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

A History of Psychosis in Bipolar Disorder is Associated With Gray Matter Volume Reduction

Psychotic symptoms are prevalent in schizophrenia, bipolar disorder, and other psychiatric and neurological disorders, yet the neurobiological underpinnings of psychosis remain obscure. In the last decade, a large number of magnetic resonance imaging studies have shown differences in local gray matter volume between patients with different psychiatric syndromes and healthy controls. Few studies have focused on the symptoms, which these syndromes are constituted of. Here, we test the association between psychosis and gray matter volume by using a sample of 167 subjects with bipolar disorder, with and without a history of psychosis, and 102 healthy controls. Magnetic resonance images were analyzed on group level using a voxel-wise mass univariate analysis (Voxel-Based Morphometry). We found that patients with a history of psychosis had smaller gray matter volume in left fusiform gyrus, the right rostral dorsolateral prefrontal cortex, and the left inferior frontal gyrus compared with patients without psychosis and with healthy controls. There was no volume difference in these areas between the no-psychosis group and healthy controls. These areas have previously been structurally and functionally coupled to delusions and hallucinations. Our finding adds further evidence to the probability of these regions as key areas in the development of psychotic symptoms.

Disrupted salience network functional connectivity and white-matter microstructure in persons at risk for psychosis: findings from the LYRIKS study

BACKGROUND

Salience network (SN) dysconnectivity has been hypothesized to contribute to schizophrenia. Nevertheless, little is known about the functional and structural dysconnectivity of SN in subjects at risk for psychosis. We hypothesized that SN functional and structural connectivity would be disrupted in subjects with At-Risk Mental State (ARMS) and would be associated with symptom severity and disease progression.

METHOD

We examined 87 ARMS and 37 healthy participants using both resting-state functional magnetic resonance imaging and diffusion tensor imaging. Group differences in SN functional and structural connectivity were examined using a seed-based approach and tract-based spatial statistics. Subject-level functional connectivity measures and diffusion indices of disrupted regions were correlated with CAARMS scores and compared between ARMS with and without transition to psychosis.

RESULTS

ARMS subjects exhibited reduced functional connectivity between the left ventral anterior insula and other SN regions. Reduced fractional anisotropy (FA) and axial diffusivity were also found along white-matter tracts in close proximity to regions of disrupted functional connectivity, including frontal-striatal-thalamic circuits and the cingulum. FA measures extracted from these disrupted white-matter regions correlated with individual symptom severity in the ARMS group. Furthermore, functional connectivity between the bilateral insula and FA at the forceps minor were further reduced in subjects who transitioned to psychosis after 2 years.

CONCLUSIONS

Our findings support the insular dysconnectivity of the proximal SN hypothesis in the early stages of psychosis. Further developed, the combined structural and functional SN assays may inform the prognosis of persons at-risk for psychosis.

Mind-wandering as spontaneous thought: a dynamic framework

Most research on mind-wandering has characterized it as a mental state with contents that are task unrelated or stimulus independent. However, the dynamics of mind-wandering - how mental states change over time - have remained largely neglected. Here, we introduce a dynamic framework for understanding mind-wandering and its relationship to the recruitment of large-scale brain networks. We propose that mind-wandering is best understood as a member of a family of spontaneous-thought phenomena that also includes creative thought and dreaming. This dynamic framework can shed new light on mental disorders that are marked by alterations in spontaneous thought, including depression, anxiety and attention deficit hyperactivity disorder.

The role of the ventro-lateral prefrontal cortex in idiom comprehension: An rTMS study

Previous research is equivocal with respect to the neural substrates of idiom processing. Particularly elusive is the role of the left ventro-lateral prefrontal cortex (VLPFC), a region implicated in semantic control generally. Although fMRI studies have shown that the left VLPFC is active during idiom processing (see Rapp et al. (2012), for review), rTMS studies have failed to corroborate a clear role of this prefrontal region (e.g., Oliveri et al., 2004). We investigated this issue using a semantic meaningfulness judgment task that compared idiom comprehension following rTMS-stimulation to the left VLPFC relative to a control site (vertex). We also investigated whether individual differences in general cognitive capacity among comprehenders modulated the effects of rTMS. The results indicate that left VLPFC stimulation particularly affected the processing of low-familiar idioms, possibly because these items involve a maximal semantic conflict between a salient literal and less-known figurative meaning. Of note, this pattern only emerged for comprehenders with higher cognitive control capacity, possibly because they were more likely to activate or maintain multiple semantic representations during idiom processing, which required VLPFC integrity. Taken together, the results support the importance of the left VLPFC to idiom processing.

Opportunities and Challenges for Psychiatry in the Connectomic Era

Most major psychiatric disorders arise from disturbances of anatomically distributed neural systems rather than isolated dysfunction of circumscribed brain regions. The past decade has witnessed rapid advances in our capacity to measure, map, and model neural connectivity in diverse species and at different resolution scales, from the level of individual neurons and synapses to large-scale systems spanning the entire brain. In this review, we consider how these techniques, when grounded in the theory and methods of network science, can contribute to a biological understanding of mental illness. We focus in particular on attempts to accurately map brain network disturbances in clinical populations and to model the mechanistic causes of these changes. This work suggests that pathology within highly connected hub regions is a consistent finding across a broad array of phenotypically diverse disorders, and that disparate changes in brain network organization can sometimes be explained by a surprisingly small and simple set of mechanisms.

Multi-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients

Structural Magnetic Resonance Imaging (MRI) studies have attempted to use brain measures obtained at the first-episode of psychosis to predict subsequent outcome, with inconsistent results. Thus, there is a real need to validate the utility of brain measures in the prediction of outcome using large datasets, from independent samples, obtained with different protocols and from different MRI scanners. This study had three main aims: 1) to investigate whether structural MRI data from multiple centers can be combined to create a machine-learning model able to predict a strong biological variable like sex; 2) to replicate our previous finding that an MRI scan obtained at first episode significantly predicts subsequent illness course in other independent datasets; and finally, 3) to test whether these datasets can be combined to generate multicenter models with better accuracy in the prediction of illness course. The multi-center sample included brain structural MRI scans from 256 males and 133 females patients with first episode psychosis, acquired in five centers: University Medical Center Utrecht (The Netherlands) (n=67); Institute of Psychiatry, Psychology and Neuroscience, London (United Kingdom) (n=97); University of São Paulo (Brazil) (n=64); University of Cantabria, Santander (Spain) (n=107); and University of Melbourne (Australia) (n=54). All images were acquired on 1.5-Tesla scanners and all centers provided information on illness course during a follow-up period ranging 3 to 7years. We only included in the analyses of outcome prediction patients for whom illness course was categorized as either "continuous" (n=94) or "remitting" (n=118). Using structural brain scans from all centers, sex was predicted with significant accuracy (89%; p<0.001). In the single- or multi-center models, illness course could not be predicted with significant accuracy. However, when reducing heterogeneity by restricting the analyses to male patients only, classification accuracy improved in some samples. This study provides proof of concept that combining multi-center MRI data to create a well performing classification model is possible. However, to create complex multi-center models that perform accurately, each center should contribute a sample either large or homogeneous enough to first allow accurate classification within the single-center.

Brain change trajectories that differentiate the major psychoses

BACKGROUND

Bipolar disorder and schizophrenia are highly heritable, often chronic and debilitating psychotic disorders that can be difficult to differentiate clinically. Their brain phenotypes appear to overlap in both cross-sectional and longitudinal structural neuroimaging studies, with some evidence to suggest areas of differentiation with differing trajectories. The aim of this review was to investigate the notion that longitudinal trajectories of alterations in brain structure could differentiate the two disorders.

DESIGN

Narrative review. We searched MEDLINE and Web of Science databases in May 2016 for studies that used structural magnetic resonance imaging to investigate longitudinal between-group differences in bipolar disorder and schizophrenia. Ten studies met inclusion criteria, namely longitudinal structural magnetic resonance studies comparing bipolar disorder (or affective psychosis) and schizophrenia within the same study.

