Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium

Hippocampal subfield and amygdala nuclei volumes in schizophrenia patients with a history of violence

Schizophrenia (SCZ) is associated with an increased risk of violence compared to the general population. Previous studies have indicated smaller hippocampal and amygdala volumes in violent than non-violent psychotic patients^. However, little is known about volumetric differences at the subdivision level of these structures. In the present study, hippocampal subfields and amygdala nuclei volumes were estimated with FreeSurfer from 3 T MRI of SCZ patients with (SCZ-V, n = 24) and without (SCZ-NV, n = 51) a history of severe violence and 90 healthy controls (HC). Volumetric differences between groups were explored with a general linear model covarying for confounders, in addition to follow-up analyses in patient groups controlling for clinical characteristics such as antipsychotic medication, duration of illness and illicit substance use. SCZ-V had smaller total hippocampal volume and smaller CA1, HATA, fimbria, and molecular layer of DG volumes compared to HC. Total amygdala volume together with basal nucleus, accessory basal nucleus, CTA, and paralaminar nucleus volumes were smaller in SCZ-V compared to HC. In SCZ-NV, compared to HC, the observed smaller volumes were limited to basal and paralaminar nucleus. There were no significant differences in hippocampal subfield and amygdala nuclei volumes between SCZ-V and SCZ-NV. Follow-up analyses showed that the results in patient groups were not affected by clinical characteristics. The results suggest that smaller hippocampal subfield and amygdala nuclei volumes may be relevant to violence risk in SCZ. However, the neurobiological signature of violence in SCZ should be further investigated in larger cohorts.

Total gray matter volume is reduced in individuals with bipolar disorder currently treated with atypical antipsychotics

BACKGROUND/AIMS

Recent evidence indicates that the intake of atypical antipsychotics (AAP) is associated with gray matter abnormalities in patients with psychiatric disorders. We explored if patients with bipolar disorder (BD) who are medicated with AAP exhibit total gray matter volume (TGV) reduction compared to BD individuals not medicated with AAP and healthy controls (HC).

METHODS

In a cross-sectional design, 124 individuals with BD and 86 HC underwent 3T-MRI of the brain and clinical assessment as part of our BIPFAT-study. The TGV was estimated using Freesurfer. We used univariate covariance analysis (ANCOVA) to test for normalized TGV differences and controlled for covariates.

RESULTS

ANCOVA results indicated that 75 BD individuals taking AAP had significantly reduced normalized TGV as compared to 49 BD not taking AAP (F = 9.995, p = .002., Eta = 0.084) and 86 HC (F = 7.577, p = .007, Eta = 0.046).

LIMITATIONS

Our cross-sectional results are not suited to draw conclusions about causality. We have no clear information on treatment time and baseline volumes before drug treatment in the studied subjects. We cannot exclude that patients received different psychopharmacologic medications prior to the study point. We did not included dosages into the calculation. Many BD individuals received combinations of psychopharmacotherapy across drug classes. We did not have records displaying quantitative alcohol consumption and drug abuse in our sample.

CONCLUSIONS

Our data provide further evidence for the impact of AAP on brain structure in BD. Longitudinal studies are needed to investigate the causal directions of the proposed relationships.

Selective Review of Neuroimaging Findings in Youth at Clinical High Risk for Psychosis: On the Path to Biomarkers for Conversion

First episode psychosis (FEP), and subsequent diagnosis of schizophrenia or schizoaffective disorder, predominantly occurs during late adolescence, is accompanied by a significant decline in function and represents a traumatic experience for patients and families alike. Prior to first episode psychosis, most patients experience a prodromal period of 1-2 years, during which symptoms first appear and then progress. During that time period, subjects are referred to as being at Clinical High Risk (CHR), as a prodromal period can only be designated in hindsight in those who convert. The clinical high-risk period represents a critical window during which interventions may be targeted to slow or prevent conversion to psychosis. However, only one third of subjects at clinical high risk will convert to psychosis and receive a formal diagnosis of a primary psychotic disorder. Therefore, in order for targeted interventions to be developed and applied, predicting who among this population will convert is of critical importance. To date, a variety of neuroimaging modalities have identified numerous differences between CHR subjects and healthy controls. However, complicating attempts at predicting conversion are increasingly recognized co-morbidities, such as major depressive disorder, in a significant number of CHR subjects. The result of this is that phenotypes discovered between CHR subjects and healthy controls are likely non-specific to psychosis and generalized for major mental illness. In this paper, we selectively review evidence for neuroimaging phenotypes in CHR subjects who later converted to psychosis. We then evaluate the recent landscape of machine learning as it relates to neuroimaging phenotypes in predicting conversion to psychosis.

Structural abnormality in schizophrenia versus bipolar disorder: A whole brain cortical thickness, surface area, volume and gyrification analyses

OBJECTIVES

The profiles of cortical abnormalities in schizophrenia and bipolar disorder, and how far they resemble each other, have only been studied to a limited extent. The aim of this study was to identify and compare the changes in cortical morphology associated with these pathologies.

METHODS

A total of 384 subjects, including 128 patients with schizophrenia, 128 patients with bipolar disorder and 127 sex-age-matched healthy subjects, were examined using cortical surface-based morphology. Four cortical structural measures were studied: cortical volume (CV), cortical thickness (CT), surface area (SA) and gyrification index (GI). Group comparisons for each separate cortical measure were conducted.

RESULTS

At a threshold of P = 0.05 corrected, both patient groups showed significant widespread CV and CT reductions in similar areas compared to healthy subjects. However, the changes in schizophrenia were more pronounced. While CV decrease in bipolar disorder was exclusively explained by cortical thinning, in schizophrenia it was driven by changes in CT and partially by SA. Reduced GI was only found in schizophrenia. The direct comparison between both disorders showed significant reductions in all measures in patients with schizophrenia.

CONCLUSIONS

Cortical volume and cortical thickness deficits are shared between patients with schizophrenia and bipolar disorder, suggesting that both pathologies may be affected by similar environmental and neurodegenerative factors. However, the exclusive alteration in schizophrenia of metrics related to the geometry and curvature of the brain cortical surface (SA, GI) suggests that this group is influenced by additional neurodevelopmental and genetic factors.

Identifying schizophrenia subgroups using clustering and supervised learning

Schizophrenia has a 1% incidence rate world-wide and those diagnosed present with positive (e.g. hallucinations, delusions), negative (e.g. apathy, asociality), and cognitive symptoms. However, both symptom burden and associated brain alterations are highly heterogeneous and intimately linked to prognosis. In this study, we present a method to predict individual symptom profiles by first deriving clinical subgroups and then using machine learning methods to perform subject-level classification based on magnetic resonance imaging (MRI) derived neuroanatomical measures. Symptomatic and MRI data of 167 subjects were used. Subgroups were defined using hierarchical clustering of clinical data resulting in 3 stable clusters: 1) high symptom burden, 2) predominantly positive symptom burden, and 3) mild symptom burden. Cortical thickness estimates were obtained in 78 regions of interest and were input, along with demographic data, into three machine learning models (logistic regression, support vector machine, and random forest) to predict subgroups. Random forest performance metrics for predicting the group membership of the high and mild symptom burden groups exceeded those of the baseline comparison of the entire schizophrenia population versus normal controls (AUC: 0.81 and 0.78 vs. 0.75). Additionally, an analysis of the most important features in the random forest classification demonstrated consistencies with previous findings of regional impairments and symptoms of schizophrenia.

