9%, respectively. Similar results were found in the independent replication dataset.

CONCLUSIONS

Baseline regional activity of the brain seems to be predictive of early response to treatment for schizophrenia. This study shows that psycho-neuroimaging holds promise for influencing the clinical treatment and management of schizophrenia.

Four-way multimodal fusion of 7 T imaging data using an mCCA+jICA model in first-episode schizophrenia

Acquisition of multimodal brain imaging data for the same subject has become more common leading to a growing interest in determining the intermodal relationships between imaging modalities to further elucidate the pathophysiology of schizophrenia. Multimodal data have previously been individually analyzed and subsequently integrated; however, these analysis techniques lack the ability to examine true modality inter-relationships. The utilization of a multiset canonical correlation and joint independent component analysis (mCCA + jICA) model for data fusion allows shared or distinct abnormalities between modalities to be examined. In this study, first-episode schizophrenia patients (n_SZ =19) and matched controls (n_HC =21) completed a resting-state functional magnetic resonance imaging (fMRI) scan at 7 T. Grey matter (GM), white matter (WM), cerebrospinal fluid (CSF), and amplitude of low frequency fluctuation (ALFF) maps were used as features in a mCCA + jICA model. Results of the mCCA + jICA model indicated three joint group-discriminating components (GM-CSF, WM-ALFF, GM-ALFF) and two modality-unique group-discriminating components (GM, WM). The joint component findings are highlighted by GM basal ganglia, somatosensory, parietal lobe, and thalamus abnormalities associated with ventricular CSF volume; WM occipital and frontal lobe abnormalities associated with temporal lobe function; and GM frontal, temporal, parietal, and occipital lobe abnormalities associated with caudate function. These results support and extend major findings throughout the literature using independent single modality analyses. The multimodal fusion of 7 T data in this study provides a more comprehensive illustration of the relationships between underlying neuronal abnormalities associated with schizophrenia than examination of imaging data independently.

Gyrification Connectomes in Unmedicated Patients With Schizophrenia and Following a Short Course of Antipsychotic Drug Treatment

Schizophrenia (SZ) is a d isease characterized by brain dysconnectivity and abnormal brain development. The study of cortical gyrification in schizophrenia may capture underlying alterations reflective of neurodevelopmental abnormalities more accurately than other imaging modalities. Graph-based connectomic approaches have been previously used in schizophrenia to study structural and functional brain covariance using a diversity of techniques. The goal of the present study was to evaluate morphological covariance using a measure of local gyrification index in patients with schizophrenia. The aims of this study were two-fold: (1) Evaluate the structural covariance of local gyrification index using graph theory measures of integration and segregation in unmedicated patients with schizophrenia compared to healthy controls and (2) investigate changes in these measures following a short antipsychotic drug (APD) treatment. Using a longitudinal prospective design, structural scans were obtained prior to treatment in 34 unmedicated patients with SZ and after 6 weeks of treatment with risperidone. To control for the effect of time, 23 matched healthy controls (HC) were also scanned twice, 6 weeks apart. The cortical surface of each structural image was reconstructed and local gyrification index values were computed using FreeSurfer. Local gyrification index values where then parcellated into atlas based regions and entered into a 68 × 68 correlation matrix to construct local gyrification index connectomes for each group at each time point. Longitudinal comparisons showed significant group by time interactions for measures of segregation (clustering, local efficiency) and modularity, but not for measures of integration (path length, global efficiency). Post-hoc tests showed increased clustering, local efficiency, and modularity connectomes in unmedicated patients with SZ at baseline compared to HC. Post-hoc tests did not show significant within group differences for HCs or patients with SZ. After 6 weeks of treatment, there were no significant differences between the groups on these measures. Abnormal cortical topography is detected in schizophrenia and is modified by short term APD treatment reflective of decreases in hyper-specialization in network connectivity. We speculate that changes in the structural organization of the brain is achieved through the neuroplastic effects that APDs have on brain tissue, thus promoting more efficient brain connections and, possibly, a therapeutic effect.

Genome-wide association study of paliperidone efficacy

Supplemental Digital Content is available in the text.

Objective

Clinical response to the atypical antipsychotic paliperidone is known to vary among schizophrenic patients. We carried out a genome-wide association study to identify common genetic variants predictive of paliperidone efficacy.

Methods

We leveraged a collection of 1390 samples from individuals of European ancestry enrolled in 12 clinical studies investigating the efficacy of the extended-release tablet paliperidone ER (n₁=490) and the once-monthly injection paliperidone palmitate (n₂=550 and n₃=350). We carried out a genome-wide association study using a general linear model (GLM) analysis on three separate cohorts, followed by meta-analysis and using a mixed linear model analysis on all samples. The variations in response explained by each single nucleotide polymorphism (h²_SNP) were estimated.