RESULTS

Our review of these studies implicates illness-specific trajectories of morphological change in total grey matter volume, and in regions of the frontal, temporal and cingulate cortices. The findings in schizophrenia suggest a trajectory involving progressive grey matter loss confined to fronto-temporal cortical regions. Preliminary findings identify a similar but less severely impacted trajectory in a number of regions in bipolar disorder, however, bipolar disorder is also characterized by differential involvement across cingulate subregions.

CONCLUSION

The small number of available studies must be interpreted with caution but provide initial evidence supporting the notion that bipolar disorder and schizophrenia have differential longitudinal trajectories that are influenced by brain maturation.

Aberrant Functional Whole-Brain Network Architecture in Patients With Schizophrenia: A Meta-analysis

Findings from multiple lines of research provide evidence of aberrant functional brain connectivity in schizophrenia. By using graph-analytical measures, recent studies indicate that patients with schizophrenia exhibit changes in the organizational principles of whole-brain networks and that these changes relate to cognitive symptoms. However, there has not been a systematic investigation of functional brain network changes in schizophrenia to test the consistency of these changes across multiple studies. A comprehensive literature search was conducted to identify all available functional graph-analytical studies in patients with schizophrenia. Effect size measures were derived from each study and entered in a random-effects meta-analytical model. All models were tested for effects of potential moderator variables as well as for the presence of publication bias. The results of a total of n = 13 functional neuroimaging studies indicated that brain networks in patients with schizophrenia exhibit significant decreases in measures of local organization (g = -0.56, P = .02) and significant decreases in small-worldness (g = -0.65, P = .01) whereas global short communication paths seemed to be preserved (g = 0.26, P = .32). There was no evidence for a publication bias or moderator effects. The present meta- analysis demonstrates significant changes in whole brain network architecture associated with schizophrenia across studies.

Discriminative analysis of schizophrenia using support vector machine and recursive feature elimination on structural MRI images

Structural abnormalities in schizophrenia (SZ) patients have been well documented with structural magnetic resonance imaging (MRI) data using voxel-based morphometry (VBM) and region of interest (ROI) analyses. However, these analyses can only detect group-wise differences and thus, have a poor predictive value for individuals. In the present study, we applied a machine learning method that combined support vector machine (SVM) with recursive feature elimination (RFE) to discriminate SZ patients from normal controls (NCs) using their structural MRI data. We first employed both VBM and ROI analyses to compare gray matter volume (GMV) and white matter volume (WMV) between 41 SZ patients and 42 age- and sex-matched NCs. The method of SVM combined with RFE was used to discriminate SZ patients from NCs using significant between-group differences in both GMV and WMV as input features. We found that SZ patients showed GM and WM abnormalities in several brain structures primarily involved in the emotion, memory, and visual systems. An SVM with a RFE classifier using the significant structural abnormalities identified by the VBM analysis as input features achieved the best performance (an accuracy of 88.4%, a sensitivity of 91.9%, and a specificity of 84.4%) in the discriminative analyses of SZ patients. These results suggested that distinct neuroanatomical profiles associated with SZ patients might provide a potential biomarker for disease diagnosis, and machine-learning methods can reveal neurobiological mechanisms in psychiatric diseases.

Using human brain imaging studies as a guide toward animal models of schizophrenia

Schizophrenia is a heterogeneous and poorly understood mental disorder that is presently defined solely by its behavioral symptoms. Advances in genetic, epidemiological and brain imaging techniques in the past half century, however, have significantly advanced our understanding of the underlying biology of the disorder. In spite of these advances clinical research remains limited in its power to establish the causal relationships that link etiology with pathophysiology and symptoms. In this context, animal models provide an important tool for causally testing hypotheses about biological processes postulated to be disrupted in the disorder. While animal models can exploit a variety of entry points toward the study of schizophrenia, here we describe an approach that seeks to closely approximate functional alterations observed with brain imaging techniques in patients. By modeling these intermediate pathophysiological alterations in animals, this approach offers an opportunity to (1) tightly link a single functional brain abnormality with its behavioral consequences, and (2) to determine whether a single pathophysiology can causally produce alterations in other brain areas that have been described in patients. In this review we first summarize a selection of well-replicated biological abnormalities described in the schizophrenia literature. We then provide examples of animal models that were studied in the context of patient imaging findings describing enhanced striatal dopamine D2 receptor function, alterations in thalamo-prefrontal circuit function, and metabolic hyperfunction of the hippocampus. Lastly, we discuss the implications of findings from these animal models for our present understanding of schizophrenia, and consider key unanswered questions for future research in animal models and human patients.

Structural Brain Abnormalities in Youth With Psychosis Spectrum Symptoms

IMPORTANCE

Structural brain abnormalities are prominent in psychotic disorders, including schizophrenia. However, it is unclear when aberrations emerge in the disease process and if such deficits are present in association with less severe psychosis spectrum (PS) symptoms in youth.

OBJECTIVE

To investigate the presence of structural brain abnormalities in youth with PS symptoms.

DESIGN, SETTING, AND PARTICIPANTS

The Philadelphia Neurodevelopmental Cohort is a prospectively accrued, community-based sample of 9498 youth who received a structured psychiatric evaluation. A subsample of 1601 individuals underwent neuroimaging, including structural magnetic resonance imaging, at an academic and children's hospital health care network between November 1, 2009, and November 30, 2011.

MAIN OUTCOMES AND MEASURES

Measures of brain volume derived from T1-weighted structural neuroimaging at 3 T. Analyses were conducted at global, regional, and voxelwise levels. Regional volumes were estimated with an advanced multiatlas regional segmentation procedure, and voxelwise volumetric analyses were conducted as well. Nonlinear developmental patterns were examined using penalized splines within a general additive model. Psychosis spectrum (PS) symptom severity was summarized using factor analysis and evaluated dimensionally.

RESULTS

Following exclusions due to comorbidity and image quality assurance, the final sample included 791 participants aged youth 8 to 22 years. Fifty percent (n = 393) were female. After structured interviews, 391 participants were identified as having PS features (PS group) and 400 participants were identified as typically developing comparison individuals without significant psychopathology (TD group). Compared with the TD group, the PS group had diminished whole-brain gray matter volume (P = 1.8 × 10-10) and expanded white matter volume (P = 2.8 × 10-11). Voxelwise analyses revealed significantly lower gray matter volume in the medial temporal lobe (maximum z score = 5.2 and cluster size of 1225 for the right and maximum z score = 4.5 and cluster size of 310 for the left) as well as in frontal, temporal, and parietal cortex. Volumetric reduction in the medial temporal lobe was correlated with PS symptom severity.

CONCLUSIONS AND RELEVANCE

Structural brain abnormalities that have been commonly reported in adults with psychosis are present early in life in youth with PS symptoms and are not due to medication effects. Future longitudinal studies could use the presence of such abnormalities in conjunction with clinical presentation, cognitive profile, and genomics to predict risk and aid in stratification to guide early interventions.