Imaging-Based Subtyping for Psychiatric Syndromes

Despite considerable research evidence demonstrating significant neurobiological alterations in psychiatric disorders, incorporating neuroimaging approaches into clinical practice remains challenging. There is an urgent need for biologically validated psychiatric disease constructs that can inform diagnostic algorithms and targeted treatment development. In this article, we present a conceptual review of the most robust and impactful findings from studies that use neuroimaging methods in efforts to define distinct disease subtypes, while emphasizing cross-diagnostic and dimensional approaches. In addition, we discuss current challenges in psychoradiology and outline potential future strategies for clinically applicable translation.

Neuroimaging in Schizophrenia

Schizophrenia is a chronic psychotic disorder with a lifetime prevalence of about 1%. Onset is typically in adolescence or early adulthood; characteristic symptoms include positive symptoms, negative symptoms, and impairments in cognition. Neuroimaging studies have shown substantive evidence of brain structural, functional, and neurochemical alterations that are more pronounced in the association cortex and subcortical regions. These abnormalities are not sufficiently specific to be of diagnostic value, but there may be a role for imaging techniques to provide predictions of outcome. Incorporating multimodal imaging datasets using machine learning approaches may offer better diagnostic and predictive value in schizophrenia.

Structural Brain Alterations in Youth With Psychosis and Bipolar Spectrum Symptoms

OBJECTIVE

Adults with established diagnoses of serious mental illness (bipolar disorder and schizophrenia) exhibit structural brain abnormalities, yet less is known about how such abnormalities manifest earlier in development.

METHOD

Cross-sectional data publicly available from the Philadelphia Neurodevelopmental Cohort (PNC) were analyzed. Structural magnetic resonance neuroimaging data were collected on a subset of the PNC (N = 989; 9-22 years old). Cortical thickness, surface area (SA), and subcortical volumes were calculated. Study participants were assessed for psychiatric symptomatology using a structured interview and the following groups were created: typically developing (n = 376), psychosis spectrum (PS; n = 113), bipolar spectrum (BP; n = 117), and BP + PS (n = 109). Group and developmental differences in structural magnetic resonance neuroimaging measures were examined. In addition, the extent to which any structural aberration was related to neurocognition, global functioning, and clinical symptomatology was examined.

RESULTS

Compared with other groups, PS youth exhibited significantly decreased SA in the orbitofrontal, cingulate, precentral, and postcentral regions. PS youth also exhibited deceased thalamic volume compared with all other groups. The strongest effects for precentral and posterior cingulate SA decreases were seen during early adolescence (13-15 years old) in PS youth. The strongest effects for decreases in thalamic volume and orbitofrontal and postcentral SA were observed in mid-adolescence (16-18 years) in PS youth. Across groups, better overall functioning was associated with increased lateral orbitofrontal SA. Increased postcentral SA was associated with better executive cognition and less severe negative symptoms in the entire sample.

CONCLUSION

In a community-based sample, decreased cortical SA and thalamic volume were present early in adolescent development in youth with PS symptoms, but not in youth with BP symptoms or with BP and PS symptoms. These findings point to potential biological distinctions between PS and BP conditions, which could suggest additional biomarkers relevant to early identification.

Altered structural brain asymmetry in autism spectrum disorder in a study of 54 datasets

Altered structural brain asymmetry in autism spectrum disorder (ASD) has been reported. However, findings have been inconsistent, likely due to limited sample sizes. Here we investigated 1,774 individuals with ASD and 1,809 controls, from 54 independent data sets of the ENIGMA consortium. ASD was significantly associated with alterations of cortical thickness asymmetry in mostly medial frontal, orbitofrontal, cingulate and inferior temporal areas, and also with asymmetry of orbitofrontal surface area. These differences generally involved reduced asymmetry in individuals with ASD compared to controls. Furthermore, putamen volume asymmetry was significantly increased in ASD. The largest case-control effect size was Cohen’s d = −0.13, for asymmetry of superior frontal cortical thickness. Most effects did not depend on age, sex, IQ, severity or medication use. Altered lateralized neurodevelopment may therefore be a feature of ASD, affecting widespread brain regions with diverse functions. Large-scale analysis was necessary to quantify subtle alterations of brain structural asymmetry in ASD.

Changes in brain structure asymmetry have been reported in autism spectrum disorder. Here the authors investigate this issue using a large-scale sample consisting of 54 data sets.

Abnormal auditory tonotopy in patients with schizophrenia

Auditory hallucinations are among the most prevalent and most distressing symptoms of schizophrenia. Despite significant progress, it is still unclear whether auditory hallucinations arise from abnormalities in primary sensory processing or whether they represent failures of higher-order functions. To address this knowledge gap, we capitalized on the increased spatial resolution afforded by ultra-high field imaging at 7 Tesla to investigate the tonotopic organization of the auditory cortex in patients with schizophrenia with a history of recurrent hallucinations. Tonotopy is a fundamental feature of the functional organization of the auditory cortex that is established very early in development and predates the onset of symptoms by decades. Compared to healthy participants, patients showed abnormally increased activation and altered tonotopic organization of the auditory cortex during a purely perceptual task, which involved passive listening to tones across a range of frequencies (88–8000 Hz). These findings suggest that the predisposition to auditory hallucinations is likely to be predicated on abnormalities in the functional organization of the auditory cortex and which may serve as a biomarker for the early identification of vulnerable individuals.

Impact of Polygenic Risk for Schizophrenia on Cortical Structure in UK Biobank

BACKGROUND

Schizophrenia is a neurodevelopmental disorder with many genetic variants of individually small effect contributing to phenotypic variation. Lower cortical thickness (CT), surface area, and cortical volume have been demonstrated in people with schizophrenia. Furthermore, a range of obstetric complications (e.g., lower birth weight) are consistently associated with an increased risk for schizophrenia. We investigated whether a high polygenic risk score for schizophrenia (PGRS-SCZ) is associated with CT, surface area, and cortical volume in UK Biobank, a population-based sample, and tested for interactions with birth weight.

METHODS

Data were available for 2864 participants (n_male/n_female = 1382/1482; mean age = 62.35 years, SD = 7.40). Linear mixed models were used to test for associations among PGRS-SCZ and cortical volume, surface area, and CT and between PGRS-SCZ and birth weight. Interaction effects of these variables on cortical structure were also tested.

RESULTS

We found a significant negative association between PGRS-SCZ and global CT; a higher PGRS-SCZ was associated with lower CT across the whole brain. We also report a significant negative association between PGRS-SCZ and insular lobe CT. PGRS-SCZ was not associated with birth weight and no PGRS-SCZ × birth weight interactions were found.

CONCLUSIONS

These results suggest that individual differences in CT are partly influenced by genetic variants and are most likely not due to factors downstream of disease onset. This approach may help to elucidate the genetic pathophysiology of schizophrenia. Further investigation in case-control and high-risk samples could help identify any localized effects of PGRS-SCZ, and other potential schizophrenia risk factors, on CT as symptoms develop.

Global brain volume reductions in a sub-chronic phencyclidine animal model for schizophrenia and their relationship to recognition memory

BACKGROUND

Cognitive deficits and structural brain changes co-occur in patients with schizophrenia. Improving our understanding of the relationship between these is important to develop improved therapeutic strategies. Back-translation of these findings into rodent models for schizophrenia offers a potential means to achieve this goal.