Results

No SNP passed genome-wide significance in the GLM-based analyses with suggestive signals from rs56240334 [P=7.97×10⁻⁸ for change in the Clinical Global Impression Scale-Severity (CGI-S); P=8.72×10⁻⁷ for change in the total Positive and Negative Syndrome Scale (PANSS)] in the intron of ADCK1. The mixed linear model-based association P-values for rs56240334 were consistent with the results from GLM-based analyses and the association with change in CGI-S (P=4.26×10⁻⁸) reached genome-wide significance (i.e. P<5×10⁻⁸). We also found suggestive evidence for a polygenic contribution toward paliperidone treatment response with estimates of heritability, h²_SNP, ranging from 0.31 to 0.43 for change in the total PANSS score, the PANSS positive Marder factor score, and CGI-S.

Conclusion

Genetic variations in the ADCK1 gene may differentially predict paliperidone efficacy in schizophrenic patients. However, this finding should be replicated in additional samples.

First- and second-generation antipsychotic drug treatment and subcortical brain morphology in schizophrenia

Antipsychotic medication may influence brain structure, but to what extent effects of first-generation antipsychotics (FGAs) and second-generation antipsychotics (SGAs) differ is still not clear. Here we aimed to disentangle the effects of FGA and SGA on variation in volumes of subcortical structures in patients with long-term treated schizophrenia. Magnetic resonance images were obtained from 95 patients with schizophrenia and 106 healthy control subjects. Among the patients, 40 received only FGA and 42 received only SGA. FreeSurfer 5.3.0 was used to obtain volumes of 27 subcortical structures as well as total brain volume and estimated intracranial volume. Findings of reduced total brain volume, enlarged ventricular volume and reduced hippocampal volume bilaterally among patients were replicated, largely independent of medication class. In the basal ganglia, FGA users had larger putamen bilaterally and right caudate volume compared to healthy controls, and the right putamen was significantly larger than among SGA users. FGA and SGA users had similar and larger globus pallidus volumes compared to healthy controls. Post hoc analyses revealed that the difference between FGA and SGA could be attributed to smaller volumes in the clozapine users specifically. We therefore conclude that basal ganglia volume enlargements are not specific to FGA.

Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data

Neuroimaging techniques have greatly enhanced the understanding of neurodiversity (human brain variation across individuals) in both health and disease. The ultimate goal of using brain imaging biomarkers is to perform individualized predictions. Here we proposed a generalized framework that can predict explicit values of the targeted measures by taking advantage of joint information from multiple modalities. This framework also enables whole brain voxel-wise searching by combining multivariate techniques such as ReliefF, clustering, correlation-based feature selection and multiple regression models, which is more flexible and can achieve better prediction performance than alternative atlas-based methods. For 50 healthy controls and 47 schizophrenia patients, three kinds of features derived from resting-state fMRI (fALFF), sMRI (gray matter) and DTI (fractional anisotropy) were extracted and fed into a regression model, achieving high prediction for both cognitive scores (MCCB composite r=0.7033, MCCB social cognition r=0.7084) and symptomatic scores (positive and negative syndrome scale [PANSS] positive r=0.7785, PANSS negative r=0.7804). Moreover, the brain areas likely responsible for cognitive deficits of schizophrenia, including middle temporal gyrus, dorsolateral prefrontal cortex, striatum, cuneus and cerebellum, were located with different weights, as well as regions predicting PANSS symptoms, including thalamus, striatum and inferior parietal lobule, pinpointing the potential neuromarkers. Finally, compared to a single modality, multimodal combination achieves higher prediction accuracy and enables individualized prediction on multiple clinical measures. There is more work to be done, but the current results highlight the potential utility of multimodal brain imaging biomarkers to eventually inform clinical decision-making.

Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium

The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.

In search of multimodal neuroimaging biomarkers of cognitive deficits in schizophrenia

BACKGROUND

The cognitive deficits of schizophrenia are largely resistant to current treatments and thus are a lifelong illness burden. The Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) provides a reliable and valid assessment of cognition across major cognitive domains; however, the multimodal brain alterations specifically associated with MCCB in schizophrenia have not been examined.

METHODS

The interrelationships between MCCB and the abnormalities seen in three types of neuroimaging-derived maps-fractional amplitude of low-frequency fluctuations (fALFF) from resting-state functional magnetic resonance imaging (MRI), gray matter (GM) density from structural MRI, and fractional anisotropy from diffusion MRI-were investigated by using multiset canonical correlation analysis in data from 47 schizophrenia patients treated with antipsychotic medications and 50 age-matched healthy control subjects.

RESULTS

One multimodal component (canonical variant 8) was identified as both group differentiating and significantly correlated with the MCCB composite. It demonstrated 1) increased cognitive performance associated with higher fALFF (intensity of regional spontaneous brain activity) and higher GM volumes in thalamus, striatum, hippocampus, and the mid-occipital region, with co-occurring fractional anisotropy changes in superior longitudinal fascicules, anterior thalamic radiation, and forceps major; 2) higher fALFF but lower GM volume in dorsolateral prefrontal cortex related to worse cognition in schizophrenia; and 3) distinct domains of MCCB might exhibit dissociable multimodal signatures, e.g., increased fALFF in inferior parietal lobule particularly correlated with decreased social cognition. Medication dose did not relate to these findings in schizophrenia.