Exome Sequence Data From Multigenerational Families Implicate AMPA Receptor Trafficking in Neurocognitive Impairment and Schizophrenia Risk

Schizophrenia is a mental disorder characterized by impairments in behavior, thought, and neurocognitive performance. We searched for susceptibility loci at a quantitative trait locus (QTL) previously reported for abstraction and mental flexibility (ABF), a cognitive function often compromised in schizophrenia patients and their unaffected relatives. Exome sequences were determined for 134 samples in 8 European American families from the original linkage study, including 25 individuals with schizophrenia or schizoaffective disorder. At chromosome 5q32-35.3, we analyzed 407 protein-altering variants for association with ABF and schizophrenia status. For replication, significant, Bonferroni-corrected findings were tested against cognitive traits in Mexican American families (n = 959), as well as interrogated for schizophrenia risk using GWAS results from the Psychiatric Genomics Consortium (PGC). From the gene SYNPO, rs6579797 (MAF = 0.032) shows significant associations with ABF (P = .015) and schizophrenia (P = .040), as well as jointly (P = .0027). In the Mexican American pedigrees, rs6579797 exhibits significant associations with IQ (P = .011), indicating more global effects on neurocognition. From the PGC results, other SYNPO variants were identified with near significant effects on schizophrenia risk, with a local linkage disequilibrium block displaying signatures of positive selection. A second missense variant within the QTL, rs17551608 (MAF = 0.19) in the gene WWC1, also displays a significant effect on schizophrenia in our exome sequences (P = .038). Remarkably, the protein products of SYNPO and WWC1 are interaction partners involved in AMPA receptor trafficking, a brain process implicated in synaptic plasticity. Our study reveals variants in these genes with significant effects on neurocognition and schizophrenia risk, identifying a potential pathogenic mechanism for schizophrenia spectrum disorders.

ERBB4 polymorphism and family history of psychiatric disorders on age-related cortical changes in healthy children

Genetic variations in ERBB4 were associated with increased susceptibility for schizophrenia (SCZ) and bipolar disorders (BPD). Structural imaging studies showed cortical abnormalities in adolescents and adults with SCZ or BPD. However, less is known about subclinical cortical changes or the influence of ERBB4 on cortical development. 971 healthy children (ages 3-20 years old; 462 girls and 509 boys) were genotyped for the ERBB4-rs7598440 variants, had structural MRI, and cognitive evaluation (NIH Toolbox ®). We investigated the effects of ERBB4 variants and family history of SCZ and/or BPD (FH) on cortical measures and cognitive performances across ages 3-20 years using a general additive model. Variations in ERBB4 and FH impact differentially the age-related cortical changes in regions often affected by SCZ and BPD. The ERBB4-TT-risk genotype children with no FH had subtle cortical changes across the age span, primarily located in the left temporal lobe and superior parietal cortex. In contrast, the TT-risk genotype children with FH had more pronounced age-related changes, mainly in the frontal lobes compared to the non-risk genotype children. Interactive effects of age, FH and ERBB4 variations were also found on episodic memory and working memory, which are often impaired in SCZ and BPD. Healthy children carrying the risk-genotype in ERBB4 and/or with FH had cortical measures resembling those reported in SCZ or BPD. These subclinical cortical variations may provide early indicators for increased risk of psychiatric disorders and improve our understanding of the effect of the NRG1-ERBB4 pathway on brain development.

Microglial activation and progressive brain changes in schizophrenia

Schizophrenia is a debilitating disorder that typically begins in adolescence and is characterized by perceptual abnormalities, delusions, cognitive and behavioural disturbances and functional impairments. While current treatments can be effective, they are often insufficient to alleviate the full range of symptoms. Schizophrenia is associated with structural brain abnormalities including grey and white matter volume loss and impaired connectivity. Recent findings suggest these abnormalities follow a neuroprogressive course in the earliest stages of the illness, which may be associated with episodes of acute relapse. Neuroinflammation has been proposed as a potential mechanism underlying these brain changes, with evidence of increased density and activation of microglia, immune cells resident in the brain, at various stages of the illness. We review evidence for microglial dysfunction in schizophrenia from both neuroimaging and neuropathological data, with a specific focus on studies examining microglial activation in relation to the pathology of grey and white matter. The studies available indicate that the link between microglial dysfunction and brain change in schizophrenia remains an intriguing hypothesis worthy of further examination. Future studies in schizophrenia should: (i) use multimodal imaging to clarify this association by mapping brain changes longitudinally across illness stages in relation to microglial activation; (ii) clarify the nature of microglial dysfunction with markers specific to activation states and phenotypes; (iii) examine the role of microglia and neurons with reference to their overlapping roles in neuroinflammatory pathways; and (iv) examine the impact of novel immunomodulatory treatments on brain structure in schizophrenia.

Revisiting the Basic Symptom Concept: Toward Translating Risk Symptoms for Psychosis into Neurobiological Targets

In its initial formulation, the concept of basic symptoms (BSs) integrated findings on the early symptomatic course of schizophrenia and first in vivo evidence of accompanying brain aberrations. It argued that the subtle subclinical disturbances in mental processes described as BSs were the most direct self-experienced expression of the underlying neurobiological aberrations of the disease. Other characteristic symptoms of psychosis (e.g., delusions and hallucinations) were conceptualized as secondary phenomena, resulting from dysfunctional beliefs and suboptimal coping styles with emerging BSs and/or concomitant stressors. While BSs can occur in many mental disorders, in particular affective disorders, a subset of perceptive and cognitive BSs appear to be specific to psychosis and are currently employed in two alternative risk criteria. However, despite their clinical recognition in the early detection of psychosis, neurobiological research on the aetiopathology of psychosis with neuroimaging methods has only just begun to consider the neural correlate of BSs. This perspective paper reviews the emerging evidence of an association between BSs and aberrant brain activation, connectivity patterns, and metabolism, and outlines promising routes for the use of BSs in aetiopathological research on psychosis.

Genome-wide significant linkage of schizophrenia-related neuroanatomical trait to 12q24

The insula and medial prefrontal cortex (mPFC) share functional, histological, transcriptional, and developmental characteristics, and they serve higher cognitive functions of theoretical relevance to schizophrenia and related disorders. Meta-analyses and multivariate analysis of structural magnetic resonance imaging (MRI) scans indicate that gray matter density and volume reductions in schizophrenia are the most consistent and pronounced in a network primarily composed of the insula and mPFC. We used source-based morphometry, a multivariate technique optimized for structural MRI, in a large sample of randomly ascertained pedigrees (N = 887) to derive an insula-mPFC component and to investigate its genetic determinants. Firstly, we replicated the insula-mPFC gray matter component as an independent source of gray matter variation in the general population, and verified its relevance to schizophrenia in an independent case-control sample. Secondly, we showed that the neuroanatomical variation defined by this component is largely determined by additive genetic variation (h(2)  = 0.59), and genome-wide linkage analysis resulted in a significant linkage peak at 12q24 (LOD = 3.76). This region has been of significant interest to psychiatric genetics as it contains the Darier's disease locus and other proposed susceptibility genes (e.g., DAO, NOS1), and it has been linked to affective disorders and schizophrenia in multiple populations. Thus, in conjunction with previous clinical studies, our data imply that one or more psychiatric risk variants at 12q24 are co-inherited with reductions in mPFC and insula gray matter concentration. © 2015 Wiley Periodicals, Inc.

Structural covariance in schizophrenia and first-episode psychosis: An approach based on graph analysis

Schizophrenia is a neurodevelopmental disorder that produces abnormalities across different brain regions. Measuring structural covariance with MRI is a well-established approach to investigate common changes in distinct systems. We investigated structural covariance in schizophrenia in a large Brazilian sample of individuals with chronic schizophrenia (n = 143), First Episode Psychosis (n = 32), and matched healthy controls (n = 82) using a combination of graph analysis and computational neuroanatomy. Firstly, we proposed the connectivity-closeness and integrity-closeness centrality measures and them compared healthy controls with chronic schizophrenia regarding these metrics. We then conducted a second analysis on the mapped regions comparing the pairwise difference between the three groups. Our results show that compared with controls, both patient groups (in pairwise comparisons) had a reduced integrity-closeness in pars orbitalis and insula, suggesting that the relationship between these areas and other brain regions is increased in schizophrenia. No differences were found between the First Episode Psychosis and Schizophrenia groups. Since in schizophrenia the brain is affected as a whole, this may mirror that these regions may be related to the generalized structural alteration seen in schizophrenia.

