Mapping grey matter reductions in schizophrenia: an anatomical likelihood estimation analysis of voxel-based morphometry studies

Stable biomarker identification for predicting schizophrenia in the human connectome

Schizophrenia, as a psychiatric disorder, has recognized brain alterations both at the structural and at the functional magnetic resonance imaging level. The developing field of connectomics has attracted much attention as it allows researchers to take advantage of powerful tools of network analysis in order to study structural and functional connectivity abnormalities in schizophrenia. Many methods have been proposed to identify biomarkers in schizophrenia, focusing mainly on improving the classification performance or performing statistical comparisons between groups. However, the stability of biomarkers selection has been for long overlooked in the connectomics field. In this study, we follow a machine learning approach where the identification of biomarkers is addressed as a feature selection problem for a classification task. We perform a recursive feature elimination and support vector machines (RFE-SVM) approach to identify the most meaningful biomarkers from the structural, functional, and multi-modal connectomes of healthy controls and patients. Furthermore, the stability of the retrieved biomarkers is assessed across different subsamplings of the dataset, allowing us to identify the affected core of the pathology. Considering our technique altogether, it demonstrates a principled way to achieve both accurate and stable biomarkers while highlighting the importance of multi-modal approaches to brain pathology as they tend to reveal complementary information.

Cortical Volume Differences in Subjects at Risk for Psychosis Are Driven by Surface Area

In subjects at risk for psychosis, the studies on gray matter volume (GMV) predominantly reported volume loss compared with healthy controls (CON). However, other important morphological measurements such as cortical surface area (CSA) and cortical thickness (CT) were not systematically compared. So far, samples mostly comprised subjects at genetic risk or at clinical risk fulfilling an ultra-high risk (UHR) criterion. No studies comparing UHR subjects with at-risk subjects showing only basic symptoms (BS) investigated the differences in CSA or CT. Therefore, we aimed to unravel the contribution of the 2 morphometrical measures constituting the cortical volume (CV) and to test whether these groups inhere different morphometric features. We conducted a surface-based morphometric analysis in 34 CON, 46 BS, and 39 UHR to examine between-group differences in CV, CSA, and CT vertex-wise across the whole cortex. Compared with BS and CON, UHR individuals presented increased CV in frontal and parietal regions, which was driven by larger CSA. These groups did not differ in CT. Yet, at-risk subjects who later developed schizophrenia showed thinning in the occipital cortex. Furthermore, BS presented increased CSA compared with CON. Our results suggest that volumetric differences in UHR subjects are driven by CSA while CV loss in converters seems to be based on cortical thinning. We attribute the larger CSA in UHR to aberrant pruning representing a vulnerability to develop psychotic symptoms reflected in different levels of vulnerability for BS and UHR, and cortical thinning to a presumably stress-related cortical decomposition.

Spatial Patterning of Tissue Volume Loss in Schizophrenia Reflects Brain Network Architecture

BACKGROUND

There is growing recognition that connectome architecture shapes cortical and subcortical gray matter atrophy across a spectrum of neurological and psychiatric diseases. Whether connectivity contributes to tissue volume loss in schizophrenia in the same manner remains unknown.

METHODS

Here, we relate tissue volume loss in patients with schizophrenia to patterns of structural and functional connectivity. Gray matter deformation was estimated in a sample of 133 individuals with chronic schizophrenia (48 women, mean age 34.7 ± 12.9 years) and 113 control subjects (64 women, mean age 23.5 ± 8.4 years). Deformation-based morphometry was used to estimate cortical and subcortical gray matter deformation from T1-weighted magnetic resonance images. Structural and functional connectivity patterns were derived from an independent sample of 70 healthy participants using diffusion spectrum imaging and resting-state functional magnetic resonance imaging.

RESULTS

We found that regional deformation is correlated with the deformation of structurally and functionally connected neighbors. Distributed deformation patterns are circumscribed by specific functional systems (the ventral attention network) and cytoarchitectonic classes (limbic class), with an epicenter in the anterior cingulate cortex.

CONCLUSIONS

Altogether, the present study demonstrates that brain tissue volume loss in schizophrenia is conditioned by structural and functional connectivity, accounting for 25% to 35% of regional variance in deformation.

Regional brain volumes in brief psychotic disorder

Brief psychotic disorder (BPD) is a relatively rare representative of psychotic disorders. Structural brain abnormalities in BPD are not known. We compared 30 patients with BPD and 30 matched healthy controls using high-resolution structural T1-weighted magnetic resonance imaging (MRI). We performed cortical/subcortical reconstruction and volumetric segmentation using FreeSurfer v6.0. Results revealed that the caudal/rostral middle frontal cortex, superior frontal cortex, and the frontal pole were significantly smaller in patients with BPD compared to controls. The number of lifetime psychotic episodes negatively correlated with caudal middle frontal and frontal pole volumes. These results indicate structural abnormalities of the frontal cortex in BPD, which are associated with the number of psychotic relapses.

Differentiation of schizophrenia using structural MRI with consideration of scanner differences: A real-world multisite study

AIM

Neuroimaging studies have revealed that patients with schizophrenia exhibit reduced gray matter volume in various regions. With these findings, various studies have indicated that structural MRI can be useful for the diagnosis of schizophrenia. However, multisite studies are limited. Here, we evaluated a simple model that could be used to differentiate schizophrenia from control subjects considering MRI scanner differences employing voxel-based morphometry.

METHODS

Subjects were 541 patients with schizophrenia and 1252 healthy volunteers. Among them, 95 patients and 95 controls (Dataset A) were used for the generation of regions of interest (ROI), and the rest (Dataset B) were used to evaluate our method. The two datasets were comprised of different subjects. Three-dimensional T1-weighted MRI scans were taken for all subjects and gray-matter images were extracted. To differentiate schizophrenia, we generated ROI for schizophrenia from Dataset A. Then, we determined volume within the ROI for each subject from Dataset B. Using the extracted volume data, we calculated a differentiation feature considering age, sex, and intracranial volume for each MRI scanner. Receiver-operator curve analyses were performed to evaluate the differentiation feature.

RESULTS

The area under the curve ranged from 0.74 to 0.84, with accuracy from 69% to 76%. Receiver-operator curve analysis with all samples revealed an area under the curve of 0.76 and an accuracy of 73%.

CONCLUSION

We moderately successfully differentiated schizophrenia from control using structural MRI from differing scanners from multiple sites. This could be useful for applying neuroimaging techniques to clinical settings for the accurate diagnosis of schizophrenia.

Dysregulation of kynurenine metabolism is related to proinflammatory cytokines, attention, and prefrontal cortex volume in schizophrenia

The kynurenine pathway (KP) of tryptophan (TRP) catabolism links immune system activation with neurotransmitter signaling. The KP metabolite kynurenic acid (KYNA) is increased in the brains of people with schizophrenia. We tested the extent to which: (1) brain KP enzyme mRNAs, (2) brain KP metabolites, and (3) plasma KP metabolites differed on the basis of elevated cytokines in schizophrenia vs. control groups and the extent to which plasma KP metabolites were associated with cognition and brain volume in patients displaying elevated peripheral cytokines. KP enzyme mRNAs and metabolites were assayed in two independent postmortem brain samples from a total of 71 patients with schizophrenia and 72 controls. Plasma KP metabolites, cognition, and brain volumes were measured in an independent cohort of 96 patients with schizophrenia and 81 healthy controls. Groups were stratified based on elevated vs. normal proinflammatory cytokine mRNA levels. In the prefrontal cortex (PFC), kynurenine (KYN)/TRP ratio, KYNA levels, and mRNA for enzymes, tryptophan dioxygenase (TDO) and kynurenine aminotransferases (KATI/II), were significantly increased in the high cytokine schizophrenia subgroup. KAT mRNAs significantly correlated with mRNA for glial fibrillary acidic protein in patients. In plasma, the high cytokine schizophrenia subgroup displayed an elevated KYN/TRP ratio, which correlated inversely with attention and dorsolateral prefrontal cortex (DLPFC) volume. This study provides further evidence for the role of inflammation in a subgroup of patients with schizophrenia and suggests a molecular mechanism through which inflammation could lead to schizophrenia. Proinflammatory cytokines may elicit conversion of TRP to KYN in the periphery and increase the N-methyl-D-aspartate receptor antagonist KYNA via increased KAT mRNA and possibly more enzyme synthesis activity in brain astrocytes,  leading to DLPFC volume loss, and attention impairment in schizophrenia.

