Neuroanatomical abnormalities in schizophrenia: a multimodal voxelwise meta-analysis and meta-regression analysis

Glutamate imaging (GluCEST) reveals lower brain GluCEST contrast in patients on the psychosis spectrum

Psychosis commonly develops in adolescence or early adulthood. Youths at clinical high risk (CHR) for psychosis exhibit similar, subtle symptoms to those with schizophrenia (SZ). Malfunctioning neurotransmitter systems, such as glutamate, are implicated in the disease progression of psychosis. Yet, in vivo imaging techniques for measuring glutamate across the cortex are limited. Here, we use a novel 7 Tesla MRI glutamate imaging technique (GluCEST) to estimate changes in glutamate levels across cortical and subcortical regions in young healthy individuals and ones on the psychosis spectrum. Individuals on the psychosis spectrum (PS; n=19) and healthy young individuals (HC; n=17) underwent MRI imaging at 3 and 7 T. At 7 T, a single slice GluCEST technique was used to estimate in vivo glutamate. GluCEST contrast was compared within and across the subcortex, frontal, parietal and occipital lobes. Subcortical (χ2 (1)=4.65, P=0.031) and lobular (χ2 (1)=5.17, P=0.023) GluCEST contrast levels were lower in PS compared with HC. Abnormal GluCEST contrast levels were evident in both CHR (n=14) and SZ (n=5) subjects, and correlated differentially, across regions, with clinical symptoms. Our findings describe a pattern of abnormal brain neurochemistry early in the course of psychosis. Specifically, CHR and young SZ exhibit diffuse abnormalities in GluCEST contrast attributable to a major contribution from glutamate. We suggest that neurochemical profiles of GluCEST contrast across cortex and subcortex may be considered markers of early psychosis. GluCEST methodology thus shows promise to further elucidate the progression of the psychosis disease state.

Functional changes of neural circuits in stroke patients with dysphagia: A meta-analysis

OBJECTIVE

Dysphagia is a common problem in stroke patients with unclear pathogenesis. Several recent functional magnetic resonance imaging (fMRI) studies had been carried out to explore the cerebral functional changes in dysphagic stroke patients. The aim of this study was to analysis these imaging findings using a meta-analysis.

METHODS

We used seed-based d mapping (SDM) to conduct a meta-analysis for dysphagic stroke patients prior to any kind of special treatment for dysphagia. A systematic search was conducted for the relevant studies. SDM meta-analysis method was used to examine regions of increased and decreased functional activation between dysphagic stroke patients and healthy controls.

RESULTS

Finally, six studies including 81 stroke patients with dysphagia and 78 healthy controls met the inclusion standards. When compared with healthy controls, stroke patients with dysphagia showed hyperactivation in left cingulate gyrus, left precentral gyrus and right posterior cingulate gyrus, and hypoactivation in right cuneus and left middle frontal gyrus.

CONCLUSIONS

The hyperactivity of precentral gyrus is crucial in stroke patients with dysphagia and may be associated with the severity of stroke. Besides the motor areas, the default-mode network regions (DMN) and affective network regions (AN) circuits are also involved in dysphagia after stroke.

Investigating the link between drug-naive first episode psychoses (FEPs), weight gain abnormalities and brain structural damages: Relevance and implications for therapy

Evidence suggests that obesity and overweight may be associated with severe brain structural abnormalities and poor cognitive and functional outcomes in the general population. Despite these observations and the high prevalence of weight gain abnormalities in patients with psychosis spectrum disorders (PSDs), no studies have investigated the impact that these metabolic disturbances may have on brain structures and development in the earliest stages of PSDs. In the present review we shed light on the association between weight gain and brain structural abnormalities that may affect the course of illness in drug-naïve FEPs. Given the lack of studies directly investigating this issue, we firstly identified and critically evaluated the literature assessing weight gain abnormalities and gray or white matter (GM, WM) volumes (either globally or in specific regions of interest) in otherwise healthy obese/overweight adolescents and young adults. We then compared the results of this systematic review with those of two recent meta-analysis investigating GM and WM abnormalities in drug-naïve FEPs. Weight gain in otherwise healthy subjects was consistently associated with frontal and temporal GM atrophy and with reduced integrity of WM in the corpus callosum. Of relevance, all these brain regions are affected in drug-naïve FEPs, and their integrity is associated with clinical, cognitive and functional outcomes. The underlying mechanisms that may explain the association between weight gain, adiposity, and brain damage in both healthy subjects and drug-naïve FEPs are widely discussed. On the basis of this knowledge, we tried: a) to deduce an integrative model for the development of obesity in psychosis spectrum disorders; b) to identify the key vulnerability factors underlying the association between weight gain and psychosis; c) to provide information on new potential targets of intervention.

Shared abnormality of white matter integrity in schizophrenia and bipolar disorder: A comparative voxel-based meta-analysis

Patients with schizophrenia and bipolar disorder (BD) shared a significant overlap in genetic susceptibility, pharmacological treatment responses, neuropsychological deficits, and epidemiological features. However, it remains unknown whether these clinical overlaps are mediated by shared or disorder-specific abnormalities of white matter integrity. In this voxel-based meta-analytic comparison of whole-brain white matter integrity, we aimed to identify the shared or disorder-specific structural abnormalities between schizophrenia and BD. A comprehensive literature search was conducted up to February 2016 to identify studies that compared between patients and healthy controls (HC) by using whole-brain diffusion approach (schizophrenia: 24 datasets with 754 patients vs. 775 HC; BD: 23 datasets with 705 patients vs. 679 HC). Voxel-wise meta-analyses were conducted and restricted to unified template using seed-based d-Mapping. Abnormal white matter integrity was calculated within each condition and a direct comparison of effect size was performed of alterations between two conditions. Two regions with significant reductions of fractional anisotropy (FA) characterized abnormal water diffusion in both disorders: the genu of the corpus callosum (CC) and posterior cingulum fibers. There was no significant difference found between the two disorders. Our results highlighted shared impairments of FA at genu of the CC and left posterior cingulum fibers, which suggests that, phenotypic overlap between schizophrenia and BD could be related to common brain circuit dysfunction.

Hemispheric lateralization abnormalities of the white matter microstructure in patients with schizophrenia and bipolar disorder

BACKGROUND

Hemispheric lateralization of the brain occurs during development and underpins specialized functions. It is posited that aberrant neurodevelopment leads to abnormal brain lateralization in individuals with psychotic illnesses. Here, we sought to examine whether white matter hemispheric lateralization is abnormal in individuals with the psychotic spectrum disorders of schizophrenia and bipolar disorder.

METHODS

We examined the white matter microstructure lateralization in patients with schizophrenia, bipolar disorder with psychotic features and healthy controls by measuring the laterality indices of fractional anisotropy (FA) and mean diffusivity (MD). We also correlated the laterality indices with clinical measures.