A Neuroanatomical Signature for Schizophrenia Across Different Ethnic Groups

Schizophrenia is a disabling clinical syndrome found across the world. While the incidence and clinical expression of this illness are strongly influenced by ethnic factors, it is unclear whether patients from different ethnicities show distinct brain deficits. In this multicentre study, we used structural Magnetic Resonance Imaging to investigate neuroanatomy in 126 patients with first episode schizophrenia who came from 4 ethnically distinct cohorts (White Caucasians, African-Caribbeans, Japanese, and Chinese). Each patient was individually matched with a healthy control of the same ethnicity, gender, and age (±1 year). We report a reduction in the gray matter volume of the right anterior insula in patients relative to controls (P < .05 corrected); this reduction was detected in all 4 ethnic groups despite differences in psychopathology, exposure to antipsychotic medication and image acquisition sequence. This finding provides evidence for a neuroanatomical signature of schizophrenia expressed above and beyond ethnic variations in incidence and clinical expression. In light of the existing literature, implicating the right anterior insula in bipolar disorder, depression, addiction, obsessive-compulsive disorder, and anxiety, we speculate that the neuroanatomical deficit reported here may represent a transdiagnostic feature of Axis I disorders.

Effects of oxytocin and genetic variants on brain and behaviour: Implications for treatment in schizophrenia

Impairments in social cognition and poor social functioning are core features of schizophrenia-spectrum disorders. In recent years, there has been a move towards developing new treatment strategies that specifically target social cognitive and social behavioural deficits. Oxytocin (OXT) is one such strategy that has gained increasing attention. There is a strong rationale for studying OXT in psychosis, from both an evolutionary perspective and neurodevelopmental-cognitive model of schizophrenia. Thus, the aim of this review was to critique and examine the observational and clinical oxytocin trial literature in schizophrenia-spectrum disorders. A handful of clinical trials suggest that OXT treatment may be beneficial for remediating social cognitive impairments, psychiatric symptoms, and improving social outcomes. However, inconsistencies exist in this literature, which may be explained by individual differences in the underlying neural response to OXT treatment and/or variation in the oxytocin and oxytocin receptor genes. Therefore, we additionally reviewed the evidence for structural and functional neural intermediate phenotypes in humans that link genetic variants to social behaviour/thinking, and discuss the implications of such interactions in the context of dysfunctional brain networks in schizophrenia. Factors that pose challenges for future OXT clinical research include the impact of age, sex, and ancestry, task-specific effects, bioavailability and pharmacokinetics, as well as neurotransmitter and drug interactions. While initial findings from OXT single dose/clinical trial studies are promising, more interdisciplinary research in both healthy and psychiatric populations is needed before determining whether OXT is a viable treatment option/adjunct for addressing poor illness outcomes in psychotic disorders.

Lack of Evidence for Regional Brain Volume or Cortical Thickness Abnormalities in Youths at Clinical High Risk for Psychosis: Findings From the Longitudinal Youth at Risk Study

There is cumulative evidence that young people in an "at-risk mental state" (ARMS) for psychosis show structural brain abnormalities in frontolimbic areas, comparable to, but less extensive than those reported in established schizophrenia. However, most available data come from ARMS samples from Australia, Europe, and North America while large studies from other populations are missing. We conducted a structural brain magnetic resonance imaging study from a relatively large sample of 69 ARMS individuals and 32 matched healthy controls (HC) recruited from Singapore as part of the Longitudinal Youth At-Risk Study (LYRIKS). We used 2 complementary approaches: a voxel-based morphometry and a surface-based morphometry analysis to extract regional gray and white matter volumes (GMV and WMV) and cortical thickness (CT). At the whole-brain level, we did not find any statistically significant difference between ARMS and HC groups concerning total GMV and WMV or regional GMV, WMV, and CT. The additional comparison of 2 regions of interest, hippocampal, and ventricular volumes, did not return any significant difference either. Several characteristics of the LYRIKS sample like Asian origins or the absence of current illicit drug use could explain, alone or in conjunction, the negative findings and suggest that there may be no dramatic volumetric or CT abnormalities in ARMS.

Childhood neglect predicts disorganization in schizophrenia through grey matter decrease in dorsolateral prefrontal cortex

OBJECTIVE

Psychosocial trauma during childhood is associated with schizophrenia vulnerability. The pattern of grey matter decrease is similar to brain alterations seen in schizophrenia. Our objective was to explore the links between childhood trauma, brain morphology and schizophrenia symptoms.

METHOD

Twenty-one patients with schizophrenia stabilized with atypical antipsychotic monotherapy and 30 healthy control subjects completed the study. Anatomical MRI images were analysed using optimized voxel-based morphometry (VBM). Childhood trauma was assessed with the Childhood Trauma Questionnaire, and symptoms were rated on the Scale for the Assessment of Negative Symptoms (SANS) and Scale for the Assessment of Positive Symptoms (SAPS) (disorganization, positive and negative symptoms). In the schizophrenia group, we used structural equation modelling in a path analysis.

RESULTS

Total grey matter volume was negatively associated with emotional neglect (EN) in patients with schizophrenia. Whole-brain VBM analyses of grey matter in the schizophrenia group revealed a specific inversed association between EN and the right dorsolateral prefrontal cortex (DLPFC). Path analyses identified a well-fitted model in which EN predicted grey matter density in DLPFC, which in turn predicted the disorganization score.

CONCLUSION

Our findings suggest that EN during childhood could have an impact on psychopathology in schizophrenia, which would be mediated by developmental effects on brain regions such as the DLPFC.

Patterns of Gray Matter Abnormalities in Schizophrenia Based on an International Mega-analysis

Analyses of gray matter concentration (GMC) deficits in patients with schizophrenia (Sz) have identified robust changes throughout the cortex. We assessed the relationships between diagnosis, overall symptom severity, and patterns of gray matter in the largest aggregated structural imaging dataset to date. We performed both source-based morphometry (SBM) and voxel-based morphometry (VBM) analyses on GMC images from 784 Sz and 936 controls (Ct) across 23 scanning sites in Europe and the United States. After correcting for age, gender, site, and diagnosis by site interactions, SBM analyses showed 9 patterns of diagnostic differences. They comprised separate cortical, subcortical, and cerebellar regions. Seven patterns showed greater GMC in Ct than Sz, while 2 (brainstem and cerebellum) showed greater GMC for Sz. The greatest GMC deficit was in a single pattern comprising regions in the superior temporal gyrus, inferior frontal gyrus, and medial frontal cortex, which replicated over analyses of data subsets. VBM analyses identified overall cortical GMC loss and one small cluster of increased GMC in Sz, which overlapped with the SBM brainstem component. We found no significant association between the component loadings and symptom severity in either analysis. This mega-analysis confirms that the commonly found GMC loss in Sz in the anterior temporal lobe, insula, and medial frontal lobe form a single, consistent spatial pattern even in such a diverse dataset. The separation of GMC loss into robust, repeatable spatial patterns across multiple datasets paves the way for the application of these methods to identify subtle genetic and clinical cohort effects.

Voxel-based morphometry for separation of schizophrenia from other types of psychosis in first episode psychosis

BACKGROUND

Schizophrenia is a psychiatric disorder which involves distortions in thought and perception, blunted affect, and behavioural disturbances. The longer psychosis goes unnoticed and untreated, the more severe the repercussions for relapse and recovery. There is some evidence that early intervention services can help, and diagnostic techniques that could contribute to early intervention may offer clinical utility in these situations. The index test being evaluated in this review is the structural magnetic resonance imaging (MRI) analysis technique known as voxel-based morphometry (VBM) that estimates the distribution of grey matter tissue volume across several brain regions. This review is an exploratory examination of the diagnostic 'potential' of VBM for use as an additional tool in the clinical examination of patients with first episode psychosis to establish whether an individual will progress on to developing schizophrenia as opposed to other types of psychosis.

OBJECTIVES

To determine whether VBM applied to the brain can be used to differentiate schizophrenia from other types of psychosis in participants who have received a clinical diagnosis of first episode psychosis.