Neural correlates of prospection impairments in schizophrenia: Evidence from voxel-based morphometry analysis

Prospection, which has a close relationship with motivation and goal-directed behavior, could be a potential target for alleviating negative symptoms. The present study aimed to examine the structural neural correlates of prospection impairments and the involvement of working memory in prospection in schizophrenia patients. Thirty-seven patients with schizophrenia and 28 healthy controls were recruited and all of them completed a prospection task. Working memory was assessed with the Letter Number Span test. In addition, all participants underwent a structural MRI scan. Voxel-based morphometry (VBM) analysis was used to measure grey matter (GM) volume. We found that in schizophrenia patients, GM loss in the right lateral prefrontal cortex (PFC) and the right ventral medial PFC was correlated with decreased internal details in the prospection task. Moreover, GM volume of the right lateral PFC was found to mediate the relationship between working memory and internal details in these patients. In conclusion, GM loss in the PFC is associated with prospection impairments in schizophrenia patients. Working memory deficits may partially account for prospection impairments in schizophrenia patients.

Frontostriatal functional connectivity and striatal dopamine synthesis capacity in schizophrenia in terms of antipsychotic responsiveness: an [18F]DOPA PET and fMRI study

BACKGROUND

Given that only a subgroup of patients with schizophrenia responds to first-line antipsychotic drugs, a key clinical question is what underlies treatment response. Observations that prefrontal activity correlates with striatal dopaminergic function, have led to the hypothesis that disrupted frontostriatal functional connectivity (FC) could be associated with altered dopaminergic function. Thus, the aim of this study was to investigate the relationship between frontostriatal FC and striatal dopamine synthesis capacity in patients with schizophrenia who had responded to first-line antipsychotic drug compared with those who had failed but responded to clozapine.

METHODS

Twenty-four symptomatically stable patients with schizophrenia were recruited from Seoul National University Hospital, 12 of which responded to first-line antipsychotic drugs (first-line AP group) and 12 under clozapine (clozapine group), along with 12 matched healthy controls. All participants underwent resting-state functional magnetic resonance imaging and [18F]DOPA PET scans.

RESULTS

No significant difference was found in the total PANSS score between the patient groups. Voxel-based analysis showed a significant correlation between frontal FC to the associative striatum and the influx rate constant of [18F]DOPA in the corresponding region in the first-line AP group. Region-of-interest analysis confirmed the result (control group: R2 = 0.019, p = 0.665; first-line AP group: R2 = 0.675, p < 0.001; clozapine group: R2 = 0.324, p = 0.054) and the correlation coefficients were significantly different between the groups.

CONCLUSIONS

The relationship between striatal dopamine synthesis capacity and frontostriatal FC is different between responders to first-line treatment and clozapine treatment in schizophrenia, indicating that a different pathophysiology could underlie schizophrenia in patients who respond to first-line treatments relative to those who do not.

The Fragile Brain: Stress Vulnerability, Negative Affect and GABAergic Neurocircuits in Psychosis

Persons with schizophrenia exhibit sensitivity to stress and negative affect (NA), both strongly correlated with poor functional outcome. This theoretical review suggests that NA reflects a "fragile brain," ie, vulnerable to stress, including events not experienced as stressful by healthy individuals. Based on postmortem evidence of altered gamma-aminobutyric acid (GABA) function in parvalbumin positive interneurons (PVI), animal models of PVI abnormalities and neuroimaging data with GABAergic challenge, it is suggested that GABAergic disruptions weaken cortical regions, which leads to stress vulnerability and excessive NA. Neurocircuits that respond to stressful and salient environmental stimuli, such as the hypothalamic-pituitary-adrenal axis and the amygdala, are highly dysregulated in schizophrenia, exhibiting hypo- and hyper-activity. PVI abnormalities in lateral prefrontal cortex and hippocampus have been hypothesized to affect cognitive function and positive symptoms, respectively; in the medial frontal cortex (dorsal anterior cingulate cortex and dorsal medial prefrontal cortex), these abnormalities may lead to vulnerability to stress, NA and dysregulation of stress responsive systems. Given that postmortem PVI disruptions have been identified in other conditions, such as bipolar disorder and autism, stress vulnerability may reflect a transdiagnostic dimension of psychopathology.

Hippocampal subfields and visuospatial associative memory across stages of schizophrenia-spectrum disorder

BACKGROUND

While previous studies have identified relationships between hippocampal volumes and memory performance in schizophrenia, these relationships are not apparent in healthy individuals. Further, few studies have examined the role of hippocampal subfields in illness-related memory deficits, and no study has examined potential differences across varying illness stages. The current study aimed to investigate whether individuals with early and established psychosis exhibited differential relationships between visuospatial associative memory and hippocampal subfield volumes.

METHODS

Measurements of visuospatial associative memory performance and grey matter volume were obtained from 52 individuals with a chronic schizophrenia-spectrum disorder, 28 youth with recent-onset psychosis, 52 older healthy controls, and 28 younger healthy controls.

RESULTS

Both chronic and recent-onset patients had impaired visuospatial associative memory performance, however, only chronic patients showed hippocampal subfield volume loss. Both chronic and recent-onset patients demonstrated relationships between visuospatial associative memory performance and hippocampal subfield volumes in the CA4/dentate gyrus and the stratum that were not observed in older healthy controls. There were no group by volume interactions when chronic and recent-onset patients were compared.

CONCLUSIONS

The current study extends the findings of previous studies by identifying particular hippocampal subfields, including the hippocampal stratum layers and the dentate gyrus, that appear to be related to visuospatial associative memory ability in individuals with both chronic and first-episode psychosis.

Functional Connectivity of Corticostriatal Circuitry and Psychosis-like Experiences in the General Community

BACKGROUND

Psychotic symptoms are proposed to lie on a continuum, ranging from isolated psychosis-like experiences (PLEs) in nonclinical populations to frank disorder. Here, we investigated the neurobiological correlates of this continuum by examining whether functional connectivity of dorsal corticostriatal circuitry, which is disrupted in psychosis patients and individuals at high risk for psychosis, is associated with the severity of subclinical PLEs.

METHODS

A community sample of 672 adults with no history of psychiatric or neurological illnesses completed a battery of seven questionnaires spanning various PLE domains. Principal component analysis of 12 subscales taken from seven questionnaires was used to estimate major dimensions of PLEs. Dimension scores from principal component analysis were then correlated with whole-brain voxelwise functional connectivity maps of the dorsal striatum in a subset of 353 participants who completed a resting-state neuroimaging protocol.

RESULTS

Principal component analysis identified two dimensions of PLEs that accounted for 62.57% of variance in the measures, corresponding to positive (i.e., subthreshold delusions and hallucinations) and negative (i.e., subthreshold social and physical anhedonia) symptom-like PLEs. Reduced functional connectivity between the dorsal striatum and prefrontal and motor cortices correlated with more severe positive PLEs. Increased functional connectivity between the dorsal striatum and motor cortex was associated with more severe negative PLEs.

CONCLUSIONS

Consistent with past findings in patients and individuals at high risk for psychosis, subthreshold positive symptomatology is associated with reduced functional connectivity of the dorsal circuit. This finding suggests that the connectivity of this circuit tracks the expression of psychotic phenomena across a broad spectrum of severity, extending from the subclinical domain to clinical diagnosis.

Positive and general psychopathology associated with specific gray matter reductions in inferior temporal regions in patients with schizophrenia

Schizophrenia is a complex disorder that affects perception, cognition, and emotion causing symptoms such as delusions, hallucinations, and suspiciousness. Schizophrenia is also associated with structural cortical abnormalities including lower gray matter (GM) concentration, GM volume, and cortical thickness relative to healthy control individuals. However, the association between GM measures and symptom dimensions in schizophrenia is still not well understood. Here, we applied parallel independent component analysis (pICA), a higher-order statistical approach that identifies covarying patterns within two (or more) data modalities simultaneously, to link covarying brain networks of GM concentration with covarying linear combinations of the positive and negative syndrome scale (PANSS). In a large sample of patients with schizophrenia (n = 337) the association between these two data modalities was investigated. The pICA revealed a distinct PANSS profile characterized by increased delusional symptoms, suspiciousness, hallucinations, and anxiety, that was associated with a pattern of lower GM concentration in inferior temporal gyri and fusiform gyri and higher GM concentration in the sensorimotor cortex. GM alterations replicate previous findings; additionally, applying a multivariate technique, we were able to map a very specific symptom profile onto these GM alterations extending our understanding of cortical abnormalities associated with schizophrenia. Techniques like parallel ICA can reveal linked patterns of alterations across different data modalities that can help to identify biologically-informed phenotypes which might help to improve future treatment targets.

