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Background: Enlarged pituitary gland volume could be a marker of psychotic disorders. However, previous studies report conflicting results. To better understand the role of the pituitary gland in psychosis, we examined a large transdiagnostic sample of individuals with psychotic disorders., Methods: The study included 751 participants (174 with schizophrenia, 114 with schizoaffective disorder, 167 with psychotic bipolar disorder, and 296 healthy controls) across six sites in the Bipolar-Schizophrenia Network on Intermediate Phenotypes consortium. Structural magnetic resonance images were obtained, and pituitary gland volumes were measured using the MAGeT brain algorithm. Linear mixed models examined between-group differences with controls and among patient subgroups based on diagnosis, as well as how pituitary volumes were associated with symptom severity, cognitive function, antipsychotic dose, and illness duration., Results: Mean pituitary gland volume did not significantly differ between patients and controls. No significant effect of diagnosis was observed. Larger pituitary gland volume was associated with greater symptom severity ( F = 13.61, p = 0.0002), lower cognitive function ( F = 4.76, p = 0.03), and higher antipsychotic dose ( F = 5.20, p = 0.02). Illness duration was not significantly associated with pituitary gland volume. When all variables were considered, only symptom severity significantly predicted pituitary gland volume ( F = 7.54, p = 0.006)., Conclusions: Although pituitary volumes were not increased in psychotic disorders, larger size may be a marker associated with more severe symptoms in the progression of psychosis. This finding helps clarify previous inconsistent reports and highlights the need for further research into pituitary gland-related factors in individuals with psychosis.

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.)

Background and Hypothesis: Schizophrenia is associated with widespread cortical thinning and abnormality in the structural covariance network, which may reflect connectome alterations due to treatment effect or disease progression. Notably, patients with treatment-resistant schizophrenia (TRS) have stronger and more widespread cortical thinning, but it remains unclear whether structural covariance is associated with treatment response in schizophrenia., Study Design: We organized a multicenter magnetic resonance imaging study to assess structural covariance in a large population of TRS and non-TRS, who had been resistant and responsive to non-clozapine antipsychotics, respectively. Whole-brain structural covariance for cortical thickness was assessed in 102 patients with TRS, 77 patients with non-TRS, and 79 healthy controls (HC). Network-based statistics were used to examine the difference in structural covariance networks among the 3 groups. Moreover, the relationship between altered individual differentiated structural covariance and clinico-demographics was also explored., Study Results: Patients with non-TRS exhibited greater structural covariance compared with HC, mainly in the fronto-temporal and fronto-occipital regions, while there were no significant differences in structural covariance between TRS and non-TRS or HC. Higher individual differentiated structural covariance was associated with lower general scores of the Positive and Negative Syndrome Scale in the non-TRS group, but not in the TRS group., Conclusions: These findings suggest that reconfiguration of brain networks via coordinated cortical thinning is related to treatment response in schizophrenia. Further longitudinal studies are warranted to confirm if greater structural covariance could serve as a marker for treatment response in this disease., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Introduction: Schizophrenia-spectrum disorders (SSD) represent one of the leading causes of disability worldwide and are usually underpinned by neurodevelopmental brain abnormalities observed on a structural and functional level. Nuclear medicine imaging studies of cerebral blood flow (CBF) have already provided insights into the pathophysiology of these disorders. Recent developments in non-invasive MRI techniques such as arterial spin labeling (ASL) have allowed broader examination of CBF across SSD prompting us to conduct an updated literature review of MRI-based perfusion studies. In addition, we conducted a focused meta-analysis of whole brain studies to provide a complete picture of the literature on the topic., Methods: A systematic OVID search was performed in Embase, MEDLINEOvid, and PsycINFO. Studies eligible for inclusion in the review involved: 1) individuals with SSD, first-episode psychosis or clinical-high risk for psychosis, or; 2) had healthy controls for comparison; 3) involved MRI-based perfusion imaging methods; and 4) reported CBF findings. No time span was specified for the database queries (last search: 08/2022). Information related to participants, MRI techniques, CBF analyses, and results were systematically extracted. Whole-brain studies were then selected for the meta-analysis procedure. The methodological quality of each included studies was assessed., Results: For the systematic review, the initial Ovid search yielded 648 publications of which 42 articles were included, representing 3480 SSD patients and controls. The most consistent finding was that negative symptoms were linked to cortical fronto-limbic hypoperfusion while positive symptoms seemed to be associated with hyperperfusion, notably in subcortical structures. The meta-analysis integrated results from 13 whole-brain studies, across 426 patients and 401 controls, and confirmed the robustness of the hypoperfusion in the left superior and middle frontal gyri and right middle occipital gyrus while hyperperfusion was found in the left putamen., Conclusion: This updated review of the literature supports the implication of hemodynamic correlates in the pathophysiology of psychosis symptoms and disorders. A more systematic exploration of brain perfusion could complete the search of a multimodal biomarker of SSD., Competing Interests: Declaration of Competing Interest ML reports grants from Otsuka Lundbeck Alliance, diaMentis personal fees from Otsuka Canada, personal fees from Lundbeck Canada, grants and personal fees from Janssen, and personal fees from MedAvante-Prophase, outside the submitted work. Salary awards include Canadian Institutes for Health Research (MC, ML), Fonds de la Recherche en Santé du Québec (OP, MC, ML), James McGill Professorship (ML), Quebec Bio-Imaging Network (DRC) and Michal Renata Hornstein in Cardiovascular Imaging (CJG). AM has received fees for lectures at conferences sponsored by Lundbeck and Otsuka, Global in the past and salary awards from Canada Research Chair Program., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Episodic memory ability relies on hippocampal-prefrontal connectivity. However, few studies have examined relationships between memory performance and white matter (WM) microstructure in hippocampal-prefrontal pathways in schizophrenia-spectrum disorder (SSDs). Here, we investigated these relationships in individuals with first-episode psychosis (FEP) and chronic schizophrenia-spectrum disorders (SSDs) using tractography analysis designed to interrogate the microstructure of WM tracts in the hippocampal-prefrontal pathway. Measures of WM microstructure (fractional anisotropy [FA], radial diffusivity [RD], and axial diffusivity [AD]) were obtained for 47 individuals with chronic SSDs, 28 FEP individuals, 52 older healthy controls, and 27 younger healthy controls. Tractography analysis was performed between the hippocampus and three targets involved in hippocampal-prefrontal connectivity (thalamus, amygdala, nucleus accumbens). Measures of WM microstructure were then examined in relation to episodic memory performance separately across each group. Both those with FEP and chronic SSDs demonstrated impaired episodic memory performance. However, abnormal WM microstructure was only observed in individuals with chronic SSDs. Abnormal WM microstructure in the hippocampal-thalamic pathway in the right hemisphere was associated with poorer memory performance in individuals with chronic SSDs. These findings suggest that disruptions in WM microstructure in the hippocampal-prefrontal pathway may contribute to memory impairments in individuals with chronic SSDs but not FEP., (© 2021. Springer-Verlag GmbH Germany, part of Springer Nature.)