SEARCH METHODS

In December 2013, we updated a previous search (May 2012) of MEDLINE, EMBASE, and PsycInfo using OvidSP.

SELECTION CRITERIA

We included retrospective and prospective studies that consecutively or randomly selected adolescent and adult participants (< 45 years) with a first episode of psychosis; and that evaluated the diagnostic accuracy of VBM for differentiating schizophrenia from other psychoses compared with a clinical diagnosis made by a qualified mental health professional, with or without the use of standard operational criteria or symptom checklists. We excluded studies in children, and in adult participants with organic brain disorders or who were at high risk for schizophrenia, such as people with a genetic predisposition.

DATA COLLECTION AND ANALYSIS

Two review authors screened all references for inclusion. We assessed the quality of studies using the QUADAS-2 instrument. Due to a lack of data, we were not able to extract 2 x 2 data tables for each study nor undertake any meta-analysis.

MAIN RESULTS

We included four studies with a total of 275 participants with first episode psychosis. VBM was not used to diagnose schizophrenia in any of the studies, instead VBM was used to quantify the magnitude of differences in grey matter volume. Therefore, none of the included studies reported data that could be used in the analysis, and we summarised the findings narratively for each study.

AUTHORS' CONCLUSIONS

There is no evidence to currently support diagnosing schizophrenia (as opposed to other psychotic disorders) using the pattern of brain changes seen in VBM studies in patients with first episode psychosis. VBM has the potential to discriminate between diagnostic categories but the methods to do this reliably are currently in evolution. In addition, the lack of applicability of the use of VBM to clinical practice in the studies to date limits the usefulness of VBM as a diagnostic aid to differentiate schizophrenia from other types of psychotic presentations in people with first episode of psychosis.

Schizophrenia: a tale of two critical periods for prefrontal cortical development

Schizophrenia is a disease of abnormal brain development. Considerable evidence now indicates that environmental factors have a causative role in schizophrenia. Elevated incidence of the disease has been linked to a wide range of disturbances in the prenatal environment and to social factors and drug intake during adolescence. Here we examine neurodevelopment of the prefrontal cortex in the first trimester of gestation and during adolescence to gain further insight into the neurodevelopmental processes that may be vulnerable in schizophrenia. Early embryonic development of the prefrontal cortex is characterized by cell proliferation, including renewal of progenitor cells, generation of early transient cell populations and neurogenesis of subcortical populations. Animal models show that curtailing early gestational cell proliferation produces schizophrenia-like pathology in the prefrontal cortex and mimics key behavioral and cognitive symptoms of the disease. At the other end of the spectrum, elimination of excitatory synapses is the fundamental process occurring during adolescent maturation in the prefrontal cortex. Adverse social situations that elevate stress increase dopamine stimulation of the mesocortical pathway and may lead to exaggerated synaptic pruning during adolescence. In a non-human primate model, dopamine hyperstimulation has been shown to decrease prefrontal pyramidal cell spine density and to be associated with profound cognitive dysfunction. Development of the prefrontal cortex in its earliest stage in gestation and in its final stage in adolescence represents two critical periods of vulnerability for schizophrenia in which cell proliferation and synaptic elimination, respectively, may be influenced by environmental factors.

Different and shared brain volume abnormalities in late- and early-onset schizophrenia

The differences in clinical characteristics between late- (LOS) and early-onset schizophrenia (EOS) are well documented. However, very little is known about the neural mechanisms underlying these differences. Here, we compared morphometric abnormalities between patients with EOS and those with LOS. A total of 22 patients with LOS, 24 patients with EOS and 41 healthy control subjects were included in this magnetic resonance imaging study. Brain images were analyzed using DARTEL preprocessing for voxel-based morphometry in SPM8. We tested a main effect of diagnosis in the whole-brain analysis and compared the results among the three groups. We also carried out correlation analyses between regional volumes and clinical variables. Patients with LOS showed larger gray matter (GM) volume of the left precuneus compared with healthy subjects and patients with EOS. Patients with LOS and EOS showed decreased GM volumes in the right insula, left superior temporal gyrus and left orbitofrontal gyrus compared with healthy subjects. A longer duration of illness was associated with reduced GM volume in the temporal pole in patients with EOS. Our findings may help improve our understanding of schizophrenia pathophysiology and shed light on the different and shared neurobiological underpinnings of LOS and EOS.

Cigarette smoking is associated with thinner cingulate and insular cortices in patients with severe mental illness

BACKGROUND

Magnetic resonance imaging (MRI) studies show reduced cortical thickness in patients with schizophrenia and bipolar disorder. These subtle brain abnormalities may provide insight into illness mechanisms. However, environmental and lifestyle-related factors, such as cigarette smoking, may contribute to brain structure changes. Cigarette smoking is highly prevalent in patients with severe mental illness. In nonpsychiatric samples, smoking has been associated with reduced thickness in the anterior (ACC) and posterior cingulate cortices, the insular cortex (INS), the dorsolateral prefrontal cortex and the orbitofrontal cortex.

METHODS

We examined MRI scans from patients with schizophrenia, other psychotic disorders or bipolar disorder and healthy controls using FreeSurfer.

RESULTS

We included 506 patients (49% smokers) and 237 controls (20% smokers) in our study. We found reduced cortical thickness in the left rostral ACC and the left INS in smoking patients compared with nonsmoking patients, but this difference was not found among healthy controls. No dose-response relationship was found between amount of smoking and cortical thickness in these regions. Among patients, maps of thickness along the whole cortical surface revealed reduced insular thickness but no effects in other regions. Among healthy controls, similar analyses revealed increased age-related cortical thinning in the left occipital lobe among smokers compared with nonsmokers.

LIMITATIONS

The causal direction could not be determined owing to the cross-sectional design and lack of detailed data on smoking addiction and smoking history.

CONCLUSION

The effect of cigarette smoking should be considered in MRI studies of patients with severe mental illness.

A systematic examination of brain volumetric abnormalities in recent-onset schizophrenia using voxel-based, surface-based and region-of-interest-based morphometric analyses

Background

Brain morphometric abnormalities in schizophrenia have been extensively reported in the literature. Whole-brain volumetric reductions are almost universally reported by most studies irrespective of the characteristics of the samples studied (e.g., chronic/recent-onset; medicated/neuroleptic-naïve etc.). However, the same cannot be said of the reported regional morphometric abnormalities in schizophrenia. While certain regional morphometric abnormalities are more frequently reported than others, there are no such abnormalities that are universally reported across studies. Variability of socio-demographic and clinical characteristics across study samples as well as technical and methodological issues related to acquisition and analyses of brain structural images may contribute to inconsistency of brain morphometric findings in schizophrenia. The objective of the present study therefore was to systematically examine brain morphometry in patients with recent-onset schizophrenia to find out if there are significant whole-brain or regional volumetric differences detectable at the appropriate significance threshold, after attempting to control for various confounding factors that could impact brain volumes.

Methods

Structural magnetic resonance images of 90 subjects (schizophrenia = 45; healthy subjects = 45) were acquired using a 3 Tesla magnet. Morphometric analyses were carried out following standard analyses pipelines of three most commonly used strategies, viz., whole-brain voxel-based morphometry, whole-brain surface-based morphometry, and between-group comparisons of regional volumes generated by automated segmentation and parcellation.

Results

In our sample of patients having recent-onset schizophrenia with limited neuroleptic exposure, there were no significant whole brain or regional brain morphometric abnormalities noted at the appropriate statistical significance thresholds with or without including age, gender and intracranial volume or total brain volume in the statistical analyses.

Conclusions

In the background of the conflicting findings in the literature, our findings indicate that brain morphometric abnormalities may not be directly related to the schizophrenia phenotype. Analysis of the reasons for the inconsistent results across studies as well as consideration of alternate sources of variability of brain morphology in schizophrenia such as epistatic and epigenetic mechanisms could perhaps advance our understanding of structural brain alterations in schizophrenia.