N-BiC: A Method for Multi-Component and Symptom Biclustering of Structural MRI Data: Application to Schizophrenia

OBJECTIVE

We propose and develop a novel biclustering (N-BiC) approach for performing N-way biclustering of neuroimaging data. Our approach is applicable to an arbitrary number of features from both imaging and behavioral data (e.g., symptoms). We applied it to structural MRI data from patients with schizophrenia.

METHODS

It uses a source-based morphometry approach [i.e., independent component analysis of gray matter segmentation maps] to decompose the data into a set of spatial maps, each of which includes regions that covary among individuals. Then, the loading parameters for components of interest are entered to an exhaustive search, which incorporates a modified depth-first search technique to carry out the biclustering, with the goal of obtaining submatrices where the selected rows (individuals) show homogeneity in their expressions of selected columns (components) and vice versa.

RESULTS

Findings demonstrate that multiple biclusters have an evident association with distinct brain networks for the different types of symptoms in schizophrenia. The study identifies two components: inferior temporal gyrus (16) and brainstem (7), which are related to positive (distortion/excess of normal function) and negative (diminution/loss of normal function) symptoms in schizophrenia, respectively.

CONCLUSION

N-BiC is a data-driven method of biclustering MRI data that can exhaustively explore relationships/substructures from a dataset without any prior information with a higher degree of robustness than earlier biclustering applications.

SIGNIFICANCE

The use of such approaches is important to investigate the underlying biological substrates of mental illness by grouping patients into homogeneous subjects, as the schizophrenia diagnosis is known to be relatively nonspecific and heterogeneous.

Gray Matter Microstructural Abnormalities and Working Memory Deficits in Individuals with Schizophrenia

OBJECTIVE

Working memory impairments serve as prognostic factors for patients with schizophrenia. Working memory deficits are mainly associated with gray matter (GM) thickness and volume. We investigated the association between GM diffusivity and working memory in controls and individuals with schizophrenia.

METHODS

T1 and diffusion tensor images of the brain, working memory task (letter number sequencing) scores, and the demographic data of 90 individuals with schizophrenia and 97 controls were collected from the SchizConnect database. T1 images were parcellated into the 68 GM Regions of Interest (ROI). Axial Diffusivity (AD), Fractional Anisotropy (FA), Radial Diffusivity (RD), and Trace (TR) were calculated for each of the ROIs.

RESULTS

Compared to the controls, schizophrenia group showed significantly increased AD, RD, and TR in specific regions on the frontal, temporal, and anterior cingulate area. Moreover, working memory was negatively correlated with AD, RD, and TR in the lateral orbitofrontal, superior temporal, inferior temporal, and rostral anterior cingulate area on left hemisphere in the individuals with schizophrenia.

CONCLUSION

These results demonstrated GM microstructural abnormalities in the frontal, temporal, and anterior cingulate regions of individuals with schizophrenia. Furthermore, these regional GM microstructural abnormalities suggest a neuropathological basis for the working memory deficits observed clinically in individuals with schizophrenia.

Depression, auditory-verbal hallucinations, and delusions in patients with schizophrenia: Different patterns of association with prefrontal gray and white matter volume

Structural brain abnormalities, including decreased gray matter (GM) and white matter (WM) volume, have been observed in patients with schizophrenia. These decrements were found to be associated with positive and negative symptoms, but affective symptoms (depression and anxiety) were poorly explored. We hypothesized that abnormalities in GM and WM volume might also be related to affective symptoms. GM and WM volumes were calculated from high-resolution T1 structural images acquired from 24 patients with schizophrenia and 26 healthy controls, and the associations of positive, negative, and affective symptoms with the brain volumes that showed significant reduction in patients were investigated. Patients demonstrated GM volume reductions in the bilateral prefrontal cortex, and WM volume reductions in the right frontal and left corpus callosum. Prefrontal cortex volume was significantly and inversely associated with both auditory-verbal hallucinations and depression severity. WM volume alterations, in contrast, were related to alogia, anhedonia, and delusions. The combined impact of auditory-verbal hallucinations and depression on similar sub-regions of the prefrontal cortex suggests that depression is involved in hearing voices. Further, this adverse impact of depression on prefrontal GM volume may underlie the impairment demonstrated by these patients in cognitive tasks that rely on executive processes.

Synaptic loss in schizophrenia: a meta-analysis and systematic review of synaptic protein and mRNA measures

Although synaptic loss is thought to be core to the pathophysiology of schizophrenia, the nature, consistency and magnitude of synaptic protein and mRNA changes has not been systematically appraised. Our objective was thus to systematically review and meta-analyse findings. The entire PubMed database was searched for studies from inception date to the 1st of July 2017. We selected case-control postmortem studies in schizophrenia quantifying synaptic protein or mRNA levels in brain tissue. The difference in protein and mRNA levels between cases and controls was extracted and meta-analysis conducted. Among the results, we found a significant reduction in synaptophysin in schizophrenia in the hippocampus (effect size: -0.65, p < 0.01), frontal (effect size: -0.36, p = 0.04), and cingulate cortices (effect size: -0.54, p = 0.02), but no significant changes for synaptophysin in occipital and temporal cortices, and no changes for SNAP-25, PSD-95, VAMP, and syntaxin in frontal cortex. There were insufficient studies for meta-analysis of complexins, synapsins, rab3A and synaptotagmin and mRNA measures. Findings are summarised for these, which generally show reductions in SNAP-25, PSD-95, synapsin and rab3A protein levels in the hippocampus but inconsistency in other regions. Our findings of moderate-large reductions in synaptophysin in hippocampus and frontal cortical regions, and a tendency for reductions in other pre- and postsynaptic proteins in the hippocampus are consistent with models that implicate synaptic loss in schizophrenia. However, they also identify potential differences between regions and proteins, suggesting synaptic loss is not uniform in nature or extent.

Acute stress modifies oscillatory indices of affective processing: Insight on the pathophysiology of schizophrenia spectrum disorders

OBJECTIVE

The current study evaluated the differential impact of acute psychosocial stress exposure on oscillatory correlates of affective processing in control participants and patients with schizophrenia spectrum disorders (SCZ) to elucidate the stress-mediated pathway to psychopathology.

METHODS

EEG was recorded while 21 control participants and 21 patients with SCZ performed emotional framing tasks (assessing a key aspect of emotion regulation (ER)) before and after a laboratory stress challenge (Trier Social Stress Test). EEG spectral perturbations evoked in response to neutral and aversive stimuli (presented with positive or negative contextual cues) were extracted in theta (4-8 Hz) and beta (12-30 Hz) frequencies.

RESULTS

Patients demonstrated aberrant theta and beta oscillatory activity, with impaired frontal theta-mediated framing and beta-derived motivated attention processes relative to controls. Following stress exposure, controls exhibited impaired frontal theta-mediated emotional framing, similar to the oscillatory profile observed in patients before stress.

CONCLUSIONS

The acute stress-induced oscillatory changes observed in controls were persistently present in patients, indicating an inefficiency of fronto-limbic adaptation to stress exposure.

SIGNIFICANCE

Results provide novel insight on the electrophysiological correlates of arousal and affect regulation, which are core homogeneous symptom dimensions shared across neuropsychiatric disorders, and shed light on putative mechanisms in the translation of stress into psychopathology.

Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine learning with structured sparsity

OBJECTIVE

Structural MRI (sMRI) increasingly offers insight into abnormalities inherent to schizophrenia. Previous machine learning applications suggest that individual classification is feasible and reliable and, however, is focused on the predictive performance of the clinical status in cross-sectional designs, which has limited biological perspectives. Moreover, most studies depend on relatively small cohorts or single recruiting site. Finally, no study controlled for disease stage or medication's effect. These elements cast doubt on previous findings' reproducibility.

METHOD

We propose a machine learning algorithm that provides an interpretable brain signature. Using large datasets collected from 4 sites (276 schizophrenia patients, 330 controls), we assessed cross-site prediction reproducibility and associated predictive signature. For the first time, we evaluated the predictive signature regarding medication and illness duration using an independent dataset of first-episode patients.

RESULTS

Machine learning classifiers based on neuroanatomical features yield significant intersite prediction accuracies (72%) together with an excellent predictive signature stability. This signature provides a neural score significantly correlated with symptom severity and the extent of cognitive impairments. Moreover, this signature demonstrates its efficiency on first-episode psychosis patients (73% accuracy).

CONCLUSION

These results highlight the existence of a common neuroanatomical signature for schizophrenia, shared by a majority of patients even from an early stage of the disorder.