Relatives of individuals with schizophrenia have a higher risk of developing the illness compared to the general population. Thus, youth at familial high risk (FHR) offer a unique opportunity to identify neuroimaging-based endophenotypes of psychosis. Previous studies have identified lower amygdalo-hippocampal volume in FHR, as well as lower verbal memory and emotion recognition. However, whether these phenotypes increase the risk of transition to psychosis remains unclear. To determine if individuals who develop psychosis have abnormal neurodevelopmental trajectories of the amygdala and hippocampus, we investigated longitudinal changes of these structures in a unique cohort of 82 youth FHR and 56 healthy controls during a 3-year period. Ten individuals from the FHR group converted to psychosis. Longitudinal changes were compared using linear mixed-effects models. Group differences in verbal memory and emotion recognition performance at baseline were also analyzed. Surface-based morphometry measures revealed variation in amygdalar shape (concave shape of the right dorsomedial region) in those who converted to psychosis. Significantly lower emotion recognition performance at baseline was observed in converters. Percent trial-to-trial transfer on the verbal learning task was also significantly impaired in FHR, independently of the conversion status. Our results identify abnormal shape development trajectories in the dorsomedial amygdala and lower emotion recognition abilities as phenotypes of transition to psychosis. Our findings illustrate potential markers for early identification of psychosis, aiding prevention efforts in youth at risk of schizophrenia., (© 2022. The Author(s).)

Despite previous neuroimaging studies demonstrating morphological abnormalities of the thalamus and other subcortical structures in patients with schizophrenia, the potential role of the thalamus and its subdivisions in the pathophysiology of this illness remains elusive. It is also unclear whether similar changes of these structures occur in individuals at high risk for psychosis. In this study, magnetic resonance imaging was employed with the Multiple Automatically Generated Templates (MAGeT) brain segmentation algorithm to determine volumes of the thalamic subdivisions, the striatum (caudate, putamen, and nucleus accumbens), and the globus pallidus in 62 patients with schizophrenia, 38 individuals with an at-risk mental state (ARMS) [4 of whom (10.5%) subsequently developed schizophrenia], and 61 healthy subjects. Cognitive function of the patients was assessed by using the Brief Assessment of Cognition in Schizophrenia (BACS) and the Schizophrenia Cognition Rating Scale (SCoRS). Thalamic volume (particularly the medial dorsal and ventral lateral nuclei) was smaller in the schizophrenia group than the ARMS and control groups, while there were no differences for the striatum and globus pallidus. In the schizophrenia group, the reduction of thalamic ventral lateral nucleus volume was significantly associated with lower BACS score. The pallidal volume was positively correlated with the dose of antipsychotic treatment in the schizophrenia group. These results suggest that patients with schizophrenia, but not those with ARMS, exhibit volume reduction in specific thalamic subdivisions, which may underlie core clinical features of this illness., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Exposure to maternal immune activation (MIA) in utero is a risk factor for neurodevelopmental and psychiatric disorders. MIA-induced deficits in adolescent and adult offspring have been well characterized; however, less is known about the effects of MIA exposure on embryo development. To address this gap, we performed high-resolution ex vivo MRI to investigate the effects of early (gestational day [GD]9) and late (GD17) MIA exposure on embryo (GD18) brain structure. We identify striking neuroanatomical changes in the embryo brain, particularly in the late-exposed offspring. We further examined the putative neuroanatomical underpinnings of MIA timing in the hippocampus using electron microscopy and identified differential effects due to MIA timing. An increase in apoptotic cell density was observed in the GD9-exposed offspring, while an increase in the density of neurons and glia with ultrastructural features reflective of increased neuroinflammation and oxidative stress was observed in GD17-exposed offspring, particularly in females. Overall, our findings integrate imaging techniques across different scales to identify differential impact of MIA timing on the earliest stages of neurodevelopment.