RESULTS

We included 150 patients with schizophrenia, 35 with bipolar disorder and 77 healthy controls in our analyses. Shared FA lateralization abnormalities in patients with schizophrenia and bipolar disorder were found in the cerebral peduncle and posterior limb of internal capsule, with more extensive abnormalities in patients with bipolar disorder than in those with schizophrenia. The shared MD lateralization abnormalities were more widespread, extending to the subcortical, frontal-occipital, limbic and callosal tracts, with patients with bipolar disorder showing greater abnormalities than patients with schizophrenia. While lateralization was decreased in patients with schizophrenia, the lateralization was reversed in those with bipolar disorder, underpinned by the more pronounced microstructural abnormalities in the right hemisphere. The loss of FA lateralization in patients with schizophrenia was associated with lower quality of life and psychosocial functioning.

LIMITATIONS

Owing to the cross-sectional study design, we cannot confirm whether the lateralization abnormalities are neurodevelopmental or a consequence of psychosis onset or chronicity.

CONCLUSION

Shared and distinct white matter lateralization abnormalities were found in patients with schizophrenia and bipolar disorder. In distinct regions of abnormalities, the lateralization was attenuated in patients with schizophrenia and reversed in those with bipolar disorder.

Neural Correlates of Outcome of the Psychotherapy Compared to Antidepressant Therapy in Anxiety and Depression Disorders: A Meta-Analysis

The most prevalent mental disorders, anxiety and depression, are commonly associated with structural and functional changes in the fronto-limbic brain areas. The clinical trials investigating patients with affective disorders showed different outcome to different treatments such as psychotherapy or pharmacotherapy. It is, however, still unexplored how these interventions approach affect the functional brain. This meta-analysis aims to compare the effects of psychotherapy compared to antidepressant therapy on functional brain activity in anxiety and depression disorders. Twenty-one samples with psychotherapy and seventeen samples with antidepressant therapy were included. The main finding showed an inverse effect of the two treatments on the right paracingulate activity. The patients undergoing psychotherapy showed an increase in the right paracingulate activity while pharmacological treatment led to a decrease of activation of this area. This finding seems to support the recent studies that hypothesize how psychotherapy, through the self-knowledge and the meaning processing, involves a top-down emotional regulation.

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.

White matter integrity and symptom dimensions of schizophrenia: A diffusion tensor imaging study

Impaired fiber bundle connectivity between brain regions is a key neuropathological finding in schizophrenia. Symptom dimensions in schizophrenia can be clustered into factor models. Single syndromes have been related to grey and white matter brain structure alterations. We associated all core syndromes of schizophrenia in a single patient group with changes in white matter integrity. Diffusion weighted images (3T MRI) and SAPS/SANS scores were measured in 26 male patients and 26 healthy controls. First, group differences in fractional anisotropy (FA) were calculated with TBSS. Second, core symptom dimensions of schizophrenia were correlated with FA within these altered tracts. We found differences between groups in nine white matter tracts. Hallucinations were positively correlated with FA in the left uncinate fasciculus and left corticospinal tract. Ego-disturbances (passivity phenomena) showed a positive correlation with FA in the right anterior thalamic radiation. Positive formal thought disorders (FTD) corresponded negatively with FA in the right cingulum bundle. Negative symptoms were positively associated with the right anterior thalamic radiation and negatively with the right ventral cingulum bundle. For the first time, we analyzed the whole range of psychopathological factors in one schizophrenia patient group. We could validate our novel results for positive FTD and passivity phenomena by replicating findings for hallucinations and negative symptoms. Only those brain circuits which are most vulnerable at a given time during neurodevelopment are affected by a particular pathological impact (genetic, environmental). This scenario could explain the predominance of particular psychopathological syndromes related to specific white matter anomalies.

Functional brain networks in treatment-resistant schizophrenia

INTRODUCTION

Up to 20% of individuals with schizophrenia show minimal or no response to medication and are considered to have 'treatment-resistant' schizophrenia (TRS). Unlike early and established schizophrenia, few studies have investigated resting-state functional connectivity (rs-FC) in TRS. Here, we test for disruptions in FC and altered efficiency of functional brain networks in a well-characterized cohort of TRS patients.

METHODS

Resting-state functional magnetic resonance imaging was used to investigate functional brain networks in 42 TRS participants prescribed clozapine (30 males, mean age=41.3(10)) and 42 healthy controls (24 males, mean age=38.4(10)). Graph analysis was used to characterize between-group differences in local and global efficiency of functional brain network organization as well as the strength of FC.

RESULTS

Global brain FC was reduced in TRS patients (p=0.0001). Relative to controls, 3.4% of all functional connections showed reduced strength in TRS (p<0.001), predominantly involving fronto-temporal, fronto-occipital and temporo-occipital connections. Global efficiency was reduced in TRS (p=0.0015), whereas local efficiency was increased (p=0.0042).

CONCLUSIONS

TRS is associated with widespread reductions in rs-FC and altered network topology. Increased local functional network efficiency coupled with decreased global efficiency suggests that hub-to-hub connections are preferentially affected in TRS. These findings further our understanding of the neurobiological impairments in TRS.

Schizophrenia symptomatic associations with diffusion tensor imaging measured fractional anisotropy of brain: a meta-analysis

PURPOSE

Several studies have examined the relationships between diffusion tensor imaging (DTI)-measured fractional anisotropy (FA) and the symptoms of schizophrenia, but results vary across the studies. The aim of this study was to carry out a meta-analysis of correlation coefficients reported by relevant studies to evaluate the correlative relationships between FA of various parts of the brain and schizophrenia symptomatic assessments.

METHODS

Literature was searched in several electronic databases, and study selection was based on précised eligibility criteria. Correlation coefficients between FA of a part of the brain and schizophrenia symptom were first converted into Fisher's z-scores for meta-analyses, and then overall effect sizes were back transformed to correlation coefficients.

RESULTS

Thirty-three studies (1121 schizophrenia patients; age 32.66 years [95% confidence interval (CI) 30.19, 35.13]; 65.95 % [57.63, 74.28] males) were included in this meta-analysis. Age was inversely associated with brain FA (z-scores [95% CI] -0.23 [-0.14, -0.32]; p ˂ 0.00001). Brain FA of various areas was inversely associated with negative symptoms of schizophrenia (z-score -0.30 [-0.23, -0.36]; p ˂ 0.00001) but was positively associated with positive symptoms of schizophrenia (z-score 0.16 [0.04, 0.27]; p = 0.007) and general psychopathology of schizophrenia (z-score 0.26 [0.15, 0.37]; p = 0.00001).

CONCLUSION

Although, DTI-measured brain FA is found to be inversely associated with negative symptoms and positively associated with positive symptoms and general psychopathology of schizophrenia, the effect sizes of these correlations are low and may not be clinically significant. Moreover, brain FA was also negatively associated with age of patients.