An fMRI study of theory of mind in individuals with first episode psychosis

Theory of mind (ToM), the ability to infer one's own and others' mental states, is the social cognitive process shown to have the greatest impact on functional outcome in schizophrenia. It is not yet known if neural abnormalities underlying ToM present early, during the first episode of psychosis (FEP). Fourteen FEP participants and twenty-two healthy control participants, aged 15-25, were included in analyses. All participants had a 3T magnetic resonance imaging scan and completed a block-design picture-story attribution-of-intentions ToM fMRI task, and completed a battery of behavioral social cognitive measures including a ToM task. General linear model analyses were carried out. Post-hoc regression analyses were conducted to explore whether aberrant ToM-related activation in FEP participants was associated with symptomatology and global social and occupational functioning. FEP participants, when compared to healthy controls, had significantly less activity in the right temporoparietal junction, right orbitofrontal cortex and left middle prefrontal/inferior frontal cortex, when making social attributions. Aberrant ToM-related activation in the right temporoparietal junction was associated with severity of overall psychopathology, but not functional outcome. Specific regions of the social brain network, associated with ToM, are dysfunctional in young people with FEP. Future research should determine whether alteration of normal brain functioning in relation to ToM occurs before or during illness onset.

Olfactory deficits in individuals at risk for psychosis and patients with schizophrenia: relationship with socio-cognitive functions and symptom severity

Odor identification deficits are well documented in patients with schizophrenia, but it remains unclear whether individuals at clinical high-risk for psychosis exhibit similar changes and whether their olfactory function is related to social/cognitive functions and symptomatology. In this study, we investigated odor detection sensitivity and identification ability in 32 individuals with at-risk mental state (ARMS), 59 schizophrenia patients, and 169 healthy controls using a T&T olfactometer. The ARMS and schizophrenia subjects were administered the Brief Assessment of Cognition in Schizophrenia (BACS), the Schizophrenia Cognition Rating Scale (SCoRS), and the Social and Occupational Functioning Assessment Scale (SOFAS) to assess their cognitive and social functions, and the Positive and Negative Syndrome Scale (PANSS) for clinical symptoms. Both the ARMS and schizophrenia subjects had lower odor identification ability when compared with healthy controls, while no significant difference was found in the odor detection sensitivity. The lower odor identification ability in the ARMS group correlated with the severity of negative symptoms and weakly correlated with lower performance on the BACS verbal fluency test. The olfactory measures of schizophrenia patients did not correlate with illness duration, medication, symptom severity, and social and cognitive functions. For the ARMS and schizophrenia groups, the olfactory measures did not correlate with the SOFAS and SCoRS scores. These findings suggest that high-risk subjects for psychosis already show odor identification deficits similar to those observed in schizophrenia patients, which probably reflect a biological trait related to vulnerability to psychosis.

Bidirectional Microglia-Neuron Communication in Health and Disease

Microglia are ramified cells that exhibit highly motile processes, which continuously survey the brain parenchyma and react to any insult to the CNS homeostasis. Although microglia have long been recognized as a crucial player in generating and maintaining inflammatory responses in the CNS, now it has become clear, that their function are much more diverse, particularly in the healthy brain. The innate immune response and phagocytosis represent only a little segment of microglia functional repertoire that also includes maintenance of biochemical homeostasis, neuronal circuit maturation during development and experience-dependent remodeling of neuronal circuits in the adult brain. Being equipped by numerous receptors and cell surface molecules microglia can perform bidirectional interactions with other cell types in the CNS. There is accumulating evidence showing that neurons inform microglia about their status and thus are capable of controlling microglial activation and motility while microglia also modulate neuronal activities. This review addresses the topic: how microglia communicate with other cell types in the brain, including fractalkine signaling, secreted soluble factors and extracellular vesicles. We summarize the current state of knowledge of physiological role and function of microglia during brain development and in the mature brain and further highlight microglial contribution to brain pathologies such as Alzheimer’s and Parkinson’s disease, brain ischemia, traumatic brain injury, brain tumor as well as neuropsychiatric diseases (depression, bipolar disorder, and schizophrenia).

Recognition of Schizophrenia with Regularized Support Vector Machine and Sequential Region of Interest Selection using Structural Magnetic Resonance Imaging

Structural brain abnormalities in schizophrenia have been well characterized with the application of univariate methods to magnetic resonance imaging (MRI) data. However, these traditional techniques lack sensitivity and predictive value at the individual level. Machine-learning approaches have emerged as potential diagnostic and prognostic tools. We used an anatomically and spatially regularized support vector machine (SVM) framework to categorize schizophrenia and healthy individuals based on whole-brain gray matter densities estimated using voxel-based morphometry from structural MRI scans. The regularized SVM model yielded recognition accuracy of 86.6% in the training set of 127 individuals and validation accuracy of 83.5% in an independent set of 85 individuals. A sequential region-of-interest (ROI) selection step was adopted for feature selection, improving recognition accuracy to 92.0% in the training set and 89.4% in the validation set. The combined model achieved 96.6% sensitivity and 74.1% specificity. Seven ROIs were identified as the optimal discriminatory subset: the occipital fusiform gyrus, middle frontal gyrus, pars opercularis of the inferior frontal gyrus, anterior superior temporal gyrus, superior frontal gyrus, left thalamus and left lateral ventricle. These findings demonstrate the utility of spatial and anatomical priors in SVM for neuroimaging analyses in conjunction with sequential ROI selection in the recognition of schizophrenia.

Sexually dimorphic subcortical brain volumes in emerging psychosis

BACKGROUND

In schizophrenic psychoses, the normal sexual dimorphism of the brain has been shown to be disrupted or even reversed. Little is known, however, at what time point in emerging psychosis this occurs. We have therefore examined, if these alterations are already present in the at-risk mental state (ARMS) for psychosis and in first episode psychosis (FEP) patients.

METHODS

Data from 65 ARMS (48 (73.8%) male; age=25.1±6.32) and 50 FEP (37 (74%) male; age=27±6.56) patients were compared to those of 70 healthy controls (HC; 27 (38.6%) male; age=26±4.97). Structural T1-weighted images were acquired using a 3 Tesla magnetic resonance imaging (MRI) scanner. Linear mixed effects models were used to investigate whether subcortical brain volumes are dependent on sex.

RESULTS

We found men to have larger total brain volumes (p<0.001), and smaller bilateral caudate (p=0.008) and hippocampus volume (p<0.001) than women across all three groups. Older subjects had more GM and WM volume than younger subjects. No significant sex×group interaction was found.

CONCLUSIONS

In emerging psychosis there still seem to exist patterns of normal sexual dimorphism in total brain and caudate volume. The only structure affected by reversed sexual dimorphism was the hippocampus, with women showing larger volumes than men even in HC. Thus, we conclude that subcortical volumes may not be primarily affected by disrupted sexual dimorphism in emerging psychosis.

Brain morphologic changes in early stages of psychosis: Implications for clinical application and early intervention

To date, a large number of magnetic resonance imaging (MRI) studies have been conducted in schizophrenia, which generally demonstrate gray matter reduction, predominantly in the frontal and temporo-limbic regions, as well as gross brain abnormalities (e.g., a deviated sulcogyral pattern). Although the causes as well as timing and course of these findings remain elusive, these morphologic changes (especially gross brain abnormalities and medial temporal lobe atrophy) are likely present at illness onset, possibly reflecting early neurodevelopmental abnormalities. In addition, longitudinal MRI studies suggest that patients with schizophrenia and related psychoses also have progressive gray matter reduction during the transition period from prodrome to overt psychosis, as well as initial periods after psychosis onset, while such changes may become almost stable in the chronic stage. These active brain changes during the early phases seem to be relevant to the development of clinical symptoms in a region-specific manner (e.g., superior temporal gyrus atrophy and positive psychotic symptoms), but may be at least partly ameliorated by antipsychotic medication. Recently, increasing evidence from MRI findings in individuals at risk for developing psychosis has suggested that those who subsequently develop psychosis have baseline brain changes, which could be at least partly predictive of later transition into psychosis. In this article, we selectively review previous MRI findings during the course of psychosis and also refer to the possible clinical applicability of these neuroimaging research findings, especially in the diagnosis of schizophrenia and early intervention for psychosis.