Electronic supplementary material

The online version of this article (doi:10.1186/s12952-015-0030-z) contains supplementary material, which is available to authorized users.

Detecting neuroimaging biomarkers for schizophrenia: a meta-analysis of multivariate pattern recognition studies

Multivariate pattern recognition approaches have recently facilitated the search for reliable neuroimaging-based biomarkers in psychiatric disorders such as schizophrenia. By taking into account the multivariate nature of brain functional and structural changes as well as their distributed localization across the whole brain, they overcome drawbacks of traditional univariate approaches. To evaluate the overall reliability of neuroimaging-based biomarkers, we conducted a comprehensive literature search to identify all studies that used multivariate pattern recognition to identify patterns of brain alterations that differentiate patients with schizophrenia from healthy controls. A bivariate random-effects meta-analytic model was implemented to investigate the sensitivity and specificity across studies as well as to assess the robustness to potentially confounding variables. In the total sample of n=38 studies (1602 patients and 1637 healthy controls), patients were differentiated from controls with a sensitivity of 80.3% (95% CI: 76.7-83.5%) and a specificity of 80.3% (95% CI: 76.9-83.3%). Analysis of neuroimaging modality indicated higher sensitivity (84.46%, 95% CI: 79.9-88.2%) and similar specificity (76.9%, 95% CI: 71.3-81.6%) of rsfMRI studies as compared with structural MRI studies (sensitivity: 76.4%, 95% CI: 71.9-80.4%, specificity of 79.0%, 95% CI: 74.6-82.8%). Moderator analysis identified significant effects of age (p=0.029), imaging modality (p=0.019), and disease stage (p=0.025) on sensitivity as well as of positive-to-negative symptom ratio (p=0.022) and antipsychotic medication (p=0.016) on specificity. Our results underline the utility of multivariate pattern recognition approaches for the identification of reliable neuroimaging-based biomarkers. Despite the clinical heterogeneity of the schizophrenia phenotype, brain functional and structural alterations differentiate schizophrenic patients from healthy controls with 80% sensitivity and specificity.

Brain structure correlates of emotion-based rash impulsivity

Negative urgency (the tendency to engage in rash, ill-considered action in response to intense negative emotions), is a personality trait that has been linked to problematic involvement in several risky and impulsive behaviours, and to various forms of disinhibitory psychopathology, but its neurobiological correlates are poorly understood. Here, we explored whether inter-individual variation in levels of trait negative urgency was associated with inter-individual variation in regional grey matter volumes. Using voxel-based morphometry (VBM) in a sample (n=152) of healthy participants, we found that smaller volumes of the dorsomedial prefrontal cortex and right temporal pole, regions previously linked to emotion appraisal, emotion regulation and emotion-based decision-making, were associated with higher levels of trait negative urgency. When controlling for other impulsivity linked personality traits (sensation seeking, lack of planning/perseverance) and negative emotionality per se (neuroticism), these associations remained, and an additional relationship was found between higher levels of trait negative urgency and smaller volumes of the left ventral striatum. This latter finding mirrors recent VBM findings in an animal model of impulsivity. Our findings offer novel insight into the brain structure correlates of one key source of inter-individual differences in impulsivity.

Grey matter, an endophenotype for schizophrenia? A voxel-based morphometry study in siblings of patients with schizophrenia

BACKGROUND

Grey matter, both volume and concentration, has been proposed as an endophenotype for schizophrenia given a number of reports of grey matter abnormalities in relatives of patients with schizophrenia. However, previous studies on grey matter abnormalities in relatives have produced inconsistent results. The aim of the present study was to examine grey matter differences between controls and siblings of patients with schizophrenia and to examine whether the age, genetic loading or subclinical psychotic symptoms of selected individuals could explain the previously reported inconsistencies.

METHODS

We compared the grey matter volume and grey matter concentration of healthy siblings of patients with schizophrenia and healthy controls matched for age, sex and education using voxel-based morphometry (VBM). Furthermore, we selected subsamples based on age (< 30 yr), genetic loading and subclinical psychotic symptoms to examine whether this would lead to different results.

RESULTS

We included 89 siblings and 69 controls in our study. The results showed that siblings and controls did not differ significantly on grey matter volume or concentration. Furthermore, specifically selecting participants based on age, genetic loading or subclinical psychotic symptoms did not alter these findings.

LIMITATIONS

The main limitation was that subdividing the sample resulted in smaller samples for the subanalyses. Furthermore, we used MRI data from 2 different scanner sites.

CONCLUSION

These results indicate that grey matter measured through VBM might not be a suitable endophenotype for schizophrenia.

The neuroanatomical basis of panic disorder and social phobia in schizophrenia: a voxel based morphometric study

Objective

It is known that there is a high prevalence of certain anxiety disorders among schizophrenic patients, especially panic disorder and social phobia. However, the neural underpinnings of the comorbidity of such anxiety disorders and schizophrenia remain unclear. Our study aims to determine the neuroanatomical basis of the co-occurrence of schizophrenia with panic disorder and social phobia.

Methods

Voxel-based morphometry was used in order to examine brain structure and to measure between-group differences, comparing magnetic resonance images of 20 anxious patients, 20 schizophrenic patients, 20 schizophrenic patients with comorbid anxiety, and 20 healthy control subjects.

Results

Compared to the schizophrenic patients, we observed smaller grey-matter volume (GMV) decreases in the dorsolateral prefrontal cortex and precentral gyrus in the schizophrenic-anxiety group. Additionally, the schizophrenic group showed significantly reduced GMV in the dorsolateral prefrontal cortex, precentral gyrus, orbitofrontal cortex, temporal gyrus and angular/inferior parietal gyrus when compared to the control group.

Conclusions

Our findings suggest that the comorbidity of schizophrenia with panic disorder and social phobia might be characterized by specific neuroanatomical and clinical alterations that may be related to maladaptive emotion regulation related to anxiety. Even thought our findings need to be replicated, our study suggests that the identification of neural abnormalities involved in anxiety, schizophrenia and schizophrenia-anxiety may lead to an improved diagnosis and management of these conditions.

Dissociation of anatomical and functional alterations of the default-mode network in first-episode, drug-naive schizophrenia

OBJECTIVE

Anatomical and functional alterations of the default-mode network (DMN) have been implicated in the pathophysiology of schizophrenia. However, no study is engaged to explore whether structural and functional abnormalities of the DMN overlap in schizophrenia. This study was undertaken to examine whether anatomical and functional abnormalities are present in similar or different brain regions of the DMN in first-episode, drug-naive schizophrenia.

METHODS

Forty-nine first-episode, drug-naive schizophrenia patients and 50 age-, sex-, and education-matched healthy controls underwent structural and resting-state functional magnetic resonance imaging (fMRI) scanning. The voxel-based morphometry (VBM) and fractional amplitude of low-frequency fluctuation (fALFF) methods were used to analyze imaging data.

RESULTS

The patients exhibited significantly decreased gray matter volume (GMV) in the left medial prefrontal cortex (orbital part) and increased fALFF in the left posterior cingulate cortex compared with the controls. No overlap of brain regions with anatomical and functional abnormalities was observed in the patient group. There was also no correlation between decreased GMV/increased fALFF and clinical variables in patients.

CONCLUSIONS

A dissociation pattern of brain regions with anatomical and functional changes within the DMN is revealed in schizophrenia patients.

SIGNIFICANCE

Our findings suggest that brain functional and anatomical abnormalities within the DMN might contribute independently to the pathophysiology of schizophrenia.

Brain differences in first-episode schizophrenia treated with quetiapine: a deformation-based morphometric study

RATIONALE

With the development of various imaging techniques, the deformation-based morphometry (DBM) method provides an objective automatic examination of the whole brain.

OBJECTIVES

This study aims to assess the abnormalities in the brains of first-episode schizophrenia (FES) patients treated with quetiapine using another advanced nonrigid registration method, hierarchical attribute matching mechanism for elastic registration, through the application of DBM in the entire brain.