Inferring pathobiology from structural MRI in schizophrenia and bipolar disorder: Modeling head motion and neuroanatomical specificity

Despite over 400 peer-reviewed structural MRI publications documenting neuroanatomic abnormalities in bipolar disorder and schizophrenia, the confounding effects of head motion and the regional specificity of these defects are unclear. Using a large cohort of individuals scanned on the same research dedicated MRI with broadly similar protocols, we observe reduced cortical thickness indices in both illnesses, though less pronounced in bipolar disorder. While schizophrenia (n = 226) was associated with wide-spread surface area reductions, bipolar disorder (n = 227) and healthy comparison subjects (n = 370) did not differ. We replicate earlier reports that head motion (estimated from time-series data) influences surface area and cortical thickness measurements and demonstrate that motion influences a portion, but not all, of the observed between-group structural differences. Although the effect sizes for these differences were small to medium, when global indices were covaried during vertex-level analyses, between-group effects became nonsignificant. This analysis raises doubts about the regional specificity of structural brain changes, possible in contrast to functional changes, in affective and psychotic illnesses as measured with current imaging technology. Given that both schizophrenia and bipolar disorder showed cortical thickness reductions, but only schizophrenia showed surface area changes, and assuming these measures are influenced by at least partially unique sets of biological factors, then our results could indicate some degree of specificity between bipolar disorder and schizophrenia. Hum Brain Mapp 38:3757-3770, 2017. © 2017 Wiley Periodicals, Inc.

Evaluation of machine learning algorithms and structural features for optimal MRI-based diagnostic prediction in psychosis

A relatively large number of studies have investigated the power of structural magnetic resonance imaging (sMRI) data to discriminate patients with schizophrenia from healthy controls. However, very few of them have also included patients with bipolar disorder, allowing the clinically relevant discrimination between both psychotic diagnostics. To assess the efficacy of sMRI data for diagnostic prediction in psychosis we objectively evaluated the discriminative power of a wide range of commonly used machine learning algorithms (ridge, lasso, elastic net and L0 norm regularized logistic regressions, a support vector classifier, regularized discriminant analysis, random forests and a Gaussian process classifier) on main sMRI features including grey and white matter voxel-based morphometry (VBM), vertex-based cortical thickness and volume, region of interest volumetric measures and wavelet-based morphometry (WBM) maps. All possible combinations of algorithms and data features were considered in pairwise classifications of matched samples of healthy controls (N = 127), patients with schizophrenia (N = 128) and patients with bipolar disorder (N = 128). Results show that the selection of feature type is important, with grey matter VBM (without data reduction) delivering the best diagnostic prediction rates (averaging over classifiers: schizophrenia vs. healthy 75%, bipolar disorder vs. healthy 63% and schizophrenia vs. bipolar disorder 62%) whereas algorithms usually yielded very similar results. Indeed, those grey matter VBM accuracy rates were not even improved by combining all feature types in a single prediction model. Further multi-class classifications considering the three groups simultaneously made evident a lack of predictive power for the bipolar group, probably due to its intermediate anatomical features, located between those observed in healthy controls and those found in patients with schizophrenia. Finally, we provide MRIPredict (https://www.nitrc.org/projects/mripredict/), a free tool for SPM, FSL and R, to easily carry out voxelwise predictions based on VBM images.

White Matter Disruptions in Schizophrenia Are Spatially Widespread and Topologically Converge on Brain Network Hubs

White matter abnormalities associated with schizophrenia have been widely reported, although the consistency of findings across studies is moderate. In this study, neuroimaging was used to investigate white matter pathology and its impact on whole-brain white matter connectivity in one of the largest samples of patients with schizophrenia. Fractional anisotropy (FA) and mean diffusivity (MD) were compared between patients with schizophrenia or schizoaffective disorder (n = 326) and age-matched healthy controls (n = 197). Between-group differences in FA and MD were assessed using voxel-based analysis and permutation testing. Automated whole-brain white matter fiber tracking and the network-based statistic were used to characterize the impact of white matter pathology on the connectome and its rich club. Significant reductions in FA associated with schizophrenia were widespread, encompassing more than 40% (234ml) of cerebral white matter by volume and involving all cerebral lobes. Significant increases in MD were also widespread and distributed similarly. The corpus callosum, cingulum, and thalamic radiations exhibited the most extensive pathology according to effect size. More than 50% of cortico-cortical and cortico-subcortical white matter fiber bundles comprising the connectome were disrupted in schizophrenia. Connections between hub regions comprising the rich club were disproportionately affected. Pathology did not differ between patients with schizophrenia and schizoaffective disorder and was not mediated by medication. In conclusion, although connectivity between cerebral hubs is most extensively disturbed in schizophrenia, white matter pathology is widespread, affecting all cerebral lobes and the cerebellum, leading to disruptions in the majority of the brain's fiber bundles.

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.

Characterization of brain blood flow and the amplitude of low-frequency fluctuations in major depressive disorder: A multimodal meta-analysis

BACKGROUND

In healthy subjects, there is an association between amplitude of low-frequency fluctuations (ALFF) and regional cerebral blood flow (rCBF). To date, no published meta-analysis has investigated changes in the regional ALFF in medication-free depressed patients.

METHODS

In this study, we aimed to explore whether resting-state rCBF and ALFF changes co-occur in the depressed brain without the potential confound of medication. Using signed differential mapping (SDM), we conducted two meta-analyses, one of rCBF studies and one of ALFF studies, involving medication-free patients with major depressive disorder (MDD). In addition, we conducted a multimodal meta-analysis to identify brain regions that showed abnormalities in both rCBF and ALFF.

RESULTS

A total of 16 studies were included in this series. We identified abnormalities in resting-state rCBF and ALFF in the left insula in medication-free MDD patients compared with healthy controls (HC). In addition, we observed altered resting-state rCBF in the limbic-subcortical-cortical circuit and altered ALFF in the default mode network (DMN) and some motor-related brain regions.

LIMITATIONS

The analysis techniques, patient characteristics and clinical variables of the included studies were heterogeneous.

CONCLUSIONS

The conjoint alterations in ALFF and rCBF in the left insula may represent core neuropathological changes in medication-free patients with MDD and merit further studying.

Precuneus functioning differentiates first-episode psychosis patients during the fantasy movie Alice in Wonderland

BACKGROUND

While group-level functional alterations have been identified in many brain regions of psychotic patients, multivariate machine-learning methods provide a tool to test whether some of such alterations could be used to differentiate an individual patient. Earlier machine-learning studies have focused on data collected from chronic patients during rest or simple tasks. We set out to unravel brain activation patterns during naturalistic stimulation in first-episode psychosis (FEP).

METHOD

We recorded brain activity from 46 FEP patients and 32 control subjects viewing scenes from the fantasy film Alice in Wonderland. Scenes with varying degrees of fantasy were selected based on the distortion of the 'sense of reality' in psychosis. After cleaning the data with a novel maxCorr method, we used machine learning to classify patients and healthy control subjects on the basis of voxel- and time-point patterns.

RESULTS

Most (136/194) of the voxels that best classified the groups were clustered in a bilateral region of the precuneus. Classification accuracies were up to 79.5% (p = 5.69 × 10-8), and correct classification was more likely the higher the patient's positive-symptom score. Precuneus functioning was related to the fantasy content of the movie, and the relationship was stronger in control subjects than patients.

CONCLUSIONS

These findings are the first to show abnormalities in precuneus functioning during naturalistic information processing in FEP patients. Correlational findings suggest that these alterations are associated with positive psychotic symptoms and processing of fantasy. The results may provide new insights into the neuronal basis of reality distortion in psychosis.