Background: Abnormalities in the anterior cingulate cortex (ACC) are thought to play an important role in the pathophysiology of schizophrenia. Given regional variations in ACC structure, the present study aimed to examine ACC structural subdivisions and their relationships to treatment resistance and glutamatergic levels in schizophrenia., Methods: This study included 100 patients with schizophrenia and 52 healthy controls from 2 cohorts. We applied non-negative matrix factorization to identify accurate and stable spatial components of ACC structure. Between groups, we compared ACC structural indices in each spatial component based on treatment resistance or response and tested relationships with ACC glutamate + glutamine levels., Results: We detected reductions in cortical thickness and increases in mean diffusivity in the spatial components on the surface of the cingulate sulcus, especially in patients with treatment-resistant and clozapine-resistant schizophrenia. Notably, mean diffusivity in these components was higher in patients who did not respond to clozapine compared to those who did. Furthermore, these ACC structural alterations were related to elevated ACC glutamate + glutamine levels but not related to symptomatology or antipsychotic dose., Limitations: Sample sizes, cross-sectional findings and mixed antipsychotic status were limitations of this study., Conclusion: This study identified reproducible abnormalities in ACC structures in patients with treatment-resistant and clozapine-resistant schizophrenia. Given that these spatial components play a role in inhibitory control, the present study strengthens the notion that glutamate-related disinhibition is a common biological feature of treatment resistance in schizophrenia., Competing Interests: Conflict of interest: E. Plitman has received research support from an Ontario Graduate Scholarship (OGS), a Canadian Institutes of Health Research (CIHR) Canada Graduate Scholarship–Master’s, a CIHR Vanier Canada Graduate Scholarship and the Healthy Brains for Healthy Lives Postdoctoral Fellowship. Y. Iwata has received fellowship grants from the CIHR, research support from the Japan Society for the Promotion of Science, the Japanese Society of Clinical Neuropsychopharmacology, Inokashira Hospital Grants for psychiatry research, manuscript fees from Dainippon Sumitomo Pharma and speaker’s fees from Eli Lilly, Meiji-Seika Pharma, Mochida Pharmaceutical and Yoshitomi Yakuhin within the past 3 years. Y. Noda has received a Grant-in-Aid for Young Scientists (KAKENHI); research grants from AMED; an investigator-initiated clinical study grant from Teijin Pharma Ltd.; research grants from the Japan Health Foundation, the Meiji Yasuda Mental Health Foundation, the Mitsui Life Social Welfare Foundation, the Takeda Science Foundation, the Senshin Medical Research Foundation, the Health Science Center Foundation, the Mochida Memorial Foundation for Medical and Pharmaceutical Research, the Taiju Life Social Welfare Foundation, and Daiichi Sankyo Scholarship Donation Program; and equipment-in-kind support for an investigator-initiated study from Magventure Inc, Inter Reha Co., Ltd., Rogue Resolutions Ltd. and Miyuki Giken Co., Ltd. H. Uchida has received grants from Eisai, Otsuka Pharmaceutical, Dainippon-Sumitomo Pharma, Mochida Pharmaceutical, Meiji-Seika Pharmaceutical and Novartis; speaker’s honoraria from Otsuka Pharmaceutical, Eli Lilly, Shionogi, Pfizer, Yoshitomi Yakuhin, Dainippon-Sumitomo Pharma, Meiji-Seika Pharma, MSD and Janssen Pharmaceutical; and advisory panel payments from Dainippon-Sumitomo Pharma within the past 3 years. M. Mimura has received research support from the Japan Society for the Promotion of Science and grants or speaker’s honoraria from Daiichi Sankyo, Dainippon-Sumitomo Pharma, Eisai, Eli Lilly, Fuji Film RI Pharma, Janssen Pharmaceutical, Mochida Pharmaceutical, MSD, Nippon Chemipher, Novartis Pharma, Ono Yakuhin, Otsuka Pharmaceutical, Pfizer, Takeda Yakuhin, Tsumura and Yoshitomi Yakuhin within the past 3 years. A. Graff-Guerrero has received research support from the following external funding agencies: CIHR, the US National Institutes of Health, the Ontario Mental Health Foundation, the National Alliance for Research on Schizophrenia and Depression, Mexico Instituto de Ciencia y Tecnología del Distrito Federal, Consejo Nacional de Ciencia y Tecnología, the Ministry of Economic Development and Innovation of Ontario, the Ontario Academic Health Science Center Alternate Funding Plan Innovation Fund and the W. Garfield Weston Foundation. M. Chakravarty has received research funding from the Weston Brain Institute, the Alzheimer’s Association and the Michael J. Fox Foundation. He is currently receiving support from the CIHR, the National Sciences and Engineering Research Council of Canada and McGill University’s Healthy Brains for Healthy Lives Initiative. He is an associated editor of JPN, but was not involved in the review or decision to accept this paper for publication. S. Nakajima has received grants from the Japan Society for the Promotion of Science, AMED, the Japan Research Foundation for Clinical Pharmacology, the Naito Foundation, the Takeda Science Foundation, the Uehara Memorial Foundation and the Daiichi Sankyo Scholarship Donation Program within the past 3 years, as well as research support, manuscript fees or speaker’s honoraria from Dainippon Sumitomo Pharma, Meiji-Seika Pharma, Otsuka Pharmaceutical, Shionogi and Yoshitomi Yakuhin within the past 3 years. No other competing interests declared., (© 2022 CMA Impact Inc. or its licensors.)