METHODS

Thirty FES patients and 30 normal controls were grouped by age and handedness and subjected to magnetic resonance imaging examination. The patients had relatively short durations of untreated psychosis (DUP; 6.4 ± 5.2 months), and only a single antipsychotic drug, quetiapine (dosage, 200 ± 75 mg), was used for treatment. Statistically significant changes in regional volume were analyzed via DBM. In addition, a voxel-wise analysis of correlations between the duration of treatment or dosage and volume was also performed.

RESULTS

Compared with control subjects, FES patients showed contracted regions located in Brodmann area (BA) 42 and BA 19. By contrast, expanded regions were observed in BA 38, BA 21, BA 6 and 8, and left cerebellum. A negative correlation was observed between dosage and volume in the hippocampus, while a positive correlation was found in the caudate. Meanwhile, a negative correlation was observed between duration of treatment and volume in BA 38.

CONCLUSION

Both regional volume reductions and increases were detected in the brains of FES patients treated with quetiapine compared with healthy control subjects. Such differences may be partially relevant to dosage and treatment duration in clinic.

Neuropsychology, autobiographical memory, and hippocampal volume in "younger" and "older" patients with chronic schizophrenia

Despite a wide range of studies on neuropsychology in schizophrenia, autobiographical memory (AM) has been scarcely investigated in these patients. Hence, less is known about AM in older patients and hippocampal contribution to autobiographical memories of varying remoteness. Therefore, we investigated hippocampal volume and AM along with important neuropsychological domains in patients with chronic schizophrenia and the respective relationships between these parameters. We compared 25 older patients with chronic schizophrenia to 23 younger patients and an older healthy control group (N = 21) with respect to AM, additional neuropsychological parameters, and hippocampal volume. Personal episodic and semantic memory was investigated using a semi-structured interview. Additional neuropsychological parameters were assessed by using a battery of standard neuropsychological tests. Structural magnetic resonance imaging data were analyzed with an automated region-of-interest procedure. While hippocampal volume reduction and neuropsychological impairment were more pronounced in the older than in the younger patients, both groups showed equivalent reduced AM performance for recent personal episodes. In the patient group, significant correlations between left hippocampal volume and recent autobiographical episodes as well as personal semantic memories arose. Verbal memory and working memory were significantly correlated with right hippocampal volume; executive functions, however, were associated with bilateral hippocampal volumes. These findings underline the complexity of AM and its impairments in the course of schizophrenia in comparison to rather progressive neuropsychological deficits and address the importance of hippocampal contribution.

Joint Coupling of Awake EEG Frequency Activity and MRI Gray Matter Volumes in the Psychosis Dimension: A BSNIP Study

BACKGROUND

Many studies have examined either electroencephalogram (EEG) frequency activity or gray matter volumes (GMV) in various psychoses [including schizophrenia (SZ), schizoaffective (SZA), and psychotic bipolar disorder (PBP)]. Prior work demonstrated similar EEG and gray matter abnormalities in both SZ and PBP. Integrating EEG and GMV and jointly analyzing the combined data fully elucidates the linkage between the two and may provide better biomarker- or endophenotype-specificity for a particular illness. Joint exploratory investigations of EEG and GMV are scarce in the literature and the relationship between the two in psychosis is even less explored. We investigated a joint multivariate model to test whether the linear relationship or linkage between awake EEG (AEEG) frequency activity and GMV is abnormal across the psychosis dimension and if such effects are also present in first-degree relatives.

METHODS

We assessed 607 subjects comprising 264 probands [105 SZ, 72 SZA, and 87 PBP], 233 of their first degree relatives [82 SZ relatives (SZR), 71 SZA relatives (SZAR), and 80 PBP relatives (PBPR)], and 110 healthy comparison subjects (HC). All subjects underwent structural MRI (sMRI) and EEG scans. Frequency activity and voxel-based morphometric GMV were derived from EEG and sMRI data, respectively. Seven AEEG frequency and gray matter components were extracted using Joint independent component analysis (jICA). The loading coefficients (LC) were examined for group differences using analysis of covariance. Further, the LCs were correlated with psychopathology scores to identify relationship with clinical symptoms.

RESULTS

Joint ICA revealed a single component differentiating SZ from HC (p < 0.006), comprising increased posterior alpha activity associated with decreased volume in inferior parietal lobe, supramarginal, parahippocampal gyrus, middle frontal, inferior temporal gyri, and increased volume of uncus and culmen. No components were aberrant in either PBP or SZA or any relative group. No significant association was identified with clinical symptom measures.

CONCLUSION

Our data suggest that a joint EEG and GMV model yielded a biomarker specific to SZ, not abnormal in PBP or SZA. Alpha activity was related to both increased and decreased volume in different cortical structures. Additionally, the joint model failed to identify endophenotypes across psychotic disorders.

Decreased cortical thickness in drug naïve first episode schizophrenia: in relation to serum levels of BDNF

This study was to examine cortical thickness in drug naïve, first episode schizophrenia patients, and to explore its relationship with serum levels of brain-derived neurotrophic factor (BDNF). Forty-five drug naive schizophrenia patients and 28 healthy controls were enrolled in the study. Freesurfer was used to parcellate cortical regions, and vertex-wise group analysis was used for whole brain cortical thickness. The clusters for the brain regions that demonstrated group differences were extracted, and the mean values of thickness were calculated. Serum levels of BDNF were measured using enzyme-linked immunosorbent assay (ELISA). After controlling for age and gender, significantly thinner cortical thickness was found in left insula and superior temporal gyrus in the patient group compared with the healthy control group (HC group) (p's < 0.001). Lower serum levels of BDNF were also found in the patient group compared with the HC group (p = 0.001). Correlation analysis showed a significant positive relationship between thickness of left insula and serum levels of BDNF within the HC group (r = 0.396, p = 0.037) but there was no such relationship within the patient group (r = 0.035, p = 0.819). Cortical thinning is present in drug naïve, first episode schizophrenia patients, indicating neurodevelopmental abnormalities at the onset of schizophrenia. Left insula might be an imaging biomarker in detecting the impaired protective role of neurotrophic factor for the brain development in schizophrenia.

Bias in identification of the best treatment in a Bayesian network meta-analysis for binary outcome: a simulation study

Network meta-analysis (NMA) has emerged as a useful analytical tool allowing comparison of multiple treatments based on direct and indirect evidence. Commonly, a hierarchical Bayesian NMA model is used, which allows rank probabilities (the probability that each treatment is best, second best, and so on) to be calculated for decision making. However, the statistical properties of rank probabilities are not well understood. This study investigates how rank probabilities are affected by various factors such as unequal number of studies per comparison in the network, the sample size of individual studies, the network configuration, and effect sizes between treatments. In order to explore these factors, a simulation study of four treatments (three equally effective treatments and one less effective reference) was conducted. The simulation illustrated that estimates of rank probabilities are highly sensitive to both the number of studies per comparison and the overall network configuration. An unequal number of studies per comparison resulted in biased estimates of treatment rank probabilities for every network considered. The rank probability for the treatment that was included in the fewest number of studies was biased upward. Conversely, the rank of the treatment included in the most number of studies was consistently underestimated. When the simulation was altered to include three equally effective treatments and one superior treatment, the hierarchical Bayesian NMA model correctly identified the most effective treatment, regardless of all factors varied. The results of this study offer important insight into the ability of NMA models to rank treatments accurately under several scenarios. The authors recommend that health researchers use rank probabilities cautiously in making important decisions.

Salience processing and insular cortical function and dysfunction

The brain is constantly bombarded by stimuli, and the relative salience of these inputs determines which are more likely to capture attention. A brain system known as the 'salience network', with key nodes in the insular cortices, has a central role in the detection of behaviourally relevant stimuli and the coordination of neural resources. Emerging evidence suggests that atypical engagement of specific subdivisions of the insula within the salience network is a feature of many neuropsychiatric disorders.