AIMS

The purpose of this study was to determine the extent of structural brain changes and how these relate to cognitive behaviour in a sub-chronic phencyclidine rat model.

METHODS

Performance in the novel object recognition task was examined in female Lister Hooded rats at one and six weeks after sub-chronic phencyclidine (2 mg/kg intra-peritoneal, n=15) and saline controls (1 ml/kg intra-peritoneal, n=15). Locomotor activity following acute phencyclidine challenge was also measured. Brain volume changes were assessed in the same animals using ex vivo structural magnetic resonance imaging and computational neuroanatomical analysis at six weeks.

RESULTS

Female sub-chronic phencyclidine-treated Lister Hooded rats spent significantly less time exploring novel objects (p<0.05) at both time-points and had significantly greater locomotor activity response to an acute phencyclidine challenge (p<0.01) at 3-4 weeks of washout. At six weeks, sub-chronic phencyclidine-treated Lister Hooded rats displayed significant global brain volume reductions (p<0.05; q<0.05), without apparent regional specificity. Relative volumes of the perirhinal cortex however were positively correlated with novel object exploration time only in sub-chronic phencyclidine rats at this time-point.

CONCLUSION

A sustained sub-chronic phencyclidine-induced cognitive deficit in novel object recognition is accompanied by global brain volume reductions in female Lister Hooded rats. The relative volumes of the perirhinal cortex however are positively correlated with novel object exploration, indicating some functional relevance.

The Association Between Familial Risk and Brain Abnormalities Is Disease Specific: An ENIGMA-Relatives Study of Schizophrenia and Bipolar Disorder

BACKGROUND

Schizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects.

METHODS

We performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects.

RESULTS

FDRs-BD had significantly larger ICV (d = +0.16, q < .05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = -0.12, q < .05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d < -0.09, q < .05 corrected); and third ventricle was larger (d = +0.15, q < .05 corrected). The findings were not explained by psychopathology in the relatives or control subjects.

CONCLUSIONS

Despite shared genetic liability, FDRs-SZ and FDRs-BD show a differential pattern of structural brain abnormalities, specifically a divergent effect in ICV. This may imply that the neurodevelopmental trajectories leading to brain anomalies in schizophrenia or bipolar disorder are distinct.

Altered Patterns of the Fractional Amplitude of Low-Frequency Fluctuation and Functional Connectivity Between Deficit and Non-Deficit Schizophrenia

Objective: A limited number of studies have previously reported on the regional activity [amplitude of low-frequency fluctuation (ALFF)] and functional integration [functional connectivity (FC)] of the whole brain in deficit schizophrenia (DS). The present study investigates the resting-state characteristics of the fractional ALFF (fALFF) and the FC in both DS and non-deficit schizophrenia (NDS) patients, and further explores their correlations with neurocognitive features. Methods: Demographic, resting-state functional magnetic resonance imaging (MRI), and neurocognitive data were collected from 33 DS and 41 NDS male patients, as well as in 40 male healthy controls (HCs). The voxel-wise fALFF was measured to evaluate regional cerebral function. Regions with differences in fALFF between DS and NDS patients were used as seed points in whole-brain FC analysis. Partial correlation analysis was conducted to examine associations between the fALFF or the FC of altered regions and neurocognitive assessments. Results: Both patient groups showed decreased fALFF in the sensorimotor area, visual cortex, and frontoparietal pathway, but increased fALFF in the precuneus and middle cingulate gyrus when compared with the HCs. Moreover, the NDS group demonstrated higher fALFF than HCs in the left thalamus, caudate, and hippocampus. Compared with the NDS group, the fALFF of the visual cortex was specifically increased, but that of the bilateral insula, the anterior cingulate gyrus (ACG), and the regions extended to the frontotemporal cortex was decreased in the DS group. Numerous abnormal FCs of nerve pathways were found between the two patient groups, mainly concentrated in the frontooccipital, frontotemporal, insula-visual cortex, as well as the temporooccipital pathway. Correlation analysis indicated that, in the DS group, the FC value between the left insula and the visual cortex was positively correlated with cognitive flexibility. In the NDS group, the fALFF of the right insula was negatively correlated with speech fluency, and the FC value between the ACG and the visual cortex was positively correlated with visual spatial memory. Conclusion: The present study demonstrates different altered patterns of fALFF and FC between male patients with DS and NDS. The specific altered regions of the salience network (SN) associated with impaired neurocognition in male DS patients suggest novel insights into the pathogenesis of cognitive impairment in schizophrenia.

Biomarkers in aggression

Aggressive behavior exerts an enormous impact on society remaining among the main causes of worldwide premature death. Effective primary interventions, relying on predictive models of aggression that show adequate sensitivity and specificity are currently lacking. One strategy to increase the accuracy and precision of prediction would be to include biological data in the predictive models. Clearly, to be included in such models, biological markers should be reliably associated with the specific trait under study (i.e., diagnostic biomarkers). Aggression, however, is phenotypically highly heterogeneous, an element that has hindered the identification of reliable biomarkers. However, current research is trying to overcome these challenges by focusing on more homogenous aggression subtypes and/or by studying large sample size of aggressive individuals. Further advance is coming by bioinformatics approaches that are allowing the integration of inter-species biological data as well as the development of predictive algorithms able to discriminate subjects on the basis of the propensity toward aggressive behavior. In this review we first present a brief summary of the available evidence on neuroimaging of aggression. We will then treat extensively the data on genetic determinants, including those from hypothesis-free genome-wide association studies (GWAS) and candidate gene studies. Transcriptomic and neurochemical biomarkers will then be reviewed, and we will dedicate a section on the role of metabolomics in aggression. Finally, we will discuss how biomarkers can inform the development of new pharmacological tools as well as increase the efficacy of preventive strategies.

Distinct structural brain circuits indicate mood and apathy profiles in bipolar disorder

Bipolar disorder (BD) is a severe manic-depressive illness. Patients with BD have been shown to have gray matter (GM) deficits in prefrontal, frontal, parietal, and temporal regions; however, the relationship between structural effects and clinical profiles has proved elusive when considered on a region by region or voxel by voxel basis. In this study, we applied parallel independent component analysis (pICA) to structural neuroimaging measures and the positive and negative syndrome scale (PANSS) in 110 patients (mean age 34.9 ± 11.65) with bipolar disorder, to examine networks of brain regions that relate to symptom profiles. The pICA revealed two distinct symptom profiles and associated GM concentration alteration circuits. The first PANSS pICA profile mainly involved anxiety, depression and guilty feelings, reflecting mood symptoms. Reduced GM concentration in right temporal regions predicted worse mood symptoms in this profile. The second PANSS pICA profile generally covered blunted affect, emotional withdrawal, passive/apathetic social withdrawal, depression and active social avoidance, exhibiting a withdrawal or apathy dominating component. Lower GM concentration in bilateral parietal and frontal regions showed worse symptom severity in this profile. In summary, a pICA decomposition suggested BD patients showed distinct mood and apathy profiles differing from the original PANSS subscales, relating to distinct brain structural networks.

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Structural relationships with symptoms in bipolar disorder are complex.

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A parallel ICA analysis of PANSS questions and structural images finds two correlated profiles.