Objective: Brain-based Biotypes for psychotic disorders have been developed as part of the B-SNIP consortium to create neurobiologically distinct subgroups within idiopathic psychosis, independent from traditional phenomenological diagnostic methods. In the current study, we aimed to validate the Biotype model by assessing differences in volume and shape of the amygdala and hippocampus contrasting traditional clinical diagnoses with Biotype classification., Methods: A total of 811 participants from 6 sites were included: probands with schizophrenia (n = 199), schizoaffective disorder (n = 122), psychotic bipolar disorder with psychosis (n = 160), and healthy controls (n = 330). Biotype classification, previously developed using cognitive and electrophysiological data and K-means clustering, was used to categorize psychosis probands into 3 Biotypes, with Biotype-1 (B-1) showing reduced neural salience and severe cognitive impairment. MAGeT-Brain segmentation was used to determine amygdala and hippocampal volumetric data and shape deformations., Results: When using Biotype classification, B-1 showed the strongest reductions in amygdala-hippocampal volume and the most widespread shape abnormalities. Using clinical diagnosis, probands with schizophrenia and schizoaffective disorder showed the most significant reductions of amygdala and hippocampal volumes and the most abnormal hippocampal shape compared with healthy controls. Biotype classification provided the strongest neuroanatomical differences compared with conventional DSM diagnoses, with the best discrimination seen using bilateral amygdala and right hippocampal volumes in B-1., Conclusion: These findings characterize amygdala and hippocampal volumetric and shape abnormalities across the psychosis spectrum. Grouping individuals by Biotype showed greater between-group discrimination, suggesting a promising approach and a favorable target for characterizing biological heterogeneity across the psychosis spectrum., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Neuroimaging genomic studies of autism spectrum disorder and schizophrenia have mainly adopted a 'top-down' approach, beginning with the behavioural diagnosis, and moving down to intermediate brain phenotypes and underlying genetic factors. Advances in imaging and genomics have been successfully applied to increasingly large case-control studies. As opposed to diagnostic-first approaches, the bottom-up strategy begins at the level of molecular factors enabling the study of mechanisms related to biological risk, irrespective of diagnoses or clinical manifestations. The latter strategy has emerged from questions raised by top-down studies: why are mutations and brain phenotypes over-represented in individuals with a psychiatric diagnosis? Are they related to core symptoms of the disease or to comorbidities? Why are mutations and brain phenotypes associated with several psychiatric diagnoses? Do they impact a single dimension contributing to all diagnoses? In this review, we aimed at summarizing imaging genomic findings in autism and schizophrenia as well as neuropsychiatric variants associated with these conditions. Top-down studies of autism and schizophrenia identified patterns of neuroimaging alterations with small effect-sizes and an extreme polygenic architecture. Genomic variants and neuroimaging patterns are shared across diagnostic categories suggesting pleiotropic mechanisms at the molecular and brain network levels. Although the field is gaining traction; characterizing increasingly reproducible results, it is unlikely that top-down approaches alone will be able to disentangle mechanisms involved in autism or schizophrenia. In stark contrast with top-down approaches, bottom-up studies showed that the effect-sizes of high-risk neuropsychiatric mutations are equally large for neuroimaging and behavioural traits. Low specificity has been perplexing with studies showing that broad classes of genomic variants affect a similar range of behavioural and cognitive dimensions, which may be consistent with the highly polygenic architecture of psychiatric conditions. The surprisingly discordant effect sizes observed between genetic and diagnostic first approaches underscore the necessity to decompose the heterogeneity hindering case-control studies in idiopathic conditions. We propose a systematic investigation across a broad spectrum of neuropsychiatric variants to identify putative latent dimensions underlying idiopathic conditions. Gene expression data on temporal, spatial and cell type organization in the brain have also considerable potential for parsing the mechanisms contributing to these dimensions' phenotypes. While large neuroimaging genomic datasets are now available in unselected populations, there is an urgent need for data on individuals with a range of psychiatric symptoms and high-risk genomic variants. Such efforts together with more standardized methods will improve mechanistically informed predictive modelling for diagnosis and clinical outcomes., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Many copy number variants (CNVs) confer risk for the same range of neurodevelopmental symptoms and psychiatric conditions including autism and schizophrenia. Yet, to date neuroimaging studies have typically been carried out one mutation at a time, showing that CNVs have large effects on brain anatomy. Here, we aimed to characterize and quantify the distinct brain morphometry effects and latent dimensions across 8 neuropsychiatric CNVs. We analyzed T1-weighted MRI data from clinically and non-clinically ascertained CNV carriers (deletion/duplication) at the 1q21.1 (n = 39/28), 16p11.2 (n = 87/78), 22q11.2 (n = 75/30), and 15q11.2 (n = 72/76) loci as well as 1296 non-carriers (controls). Case-control contrasts of all examined genomic loci demonstrated effects on brain anatomy, with deletions and duplications showing mirror effects at the global and regional levels. Although CNVs mainly showed distinct brain patterns, principal component analysis (PCA) loaded subsets of CNVs on two latent brain dimensions, which explained 32 and 29% of the variance of the 8 Cohen's d maps. The cingulate gyrus, insula, supplementary motor cortex, and cerebellum were identified by PCA and multi-view pattern learning as top regions contributing to latent dimension shared across subsets of CNVs. The large proportion of distinct CNV effects on brain morphology may explain the small neuroimaging effect sizes reported in polygenic psychiatric conditions. Nevertheless, latent gene brain morphology dimensions will help subgroup the rapidly expanding landscape of neuropsychiatric variants and dissect the heterogeneity of idiopathic conditions., (© 2021. The Author(s).)