Progressive deterioration of thalamic nuclei relates to cortical network decline in schizophrenia

Thalamic abnormalities are considered part of the complex pathophysiology of schizophrenia, particularly the involvement of specific thalamic nuclei. The goals of this study were to: introduce a novel atlas-based parcellation scheme for defining various thalamic nuclei; compare their integrity in a schizophrenia sample against healthy individuals at baseline and follow-up time points, as well as rates of change over time; examine relationships between the nuclei and abnormalities in known connected cortical regions; and finally, to determine if schizophrenia-related thalamic nuclei changes relate to cognitive functioning and clinical symptoms. Subjects were from a larger longitudinal 2-year follow-up study, schizophrenia (n=20) and healthy individuals (n=20) were group-matched for age, gender, and recent-alcohol use. We used high-dimensional brain mapping to obtain thalamic morphology, and applied a novel atlas-based method for delineating anterior, mediodorsal, and pulvinar nuclei. Results from cross sectional GLMs revealed group differences in bilateral mediodorsal and anterior nuclei, while longitudinal models revealed significant group-by-time interactions for the mediodorsal and pulvinar nuclei. Cortical correlations were the strongest for the pulvinar in frontal, temporal and parietal regions, followed by the mediodorsal nucleus in frontal regions, but none in the anterior nucleus. Thalamic measures did not correlate with cognitive and clinical scores at any time point or longitudinally. Overall, findings revealed a pattern of persistent progressive abnormalities in thalamic nuclei that relate to advancing cortical decline in schizophrenia, but not with measures of behavior.

Common pattern of gray-matter abnormalities in drug-naive and medicated first-episode schizophrenia: a multimodal meta-analysis

Studies of schizophrenia at drug-naive state and on antipsychotic medication have reported a number of regions of gray-matter (GM) abnormalities but the reports have been inconsistent. The aim of this study was to conduct multimodal meta-analysis to compare the cross-sectional voxel-based morphometry studies of brain GM in antipsychotic-naive first-episode schizophrenia (AN-FES) and those with antipsychotic treatment within 1 year (AT-FES) to determine the similarities and differences in these groups. We conducted two separate meta-analyses containing 24 studies with a sample size of 801 patients and 957 healthy controls. A multimodal meta-analysis method was used to compare the findings between AN-FES and AT-FES. Meta-regression analyses were done to determine the influence of different variables including age, duration of illness, and positive and negative symptom scores. Finally, jack-knife analyses were done to test the robustness of the results. AN-FES and AT-FES showed common patterns of GM abnormalities in frontal (gyrus rectus), superior temporal, left hippocampal and insular cortex. GM in the left supramarginal gyrus and left middle temporal gyrus were found to be increased in AN-FES but decreased in AT-FES, whereas left median cingulate/paracingulate gyri and right hippocampus GM was decreased in AN-FES but increased in AT-FES. Findings suggest that both AN-FES and AT-FES share frontal, temporal and insular regions as common anatomical regions to be affected indicating these to be the primary regions of GM abnormalities in both groups.

ENIGMA and the individual: Predicting factors that affect the brain in 35 countries worldwide

In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) - a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date - of schizophrenia and major depression - ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others¹, ENIGMA's genomic screens - now numbering over 30,000 MRI scans - have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants - and genetic variants in general - may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures - from tens of thousands of people - that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far.

Detection of Glutamate Alterations in the Human Brain Using 1H-MRS: Comparison of STEAM and sLASER at 7 T

PURPOSE

To assess reproducibility of glutamate measurement in the human brain by two short echo time (TE) ¹H-MRS sequences [stimulated echo acquisition mode (STEAM) and semi-localized by adiabatic selective refocusing (sLASER)] at 7 T. Reliable assessment of glutamate is important when studying a variety of neurological and neuropsychiatric disorders. At 7 T, the glutamate signal can be separated from the glutamine signal and hence more accurately measured as compared to lower field strengths. A sLASER sequence has been developed for 7 T, using field focusing at short TE, resulting in twice as much signal as can be obtained using STEAM and improved localization accuracy due to a decreased chemical shift artifact.

MATERIALS AND METHODS

Eight subjects were scanned twice using both STEAM and sLASER. Data were acquired from the frontal and occipital brain region. Subsequently, intraclass correlations were computed for the estimated metabolite concentrations.

RESULTS

sLASER has higher ICC's for glutamate concentration as compared to STEAM in both the frontal and occipital VOI, which is probably due to the higher sensitivity and localization accuracy.

CONCLUSION

We conclude that sLASER ¹H-MRS at 7 T is a reliable method to obtain reproducible measures of glutamate levels in the human brain at such high accuracy that individual variability, even between age-matched subjects, is measured.

Surface-based brain morphometry and diffusion tensor imaging in schizoaffective disorder

BACKGROUND

The profile of grey matter abnormalities and related white-matter pathology in schizoaffective disorder has only been studied to a limited extent. The aim of this study was to identify grey- and white-matter abnormalities in patients with schizoaffective disorder using complementary structural imaging techniques.

METHODS

Forty-five patients meeting Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition criteria and Research Diagnostic Criteria for schizoaffective disorder and 45 matched healthy controls underwent structural-T1 and diffusion magnetic resonance imaging to enable surface-based brain morphometry and diffusion tensor imaging analyses. Analyses were conducted to determine group differences in cortical volume, cortical thickness and surface area, as well as in fractional anisotropy and mean diffusivity.

RESULTS

At a threshold of p = 0.05 corrected, all measures revealed significant differences between patients and controls at the group level. Spatial overlap of abnormalities was observed across the various structural neuroimaging measures. In grey matter, patients with schizoaffective disorder showed abnormalities in the frontal and temporal lobes, striatum, fusiform, cuneus, precuneus, lingual and limbic regions. White-matter abnormalities were identified in tracts connecting these areas, including the corpus callosum, superior and inferior longitudinal fasciculi, anterior thalamic radiation, uncinate fasciculus and cingulum bundle.

CONCLUSION

The spatial overlap of abnormalities across the different imaging techniques suggests widespread and consistent brain pathology in schizoaffective disorder. The abnormalities were mainly detected in areas that have commonly been reported to be abnormal in schizophrenia, and to some extent in bipolar disorder, which may explain the clinical and aetiological overlap in these disorders.

Occipital bending in schizophrenia

OBJECTIVE

To investigate the prevalence of occipital bending (an occipital lobe crossing or twisting across the midline) in subjects with schizophrenia and matched healthy controls.

METHOD

Occipital bending prevalence was investigated in 37 patients with schizophrenia and 44 healthy controls.

RESULTS

Ratings showed that prevalence was nearly three times higher among schizophrenia patients (13/37 [35.1%]) than in control subjects (6/44 [13.6%]). Furthermore, those with schizophrenia had greater normalized gray matter volume but less white matter volume and had larger brain-to-cranial ratio.

CONCLUSION

The results suggest that occipital bending is more prevalent among schizophrenia patients than healthy subjects and that schizophrenia patients have different gray matter-white matter proportions. Although the cause and clinical ramifications of occipital bending are unclear, the results infer that occipital bending may be a marker of psychiatric illness.