BrainMap VBM: An environment for structural meta-analysis

The BrainMap database is a community resource that curates peer-reviewed, coordinate-based human neuroimaging literature. By pairing the results of neuroimaging studies with their relevant meta-data, BrainMap facilitates coordinate-based meta-analysis (CBMA) of the neuroimaging literature en masse or at the level of experimental paradigm, clinical disease, or anatomic location. Initially dedicated to the functional, task-activation literature, BrainMap is now expanding to include voxel-based morphometry (VBM) studies in a separate sector, titled: BrainMap VBM. VBM is a whole-brain, voxel-wise method that measures significant structural differences between or within groups which are reported as standardized, peak x-y-z coordinates. Here we describe BrainMap VBM, including the meta-data structure, current data volume, and automated reverse inference functions (region-to-disease profile) of this new community resource. CBMA offers a robust methodology for retaining true-positive and excluding false-positive findings across studies in the VBM literature. As with BrainMap's functional database, BrainMap VBM may be synthesized en masse or at the level of clinical disease or anatomic location. As a use-case scenario for BrainMap VBM, we illustrate a trans-diagnostic data-mining procedure wherein we explore the underlying network structure of 2,002 experiments representing over 53,000 subjects through independent components analysis (ICA). To reduce data-redundancy effects inherent to any database, we demonstrate two data-filtering approaches that proved helpful to ICA. Finally, we apply hierarchical clustering analysis (HCA) to measure network- and disease-specificity. This procedure distinguished psychiatric from neurological diseases. We invite the neuroscientific community to further exploit BrainMap VBM with other modeling approaches.

Parkinsonism is associated to fronto-caudate disconnectivity and cognition in schizophrenia

The present work studies the possible relation of parkinsonism and fronto-caudate dysconnectivity, as well as its relation to cognition in schizophrenia patients. We assessed parkinsonism using Simpson-Angus scale and prefronto-caudate connectivity using diffusion magnetic resonance in 22 schizophrenia patients (11 first-episodes) and 14 healthy controls. Fractional anisotropy was calculated for the white matter tracts directly linking rostral middle prefrontal (RMPF) and superior medial prefrontal (SMPF) regions with caudate nucleus. Cognition was assessed using the Brief Assessment of Cognition in Schizophrenia Scale (BACS). Total parkinsonism scores were negatively related to fractional anisotropy in the right SMPF-caudate tract in patients, which was also found in the first-episode patients alone, but not in controls. Parkinsonism was also inversely associated in patients to performance in social cognition, verbal memory, working memory and performance speed tests. In conclusion, our data support the involvement of fronto-striatal dysconnectivity in parkinsonism in schizophrenia.

Correlations between exploratory eye movement, hallucination, and cortical gray matter volume in people with schizophrenia

BACKGROUND

Widespread cortical gray matter alternations in people with schizophrenia are correlated with both psychotic symptoms and cognitive/behavioral abnormalities, including the impairments of exploratory eye movement (EEM). Particularly, the loss of gray matter density is specifically related to deficits of the responsive search score (RSS) of EEM in schizophrenia. It is unknown, however, whether the schizophrenia-related RSS deficits are associated with certain psychotic symptoms, such as hallucinations.

METHODS

In 33 participants with schizophrenia, the measurement of EEM, assessment of the hallucination severity using Positive and Negative Syndrome Scale (PANSS) and a voxel-based morphometric analysis of cortical gray matter volume (GMV) were conducted to investigate the relationships between the RSS of EEM, symptom severity, and GMV. In 29 matched healthy controls, the measurement of EEM and a voxel-based morphometric analysis of cortical GMV were also conducted to investigate the relationship between the RSS of EEM and GMV.

RESULTS

In participants with schizophrenia, the hallucination severity was significantly negatively correlated with both the RSS and the GMV of a large number of brain regions in the frontal, temporal, parietal, orbitofrontal, calcarine, cingulate, and insular cortices, and rolandic operculum, hippocampus, parahippocampal gyrus, and thalamus. Also in participants with schizophrenia, the RSS was significantly positively correlated with the GMV in the left supplementary motor area (SMA), left superior frontal cortex (SFG), bilateral precentral gyri, bilateral postcentral gyri, and bilateral middle frontal cortices. More importantly, the GMV of the SMA, SFG, and precentral gyrus in the left hemisphere was not only significantly negatively correlated with the hallucination severity but also significantly positively correlated with the RSS. No significant correlation could be revealed between the RSS and the GMV of any brain regions in healthy controls.

CONCLUSIONS

There was a significantly negative association between the hallucination severity and the RSS of EEM, suggesting that the RSS may be a potential biomarker for predicting the hallucination severity of schizophrenia. Also, the GMV of the left SMA, SFG, and precentral gyrus may be the common substrates underlying both hallucination induction and the RSS in people with schizophrenia.

Functional network dysconnectivity as a biomarker of treatment resistance in schizophrenia

Schizophrenia may develop from disruptions in functional connectivity regulated by neurotransmitters such as dopamine and acetylcholine. The modulatory effects of these neurotransmitters might explain how antipsychotics attenuate symptoms of schizophrenia and account for the variable response to antipsychotics observed in clinical practice. Based on the putative mechanisms of antipsychotics and evidence of disrupted connectivity in schizophrenia, we hypothesised that functional network connectivity, as assessed using network-based statistics, would exhibit differences between treatment response subtypes of schizophrenia and healthy controls. Resting-state functional MRI data were obtained from 17 healthy controls as well as individuals with schizophrenia who responded well to first-line atypical antipsychotics (first-line responders; FLR, n=18), had failed at least two trials of antipsychotics but responded to clozapine (treatment-resistant schizophrenia; TRS, n=18), or failed at least two trials of antipsychotics and a trial of clozapine (ultra-treatment-resistant schizophrenia; UTRS, n=16). Data were pre-processed using the Advanced Normalization Toolkit and BrainWavelet Toolbox. Network connectivity was assessed using the Network-Based Statistics toolbox in Matlab. ANOVA revealed a significant difference in functional connectivity between groups that extended between cerebellar and parietal regions to the frontal cortex (p<0.05). Post-hoc t-tests revealed weaker network connectivity in individuals with UTRS compared with healthy controls but no other differences between groups. Results demonstrated distinct differences in functional connectivity between individuals with UTRS and healthy controls. Future work must determine whether these changes occur prior to the onset of treatment and if they can be used to predict resistance to antipsychotics during first-episode psychosis.

Progressive symptom-associated prefrontal volume loss occurs in first-episode schizophrenia but not in affective psychosis

Although smaller gray matter volumes (GMV) in the prefrontal cortex (PFC) in schizophrenia and bipolar disorder have been reported cross-sectionally, there are, to our knowledge, no reports of longitudinal comparisons using manually drawn, gyrally based ROI, and their associations with symptoms. The object of this study was to determine whether first-episode schizophrenia (FESZ) and first-episode affective psychosis (FEAFF) patients show initial and progressive PFC GMV reduction in bilateral frontal pole, superior frontal gyrus (SFG), middle frontal gyrus (MFG), and inferior frontal gyrus (IFG) and examine their symptom associations. Twenty-one FESZ, 24 FEAFF and 23 healthy control subjects (HC) underwent 1.5T MRI with follow-up imaging on the same scanner ~ 1.5 years later. Groups were strikingly different in progressive GMV loss. FESZ showed significant progressive GMV loss in the left SFG, bilateral MFG, and bilateral IFG. In addition, left MFG and/or IFG GMV loss was associated with worsening of withdrawal-retardation and total BPRS symptoms scores. In contrast, FEAFF showed no significant difference in GMV compared with HC, either cross-sectionally or longitudinally. Of note, FreeSurfer run on the same images showed no significant changes longitudinally.

Abnormal regional homogeneity as a potential imaging biomarker for adolescent-onset schizophrenia: A resting-state fMRI study and support vector machine analysis

OBJECTIVE

Structural and functional abnormalities have been reported in the brain of patients with adolescent-onset schizophrenia (AOS). The brain regional functional synchronization in patients with AOS remains unclear.

METHODS

We analyzed resting-state functional magnetic resonance scans in 48 drug-naive patients with AOS and 31 healthy controls by using regional homogeneity (ReHo), a measurement that reflects brain local functional connectivity or synchronization and indicates regional integration of information processing. Then, receiver operating characteristic curves and support vector machines were used to evaluate the effect of abnormal regional homogeneity in differentiating patients from controls.

RESULTS

Patients with AOS showed significantly increased ReHo values in the bilateral superior medial prefrontal cortex (MPFC) and significantly decreased ReHo values in the left superior temporal gyrus (STG), right precentral lobule, right inferior parietal lobule (IPL), and left paracentral lobule when compared with controls. A combination of the ReHo values in bilateral superior MPFC, left STG, and right IPL was able to discriminate patients from controls with the sensitivity of 88.24%, specificity of 91.89%, and accuracy of 90.14%.

CONCLUSION

The brain regional functional synchronization abnormalities exist in drug-naive patients with AOS. A combination of ReHo values in these abnormal regions might serve as potential imaging biomarker to identify patients with AOS.