Widespread structural brain abnormalities have been consistently reported in schizophrenia, but their relation to the heterogeneous clinical manifestations remains unknown. In particular, it is unclear whether anatomical abnormalities in discrete regions give rise to discrete symptoms or whether distributed abnormalities give rise to the broad clinical profile associated with schizophrenia. Here, we apply a multivariate data-driven approach to investigate covariance patterns between multiple-symptom domains and distributed brain abnormalities in schizophrenia. Structural magnetic resonance imaging and clinical data were derived from one discovery sample (133 patients and 113 controls) and one independent validation sample (108 patients and 69 controls). Disease-related voxel-wise brain abnormalities were estimated using deformation-based morphometry. Partial least-squares analysis was used to comprehensively map clinical, neuropsychological, and demographic data onto distributed deformation in a single multivariate model. The analysis identified 3 latent clinical-anatomical dimensions that collectively accounted for 55% of the covariance between clinical data and brain deformation. The first latent clinical-anatomical dimension was replicated in an independent sample, encompassing cognitive impairments, negative symptom severity, and brain abnormalities within the default mode and visual networks. This cognitive-negative dimension was associated with low socioeconomic status and was represented across multiple races. Altogether, we identified a continuous cognitive-negative dimension of schizophrenia, centered on 2 intrinsic networks. By simultaneously taking into account both clinical manifestations and neuroanatomical abnormalities, the present results open new avenues for multi-omic stratification and biotyping of individuals with schizophrenia., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.)

Background: A growing body of neuroimaging research has revealed a relationship between blunted activation of the ventral striatum (VS) and apathy in schizophrenia. In contrast, the association between reduced striatal volume and apathy is less well established, while the relationship between VS function and structure in patients with schizophrenia remains an open question. Here, we aimed to replicate previous structural findings in a larger independent sample and to investigate the relationship between VS hypoactivation and VS volume., Methods: We included brain structural magnetic resonance imaging (MRI) data from 60 patients with schizophrenia (SZ) that had shown an association of VS hypoactivation with apathy during reward anticipation and 58 healthy controls (HC). To improve replicability, we applied analytical methods employed in two previously published studies: Voxel-based morphometry and the Multiple Automatically Generated Templates (MAGeT) algorithm. VS and dorsal striatum (DS) volume were correlated with apathy correcting for age, gender and total brain volume. Additionally, left VS activity was correlated with left VS volume., Results: We failed to replicate the association between apathy and reduced VS volume and did not find a correlation with DS volume. Functional and structural left VS measures exhibited a trend-level correlation (r s  = 0.248, p = 0.067, r 2  = 0.06)., Conclusions: Our present data suggests that functional and structural striatal neuroimaging correlates of apathy can occur independently. Replication of previous findings may have been limited by other factors (medication, illness duration, age) potentially related to striatal volume changes in SZ. Finally, associations between reward-related VS function and structure should be further explored., Competing Interests: Declaration of competing interest SK has received royalties for cognitive test and training software from Schuhfried. The other authors declare that they have no conflicts of interest., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Previous diffusion tensor imaging (DTI) studies have reported white matter alterations in patients with schizophrenia. Notably, one third of this population does not respond to first-line antipsychotics and is thus referred to as treatment-resistant schizophrenia (TRS). Despite potentially distinct neural bases between TRS and non-TRS, few studies have compared white matter integrity between these groups. In order to reflect clinical picture of TRS, we enrolled TRS patients who had severe symptoms. According to the consensus criteria for TRS. TRS was defined by severe positive symptomatology despite optimal antipsychotic treatment. Fractional anisotropy (FA), an index of white matter integrity, was examined by DTI and analyzed with tract-based spatial statistics in 24 TRS patients (mean PANSS = 108.9), 28 non-TRS patients (mean PANSS = 50.0), and 27 healthy controls (HCs) for group comparison. Additionally, correlation analyses were conducted between FA values and symptomatology. The TRS group had lower FA values in multiple tracts (cerebral peduncle, corona radiata, corpus callosum, external and internal capsules, posterior thalamic radiation, sagittal stratum, superior longitudinal fasciculus, tapetum, and uncinate fasciculus) compared to the HC group as well as the non-TRS group (p < .05; family-wise error-corrected), while no differences were found between the non-TRS and HC groups. In the TRS group, FA values in most of the tracts (other than the left anterior limb of internal capsule, left cerebral peduncle, and right uncinate fasciculus) were negatively correlated with the Positive and Negative Syndrome Scale total scores, and negative and general symptom scores. No such relationships were found in the non-TRS group. The identified white matter integrity deficits may reflect the pathophysiology of TRS., Competing Interests: Declaration of Competing Interest YN has received a Grant-in-Aid for Young Scientists (KAKENHI), a research grant from Japan Agency for Medical Research and Development (AMED), an investigator-initiated clinical study grant from TEIJIN PHARMA LIMITED. YN also receives research grants from Japan Health Foundation, Meiji Yasuda Mental Health Foundation, Mitsui Life Social Welfare Foundation, Takeda Science Foundation, SENSHIN Medical Research Foundation, Health Science Center Foundation, Mochida Memorial Foundation for Medical and Pharmaceutical Research, and Daiichi Sankyo Scholarship Donation Program. He has received research supports from Otsuka Pharmaceutical, Shionogi, and Meiji Seika Pharma. YN also receives equipment-in-kind supports for an investigator-initiated study from Magventure Inc., Inter Reha Co., Ltd., Rogue Resolutions Ltd., and Miyuki Giken Co., Ltd. EP has received research