Neuroanatomical Abnormalities in Violent Individuals with and without a Diagnosis of Schizophrenia

Several structural brain abnormalities have been associated with aggression in patients with schizophrenia. However, little is known about shared and distinct abnormalities underlying aggression in these subjects and non-psychotic violent individuals. We applied a region-of-interest volumetric analysis of the amygdala, hippocampus, and thalamus bilaterally, as well as whole brain and ventricular volumes to investigate violent (n = 37) and non-violent chronic patients (n = 26) with schizophrenia, non-psychotic violent (n = 24) as well as healthy control subjects (n = 24). Shared and distinct volumetric abnormalities were probed by analysis of variance with the factors violence (non-violent versus violent) and diagnosis (non-psychotic versus psychotic), adjusted for substance abuse, age, academic achievement and negative psychotic symptoms. Patients showed elevated vCSF volume, smaller left hippocampus and smaller left thalamus volumes. This was particularly the case for non-violent individuals diagnosed with schizophrenia. Furthermore, patients had reduction in right thalamus size. With regard to left amygdala, we found an interaction between violence and diagnosis. More specifically, we report a double dissociation with smaller amygdala size linked to violence in non-psychotic individuals, while for psychotic patients smaller size was linked to non-violence. Importantly, the double dissociation appeared to be mostly driven by substance abuse. Overall, we found widespread morphometric abnormalities in subcortical regions in schizophrenia. No evidence for shared volumetric abnormalities in individuals with a history of violence was found. Finally, left amygdala abnormalities in non-psychotic violent individuals were largely accounted for by substance abuse. This might be an indication that the association between amygdala reduction and violence is mediated by substance abuse. Our results indicate the importance of structural abnormalities in aggressive individuals.

Aberrant temporal behavior of mismatch negativity generators in schizophrenia patients and subjects at clinical high risk for psychosis

OBJECTIVE

Although disconnection syndrome has been considered a core pathophysiologic mechanism of schizophrenia, little is known about the temporal behavior of mismatch negativity (MMN) generators in individuals with schizophrenia or clinical high risk (CHR) for psychosis.

METHODS

MMN was assessed in 29 schizophrenia patients, 40 CHR subjects, and 47 healthy controls (HCs). Individual realistic head models and the minimum L2 norm algorithm were used to generate a current source density (CSD) model of MMN. The strength and time course of MMN CSD activity were calculated separately for the frontal and temporal cortices and were compared across brain regions and groups.

RESULTS

Schizophrenia patients and CHR subjects displayed lower MMN CSD strength than HCs in both the temporal and frontal cortices. We found a significant time delay in MMN generator activity in the frontal cortex relative to that in the temporal cortex in HCs. However, the sequential temporo-frontal activities of MMN generators were disrupted in both the schizophrenia and CHR groups.

CONCLUSIONS

Impairments and altered temporal behavior of MMN multiple generators were observed even in individuals at risk for psychosis.

SIGNIFICANCE

These findings suggest that aberrant MMN generator activity might be helpful in revealing the pathophysiology of schizophrenia.

The neural correlates and clinical characteristics of psychosis in the frontotemporal dementia continuum and the C9orf72 expansion

OBJECTIVE

This present study aims to address the gap in the literature regarding the severity and underlying neural correlates of psychotic symptoms in frontotemporal dementia with and without the C9orf72 gene expansion.

METHODS

Fifty-six patients with behavioural variant frontotemporal dementia (20 with concomitant amyotrophic lateral sclerosis) and 23 healthy controls underwent neuropsychological assessments, detailed clinical interview for assessment of psychosis symptoms, brain MRI and genetic testing. Carers underwent a clinical interview based upon the neuropsychiatric inventory. Patients were assessed at ForeFront, the Frontotemporal Dementia Research Group at Neuroscience Research Australia or at the Brain and Mind Centre, between January 2008 and December 2013. An index of psychosis was calculated, taking into account the degree and severity of psychosis in each case. Voxel-based morphometry analyses were used to explore relationships between the psychosis index and grey matter changes.

RESULTS

Thirty-four percent of frontotemporal dementia patients showed psychotic features. C9orf72 expansion cases were more likely to exhibit psychotic symptoms than non-carriers (64% vs. 26%; p = 0.006), which were also more severe (psychotic index 23.1 vs. 8.1; p = 0.002). Delusions comprised persecutory, somatic, jealous and grandiose types and were present in 57% of C9orf72 carriers and 19% of non-carriers (p = 0.006). Auditory, visual or tactile hallucinations were present in 36% of C9orf72 carriers and 17% of non-carriers (p = 0.13). Increased psychotic symptoms in C9orf72 expansion carriers correlated with atrophy in a distributed cortical and subcortical network that included discrete regions of the frontal, temporal and occipital cortices, as well as the thalamus, striatum and cerebellum.

CONCLUSIONS

This study underlines the need to consider and assess for psychotic symptoms in the frontotemporal dementia-amyotrophic lateral sclerosis continuum particularly in those with C9orf72 gene expansions. The network of brain regions identified in this study is strikingly similar to that identified in other psychotic disorders such as schizophrenia, which suggests that treatment strategies in psychiatry may be beneficial for the management of psychotic symptoms in frontotemporal dementia.

Abnormal asymmetries in subcortical brain volume in schizophrenia

Subcortical structures, which include the basal ganglia and parts of the limbic system, have key roles in learning, motor control and emotion, but also contribute to higher-order executive functions. Prior studies have reported volumetric alterations in subcortical regions in schizophrenia. Reported results have sometimes been heterogeneous, and few large-scale investigations have been conducted. Moreover, few large-scale studies have assessed asymmetries of subcortical volumes in schizophrenia. Here, as a work completely independent of a study performed by the ENIGMA consortium, we conducted a large-scale multisite study of subcortical volumetric differences between patients with schizophrenia and controls. We also explored the laterality of subcortical regions to identify characteristic similarities and differences between them. T1-weighted images from 1680 healthy individuals and 884 patients with schizophrenia, obtained with 15 imaging protocols at 11 sites, were processed with FreeSurfer. Group differences were calculated for each protocol and meta-analyzed. Compared with controls, patients with schizophrenia demonstrated smaller bilateral hippocampus, amygdala, thalamus and accumbens volumes as well as intracranial volume, but larger bilateral caudate, putamen, pallidum and lateral ventricle volumes. We replicated the rank order of effect sizes for subcortical volumetric changes in schizophrenia reported by the ENIGMA consortium. Further, we revealed leftward asymmetry for thalamus, lateral ventricle, caudate and putamen volumes, and rightward asymmetry for amygdala and hippocampal volumes in both controls and patients with schizophrenia. Also, we demonstrated a schizophrenia-specific leftward asymmetry for pallidum volume. These findings suggest the possibility of aberrant laterality in neural pathways and connectivity patterns related to the pallidum in schizophrenia.