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The first pair links mood symptoms with right temporal regions.

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The second pair highlights social withdrawal and apathy symptoms linked to bilateral frontal and parietal regions.

Biophysical Psychiatry-How Computational Neuroscience Can Help to Understand the Complex Mechanisms of Mental Disorders

The brain is the most complex of human organs, and the pathophysiology underlying abnormal brain function in psychiatric disorders is largely unknown. Despite the rapid development of diagnostic tools and treatments in most areas of medicine, our understanding of mental disorders and their treatment has made limited progress during the last decades. While recent advances in genetics and neuroscience have a large potential, the complexity and multidimensionality of the brain processes hinder the discovery of disease mechanisms that would link genetic findings to clinical symptoms and behavior. This applies also to schizophrenia, for which genome-wide association studies have identified a large number of genetic risk loci, spanning hundreds of genes with diverse functionalities. Importantly, the multitude of the associated variants and their prevalence in the healthy population limit the potential of a reductionist functional genetics approach as a stand-alone solution to discover the disease pathology. In this review, we outline the key concepts of a "biophysical psychiatry," an approach that employs large-scale mechanistic, biophysics-founded computational modelling to increase transdisciplinary understanding of the pathophysiology and strive toward robust predictions. We discuss recent scientific advances that allow a synthesis of previously disparate fields of psychiatry, neurophysiology, functional genomics, and computational modelling to tackle open questions regarding the pathophysiology of heritable mental disorders. We argue that the complexity of the increasing amount of genetic data exceeds the capabilities of classical experimental assays and requires computational approaches. Biophysical psychiatry, based on modelling diseased brain networks using existing and future knowledge of basic genetic, biochemical, and functional properties on a single neuron to a microcircuit level, may allow a leap forward in deriving interpretable biomarkers and move the field toward novel treatment options.

Opening up new horizons for psychiatric genetics in the Russian Federation: moving toward a national consortium

We provide an overview of the recent achievements in psychiatric genetics research in the Russian Federation and present genotype-phenotype, population, epigenetic, cytogenetic, functional, ENIGMA, and pharmacogenetic studies, with an emphasis on genome-wide association studies. The genetic backgrounds of mental illnesses in the polyethnic and multicultural population of the Russian Federation are still understudied. Furthermore, genetic, genomic, and pharmacogenetic data from the Russian Federation are not adequately represented in the international scientific literature, are currently not available for meta-analyses and have never been compared with data from other populations. Most of these problems cannot be solved by individual centers working in isolation but warrant a truly collaborative effort that brings together all the major psychiatric genetic research centers in the Russian Federation in a national consortium. For this reason, we have established the Russian National Consortium for Psychiatric Genetics (RNCPG) with the aim to strengthen the power and rigor of psychiatric genetics research in the Russian Federation and enhance the international compatibility of this research.The consortium is set up as an open organization that will facilitate collaborations on complex biomedical research projects in human mental health in the Russian Federation and abroad. These projects will include genotyping, sequencing, transcriptome and epigenome analysis, metabolomics, and a wide array of other state-of-the-art analyses. Here, we discuss the challenges we face and the approaches we will take to unlock the huge potential that the Russian Federation holds for the worldwide psychiatric genetics community.

Using proton magnetic resonance spectroscopic imaging to study glutamatergic alterations in patients with schizophrenia: A systematic review

The glutamate hypothesis of schizophrenia posits aberrant glutamatergic activity in patients with schizophrenia. Levels of glutamate and glutamine can be detected and quantified in vivo by proton magnetic resonance spectroscopy. A related technique, proton magnetic resonance spectroscopic imaging (¹H-MRSI), is particularly useful as it simultaneously collects multiple spectra, across multiple voxels, from a single acquisition. The primary aim of this study was to review and discuss the use of ¹H-MRSI to measure levels of glutamate and glutamine in patients with schizophrenia. Additionally, the advantages and disadvantages of using ¹H-MRSI to examine schizophrenia pathophysiology are discussed. A literature search was conducted through Ovid. English language studies utilizing ¹H-MRSI to measure glutamate and glutamine in patients with schizophrenia were identified. Six studies met the inclusion criteria. The included studies provide inconclusive support for glutamatergic elevations within frontal brain regions in patients with schizophrenia. The key benefit of employing ¹H-MRSI to examine schizophrenia pathophysiology appears to be its broader spatial coverage. Future ¹H-MRSI studies utilizing large sample sizes and longitudinal study designs are necessitated to further our understanding of glutamatergic alterations in patients with schizophrenia.

An international survey of Psychiatric-Mental-Health Nurses on the content validity of the International Classification of Functioning, Disability and Health Core Sets for Schizophrenia

The International Classification of Functioning, Disability and Health (ICF) Core Sets for schizophrenia describe the key problems in functioning that are experienced by individuals with this disorder. This study examines the content validity of these Core Sets and aims to identify the most frequent problems faced by people with schizophrenia, considering for this analysis the perspective of Psychiatric-Mental-Health Nurses. The study complied with the COREQ checklist for qualitative studies. A total of 101 nurses from 30 countries covering all six World Health Organization regions participated in a Delphi study. Their responses in Round 1 were linked to ICF categories, retaining those reported by at least 5% of participants. In Round 2, they were asked to rate the relevance of each of these categories to the nursing care of patients with schizophrenia. This process was repeated in Round 3. A total of 2327 concepts were extracted in Round 1 and linked to ICF categories. Following the analysis, 125 categories and 31 personal factors were presented to the experts in rounds 2 and 3. Consensus (defined as agreement ≥75%) was reached for 97 of these categories and 29 personal factors. These categories corresponded to all those (N = 25) in the Brief Core Set and 87 of the 97 categories of the Comprehensive Core Set for schizophrenia. Ten new categories emerged. The Delphi process identified the problems in functioning that nurses encounter when treating individuals with schizophrenia, and the results supported the content validity of the Core Sets. We conclude that these Core Sets offer a comprehensive framework for structuring clinical information and guiding the treatment process.

Functional fractionation of default mode network in first episode schizophrenia

A disruption in the connectivity between brain regions may underlie the core pathology in schizophrenia. One of the most consistent observations in human functional imaging is a network of brain regions referred to as the default network (DMN) that contains core subsystem, the dorsomedial prefrontal cortex (dMPFC) subsystem and the medial temporal lobe (MTL) subsystem, with differential contributions. The goal of this study was to examine abnormalities of different DMN subsystems in first episode schizophrenia and associations between these abnormalities and individual psychopathology. We recruited 203 patients and 131 healthy controls. A seed-based resting-state functional connectivity (RSFC) analysis on the 2D surface was conducted. Individual DMN functional connectivity matrices were then obtained by calculating spatial correlations between pairs of RSFC maps, characterizing the functional fractionation of the DMN. Patients showed patterns similar to controls but markedly reduced strength of DMN fractionation, with the degree centrality of the MTL subsystem significantly reduced, including the posterior inferior parietal lobule (pIPL), parahippocampal cortex (PHC) and lateral temporal cortex (LTC). Patients also exhibited hypo-connectivity within the MTL subsystem and between the MTL and dMPFC subsystems. Clinical symptoms were negatively correlated with degree centrality of LTC, pIPL and PHC in patients. Hyper-fractionation of different DMN components implied that communication and coordination throughout the dissociated components of the DMN are functionally over-segregated in schizophrenia. The associations between the hyper-fractionation with clinical symptoms suggest a role of the high fractionation in the DMN in the abnormal neuropathology observed in schizophrenia.