support from an Ontario Graduate Scholarship (OGS), a Canadian Institutes of Health Research (CIHR) Canada Graduate Scholarship-Master's, a CIHR Vanier Canada Graduate Scholarship, and he currently receives research support from the Healthy Brains for Healthy Lives Postdoctoral Fellowship. MMC has received research funding from the Weston Brain Institute, Alzheimer's Association, and Michael J. Fox Foundation. He is currently receiving support from the Canadian Institutes of Health Research, National Sciences and Engineering Research Council of Canada, and McGill University's Healthy Brains for Healthy Lives Initiative. AG-G has received research support from the following external funding agencies: CIHR, U.S National Institutes of Health, Ontario Mental Health Foundation, National Alliance for Research on Schizophrenia and Depression, Mexico Instituto de Ciencia y Tecnología del Distrito Federal, Consejo Nacional de Ciencia y Tecnología, Ministry of Economic Development and Innovation of Ontario, Ontario Academic Health Science Center Alternate Funding Plan Innovation Fund, and W. Garfield Weston Foundation. HU has received grants from Eisai, Otsuka Pharmaceutical, Dainippon-Sumitomo Pharma, Mochida Pharmaceutical, Meiji-Seika Pharmaceutical, and Novartis; speaker's honoraria from Otsuka Pharmaceutical, Eli Lilly, Shionogi, Pfizer, Yoshitomi Yakuhin, Dainippon-Sumitomo Pharma, Meiji-Seika Pharma, MSD, and Janssen Pharmaceutical; and advisory panel payments from Dainippon-Sumitomo Pharma within the past three years. MM has received research support from Japan Society for the Promotion of Science and grants or speaker's honoraria from Daiichi Sankyo, Dainippon-Sumitomo Pharma, Eisai, Eli Lilly, Fuji Film RI Pharma, Janssen Pharmaceutical, Mochida Pharmaceutical, MSD, Nippon Chemipher, Novartis Pharma, Ono Yakuhin, Otsuka Pharmaceutical, Pfizer, Takeda Yakuhin, Tsumura, and Yoshitomi Yakuhin within the past three years. SN has received fellowship grants from CIHR, Japan Research Foundation for Clinical Pharmacology, Naito Foundation, Takeda Science Foundation, Uehara Memorial Foundation, and Daiichi Sankyo Scholarship Donation Program within the past three years. SN has also received research supports, manuscript fees or speaker's honoraria from Dainippon Sumitomo Pharma, Meiji-Seika Pharma, Otsuka Pharmaceutical, Shionogi, and Yoshitomi Yakuhin within the past three years. Other authors have no financial or other relationship relevant to the subject of this manuscript., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Treatment-resistant schizophrenia may be related to structural brain alterations. However, the mechanisms underlying these changes remain unclear. The present study had two main aims: (1) to explore differences in cortical thickness between patients with treatment-resistant schizophrenia non-responsive to clozapine (ultra-treatment-resistant schizophrenia, UTRS), patients with treatment-resistant schizophrenia responsive to clozapine (Cloz-Resp), patients responsive to first-line non-clozapine antipsychotics (FL-Resp), and healthy controls (HCs); and (2) to test our hypothesis of structural compromise as a manifestation of neurotoxic effects from elevated glutamate (Glu) (i.e. glutamate-mediated excitotoxicity) by examining the relationships between glutamatergic neurometabolite levels (Glu and glutamate + glutamine (Glx)) in the dorsal anterior cingulate cortex (dACC) and cortical thickness. T1-weighted images and 1 H-MRS data were obtained from UTRS (n = 24), Cloz-Resp (n = 25), FL-Resp (n = 19), and HCs (n = 26). Vertex-wise analyses showed that patients with UTRS had widespread cortical thinning in the bilateral frontal, temporal, parietal, and occipital gyri compared to HCs and FL-Resp patients. In the patient group, negative associations were found between dACC Glx levels and cortical thickness in the right dorsolateral prefrontal cortex after correcting for multiple comparisons and controlling for age, sex, antipsychotic dose, and illness severity. In conclusion, glutamate-mediated excitotoxicity may be one of the mechanisms underlying structural compromise seen in treatment-resistant schizophrenia. Future studies should longitudinally examine the associations between glutamatergic neurometabolite levels and cortical thickness in the context of treatment and illness progression., Competing Interests: Declaration of competing interest Dr. Plitman reports receiving funding from Canadian Institute of Health Research (CIHR) and the Healthy Brains for Healthy Lives Postdoctoral Fellowship. Dr. Iwata reports receiving fellowship grants from Keio University Medical Science Foundation, Mitsukoshi Foundation, Japan Foundation for Aging and Health, and manuscript fees from Dainippon Sumitomo Pharma. Dr. Nakajima has received fellowship grants from CIHR, research support from Japan Society for the Promotion of Science, Japan Agency for Medical Research and Development, Japan Research Foundation for Clinical Pharmacology, Naito Foundation, Takeda Science Foundation, Uehara Memorial Foundation, Daiichi Sankyo, and manuscript fees or speaker's honoraria from Dainippon Sumitomo Pharma and Yoshitomi Yakuhin within the past three years. Dr. Hahn reports being on an advisory board for Alkermes in the past. Dr. Remington reports external funding from CIHR, travel support from Neurocrine Biosciences, and research support from HLS. Dr. Gerretsen reports receiving research support from CIHR, Ontario Ministry of Health and Long-Term Care, Ontario Mental Health Foundation (OMHF), and the Centre for Addiction and Mental Health (CAMH). Dr. Graff-Guerrero has received research support from the following external funding agencies: the CIHR, US NIH, OMHF, NARSAD, Mexico Instituto de Ciencia y Tecnología del Distrito Federal, Consejo Nacional De Ciencia Y Tecnología, Ministry of Economic Development and Innovation of Ontario, Ontario AHSC AFP Innovation Fund and W. Garfield Weston Foundation. All other authors report no conflict of interest., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Widespread structrual abnormalities in subcortical brain regions have been identified in patients with schizophrenia. However, only a few studies have examined the neuroanatomical profiles of patients with treatment-resistant schizophrenia. The aim of this study was to compare differences in subcortical and hippocampal volumes between: (i) treatment-resistant patients who are non-responders to both first-line antipsychotics and clozapine (URS), (ii) treatment-resistant patients who are non-responders to first-line antipsychotics but are responders to clozapine (CLZ-Resp), (iii) responders to first-line antipsychotics (FL-Resp), and (iv) healthy controls. T1-weighted