CONCLUSIONS

Our results suggest linked functional and structural deficits in distributed cortico-striato-thalamic circuits may be closely related to MCCB-measured cognitive impairments in schizophrenia.

Altered Basal Ganglia Network Integration in Schizophrenia

The basal ganglia involve in a range of functions that are disturbed in schizophrenia patients. This study decomposed the resting-state data of 28 schizophrenia patients and 31 healthy controls with spatial independent component analysis and identified increased functional integration in the bilateral caudate nucleus in schizophrenia patients. Further, the caudate nucleus in patients showed altered functional connection with the prefrontal area and cerebellum. These results identified the importance of basal ganglia in schizophrenia patients. Clinical Trial Registration: Chinese Clinical Trial Registry. Registration number ChiCTR-RCS-14004878.

Internetwork dynamic connectivity effectively differentiates schizophrenic patients from healthy controls

Increasingly more neuroimaging studies have shown that the complex symptoms of schizophrenia are linked to disrupted neural circuits and dysconnectivity of intrinsic connectivity networks. Previous studies have assumed temporal stationarity of resting-state functional connectivity, whereas temporal dynamics have rarely been explored. Here, we utilized resting-state functional MRI with a sliding window approach to measure the amplitude of low-frequency fluctuations (ALFFs) in functional connectivity in 24 patients with schizophrenia and 25 healthy controls. We found that there were significant differences in the ALFFs of specific connections, the majority of which were located between the intrinsic connectivity networks. Importantly, the experimental results of a multivariate pattern analysis of these ALFF measures showed that 81.3% (P<0.0009) of the participants were correctly classified as either schizophrenic patients or healthy controls by leave-one-out cross-validation. Our results show significant abnormality in the dynamics of internetwork functional connectivity in schizophrenia, which contributes toward the characterization and differentiation of schizophrenic patients, and may be used as a potential biomarker.

Brain Structural Effects of Antipsychotic Treatment in Schizophrenia: A Systematic Review

The findings about the progressive brain changes in schizophrenia are controversial, and the potential confounding effect of antipsychotics on brain structure is still under debate. The goal of the current article was to review the existing longitudinal neuroimaging studies addressing the impact of antipsychotic drug treatment on brain changes in schizophrenia. A comprehensive search of PubMed was performed using combinations of key terms distributed into four blocks: "MRI", "longitudinal", "schizophrenia" and "antipsychotic". Studies were considered to be eligible for the review if they were original articles. Studies that examined only changes in brain density were excluded. A total of 41 MRI studies were identified and reviewed. Longitudinal MRI studies did not provide a consistent notion of the effects of antipsychotic treatment on the pattern of brain changes over time in schizophrenia. Overall, most of the included articles did not find a linear relationship between the degree of exposure and progressive brain changes. Further short- and longterm studies are warranted to a better understanding of the influence of antipsychotics in brain structural changes in schizophrenia and also to verify whether first and second generation antipsychotics may differentially affect brain morphometry.

Basal ganglia anatomy and schizophrenia: the role of antipsychotic treatment

Progressive enlargement of basal ganglia volume has been observed in schizophrenia individuals, potentially being sustained by chronic administration of antipsychotic drugs. Here we briefly summarise the state of the art of the role of antipsychotic in leading to increased basal ganglia in schizophrenia, particularly focusing on the caudate nucleus.

Antipsychotics activate mTORC1-dependent translation to enhance neuronal morphological complexity

Although antipsychotic drugs can reduce psychotic behavior within a few hours, full efficacy is not achieved for several weeks, implying that there may be rapid, short-term changes in neuronal function, which are consolidated into long-lasting changes. We showed that the antipsychotic drug haloperidol, a dopamine receptor type 2 (D₂R) antagonist, stimulated the kinase Akt to activate the mRNA translation pathway mediated by the mammalian target of rapamycin complex 1 (mTORC1). In primary striatal D₂R-positive neurons, haloperidol-mediated activation of mTORC1 resulted in increased phosphorylation of ribosomal protein S6 (S6) and eukaryotic translation initiation factor 4E-binding protein (4E-BP). Proteomic mass spectrometry revealed marked changes in the pattern of protein synthesis after acute exposure of cultured striatal neurons to haloperidol, including increased abundance of cytoskeletal proteins and proteins associated with translation machinery. These proteomic changes coincided with increased morphological complexity of neurons that was diminished by inhibition of downstream effectors of mTORC1, suggesting that mTORC1-dependent translation enhances neuronal complexity in response to haloperidol. In vivo, we observed rapid morphological changes with a concomitant increase in the abundance of cytoskeletal proteins in cortical neurons of haloperidol-injected mice. These results suggest a mechanism for both the acute and long-term actions of antipsychotics.