Alterations in white matter microstructure and cortical thickness in individuals at ultra-high risk of psychosis: A multimodal tractography and surface-based morphometry study

There is increasing evidence of white matter (WM) and grey matter pathology in subjects at ultra-high risk of psychosis (UHR), although a limited number of diffusion-weighted magnetic resonance imaging (DW-MRI) and surface-based morphometry (SBM) studies have revealed anatomically inconsistent results. The present multimodal study applies tractography and SBM to analyze WM microstructure, whole-brain cortical anatomy, and potential interconnections between WM and grey matter abnormalities in UHR subjects. Thirty young male UHR patients and 30 healthy controls underwent DW-MRI and T1-weighted MRI. Fractional anisotropy; mean, radial, and axial diffusivity in 18 WM tracts; and vertex-based cortical thickness, area, and volume were analyzed. We found increased radial diffusivity in the left anterior thalamic radiation and reduced bilateral thickness across the frontal, temporal, and parietal cortices. No correlations between WM and grey matter abnormalities were identified. These results provide further evidence that WM microstructure abnormalities and cortical anatomical changes occur in the UHR state. Disruption of structural connectivity in the prefrontal-subcortical circuitry, likely caused by myelin pathology, and cortical thickness reduction affecting the networks presumably involved in processing and coordination of external and internal information streams may underlie the widespread deficits in neurocognitive and social functioning that are consistently reported in UHR subjects.

Dysconnectivity of Multiple Brain Networks in Schizophrenia: A Meta-Analysis of Resting-State Functional Connectivity

Background: Seed-based studies on resting-state functional connectivity (rsFC) in schizophrenia have shown disrupted connectivity involving a number of brain networks; however, the results have been controversial. Methods: We conducted a meta-analysis based on independent component analysis (ICA) brain templates to evaluate dysconnectivity within resting-state brain networks in patients with schizophrenia. Seventy-six rsFC studies from 70 publications with 2,588 schizophrenia patients and 2,567 healthy controls (HCs) were included in the present meta-analysis. The locations and activation effects of significant intergroup comparisons were extracted and classified based on the ICA templates. Then, multilevel kernel density analysis was used to integrate the results and control bias. Results: Compared with HCs, significant hypoconnectivities were observed between the seed regions and the areas in the auditory network (left insula), core network (right superior temporal cortex), default mode network (right medial prefrontal cortex, and left precuneus and anterior cingulate cortices), self-referential network (right superior temporal cortex), and somatomotor network (right precentral gyrus) in schizophrenia patients. No hyperconnectivity between the seed regions and any other areas within the networks was detected in patients, compared with the connectivity in HCs. Conclusions: Decreased rsFC within the self-referential network and default mode network might play fundamental roles in the malfunction of information processing, while the core network might act as a dysfunctional hub of regulation. Our meta-analysis is consistent with diffuse hypoconnectivities as a dysregulated brain network model of schizophrenia.

White matter neuron biology and neuropathology in schizophrenia

Schizophrenia is considered a neurodevelopmental disorder as it often manifests before full brain maturation and is also a cerebral cortical disorder where deficits in GABAergic interneurons are prominent. Whilst most neurons are located in cortical and subcortical grey matter regions, a smaller population of neurons reside in white matter tracts of the primate and to a lesser extent, the rodent brain, subjacent to the cortex. These interstitial white matter neurons (IWMNs) have been identified with general markers for neurons [e.g., neuronal nuclear antigen (NeuN)] and with specific markers for neuronal subtypes such as GABAergic neurons. Studies of IWMNs in schizophrenia have primarily focused on their density underneath cortical areas known to be affected in schizophrenia such as the dorsolateral prefrontal cortex. Most of these studies of postmortem brains have identified increased NeuN+ and GABAergic IWMN density in people with schizophrenia compared to healthy controls. Whether IWMNs are involved in the pathogenesis of schizophrenia or if they are increased because of the cortical pathology in schizophrenia is unknown. We also do not understand how increased IWMN might contribute to brain dysfunction in the disorder. Here we review the literature on IWMN pathology in schizophrenia. We provide insight into the postulated functional significance of these neurons including how they may contribute to the pathophysiology of schizophrenia.

Brain Heterogeneity in Schizophrenia and Its Association With Polygenic Risk

Importance

Between-individual variability in brain structure is determined by gene-environment interactions, possibly reflecting differential sensitivity to environmental and genetic perturbations. Magnetic resonance imaging (MRI) studies have revealed thinner cortices and smaller subcortical volumes in patients with schizophrenia. However, group-level comparisons may mask considerable within-group heterogeneity, which has largely remained unnoticed in the literature.

Objectives

To compare brain structural variability between individuals with schizophrenia and healthy controls and to test whether respective variability reflects the polygenic risk score (PRS) for schizophrenia in an independent sample of healthy controls.

Design, Setting, and Participants

This case-control and polygenic risk analysis compared MRI-derived cortical thickness and subcortical volumes between healthy controls and patients with schizophrenia across 16 cohorts and tested for associations between PRS and MRI features in a control cohort from the UK Biobank. Data were collected from October 27, 2004, through April 12, 2018, and analyzed from December 3, 2017, through August 1, 2018.

Main Outcomes and Measures

Mean and dispersion parameters were estimated using double generalized linear models. Vertex-wise analysis was used to assess cortical thickness, and regions-of-interest analyses were used to assess total cortical volume, total surface area, and white matter, subcortical, and hippocampal subfield volumes. Follow-up analyses included within-sample analysis, test of robustness of the PRS threshold, population covariates, outlier removal, and control for image quality.

Results

A comparison of 1151 patients with schizophrenia (mean [SD] age, 33.8 [10.6] years; 68.6% male [n = 790] and 31.4% female [n = 361]) with 2010 healthy controls (mean [SD] age, 32.6 [10.4] years; 56.0% male [n = 1126] and 44.0% female [n = 884]) revealed higher heterogeneity in schizophrenia for cortical thickness and area (t = 3.34), cortical (t = 3.24) and ventricle (t range, 3.15-5.78) volumes, and hippocampal subfields (t range, 2.32-3.55). In the UK Biobank sample of 12 490 participants (mean [SD] age, 55.9 [7.5] years; 48.2% male [n = 6025] and 51.8% female [n = 6465]), higher PRS was associated with thinner frontal and temporal cortices and smaller left CA2/3 (t = -3.00) but was not significantly associated with dispersion.

Conclusions and Relevance

This study suggests that schizophrenia is associated with substantial brain structural heterogeneity beyond the mean differences. These findings may reflect higher sensitivity to environmental and genetic perturbations in patients, supporting the heterogeneous nature of schizophrenia. A higher PRS was associated with thinner frontotemporal cortices and smaller hippocampal subfield volume, but not heterogeneity. This finding suggests that brain variability in schizophrenia results from interactions between environmental and genetic factors that are not captured by the PRS. Factors contributing to heterogeneity in frontotemporal cortices and hippocampus are key to furthering our understanding of how genetic and environmental factors shape brain biology in schizophrenia.