images of 103 participants (27 URS, 29 CLZ-Resp, 21 FL-Resp, and 26 healthy controls) were obtained. Group differences in striatal, thalamic, globus pallidus, amygdala, and hippocampus volumes were examined. Multiple regression analyses were performed to examine the associations between subcortical and hippocampal volumes and participant characteristics. The FL-Resp group showed larger striatal and globus pallidus volumes compared to the URS group and larger post-commissural putamen and globus pallidus volumes compared to healthy controls. The URS group showed smaller thalamic volume compared to healthy controls. There were no subcortical or hippocampal volume differences between the URS and CLZ-Resp groups. Differences in subcortical and hippocampal structural volumes were not related to symptom severity or chlorpromazine antipsychotic dose equivalents. Our findings suggest different structural volume alterations in subcortical brain regions between treatment-resistant schizophrenia and responders to first-line antipsychotics. Whether subcortical structure compromise is a distinct pathophysiological marker of treatment-resistant schizophrenia, or a result of antipsychotic exposure, remains to be explored., Competing Interests: Declaration of Competing Interest J.K. has received funding from the CAMH Foundation and the Ontario Graduate Scholarship (OGS). E.P. has received funding from the Healthy Brains for Healthy Lives Postdoctoral Fellowship, the Vanier Canada Graduate Scholarship, the OGS, and the Canada Graduate Scholarship – Master's. Y.I. has received fellowship grants from Keio University Medical Science Foundation, Mitsukoshi Foundation, Japan Foundation for Aging and Health, and manuscript fees from Dainippon Sumitomo Pharma. S.N. has received fellowship grants from the Canadian Institutes of Health Research (CIHR), research support from Japan Society for the Promotion of Science, Japan Agency for Medical Research and Development, Japan Research Foundation for Clinical Pharmacology, Naito Foundation, Takeda Science Foundation, Uehara Memorial Foundation, and Daiichi Sankyo Scholarship Donation Program within the past 3 years. He has also received research support, manuscript fees, or speaker's honoraria from Dainippon Sumitomo Pharma, Meiji-Seika Pharma, Otsuka Pharmaceutical, Shionogi, and Yoshitomi Yakuhin within the past 3 years. J.K.C. has received funding from the CIHR Doctoral Award and the Canada Graduate Scholarship – Master's. F.C. has received funding from CIHR, the Ontario Mental Health Post-Doctoral Fellowship Award, CAMH Foundation, the Brain & Behavior Research Foundation (Formerly NARSAD), and the Vancouver Coastal Health Research Institute. G.R. has received consultant fees from Neurocrine Biosciences and Synchroneuron, as well as research support from Novartis. P.G. reports receiving research support from CIHR, Ontario Ministry of Health and Long-Term Care, Ontario Mental Health Foundation (OMHF), and CAMH. A.G.-G. has received support from the United States National Institute of Health, CIHR, OMHF, Consejo Nacional de Ciencia y Tecnología, the Instituto de Ciencia y Tecnología del DF, the Brain & Behavior Research Foundation (Formerly NARSAD), the Ontario Ministry of Health and Long-Term Care, the Ontario Ministry of Research and Innovation Early Research Award, and Janssen. All other authors have declared that there are no conflicts of interest in relation to the subject of this study., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background: There is growing recognition that connectome architecture shapes cortical and subcortical gray matter atrophy across a spectrum of neurological and psychiatric diseases. Whether connectivity contributes to tissue volume loss in schizophrenia in the same manner remains unknown., Methods: Here, we relate tissue volume loss in patients with schizophrenia to patterns of structural and functional connectivity. Gray matter deformation was estimated in a sample of 133 individuals with chronic schizophrenia (48 women, mean age 34.7 ± 12.9 years) and 113 control subjects (64 women, mean age 23.5 ± 8.4 years). Deformation-based morphometry was used to estimate cortical and subcortical gray matter deformation from T1-weighted magnetic resonance images. Structural and functional connectivity patterns were derived from an independent sample of 70 healthy participants using diffusion spectrum imaging and resting-state functional magnetic resonance imaging., Results: We found that regional deformation is correlated with the deformation of structurally and functionally connected neighbors. Distributed deformation patterns are circumscribed by specific functional systems (the ventral attention network) and cytoarchitectonic classes (limbic class), with an epicenter in the anterior cingulate cortex., Conclusions: Altogether, the present study demonstrates that brain tissue volume loss in schizophrenia is conditioned by structural and functional connectivity, accounting for 25% to 35% of regional variance in deformation., (Copyright © 2019 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Approximately 30% of patients with schizophrenia do not respond to antipsychotics and are thus considered to have treatment-resistant schizophrenia (TRS). To date, only four studies have examined glutamatergic neurometabolite levels using proton magnetic resonance spectroscopy ( 1 H-MRS) in patients with TRS, collectively suggesting that glutamatergic dysfunction may be implicated in the pathophysiology of TRS. Notably, the TRS patient population in these studies had mild-to-moderate illness severity, which is not entirely reflective of what is observed in clinical practice. In this present work, we compared glutamate + glutamine (Glx) levels in the dorsal anterior cingulate cortex (dACC) and caudate among patients with TRS, patients with non-TRS, and healthy controls (HCs), using 3T 1 H-MRS (PRESS, TE = 35 ms). TRS criteria were defined by severe positive symptoms (i.e., ≥5 on 2 Positive and Negative Syndrome Scale (PANSS)-positive symptom items or ≥4 on 3 PANSS-positive symptom items), despite standard antipsychotic treatment. A total of 95 participants were included (29 TRS patients [PANSS = 111.2 ± 20.4], 33 non-TRS patients [PANSS = 49.8 ± 13.7], and 33 HCs). dACC Glx levels were higher in the TRS group vs. HCs (group effect: F[2,75] = 4.74, p = 0.011; TRS vs. HCs: p = 0.012). No group differences were identified in the caudate. There were no associations between Glx levels and clinical severity in either patient group. Our results are suggestive of greater heterogeneity in TRS relative to non-TRS with respect to dACC Glx levels, necessitating further research to determine biological subtypes of TRS.