Theory of mind and executive functions in schizophrenia and bipolar disorder: A cross-diagnostic latent class analysis for identification of neuropsychological subtypes

OBJECTIVE

Executive dysfunction is a common feature of schizophrenia and bipolar disorder (BP). While deficits in social cognitive abilities, including theory of mind (ToM), have been suggested to be specific to schizophrenia, available evidence suggests that there is also a significant overlap in social cognitive performances of both disorders. However, there is significant heterogeneity of executive dysfunction and ToM deficits in BP and schizophrenia. Cross-diagnostic data-driven methods can reveal potential neurocognitive subtypes characterized by relatively selective deficits in social cognition.

METHODS

Neurocognitive subgroups were investigated using latent class analysis, based on executive functions and ToM, in a mixed sample of 97 clinically stable patients with schizophrenia or BP and 27 healthy controls.

RESULTS

Four neurocognitive subgroups, including a "neuropsychologically normal" cluster, a severe global impairment cluster and two clusters of mixed cognitive profiles were found. Severe impairment cluster was characterized by particularly severe ToM deficits and predominantly included patients with schizophrenia. Schizophrenia patients in this cluster had severe negative symptoms. In contrast, individuals with BP compared to schizophrenia patients were more likely to be included in the "neuropsychologically normal" cluster.

CONCLUSION

Identification of distinctive neurobiological subtypes of patients based on social and non-social cognitive profiles can improve classification of major psychoses. Neurocognitive subgroupings of patients might be also beneficial for intervention strategies including cognitive rehabilitation.

Connectivity of the anterior insula differentiates participants with first-episode schizophrenia spectrum disorders from controls: a machine-learning study

BACKGROUND

Early diagnosis of schizophrenia could improve the outcomes and limit the negative effects of untreated illness. Although participants with schizophrenia show aberrant functional connectivity in brain networks, these between-group differences have a limited diagnostic utility. Novel methods of magnetic resonance imaging (MRI) analyses, such as machine learning (ML), may help bring neuroimaging from the bench to the bedside. Here, we used ML to differentiate participants with a first episode of schizophrenia-spectrum disorder (FES) from healthy controls based on resting-state functional connectivity (rsFC).

METHOD

We acquired resting-state functional MRI data from 63 patients with FES who were individually matched by age and sex to 63 healthy controls. We applied linear kernel support vector machines (SVM) to rsFC within the default mode network, the salience network and the central executive network.

RESULTS

The SVM applied to the rsFC within the salience network distinguished the FES from the control participants with an accuracy of 73.0% (p = 0.001), specificity of 71.4% and sensitivity of 74.6%. The classification accuracy was not significantly affected by medication dose, or by the presence of psychotic symptoms. The functional connectivity within the default mode or the central executive networks did not yield classification accuracies above chance level.

CONCLUSIONS

Seed-based functional connectivity maps can be utilized for diagnostic classification, even early in the course of schizophrenia. The classification was probably based on trait rather than state markers, as symptoms or medications were not significantly associated with classification accuracy. Our results support the role of the anterior insula/salience network in the pathophysiology of FES.

Body mass index and brain white matter structure in young adults at risk for psychosis - The Oulu Brain and Mind Study

Antipsychotic medications and psychotic illness related factors may affect both weight and brain structure in people with psychosis. Genetically high-risk individuals offer an opportunity to study the relationship between body mass index (BMI) and brain structure free from these potential confounds. We examined the effect of BMI on white matter (WM) microstructure in subjects with familial risk for psychosis (FR). We used diffusion tensor imaging and tract-based spatial statistics to explore the effect of BMI on whole brain FA in 42 (13 males) participants with FR and 46 (16 males) control participants aged 20-25 years drawn from general population-based Northern Finland Birth Cohort 1986. We also measured axial, radial and mean diffusivities. Most of the participants were normal weight rather than obese. In the FR group, decrease in fractional anisotropy and increase in radial diffusivity were associated with an increase in BMI in several brain areas. In controls the opposite pattern was seen in participants with higher BMI. There was a statistically significant interaction between group and BMI on FA and radial and mean diffusivities. Our results suggest that the effect of BMI on WM differs between individuals with FR for psychosis and controls.

Relation between cannabis use and subcortical volumes in people at clinical high risk of psychosis

Among people at genetic risk of schizophrenia, those who use cannabis show smaller thalamic and hippocampal volumes. We evaluated this relationship in people at clinical high risk (CHR) of psychosis. The Alcohol and Drug Use Scale was used to identify 132 CHR cannabis users, the majority of whom were non-dependent cannabis users, 387 CHR non-users, and 204 healthy control non-users, and all participants completed magnetic resonance imaging scans. Volumes of the thalamus, hippocampus and amygdala were extracted with FreeSurfer, and compared across groups. Comparing all CHR participants with healthy control participants revealed no significant differences in volumes of any ROI. However, when comparing CHR users to CHR non-users, a significant ROI×Cannabis group effect emerged: CHR users showed significantly smaller amygdala compared to CHR non-users. However, when limiting analysis to CHR subjects who reported using alcohol at a 'use without impairment' severity level, the amygdala effect was non-significant; rather, smaller hippocampal volumes were seen in CHR cannabis users compared to non-users. Controlling statistically for effects of alcohol and tobacco use rendered all results non-significant. These results highlight the importance of controlling for residual confounding effects of other substance use when examining the relationship between cannabis use and neural structure.

White matter volume change and its correlation with symptom severity in patients with schizophrenia: a VBM-DARTEL study

The aim of this study was to evaluate the white matter (WM) volume change and its correlation with symptom severity in patients with schizophrenia using voxel-based morphometry. A total of 20 patients with schizophrenia and 20 age-matched healthy controls participated in this study. MR image data were processed using SPM8 software with diffeomorphic anatomical registration through an exponentiated Lie algebra (DARTEL) algorithm. The patients with schizophrenia showed significant decreases (P=0.042) in the WM volumes of the temporal lobe and superior frontal gyrus compared with the healthy controls. The WM volumes of the middle temporal gyrus were negatively correlated with the scores of both the Positive Subscale (Pearson's ρ=-0.68, P=0.001) and the Negative Subscale (ρ=-0.71, P=0.0005) in the Positive and Negative Syndrome Scale. In addition, the scores of the General Psychopathology Subscale were negatively correlated with the WM volumes of the superior frontal gyrus (ρ=-0.68, P=0.0009). This study evaluated the WM volume of patients with schizophrenia compared with healthy controls using DARTEI-based voxel-based morphometry and also assessed the correlation of the localized WM volume changes with the Positive and Negative Syndrome Scale. These findings will be useful to understand the neuropathology associated with WM abnormality in schizophrenia.