Wnt/β-catenin signaling in brain development and mental disorders: keeping TCF7L2 in mind

Canonical Wnt signaling, which is transduced by β-catenin and lymphoid enhancer factor 1/T cell-specific transcription factors (LEF1/TCFs), regulates many aspects of metazoan development and tissue renewal. Although much evidence has associated canonical Wnt/β-catenin signaling with mood disorders, the mechanistic links are still unknown. Many components of the canonical Wnt pathway are involved in cellular processes that are unrelated to classical canonical Wnt signaling, thus further blurring the picture. The present review critically evaluates the involvement of classical Wnt/β-catenin signaling in developmental processes that putatively underlie the pathology of mental illnesses. Particular attention is given to the roles of LEF1/TCFs, which have been discussed surprisingly rarely in this context. Highlighting recent discoveries, we propose that alterations in the activity of LEF1/TCFs, and particularly of transcription factor 7-like 2 (TCF7L2), result in defects previously associated with neuropsychiatric disorders, including imbalances in neurogenesis and oligodendrogenesis, the functional disruption of thalamocortical circuitry and dysfunction of the habenula.

Mapping causal pathways from genetics to neuropsychiatric disorders using genome-wide imaging genetics: Current status and future directions

Imaging genetics aims to identify genetic variants associated with the structure and function of the human brain. Recently, collaborative consortia have been successful in this goal, identifying and replicating common genetic variants influencing gross human brain structure as measured through magnetic resonance imaging. In this review, we contextualize imaging genetic associations as one important link in understanding the causal chain from genetic variant to increased risk for neuropsychiatric disorders. We provide examples in other fields of how identifying genetic variant associations to disease and multiple phenotypes along the causal chain has revealed a mechanistic understanding of disease risk, with implications for how imaging genetics can be similarly applied. We discuss current findings in the imaging genetics research domain, including that common genetic variants can have a slightly larger effect on brain structure than on risk for disorders like schizophrenia, indicating a somewhat simpler genetic architecture. Also, gross brain structure measurements share a genetic basis with some, but not all, neuropsychiatric disorders, invalidating the previously held belief that they are broad endophenotypes, yet pinpointing brain regions likely involved in the pathology of specific disorders. Finally, we suggest that in order to build a more detailed mechanistic understanding of the effects of genetic variants on the brain, future directions in imaging genetics research will require observations of cellular and synaptic structure in specific brain regions beyond the resolution of magnetic resonance imaging. We expect that integrating genetic associations at biological levels from synapse to sulcus will reveal specific causal pathways impacting risk for neuropsychiatric disorders.

Wnt/β-catenin signaling in brain development and mental disorders: keeping TCF7L2 in mind

Canonical Wnt signaling, which is transduced by β-catenin and lymphoid enhancer factor 1/T cell-specific transcription factors (LEF1/TCFs), regulates many aspects of metazoan development and tissue renewal. Although much evidence has associated canonical Wnt/β-catenin signaling with mood disorders, the mechanistic links are still unknown. Many components of the canonical Wnt pathway are involved in cellular processes that are unrelated to classical canonical Wnt signaling, thus further blurring the picture. The present review critically evaluates the involvement of classical Wnt/β-catenin signaling in developmental processes that putatively underlie the pathology of mental illnesses. Particular attention is given to the roles of LEF1/TCFs, which have been discussed surprisingly rarely in this context. Highlighting recent discoveries, we propose that alterations in the activity of LEF1/TCFs, and particularly of transcription factor 7-like 2 (TCF7L2), result in defects previously associated with neuropsychiatric disorders, including imbalances in neurogenesis and oligodendrogenesis, the functional disruption of thalamocortical circuitry and dysfunction of the habenula.

A preliminary study of cortical morphology in schizophrenia patients with a history of violence

Clinical studies of patients with schizophrenia and a history of violence are challenging both from an ethical and practical perspective, and the neurobiological underpinnings remain largely unknown. We here present a comprehensive account of the brain cortical characteristics associated with violence in schizophrenia. We obtained 3T MRI scans and thorough clinical characterization of schizophrenia patients with a history of violence (murder, attempted murder, criminal assault, SCZ-V, n = 11), schizophrenia patients with no history of violence (SCZ-NV, n = 17), and healthy controls (HC, n = 19). Cortical thickness, area, and folding were analyzed vertex-wise across the cortical mantle (FreeSurfer). SCZ-V had significantly increased cortical folding in the visual and orbitofrontal cortex, and reduced cortical thickness within the precentral-, parietal-, temporal-, and fusiform cortex compared to SCZ-NV, as well as widespread regional thinning and increased folding compared to HC. There were no group differences in cortical area. A major limitation is the small subject sample. If replicated, the results from this pilot study suggest cortical abnormalities in areas involved in sensory processing, emotion recognition, and reward to be of importance to the neurobiology of violence in schizophrenia.

Mitochondrial Dysfunction Leads to Cortical Under-Connectivity and Cognitive Impairment

Under-connectivity between cerebral cortical association areas may underlie cognitive deficits in neurodevelopmental disorders, including the 22q11.2 deletion syndrome (22q11DS). Using the LgDel 22q11DS mouse model, we assessed cellular, molecular, and developmental origins of under-connectivity and its consequences for cognitive function. Diminished 22q11 gene dosage reduces long-distance projections, limits axon and dendrite growth, and disrupts mitochondrial and synaptic integrity in layer 2/3 but not 5/6 projection neurons (PNs). Diminished dosage of Txnrd2, a 22q11 gene essential for reactive oxygen species catabolism in brain mitochondria, recapitulates these deficits in WT layer 2/3 PNs; Txnrd2 re-expression in LgDel layer 2/3 PNs rescues them. Anti-oxidants reverse LgDel- or Txnrd2-related layer 2/3 mitochondrial, circuit, and cognitive deficits. Accordingly, Txnrd2-mediated oxidative stress reduces layer 2/3 connectivity and impairs cognition in the context of 22q11 deletion. Anti-oxidant restoration of mitochondrial integrity, cortical connectivity, and cognitive behavior defines oxidative stress as a therapeutic target in neurodevelopmental disorders.

Prediction, Psychosis, and the Cerebellum

An increasingly influential hypothesis posits that many of the diverse symptoms of psychosis can be viewed as reflecting dysfunctional predictive mechanisms. Indeed, to perceive something is to take a sensory input and make a prediction of the external source of that signal; thus, prediction is perhaps the most fundamental neural computation. Given the ubiquity of prediction, a more challenging problem is to specify the unique predictive role or capability of a particular brain structure. This question is relevant when considering recent claims that one aspect of the predictive deficits observed in psychotic disorders might be related to cerebellar dysfunction, a subcortical structure known to play a critical role in predictive sensorimotor control and perhaps higher-level cognitive function. Here, we review evidence bearing on this question. We first focus on clinical, behavioral, and neuroimaging findings suggesting cerebellar involvement in psychosis and, specifically, schizophrenia. We then review a relatively novel line of research exploring whether computational models of cerebellar motor function can also account for cerebellar involvement in higher-order human cognition, and in particular, language function. We end the review by highlighting some key gaps in these literatures, limitations that currently preclude strong conclusions regarding cerebellar involvement in psychosis.