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.

Early Intervention and a Direction of Novel Therapeutics for the Improvement of Functional Outcomes in Schizophrenia: A Selective Review

BACKGROUND

A recent review reported that the median proportion of patients recovering from schizophrenia was 13.5% and that this did not change over time. Various factors including the duration of untreated psychosis, cognitive impairment, negative symptoms, and morphological changes in the brain influence the functional outcome of schizophrenia. The authors herein reviewed morphological changes in the brain of schizophrenia patients, effects of early intervention, and a direction of developing novel therapeutics to achieve significant improvement of the functional outcome.

METHODS

A selective review of the literature including studies from our department was performed.

RESULTS

Longitudinal structural neuroimaging studies on schizophrenia revealed that volume reductions in the peri-Sylvian regions (e.g., superior temporal gyrus and insula), which are related to positive psychotic symptoms, progress around the onset (critical stage) of schizophrenia, but become stable in the chronic stage. On the other hand, morphological changes in the fronto-thalamic regions and lateral ventricle, which are related to negative symptoms, neurocognitive dysfunction, and the functional outcome, progress during both the critical and chronic stages. These changes in the peri-Sylvian and fronto-thalamic regions may provide a pathophysiological basis for Crow's two-syndrome classification. Accumulated evidence from early intervention trials suggests that the transition risk from an at-risk mental state (ARMS) to psychosis is approximately 30%. Differences in the cognitive performance, event-related potentials (e.g., mismatch negativity), and brain morphology have been reported between ARMS subjects who later developed psychosis and those who did not. Whether early intervention for ARMS significantly improves the long-term recovery rate of schizophrenia patients remains unknown. With respect to the development of novel therapeutics, animal models of schizophrenia based on the N-methyl-d-aspartate receptor hypofunction hypothesis successfully mimicked behavioral changes associated with cognitive impairments characteristic of the disease. Furthermore, these animal models elicited histological changes in the brain similar to those observed in schizophrenia patients, i.e., decreased numbers of parvalbumin-positive interneurons and dendritic spines of pyramidal neurons in the frontal cortex. Some antioxidant compounds were found to ameliorate these behavioral and histological abnormalities.

CONCLUSION

Early intervention coupled with novel therapeutics may offer a promising approach for substantial improvement of the functional outcome of schizophrenia patients.

Gray matter morphological anomalies in the cerebellar vermis in first-episode schizophrenia patients with cognitive deficits

BACKGROUND

Cognitive deficits are a core feature of early schizophrenia. However, the pathological foundations underlying cognitive deficits are still unknown. The present study examined the association between gray matter density and cognitive deficits in first-episode schizophrenia.

METHOD

Structural magnetic resonance imaging of the brain was performed in 34 first-episode schizophrenia patients and 21 healthy controls. Patients were divided into two subgroups according to working memory task performance. The three groups were well matched for age, gender, and education, and the two patient groups were also further matched for diagnosis, duration of illness, and antipsychotic treatment. Voxel-based morphometric analysis was performed to estimate changes in gray matter density in first-episode schizophrenia patients with cognitive deficits. The relationships between gray matter density and clinical outcomes were explored.

RESULTS

Patients with cognitive deficits were found to have reduced gray matter density in the vermis and tonsil of cerebellum compared with patients without cognitive deficits and healthy controls, decreased gray matter density in left supplementary motor area, bilateral precentral gyrus compared with patients without cognitive deficits. Classifier results showed GMD in cerebellar vermis tonsil cluster could differentiate SZ-CD from controls, left supplementary motor area cluster could differentiate SZ-CD from SZ-NCD. Gray matter density values of the cerebellar vermis cluster in patients groups were positively correlated with cognitive severity.

CONCLUSIONS

Decreased gray matter density in the vermis and tonsil of cerebellum may underlie early psychosis and serve as a candidate biomarker for schizophrenia with cognitive deficits.

Heterogeneity and Homogeneity of Regional Brain Structure in Schizophrenia: A Meta-analysis

IMPORTANCE

Schizophrenia is associated with alterations in mean regional brain volumes. However, it is not known whether the clinical heterogeneity seen in the disorder is reflected at the neurobiological level, for example, in differences in the interindividual variability of these brain volumes relative to control individuals.

OBJECTIVE

To investigate whether patients with first-episode schizophrenia exhibit greater variability of regional brain volumes in addition to mean volume differences.

DATA SOURCES

Studies that reported regional brain volumetric measures in patients and controls by using magnetic resonance imaging in the MEDLINE, EMBASE, and PsycINFO databases from inception to October 1, 2016, were examined.

STUDY SELECTION

Case-control studies that reported regional brain volumes in patients with first-episode schizophrenia and healthy controls by using magnetic resonance imaging were selected.

DATA EXTRACTION AND SYNTHESIS

Means and variances (SDs) were extracted for each measure to calculate effect sizes, which were combined using multivariate meta-analysis.

MAIN OUTCOMES AND MEASURES

Relative variability of regional brain volumetric measurements in patients compared with control groups as indexed by the variability ratio (VR) and coefficient of variation ratio (CVR). Hedges g was used to quantify mean differences.

RESULTS

A total of 108 studies that reported measurements from 3901 patients (1272 [32.6%] female) with first-episode schizophrenia and 4040 controls (1613 [39.9%] female) were included in the analyses. Variability of putamen (VR, 1.13; 95% CI, 1.03-1.24; P = .01), temporal lobe (VR, 1.12; 95% CI, 1.04-1.21; P = .004), thalamus (VR, 1.16; 95% CI, 1.07-1.26; P < .001), and third ventricle (VR, 1.43; 95% CI, 1.20-1.71; P < 1 × 10-5) volume was significantly greater in patients, whereas variability of anterior cingulate cortex volume was lower (VR, 0.89; 95% CI, 0.81-0.98; P = .02). These findings were robust to choice of outcome measure. There was no evidence of altered variability of caudate nucleus or frontal lobe volumes. Mean volumes of the lateral (g = 0.40; 95% CI, 0.29-0.51; P < .001) and third ventricles (g = 0.43; 95% CI, 0.26-0.59; P < .001) were greater, whereas mean volumes of the amygdala (g = -0.46; -0.65 to -0.26; P < .001), anterior cingulate cortex (g = -0.26; 95% CI, -0.43 to -0.10; P = .005), frontal lobe (g = -0.31; 95% CI, -0.44 to -0.19; P = .001), hippocampus (g = -0.66; 95% CI, -0.84 to -0.47; P < .001), temporal lobe (g = -0.22; 95% CI, -0.36 to -0.09; P = .001), and thalamus (g = -0.36; 95% CI, -0.57 to -0.15; P = .001) were lower in patients. There was no evidence of altered mean volume of caudate nucleus or putamen.

CONCLUSIONS AND RELEVANCE

In addition to altered mean volume of many brain structures, schizophrenia is associated with significantly greater variability of temporal cortex, thalamus, putamen, and third ventricle volumes, consistent with biological heterogeneity in these regions, but lower variability of anterior cingulate cortex volume. This finding indicates greater homogeneity of anterior cingulate volume and, considered with the significantly lower mean volume of this region, suggests that this is a core region affected by the disorder.

Age-related brain structural alterations as an intermediate phenotype of psychosis

BACKGROUND

There is only limited agreement with respect to location, directionality and functional implications of brain structural alterations observed in patients with schizophrenia. Additionally, their link to occurrence of psychotic symptoms remains unclear. A viable way of addressing these questions is to examine populations in an at-risk mental state (ARMS) before the transition to psychosis.

METHODS

We tested for structural brain alterations in individuals in an ARMS compared with healthy controls and patients with first-episode psychosis (FEP) using voxel-based morphometry and measures of cortical thickness. Furthermore, we evaluated if these alterations were modified by age and whether they were linked to the observed clinical symptoms.

RESULTS

Our sample included 59 individuals with ARMS, 26 healthy controls and 59 patients with FEP. We found increased grey matter volume and cortical thickness in individuals with ARMS and a similar pattern of structural alterations in patients with FEP. We further found stronger age-related reductions in grey matter volume and cortical thickness in both patients with FEP and individuals with ARMS, linking these alterations to observed clinical symptoms.

LIMITATIONS

The ARMS group comprised subgroups with heterogeneous levels of psychosis risk and medication status. Furthermore, the cross-sectional nature of our study and the reduced number of older patients limit conclusions with respect to observed interactions with age.

CONCLUSION

Our findings on consistent structural alterations in individuals with ARMS and patients with FEP and their link to clinical symptoms have major implications for understanding their time of occurrence and relevance to psychotic symptoms. Interactions with age found for these alterations may explain the heterogeneity of findings reported in the literature.