Schizophrenia patient-derived olfactory neurosphere-derived cells do not respond to extracellular reelin

Reelin expression is reduced in various regions in the post-mortem brain of schizophrenia patients but the exact role of reelin function in the neurobiology of schizophrenia remains elusive. Absence of reelin in knockout mouse causes inverted lamination of the neocortex due to aberrant neuronal migration. The aim of this study was to utilize patient-derived olfactory neurosphere-derived (ONS) cells to investigate whether extracellular reelin alters cell motility in schizophrenia patient-derived cells. ONS cells from nine patients were compared with cells from nine matched healthy controls. Automated high-throughput imaging and analysis were used to track motility of individual living cells on reelin-coated surfaces produced from reelin secreted into the medium by HEK293FT cells transfected with the full-length reelin plasmid pCrl. Automated assays were used to quantify intracellular cytoskeleton composition, cell morphology, and focal adhesions. Expression of reelin and components of the reelin signaling pathway were measured by western blot and flow cytometry. Reelin inhibited the motility of control cells but not patient cells, and increased the number and size of focal adhesions in control cells but not patient cells. Patient and control cells expressed similar levels of the reelin receptors and the reelin signaling protein, Dab1, but patient cells expressed less reelin. Patient cells were smaller than control cells and had less actin and acetylated α-tubulin, components of the cytoskeleton. These findings are the first direct evidence that cellular responses to reelin are impaired in schizophrenia and are consistent with the role of reelin in cytoarchitectural deficits observed in schizophrenia patient brains.

Dynamic cerebral reorganization in the pathophysiology of schizophrenia: a MRI-derived cortical thickness study

BACKGROUND

A structural neuroanatomical change indicating a reduction in brain tissue is a notable feature of schizophrenia. Several pathophysiological processes such as aberrant cortical maturation, progressive tissue loss and compensatory tissue increase could contribute to the structural changes seen in schizophrenia.

METHOD

We studied cortical thickness using surface-based morphometry in 98 clinically stable patients with schizophrenia and 83 controls. Using a pattern classification approach, we studied whether the features that discriminate patients from controls vary across the different stages of the illness. Using a covariance analysis, we also investigated if concurrent increases accompany decreases in cortical thickness.

RESULTS

Very high levels of accuracy (96.3%), specificity (98.8%) and sensitivity (88%) were noted when classifying patients with <2 years of illness from controls. Within the patient group, reduced thickness was consistently accompanied by increased thickness in distributed brain regions. A pattern of cortical amelioration or normalization (i.e. reduced deviation from controls) was noted with increasing illness duration. While temporo-limbic and fronto-parietal regions showed reduced thickness, the occipital cortex showed increased thickness, especially in those with a long-standing illness.

CONCLUSION

A compensatory remodelling process might contribute to the cortical thickness variations in different stages of schizophrenia. Subtle cerebral reorganization reflecting the inherent plasticity of brain may occur concomitantly with processes contributing to tissue reduction in adult patients with schizophrenia.

Deep Independence Network Analysis of Structural Brain Imaging: Application to Schizophrenia

Linear independent component analysis (ICA) is a standard signal processing technique that has been extensively used on neuroimaging data to detect brain networks with coherent brain activity (functional MRI) or covarying structural patterns (structural MRI). However, its formulation assumes that the measured brain signals are generated by a linear mixture of the underlying brain networks and this assumption limits its ability to detect the inherent nonlinear nature of brain interactions. In this paper, we introduce nonlinear independent component estimation (NICE) to structural MRI data to detect abnormal patterns of gray matter concentration in schizophrenia patients. For this biomedical application, we further addressed the issue of model regularization of nonlinear ICA by performing dimensionality reduction prior to NICE, together with an appropriate control of the complexity of the model and the usage of a proper approximation of the probability distribution functions of the estimated components. We show that our results are consistent with previous findings in the literature, but we also demonstrate that the incorporation of nonlinear associations in the data enables the detection of spatial patterns that are not identified by linear ICA. Specifically, we show networks including basal ganglia, cerebellum and thalamus that show significant differences in patients versus controls, some of which show distinct nonlinear patterns.

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.

Diagnostic potential of structural neuroimaging for depression from a multi-ethnic community sample

BACKGROUND

At present, we do not have any biological tests which can contribute towards a diagnosis of depression. Neuroimaging measures have shown some potential as biomarkers for diagnosis. However, participants have generally been from the same ethnic background while the applicability of a biomarker would require replication in individuals of diverse ethnicities.

AIMS

We sought to examine the diagnostic potential of the structural neuroanatomy of depression in a sample of a wide ethnic diversity.

METHOD

Structural magnetic resonance imaging (MRI) scans were obtained from 23 patients with major depressive disorder in an acute depressive episode (mean age: 39.8 years) and 20 matched healthy volunteers (mean age: 38.8 years). Participants were of Asian, African and Caucasian ethnicity recruited from the general community.

RESULTS

Structural neuroanatomy combining white and grey matter distinguished patients from controls at the highest accuracy of 81% with the most stable pattern being at around 70%. A widespread network encompassing frontal, parietal, occipital and cerebellar regions contributed towards diagnostic classification.

CONCLUSIONS

These findings provide an important step in the development of potential neuroimaging-based tools for diagnosis as they demonstrate that the identification of depression is feasible within a multi-ethnic group from the community.

DECLARATION OF INTERESTS

C.H.Y.F. has held recent research grants from Eli Lilly and Company and GlaxoSmithKline. L.M. is a former employee and stockholder of Eli Lilly and Company.

COPYRIGHT AND USAGE

© The Royal College of Psychiatrists 2016. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) licence.

A Common CYFIP1 Variant at the 15q11.2 Disease Locus Is Associated with Structural Variation at the Language-Related Left Supramarginal Gyrus

Copy number variants (CNVs) at the Breakpoint 1 to Breakpoint 2 region at 15q11.2 (BP1-2) are associated with language-related difficulties and increased risk for developmental disorders in which language is compromised. Towards underlying mechanisms, we investigated relationships between single nucleotide polymorphisms (SNPs) across the region and quantitative measures of human brain structure obtained by magnetic resonance imaging of healthy subjects. We report an association between rs4778298, a common variant at CYFIP1, and inter-individual variation in surface area across the left supramarginal gyrus (lh.SMG), a cortical structure implicated in speech and language in independent discovery (n = 100) and validation cohorts (n = 2621). In silico analyses determined that this same variant, and others nearby, is also associated with differences in levels of CYFIP1 mRNA in human brain. One of these nearby polymorphisms is predicted to disrupt a consensus binding site for FOXP2, a transcription factor implicated in speech and language. Consistent with a model where FOXP2 regulates CYFIP1 levels and in turn influences lh.SMG surface area, analysis of publically available expression data identified a relationship between expression of FOXP2 and CYFIP1 mRNA in human brain. We propose that altered CYFIP1 dosage, through aberrant patterning of the lh.SMG, may contribute to language-related difficulties associated with BP1-2 CNVs. More generally, this approach may be useful in clarifying the contribution of individual genes at CNV risk loci.

Patterns of regional gray matter loss at different stages of schizophrenia: A multisite, cross-sectional VBM study in first-episode and chronic illness

Background: Structural brain abnormalities in schizophrenia have been repeatedly demonstrated in magnetic resonance imaging (MRI) studies, but it remains unclear whether these are static or progressive in nature. While longitudinal MRI studies have been traditionally used to assess the issue of progression of brain abnormalities in schizophrenia, information from cross-sectional neuroimaging studies directly comparing first-episode and chronic schizophrenia patients to healthy controls may also be useful to further clarify this issue. With the recent interest in multisite mega-analyses combining structural MRI data from multiple centers aiming at increased statistical power, the present multisite voxel-based morphometry (VBM) study was carried out to examine patterns of brain structural changes according to the different stages of illness and to ascertain which (if any) of such structural abnormalities would be specifically correlated to potential clinical moderators, including cumulative exposure to antipsychotics, age of onset, illness duration and overall illness severity.