Antipsychotic treatment and basal ganglia volumes: Exploring the role of receptor occupancy, dosage and remission status

Antipsychotic treatment may affect brain morphology, and enlargement of the basal ganglia (BG) is a replicated finding. Here we investigated associations between antipsychotic treatment and BG volumes in patients with psychotic and bipolar disorders. We hypothesized that current treatment and, among those medicated, higher dosage, estimated D2R occupancy and being in remission would predict larger BG volumes. Structural covariance analysis was performed to examine if correlations between BG volumes and cortical thickness differed by treatment status. 224 patients treated with antipsychotics; 26 previously treated, 29 never treated and 301 healthy controls (HC) were included from the TOP study cohort (NORMENT, Norway). T1-weighted MR images were processed using FreeSurfer. D2R occupancy was estimated based on serum concentration measurements for patients receiving stable monotherapy. Statistical analyses were adjusted for age, gender and estimated intracranial volume (ICV). We found larger right (p < 0.003) and left putamen (p < 0.02) and right globus pallidus (GP) (p < 0.03) in currently medicated patients compared to HC. Bilateral regional cortical thinning was also observed in currently and previously medicated patients compared to HC. In medicated patients, higher chlorpromazine equivalent dose (CPZ) was associated with larger left GP (p < 0.04). There was no association with estimated D2R occupancy (n = 47) or remission status. Lower positive correlation between left putamen volume and cortical thickness of the left lateral occipital cortex was found in medicated patients compared to HC. We replicated the BG enlargement in medicated patients, but found no association with estimated D2R occupancy. Further studies are needed to clarify the underlying mechanisms.

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

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

Common Polygenic Variations for Psychiatric Disorders and Cognition in Relation to Brain Morphology in the General Pediatric Population

OBJECTIVE

This study examined the relation between polygenic scores (PGSs) for 5 major psychiatric disorders and 2 cognitive traits with brain magnetic resonance imaging morphologic measurements in a large population-based sample of children. In addition, this study tested for differences in brain morphology-mediated associations between PGSs for psychiatric disorders and PGSs for related behavioral phenotypes.

METHOD

Participants included 1,139 children from the Generation R Study assessed at 10 years of age with genotype and neuroimaging data available. PGSs were calculated for schizophrenia, bipolar disorder, major depression disorder, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, intelligence, and educational attainment using results from the most recent genome-wide association studies. Image processing was performed using FreeSurfer to extract cortical and subcortical brain volumes.

RESULTS

Greater genetic susceptibility for ADHD was associated with smaller caudate volume (strongest prior = 0.01: β = -0.07, p = .006). In boys, mediation analysis estimates showed that 11% of the association between the PGS for ADHD and the PGS attention problems was mediated by differences in caudate volume (n = 535), whereas mediation was not significant in girls or the entire sample. PGSs for educational attainment and intelligence showed positive associations with total brain volume (strongest prior = 0.5: β = 0.14, p = 7.12 × 10^-8; and β = 0.12, p = 6.87 × 10^-7, respectively).

CONCLUSION

The present findings indicate that the neurobiological manifestation of polygenic susceptibility for ADHD, educational attainment, and intelligence involve early morphologic differences in caudate and total brain volumes in childhood. Furthermore, the genetic risk for ADHD might influence attention problems through the caudate nucleus in boys.

Altered dynamic global signal topography in antipsychotic-naive adolescents with early-onset schizophrenia

Schizophrenia (SCZ) is a severe neuropsychiatric disease associated with dysfunction of brain regions and networks. Recent, functional magnetic resonance imaging (fMRI) studies have determined that the global signal (GS) is an important source of the local neuronal activity. However, the dynamics of this effect in SCZ remains unknown. To address this issue, 39 drug-naive patients with early-onset schizophrenia (EOS) and 31 age-, gender- and education-matched healthy controls underwent resting-state fMRI scans. Dynamic functional connectivity (DFC) was employed to assess the dynamic patterns of the GS in EOS. Dynamic analysis demonstrated that the topography of the GS in EOS can be divided into five different states. In the state1, the GS mainly affected the sensory regions. In the state2, the GS mainly affected the default mode network (DMN). In the state3, the GS mainly affected the frontoparietal network and the cingulate-opercular network. In the state4, the GS mainly affected the sensory and subcortical regions. In the state5, the GS mainly affected the sensory regions and DMN. In particular, the changes in the cerebellum, putamen and supramarginal gyrus was inversely proportional to the clinical symptoms. Our findings demonstrate that the influence of the GS on brain networks is dynamic and changes of this relationship may associate with clinical behavior in SCZ.

Effects of a GWAS-Supported Schizophrenia Variant in the DRD2 Locus on Disease Risk, Anhedonia, and Prefrontal Cortical Thickness

The study aimed to confirm the association of the schizophrenia genome-wide association study (GWAS) hit rs2514218 located near the DRD2 gene with the risk of the disease and to investigate the relationships between rs2514218 and schizophrenia-related clinical and neuroimaging phenotypes. Genotypes at the rs2514218 site were determined for 2148 schizophrenia spectrum patients and 1273 control subjects from the Russian population. In subsets of subjects, we assessed symptomatic dimensions using the Positive and Negative Syndrome Scale (n = 1651) and Temporal Experience of Pleasure Scale (n = 471). At the brain level, gray matter volumes in striatal structures and cortical thickness in the lateral prefrontal cortical regions were investigated (n = 97). Genotype frequencies did not differ between patients and controls. The allelic association analysis yielded a near-threshold p value (p = 0.054), the magnitude (OR = 0.90), and direction of the minor allele (T) effect being in accord with those in the schizophrenia GWAS. Also, patients homozygous for the risk allele C had more severe consummatory anhedonia and a thinner cortex than controls and patients carrying the T allele. The largest effect size of the genotype with diagnosis interaction was seen in the right pars opercularis area. The findings support the role of rs2514218 in schizophrenia risk and presentation and suggest rs2514218 has an influence on brain morphology and negative symptoms.

Maintenance treatment for patients with a first psychotic episode

PURPOSE OF REVIEW

To provide an update of recent studies relevant for maintenance treatment with antipsychotic medication after a first psychotic episode (FEP).

RECENT FINDINGS

Despite controversy derived from a follow-up analysis from an earlier study showing that attempted early discontinuation after remission was associated with improved long-term functioning, most other studies support better long-term outcome with continuous maintenance treatment after the first episode. However, the main question is not whether, but for how long maintenance treatment after FEP should be offered. Consistent evidence shows that withdrawal from antipsychotics increases the risk for a relapse or re-hospitalization. On the other hand, maintenance treatment is associated with the risk to develop burdensome antipsychotic-induced side-effects and one should keep in mind that around 20% of FEP will not have a second episode. In this regard, the decision for maintenance treatment for periods above some months must be the result of a comprehensive risk-benefit evaluation during a shared decision-making process.

SUMMARY

There is no replicated evidence that prognosis can be improved by discontinuing antipsychotic medication after a FEP. There is a clear need for additional studies to develop single-subject outcome predictors and to identify long-term efficacy of maintenance treatment beyond relapse (e.g. recovery).