PET imaging of putative microglial activation in individuals at ultra-high risk for psychosis, recently diagnosed and chronically ill with schizophrenia

We examined putative microglial activation as a function of illness course in schizophrenia. Microglial activity was quantified using [11C](R)-(1-[2-chrorophynyl]-N-methyl-N-[1-methylpropyl]-3 isoquinoline carboxamide (11C-(R)-PK11195) positron emission tomography (PET) in: (i) 10 individuals at ultra-high risk (UHR) of psychosis; (ii) 18 patients recently diagnosed with schizophrenia; (iii) 15 patients chronically ill with schizophrenia; and, (iv) 27 age-matched healthy controls. Regional-binding potential (BPND) was calculated using the simplified reference-tissue model with four alternative reference inputs. The UHR, recent-onset and chronic patient groups were compared to age-matched healthy control groups to examine between-group BPND differences in 6 regions: dorsal frontal, orbital frontal, anterior cingulate, medial temporal, thalamus and insula. Correlation analysis tested for BPND associations with gray matter volume, peripheral cytokines and clinical variables. The null hypothesis of equality in BPND between patients (UHR, recent-onset and chronic) and respective healthy control groups (younger and older) was not rejected for any group comparison or region. Across all subjects, BPND was positively correlated to age in the thalamus (r=0.43, P=0.008, false discovery rate). No correlations with regional gray matter, peripheral cytokine levels or clinical symptoms were detected. We therefore found no evidence of microglial activation in groups of individuals at high risk, recently diagnosed or chronically ill with schizophrenia. While the possibility of 11C-(R)-PK11195-binding differences in certain patient subgroups remains, the patient cohorts in our study, who also displayed normal peripheral cytokine profiles, do not substantiate the assumption of microglial activation in schizophrenia as a regular and defining feature, as measured by 11C-(R)-PK11195 BPND.

Alterations in prefrontal connectivity in schizophrenia assessed using diffusion magnetic resonance imaging

BACKGROUND

Spatial and biological characteristics of structural frontal disconnectivity in schizophrenia remain incompletely understood. Simultaneous streamline count (SC) and fractional anisotropy (FA) analyses may yield relevant complementary information to this end.

METHODS

Using 3T diffusion magnetic resonance imaging both SC and FA were calculated for the tracts linking lateral and medial subregions of prefrontal cortex (PFC) to cingulate, hippocampus, caudate and thalamus in 27 schizophrenia patients (14 first-episodes) and 27 controls. Relationships of these parameters with cognition, symptoms, treatment doses and illness duration were assessed where significant between-groups differences were detected.

RESULTS

Patients showed lower SC and FA in the tracts linking lateral and medial PFC to thalamus (likely corresponding to anterior thalamic peduncle) and lower FA in those linking PFC to caudate (likely through internal capsule), right caudal anterior cingulate and left hippocampus (likely corresponding to hippocampal-prefrontal pathway). Moreover, patients showed greater SC values for the tracts linking medial PFC and left caudal anterior cingulate. SC and FA values for the tracts linking PFC and caudal anterior cingulate were positively related to motor speed, executive function, problem solving and completed categories in WCST. FA for the tract linking right lateral PFC and caudate was directly related to positive symptoms and FA for the tract linking left medial PFC and left thalamus was inversely related to negative symptoms. Treatment doses were not associated with SC or FA values in any tract. Illness duration was negatively associated with SC and FA in the tracts linking PFC and subcortical areas.

CONCLUSIONS

Widespread alterations in frontal structural connectivity of PFC can be found in schizophrenia, and are related to cognition, symptoms and illness duration.

Structural brain changes in schizophrenia at different stages of the illness: A selective review of longitudinal magnetic resonance imaging studies

OBJECTIVE

Schizophrenia is a devastating mental disorder accompanied by aberrant structural brain connectivity. The question whether schizophrenia is a progressive brain disorder is yet to be resolved. Thus, it is not clear when these structural alterations occur and how they develop over time.

METHODS

In our selective review, we summarized recent findings from longitudinal magnetic resonance imaging studies investigating structural brain alterations and its impact on clinical outcome at different stages of the illness: (1) subjects at ultra-high risk of developing psychosis, (2) patients with a first episode psychosis, and (3) chronically ill patients. Moreover, we reviewed studies examining the longitudinal effects of medication on brain structure in patients with schizophrenia.

RESULTS

(1) Studies from pre-clinical stages to conversion showed a more pronounced cortical gray matter loss (i.e. superior temporal and inferior frontal regions) in those individuals who later made transition to psychosis. (2) Studies investigating patients with a first episode psychosis revealed a decline in multiple gray matter regions (i.e. frontal regions and thalamus) over time as well as progressive cortical thinning in the superior and inferior frontal cortex. (3) Studies focusing on patients with chronic schizophrenia showed that gray matter decreased to a greater extent (i.e. frontal and temporal areas, thalamus, and cingulate cortices)-especially in poor-outcome patients. Very few studies reported effects on white matter microstructure in the longitudinal course of the illness.

CONCLUSION

There is adequate evidence to suggest that schizophrenia is associated with progressive gray matter abnormalities particularly during the initial stages of illness. However, causal relationships between structural changes and illness course-especially in chronically ill patients-should be interpreted with caution. Findings might be confounded by longer periods of treatment and higher doses of antipsychotics or epiphenomena related to the illness.

Structural neuroimaging across early-stage psychosis: Aberrations in neurobiological trajectories and implications for the staging model

OBJECTIVE

This review critically examines the structural neuroimaging evidence in psychotic illness, with a focus on longitudinal imaging across the first-episode psychosis and ultra-high-risk of psychosis illness stages.

METHODS

A thorough search of the literature involving specifically longitudinal neuroimaging in early illness stages of psychosis was conducted. The evidence supporting abnormalities in brain morphology and altered neurodevelopmental trajectories is discussed in the context of a clinical staging model.

RESULTS

In general, grey matter (and, to a lesser extent, white matter) declines across multiple frontal, temporal (especially superior regions), insular and parietal regions during the first episode of psychosis, which has a steeper trajectory than that of age-matched healthy counterparts. Although the ultra-high-risk of psychosis literature is considerably mixed, evidence indicates that certain volumetric structural aberrations predate psychotic illness onset (e.g. prefrontal cortex thinning), while other abnormalities present in ultra-high-risk of psychosis populations are potentially non-psychosis-specific (e.g. hippocampal volume reductions).

CONCLUSION

We highlight the advantages of longitudinal designs, discuss the implications such studies have on clinical staging and provide directions for future research.

Multi-center machine learning in imaging psychiatry: A meta-model approach

One of the biggest problems in automated diagnosis of psychiatric disorders from medical images is the lack of sufficiently large samples for training. Sample size is especially important in the case of highly heterogeneous disorders such as schizophrenia, where machine learning models built on relatively low numbers of subjects may suffer from poor generalizability. Via multicenter studies and consortium initiatives researchers have tried to solve this problem by combining data sets from multiple sites. The necessary sharing of (raw) data is, however, often hindered by legal and ethical issues. Moreover, in the case of very large samples, the computational complexity might become too large. The solution to this problem could be distributed learning. In this paper we investigated the possibility to create a meta-model by combining support vector machines (SVM) classifiers trained on the local datasets, without the need for sharing medical images or any other personal data. Validation was done in a 4-center setup comprising of 480 first-episode schizophrenia patients and healthy controls in total. We built SVM models to separate patients from controls based on three different kinds of imaging features derived from structural MRI scans, and compared models built on the joint multicenter data to the meta-models. The results showed that the combined meta-model had high similarity to the model built on all data pooled together and comparable classification performance on all three imaging features. Both similarity and performance was superior to that of the local models. We conclude that combining models is thus a viable alternative that facilitates data sharing and creating bigger and more informative models.

Brain structure, function, and neurochemistry in schizophrenia and bipolar disorder-a systematic review of the magnetic resonance neuroimaging literature

Since Emil Kraepelin's conceptualization of endogenous psychoses as dementia praecox and manic depression, the separation between primary psychotic disorders and primary affective disorders has been much debated. We conducted a systematic review of case-control studies contrasting magnetic resonance imaging studies in schizophrenia and bipolar disorder. A literature search in PubMed of studies published between January 2005 and December 2016 was conducted, and 50 structural, 29 functional, 7 magnetic resonance spectroscopy, and 8 combined imaging and genetic studies were deemed eligible for systematic review. Structural neuroimaging studies suggest white matter integrity deficits that are consistent across the illnesses, while gray matter reductions appear more widespread in schizophrenia compared to bipolar disorder. Spectroscopy studies in cortical gray matter report evidence of decreased neuronal integrity in both disorders. Functional neuroimaging studies typically report similar functional architecture of brain networks in healthy controls and patients across the psychosis spectrum, but find differential extent of alterations in task related activation and resting state connectivity between illnesses. The very limited imaging-genetic literature suggests a relationship between psychosis risk genes and brain structure, and possible gene by diagnosis interaction effects on functional imaging markers. While the existing literature suggests some shared and some distinct neural markers in schizophrenia and bipolar disorder, it will be imperative to conduct large, well designed, multi-modal neuroimaging studies in medication-naïve first episode patients that will be followed longitudinally over the course of their illness in an effort to advance our understanding of disease mechanisms.