The 4th Schizophrenia International Research Society Conference, 5-9 April 2014, Florence, Italy: a summary of topics and trends

The 4th Schizophrenia International Research Society Conference was held in Florence, Italy, April 5-9, 2014 and this year had as its emphasis, "Fostering Collaboration in Schizophrenia Research". Student travel awardees served as rapporteurs for each oral session, summarized the important contributions of each session and then each report was integrated into a final summary of data discussed at the entire conference by topic. It is hoped that by combining data from different presentations, patterns of interest will emerge and thus lead to new progress for the future. In addition, the following report provides an overview of the conference for those who were present, but could not participate in all sessions, and those who did not have the opportunity to attend, but who would be interested in an update on current investigations ongoing in the field of schizophrenia research.

No effect of schizophrenia risk genes MIR137, TCF4, and ZNF804A on macroscopic brain structure

Single nucleotide polymorphisms (SNPs) within the MIR137, TCF4, and ZNF804A genes show genome-wide association to schizophrenia. However, the biological basis for the associations is unknown. Here, we tested the effects of these genes on brain structure in 1300 healthy adults. Using volumetry and voxel-based morphometry, neither gene-wide effects--including the combined effect of the genes--nor single SNP effects--including specific psychosis risk SNPs--were found on total brain volume, grey matter, white matter, or hippocampal volume. These results suggest that the associations between these risk genes and schizophrenia are unlikely to be mediated via effects on macroscopic brain structure.

Decreased gray matter volume in the left middle temporal gyrus as a candidate biomarker for schizophrenia: a study of drug naive, first-episode schizophrenia patients and unaffected siblings

BACKGROUND

Studies have shown that patients with schizophrenia and their siblings share decreased gray matter (GM) volumes in certain brain regions, which may represent candidate endophenotypes of schizophrenia. However, the specificity and utility of these possible endophenotypes in relation to schizophrenia remain unclear.

METHODS

Twenty drug-naive, first-episode schizophrenia patients and 20 first-degree unaffected siblings from the same families as the patients (USS group), a separate group of 25 first-degree unaffected siblings of schizophrenia patients from other families (USO group), and 43 healthy controls were recruited. Voxel-based morphometry (VBM) was used to analyze structural imaging data.

RESULTS

The VBM analysis showed a significant difference in GM volume between the combined sibling group and the control group in the left middle temporal gyrus (MTG). Group comparison showed that the patients, the USS, and the USO had significantly decreased GM volume of the left MTG compared with the controls; such a difference did not exist among the patients and the two sibling groups. A receiver operating characteristic curve (ROC curve) analysis showed good predictive value of the mean cluster volume in the left MTG to distinguish patients, USS, and USO from healthy controls. There were no significant correlations between the mean cluster volume in the left MTG and clinical variables in the patients.

CONCLUSIONS

The GM volume decrease of the left MTG may be utilized as a candidate biomarker for schizophrenia. The novel design of including a USO group in our study enhances both the specificity and the heritability of the biomarker identified.

Grey-matter texture abnormalities and reduced hippocampal volume are distinguishing features of schizophrenia

Neurodevelopmental processes are widely believed to underlie schizophrenia. Analysis of brain texture from conventional magnetic resonance imaging (MRI) can detect disturbance in brain cytoarchitecture. We tested the hypothesis that patients with schizophrenia manifest quantitative differences in brain texture that, alongside discrete volumetric changes, may serve as an endophenotypic biomarker. Texture analysis (TA) of grey matter distribution and voxel-based morphometry (VBM) of regional brain volumes were applied to MRI scans of 27 patients with schizophrenia and 24 controls. Texture parameters (uniformity and entropy) were also used as covariates in VBM analyses to test for correspondence with regional brain volume. Linear discriminant analysis tested if texture and volumetric data predicted diagnostic group membership (schizophrenia or control). We found that uniformity and entropy of grey matter differed significantly between individuals with schizophrenia and controls at the fine spatial scale (filter width below 2mm). Within the schizophrenia group, these texture parameters correlated with volumes of the left hippocampus, right amygdala and cerebellum. The best predictor of diagnostic group membership was the combination of fine texture heterogeneity and left hippocampal size. This study highlights the presence of distributed grey-matter abnormalities in schizophrenia, and their relation to focal structural abnormality of the hippocampus. The conjunction of these features has potential as a neuroimaging endophenotype of schizophrenia.

Structural alterations of the social brain: a comparison between schizophrenia and autism

Autism spectrum disorder and schizophrenia share a substantial number of etiologic and phenotypic characteristics. Still, no direct comparison of both disorders has been performed to identify differences and commonalities in brain structure. In this voxel based morphometry study, 34 patients with autism spectrum disorder, 21 patients with schizophrenia and 26 typically developed control subjects were included to identify global and regional brain volume alterations. No global gray matter or white matter differences were found between groups. In regional data, patients with autism spectrum disorder compared to typically developed control subjects showed smaller gray matter volume in the amygdala, insula, and anterior medial prefrontal cortex. Compared to patients with schizophrenia, patients with autism spectrum disorder displayed smaller gray matter volume in the left insula. Disorder specific positive correlations were found between mentalizing ability and left amygdala volume in autism spectrum disorder, and hallucinatory behavior and insula volume in schizophrenia. Results suggest the involvement of social brain areas in both disorders. Further studies are needed to replicate these findings and to quantify the amount of distinct and overlapping neural correlates in autism spectrum disorder and schizophrenia.

The course of neuropsychological impairment and brain structure abnormalities in psychotic disorders

Neuropsychological impairment and abnormalities in brain structure are commonly observed in psychotic disorders, including schizophrenia and bipolar disorder. Shared deficits in neuropsychological functioning and abnormalities in brain structure suggest overlapping neuropathology between schizophrenia and bipolar disorder which has important implications for psychiatric nosology, treatment, and our understanding of the etiology of psychotic illnesses. However, the emergence and trajectory of brain dysfunction in psychotic disorders is less well understood. Differences in the course and progression of neuropsychological impairment and brain abnormalities among psychotic disorders may point to unique neuropathological processes. This article reviews the course of neuropsychological impairment and brain structure abnormalities in schizophrenia and bipolar disorder.

Alterations in cortical and extrastriatal subcortical dopamine function in schizophrenia: systematic review and meta-analysis of imaging studies

BACKGROUND

The hypothesis that cortical dopaminergic alterations underlie aspects of schizophrenia has been highly influential.

AIMS

To bring together and evaluate the imaging evidence for dopaminergic alterations in cortical and other extrastriatal regions in schizophrenia.

METHOD

Electronic databases were searched for in vivo molecular studies of extrastriatal dopaminergic function in schizophrenia. Twenty-three studies (278 patients and 265 controls) were identified. Clinicodemographic and imaging variables were extracted and effect sizes determined for the dopaminergic measures. There were sufficient data to permit meta-analyses for the temporal cortex, thalamus and substantia nigra but not for other regions.

RESULTS

The meta-analysis of dopamine D2/D3 receptor availability found summary effect sizes of d = -0.32 (95% CI -0.68 to 0.03) for the thalamus, d = -0.23 (95% CI -0.54 to 0.07) for the temporal cortex and d = 0.04 (95% CI -0.92 to 0.99) for the substantia nigra. Confidence intervals were wide and all included no difference between groups. Evidence for other measures/regions is limited because of the small number of studies and in some instances inconsistent findings, although significant differences were reported for D2/D3 receptors in the cingulate and uncus, for D1 receptors in the prefrontal cortex and for dopamine transporter availability in the thalamus.

CONCLUSIONS

There is a relative paucity of direct evidence for cortical dopaminergic alterations in schizophrenia, and findings are inconclusive. This is surprising given the wide influence of the hypothesis. Large, well-controlled studies in drug-naive patients are warranted to definitively test this hypothesis.