Methods: We gathered a large sample of schizophrenia patients (161, being 99 chronic and 62 first-episode) and controls (151) from four previous morphometric MRI studies (1.5 T) carried out in the same geographical region of Brazil. Image processing and analyses were conducted using Statistical Parametric Mapping (SPM8) software with the diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) algorithm. Group effects on regional gray matter (GM) volumes were investigated through whole-brain voxel-wise comparisons using General Linear Model Analysis of Co-variance (ANCOVA), always including total GM volume, scan protocol, age and gender as nuisance variables. Finally, correlation analyses were performed between the aforementioned clinical moderators and regional and global brain volumes.

Results: First-episode schizophrenia subjects displayed subtle volumetric deficits relative to controls in a circumscribed brain regional network identified only in small volume-corrected (SVC) analyses (p < 0.05, FWE-corrected), including the insula, temporolimbic structures and striatum. Chronic schizophrenia patients, on the other hand, demonstrated an extensive pattern of regional GM volume decreases relative to controls, involving bilateral superior, inferior and orbital frontal cortices, right middle frontal cortex, bilateral anterior cingulate cortices, bilateral insulae and right superior and middle temporal cortices (p < 0.05, FWE-corrected over the whole brain). GM volumes in several of those brain regions were directly correlated with age of disease onset on SVC analyses for conjoined (first-episode and chronic) schizophrenia groups. There were also widespread foci of significant negative correlation between duration of illness and relative GM volumes, but such findings remained significant only for the right dorsolateral prefrontal cortex after accounting for the influence of age of disease onset. Finally, significant negative correlations were detected between life-time cumulative exposure to antipsychotics and total GM and white matter volumes in schizophrenia patients, but no significant relationship was found between indices of antipsychotic usage and relative GM volume in any specific brain region.

Conclusion: The above data indicate that brain changes associated with the diagnosis of schizophrenia are more widespread in chronic schizophrenia compared to first-episode patients. Our findings also suggest that relative GM volume deficits may be greater in (presumably more severe) cases with earlier age of onset, as well as varying as a function of illness duration in specific frontal brain regions. Finally, our results highlight the potentially complex effects of the continued use of antipsychotic drugs on structural brain abnormalities in schizophrenia, as we found that cumulative doses of antipsychotics affected brain volumes globally rather than selectively on frontal-temporal regions.

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Structural brain changes are more widespread in chronic than first-episode schizophrenia.

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Regional GM deficits may be greater in cases with earlier age of onset.

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Illness duration seems to impact in some specific frontal structural brain changes.

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Antipsychotics seem to affect brain volumes globally rather than regionally.

Clinical Utility and Lifespan Profiling of Neurological Soft Signs in Schizophrenia Spectrum Disorders

Neurological soft signs (NSSs) bear the promise for early detection of schizophrenia spectrum disorders. Nonetheless, the sensitivity and specificity of NSSs in the psychosis continuum remains a topic of controversy. It is also unknown how NSSs reveal neurodevelopmental abnormality in schizophrenia. We investigated the effect sizes of NSSs in differentiating individuals with schizophrenia spectrum disorders from individuals with other psychiatric conditions and from covariate-matched healthy subjects. We also investigated the partitioned age-related variations of NSSs in both schizophrenia and healthy individuals. NSSs were assessed by the abridged version of the Cambridge Neurological Inventory (CNI) in 3105 participants, consisting of healthy individuals (n=1577), unaffected first-degree relatives of schizophrenia patients (n= 155), individuals with schizotypal personality disorder (n= 256), schizophrenia patients (n= 738), and other psychiatric patients (n= 379). Exact matching and propensity score matching procedures were performed to control for covariates. Multiple regression was used to partition age-related variations. Individuals along the schizophrenia continuum showed elevated levels of NSSs, with moderate effect sizes, in contrast to other psychiatric patients who had minimal NSSs, as well as matched healthy controls. Furthermore, the age-and-NSS relationship in schizophrenia patients was represented by a flat but overall elevated pattern, in contrast to a U-shaped pattern in healthy individuals. In sum, NSSs capture a moderate portion of psychosis proneness with reasonable specificity. Lifespan profiling reveals an abnormal developmental trajectory of NSSs in schizophrenia patients, which supports the endophenotype hypothesis of NSSs by associating it with the neurodevelopmental model of schizophrenia.

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.

Diffusion Imaging of White Matter In Schizophrenia: Progress and Future Directions

Diffusion tensor imaging (DTI) is a powerful tool for the in-vivo assessment of white matter microstructure. The application of DTI methodologies to the study of schizophrenia has supported and advanced the hypothesis of schizophrenia as a disorder of disrupted connectivity. In the context of impaired structural connectivity, the extended time frame of white matter development may offer unique opportunities for treatment that can capitalize on the neural flexibility that is still present in the period leading up to and after disease onset. Therefore, it is important to gain a clear understanding of white matter deficits and how they may emerge and change across the illness. However, while there is broad consistency in the findings of white matter deficits in patients with schizophrenia, there is also a great deal of variability in specific findings across studies. In this review, the aim is to move beyond summarizing case-control analyses, to consider the many factors that may impact DTI measures, to explain variability of findings, and to explore future directions for the field. The topics explored include ways to parse DTI patterns associated with different disease subtypes, ways in which novel and established treatments might interact with or enhance white matter, ways of dissociating developmental change from the disease process itself, and understanding the role of emerging analytic methodologies.

Amygdala volume is reduced in early course schizophrenia

Subcortical structural alterations have been implicated in the neuropathology of schizophrenia. Yet, the extent of anatomical alterations for subcortical structures across illness phases remains unknown. To assess this, magnetic resonance imaging (MRI) was used to examine volume differences of major subcortical structures: thalamus, nucleus accumbens, caudate, putamen, globus pallidus, amygdala and hippocampus. These differences were examined across four groups: (i) healthy comparison subjects (HCS, n=96); (ii) individuals at high risk (HR, n=21) for schizophrenia; (iii) early-course schizophrenia patients (EC-SCZ, n=28); and (iv) chronic schizophrenia patients (C-SCZ, n=20). Raw gray matter volumes and volumetric ratios (volume of specific structure/total gray matter volume) were extracted using automated segmentation tools. EC-SCZ group exhibited smaller bilateral amygdala volumetric ratios, compared to HCS and HR subjects. Findings did not change when corrected for age, level of education and medication use. Amygdala raw volumes did not differ among groups once adjusted for multiple comparisons, but the smaller amygdala volumetric ratio in EC-SCZ survived Bonferroni correction. Other structures were not different across the groups following Bonferroni correction. Smaller amygdala volumes during early illness course may reflect pathophysiologic changes specific to illness development, including disrupted salience processing and acute stress responses.