Predicting brain structure in population-based samples with biologically informed genetic scores for schizophrenia

Schizophrenia is associated with brain structural abnormalities including gray and white matter volume reductions. Whether these alterations are caused by genetic risk variants for schizophrenia is unclear. Previous attempts to detect associations between polygenic factors for schizophrenia and structural brain phenotypes in healthy subjects have been negative or remain non-replicated. In this study, we used genetic risk scores that were based on the accumulated effect of selected risk variants for schizophrenia belonging to specific biological systems like synaptic function, neurodevelopment, calcium signaling, and glutamatergic neurotransmission. We hypothesized that this "biologically informed" approach would provide the missing link between genetic risk for schizophrenia and brain structural phenotypes. We applied whole-brain voxel-based morphometry (VBM) analyses in two population-based target samples and subsequent regions of interest (ROIs) analyses in an independent replication sample (total N = 2725). No consistent association between the genetic scores and brain volumes were observed in the investigated samples. These results suggest that in healthy subjects with a higher genetic risk for schizophrenia additional factors apart from common genetic variants (e.g., infection, trauma, rare genetic variants, or gene-gene interactions) are required to induce structural abnormalities of the brain. Further studies are recommended to test for possible gene-gene or gene-environment effects. © 2017 Wiley Periodicals, Inc.

A neuroimaging study of emotion-cognition interaction in schizophrenia: the effect of ziprasidone treatment

Functional and structural brain changes associated with the cognitive processing of emotional visual stimuli were assessed in schizophrenic patients after 16 weeks of antipsychotic treatment with ziprasidone. Forty-five adults aged 18 to 40 were recruited: 15 schizophrenia patients (DSM-IV criteria) treated with ziprasidone (mean daily dose = 120 mg), 15 patients treated with other antipsychotics, and 15 healthy controls who did not receive any medication. Functional and structural neuroimaging data were acquired at baseline and 16 weeks after treatment initiation. In each session, participants selected stimuli, taken from standardized sets, based on their emotional valence. After ziprasidone treatment, several prefrontal regions, typically involved in cognitive control (anterior cingulate and ventrolateral prefrontal cortices), were significantly activated in patients in response to positive versus negative stimuli. This effect was greater whenever they had to select negative compared to positive stimuli, indicating an asymmetric effect of cognitive treatment of emotionally laden information. No such changes were observed for patients under other antipsychotics. In addition, there was an increase in the brain volume commonly recruited by healthy controls and patients under ziprasidone, in response to cognitive processing of emotional information. The structural analysis showed no significant changes in the density of gray and white matter in ziprasidone-treated patients compared to patients receiving other antipsychotic treatments. Our results suggest that functional changes in brain activity after ziprasidone medication precede structural and clinical manifestations, as markers that the treatment is efficient in restoring the functionality of prefrontal circuits involved in processing emotionally laden information in schizophrenia.

Neuroanatomical Predictors of Functional Outcome in Individuals at Ultra-High Risk for Psychosis

Most individuals at ultra-high risk (UHR) for psychosis do not transition to frank illness. Nevertheless, many have poor clinical outcomes and impaired psychosocial functioning. This study used voxel-based morphometry to investigate if baseline grey and white matter brain densities at identification as UHR were associated with functional outcome at medium- to long-term follow-up. Participants were help-seeking UHR individuals (n = 109, 54M:55F) who underwent magnetic resonance imaging at baseline; functional outcome was assessed an average of 9.2 years later. Primary analysis showed that lower baseline grey matter density, but not white matter density, in bilateral frontal and limbic areas, and left cerebellar declive were associated with poorer functional outcome (Social and Occupational Functioning Assessment Scale [SOFAS]). These findings were independent of transition to psychosis or persistence of the at-risk mental state. Similar regions were significantly associated with lower self-reported levels of social functioning and increased negative symptoms at follow-up. Exploratory analyses showed that lower baseline grey matter densities in middle and inferior frontal gyri were significantly associated with decline in Global Assessment of Functioning (GAF) score over follow-up. There was no association between baseline grey matter density and IQ or positive symptoms at follow-up. The current findings provide novel evidence that those with the poorest functional outcomes have the lowest grey matter densities at identification as UHR, regardless of transition status or persistence of the at-risk mental state. Replication and validation of these findings may allow for early identification of poor functional outcome and targeted interventions.

No Evidence of Association between Childhood Urban Environment and Cortical Thinning in Psychotic Disorder

Background

The alterations in cortical morphology, such as cortical thinning, observed in psychotic disorder, may be the outcome of interacting genetic and environmental effects. It has been suggested that urban upbringing may represent a proxy environmental effect impacting cortical thickness (CT). Therefore, the current study examined whether the association between group as a proxy genetic variable (patients with psychotic disorder [high genetic risk], healthy siblings of patients [intermediate risk] and healthy control subjects [average risk]) and CT was conditional on different levels of the childhood urban environment and whether this was sex-dependent.

Methods

T1-weighted MRI scans were acquired from 89 patients with a psychotic disorder, 95 non-psychotic siblings of patients with psychotic disorder and 87 healthy control subjects. Freesurfer software was used to measure CT. Developmental urban exposure was classified as low, medium, and high, reflecting the population density and the number of moves between birth and the 15^th birthday, using data from the Dutch Central Bureau of Statistics and the equivalent database in Belgium. Multilevel regression analyses were used to examine the association between group, sex, and urban upbringing (as well as their interactions) and cortical CT as the dependent variable.

Results

CT was significantly smaller in the patient group compared to the controls (B = -0.043, p <0.001), but not in the siblings compared to the controls (B = -0.013, p = 0.31). There was no main effect of developmental urbanicity on CT (B = 0.001, p = 0.91). Neither the three-way group × urbanicity × sex interaction (χ² = 3.73, p = 0.16), nor the two-way group × urbanicity interaction was significant (χ² = 0.51, p = 0.77).

Conclusion

The negative association between (familial risk for) psychotic disorder and CT was not moderated by developmental urbanicity, suggesting that reduced CT is not the outcome of familial sensitivity to the proxy environmental factor ‘urban upbringing’.

Biclustered Independent Component Analysis for Complex Biomarker and Subtype Identification from Structural Magnetic Resonance Images in Schizophrenia

Clinical and cognitive symptoms domain-based subtyping in schizophrenia (Sz) has been critiqued due to the lack of neurobiological correlates and heterogeneity in symptom scores. We, therefore, present a novel data-driven framework using biclustered independent component analysis to detect subtypes from the reliable and stable gray matter concentration (GMC) of patients with Sz. The developed methodology consists of the following steps: source-based morphometry (SBM) decomposition, selection and sorting of two component loadings, subtype component reconstruction using group information-guided ICA (GIG-ICA). This framework was applied to the top two group discriminative components namely the insula/superior temporal gyrus/inferior frontal gyrus (I-STG-IFG component) and the superior frontal gyrus/middle frontal gyrus/medial frontal gyrus (SFG-MiFG-MFG component) from our previous SBM study, which showed diagnostic group difference and had the highest effect sizes. The aggregated multisite dataset consisted of 382 patients with Sz regressed of age, gender, and site voxelwise. We observed two subtypes (i.e., two different subsets of subjects) each heavily weighted on these two components, respectively. These subsets of subjects were characterized by significant differences in positive and negative syndrome scale (PANSS) positive clinical symptoms (p = 0.005). We also observed an overlapping subtype weighing heavily on both of these components. The PANSS general clinical symptom of this subtype was trend level correlated with the loading coefficients of the SFG-MiFG-MFG component (r = 0.25; p = 0.07). The reconstructed subtype-specific component using GIG-ICA showed variations in voxel regions, when compared to the group component. We observed deviations from mean GMC along with conjunction of features from two components characterizing each deciphered subtype. These inherent variations in GMC among patients with Sz could possibly indicate the need for personalized treatment and targeted drug development.