Structural similarity networks predict clinical outcome in early-phase psychosis

Despite recent advances, there is still a major need for prediction of treatment success in schizophrenia, a condition long considered a disorder of dysconnectivity in the brain. Graph theory provides a means to characterize the connectivity in both healthy and abnormal brains. We calculated structural similarity networks in each participant and hypothesized that the "hubness", i.e., the number of edges connecting a node to the rest of the network, would be associated with clinical outcome. This prospective controlled study took place at an academic research center and included 82 early-phase psychosis patients (23 females; mean age [SD] = 21.6 [5.5] years) and 58 healthy controls. Medications were administered in a double-blind randomized manner, and patients were scanned at baseline prior to treatment with second-generation antipsychotics. Symptoms were assessed with the Brief Psychiatric Rating Scale at baseline and over the course of 12 weeks. Nodal degree of structural similarity networks was computed for each subject and entered as a predictor of individual treatment response into a partial least squares (PLS) regression. The model fit was significant in a permutation test with 1000 permutations (P = 0.006), and the first two PLS regression components explained 29% (95% CI: 27; 30) of the variance in treatment response after cross-validation. Nodes loading strongly on the first PLS component were primarily located in the orbito- and prefrontal cortex, whereas nodes loading strongly on the second PLS component were primarily located in the superior temporal, precentral, and middle cingulate cortex. These data suggest a link between brain network morphology and clinical outcome in early-phase psychosis.

Telomere length is associated with childhood trauma in patients with severe mental disorders

Reduced telomere length (TL) and structural brain abnormalities have been reported in patients with schizophrenia (SZ) and bipolar disorder (BD). Childhood traumatic events are more frequent in SZ and BD than in healthy individuals (HC), and based on recent findings in healthy individuals could represent one important factor for TL and brain aberrations in patients. The study comprised 1024 individuals (SZ [n = 373]; BD [n = 249] and HC [n = 402]). TL was measured by quantitative polymerase chain reaction (qPCR), and childhood trauma was assessed using the Childhood Trauma Questionnaire (CTQ). Diagnosis was obtained by the Structured Clinical Interview (SCID) for the diagnostic and statistical manual of mental disorders-IV (DSM-IV). FreeSurfer was used to obtain regional and global brain volumes from T1-weighted magnetic resonance imaging (MRI) brain scans. All analyses were adjusted for current age and sex. Patients had on average shorter TL (F = 7.87, p = 0.005, Cohen's d = 0.17) and reported more childhood trauma experiences than HC (χ² = 148.9, p < 0.001). Patients with a history of childhood sexual, physical or emotional abuse had shorter TL relative to HC and to patients without a history of childhood abuse (F = 6.93, p = 0.006, Cohen's d = 0.16). After adjusting for childhood abuse, no difference in TL was observed between patients and HC (p = 0.12). There was no statistically significant difference in reported childhood abuse exposure or TL between SZ and BD. Our analyses revealed no significant associations between TL and clinical characteristics or brain morphometry. We demonstrate shorter TL in SZ and BD compared with HC and showed that TL is sensitive to childhood trauma experiences. Further studies are needed to identify the biological mechanisms of this relationship.

Interaction of schizophrenia polygenic risk and cortisol level on pre-adolescent brain structure

The etiology of schizophrenia is multi-factorial with early neurodevelopmental antecedents, likely to result from a complex interaction of genetic and environmental risk. However, few studies have examined how schizophrenia polygenic risk scores (PRS) are moderated by environmental factors in shaping neurodevelopmental brain structure, prior to the onset of psychotic symptoms. Here, we examined whether hair cortisol, a quantitative metric of chronic stress, moderated the association between genetic risk for schizophrenia and pre-adolescent brain structure. This study was embedded within the Generation R Study, involving pre-adolescents of European ancestry assessed regarding schizophrenia PRS, hair cortisol, and brain imaging (n = 498 structural; n = 526 diffusion tensor imaging). Linear regression was performed to determine the association between schizophrenia PRS, hair cortisol level, and brain imaging outcomes. Although no single measure exceeded the multiple testing threshold, nominally significant interactions were observed for total ventricle volume (P_interaction = 0.02) and global white matter microstructure (P_interaction = 0.01) - two of the most well replicated brain structural findings in schizophrenia. These findings provide suggestive evidence for the joint effects of schizophrenia liability and cortisol levels on brain correlates in the pediatric general population. Given the widely replicated finding of ventricular enlargement and lower white matter integrity among schizophrenia patients, our findings generate novel hypotheses for future research on gene-environment interactions affecting the neurodevelopmental pathophysiology of schizophrenia.

A promising structural magnetic resonance imaging assessment in patients with preclinical cognitive decline and diabetes mellitus

Subjective cognitive decline (SCD) is frequently reported in diabetic patients. Diabetes mellitus (DM) is associated with changes in the microstructure of the brain arise in diabetic patients, including changes in gray matter volume (GMV). However, the underlying mechanisms of changes in GMV in DM patients with cognitive impairment remain uncertain. Here, we present an overview of amyloid-β-dependent cognitive impairment in DM patients with SCD. Moreover, we review the evolving insights from studies on the GMV changes in GMV and cognitive dysfunction to which provide the mechanisms of cognitive impairment in T2DM. Ultimately, the novel structural magnetic resonance imaging (MRI) protocol was used for detecting neuroimaging biomarkers that can predict the clinical outcomes in diabetic patients with SCD. A reliable MRI protocol would be helpful to detect neurobiomarkers, and to understand the pathological mechanisms of preclinical cognitive impairment in diabetic patients.

Comprehensive functional genomic resource and integrative model for the human brain

Despite progress in defining genetic risk for psychiatric disorders, their molecular mechanisms remain elusive. Addressing this, the PsychENCODE Consortium has generated a comprehensive online resource for the adult brain across 1866 individuals. The PsychENCODE resource contains ~79,000 brain-active enhancers, sets of Hi-C linkages, and topologically associating domains; single-cell expression profiles for many cell types; expression quantitative-trait loci (QTLs); and further QTLs associated with chromatin, splicing, and cell-type proportions. Integration shows that varying cell-type proportions largely account for the cross-population variation in expression (with >88% reconstruction accuracy). It also allows building of a gene regulatory network, linking genome-wide association study variants to genes (e.g., 321 for schizophrenia). We embed this network into an interpretable deep-learning model, which improves disease prediction by ~6-fold versus polygenic risk scores and identifies key genes and pathways in psychiatric disorders.

Antipsychotic and benzodiazepine use and brain morphology in schizophrenia and affective psychoses - Systematic reviews and birth cohort study

The aim of this paper was to investigate differences in brain structure volumes between schizophrenia and affective psychoses, and whether cumulative lifetime antipsychotic or benzodiazepine doses relate to brain morphology in these groups. We conducted two systematic reviews on the topic and investigated 44 schizophrenia cases and 19 with affective psychoses from the Northern Finland Birth Cohort 1966. The association between lifetime antipsychotic and benzodiazepine dose and brain MRI scans at the age of 43 was investigated using linear regression. Intracranial volume, sex, illness severity, and antipsychotic/benzodiazepine doses were used as covariates. There were no differences between the groups in brain structure volumes. In schizophrenia, after adjusting for benzodiazepine dose and symptoms, a negative association between lifetime antipsychotic dose and the nucleus accumbens volume remained. In affective psychoses, higher lifetime benzodiazepine dose associated with larger volumes of total gray matter and hippocampal volume after controlling for antipsychotic use and symptoms. It seems that in addition to antipsychotics, the severity of symptoms and benzodiazepine dose are also associated with brain structure volumes. These results suggest, that benzodiazepine effects should also be investigated also independently and not only as a confounder.