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., (Copyright © 2019. Published by Elsevier B.V.)

Machine learning is a powerful tool that has previously been used to classify schizophrenia (SZ) patients from healthy controls (HC) using magnetic resonance images. Each study, however, uses different datasets, classification algorithms, and validation techniques. Here, we perform a critical appraisal of the accuracy of machine learning methodologies used in SZ/HC classifications studies by comparing three machine learning algorithms (logistic regression [LR], support vector machines [SVMs], and linear discriminant analysis [LDA]) on three independent datasets (435 subjects total) using two tissue density estimates and cortical thickness (CT). Performance is assessed using 10-fold cross-validation, as well as a held-out validation set. Classification using CT outperformed tissue densities, but there was no clear effect of dataset. LR, SVMs, and LDA each yielded the highest accuracies for a different feature set and validation paradigm, but most accuracies were between 55 and 70%, well below previously reported values. The highest accuracy achieved was 73.5% using CT data and an SVM. Taken together, these results illustrate some of the obstacles to constructing effective disease classifiers, and suggest that tissue densities and CT may not be sufficiently sensitive for SZ/HC classification given current available methodologies and sample sizes., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: While previous studies have identified relationships between hippocampal volumes and memory performance in schizophrenia, these relationships are not apparent in healthy individuals. Further, few studies have examined the role of hippocampal subfields in illness-related memory deficits, and no study has examined potential differences across varying illness stages. The current study aimed to investigate whether individuals with early and established psychosis exhibited differential relationships between visuospatial associative memory and hippocampal subfield volumes., Methods: Measurements of visuospatial associative memory performance and grey matter volume were obtained from 52 individuals with a chronic schizophrenia-spectrum disorder, 28 youth with recent-onset psychosis, 52 older healthy controls, and 28 younger healthy controls., Results: Both chronic and recent-onset patients had impaired visuospatial associative memory performance, however, only chronic patients showed hippocampal subfield volume loss. Both chronic and recent-onset patients demonstrated relationships between visuospatial associative memory performance and hippocampal subfield volumes in the CA4/dentate gyrus and the stratum that were not observed in older healthy controls. There were no group by volume interactions when chronic and recent-onset patients were compared., Conclusions: The current study extends the findings of previous studies by identifying particular hippocampal subfields, including the hippocampal stratum layers and the dentate gyrus, that appear to be related to visuospatial associative memory ability in individuals with both chronic and first-episode psychosis.

Exposure to maternal infection in utero increases the risk that offspring will develop neurodevelopmental disorders such as autism spectrum disorder (ASD) and schizophrenia. Research in animal models has confirmed this link and demonstrated that maternal immune activation (MIA) is sufficient to induce alterations in offspring neurodevelopment. Building homology between observations made in humans and animal models is a challenge; however, neuroimaging allows for homologous characterization of developmental trajectories across species. This systematic review aims to discuss findings from human and animal studies that performed neuroimaging in offspring exposed to maternal infection, inflammation, or MIA, in the context of neurodevelopmental disorders., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

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 ( 1 H-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 1 H-MRSI to measure levels of glutamate and glutamine in patients with schizophrenia. Additionally, the advantages and disadvantages of using 1 H-MRSI to examine schizophrenia pathophysiology are discussed. A literature search was conducted through Ovid. English language studies utilizing 1 H-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 1 H-MRSI to examine schizophrenia pathophysiology appears to be its broader spatial coverage. Future 1 H-MRSI studies utilizing large sample sizes and longitudinal study designs are necessitated to further our understanding of glutamatergic alterations in patients with schizophrenia., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Objective: Cortical thickness reductions in schizophrenia are irregularly distributed across multiple loci. The authors hypothesized that cortical connectivity networks would explain the distribution of cortical thickness reductions across the cortex, and, specifically, that cortico-cortical connectivity between loci with these reductions would be exceptionally strong and form an interconnected network. This hypothesis was tested in three cross-sectional schizophrenia cohorts: first-episode psychosis, chronic schizophrenia, and treatment-resistant schizophrenia., Methods: Structural brain images were acquired for 70 patients with first-episode psychosis, 153 patients with chronic schizophrenia, and 47 patients with treatment-resistant schizophrenia and in matching healthy control groups (N=57, N=168, and N=54, respectively). Cortical thickness was compared between the patient and respective control groups at 148 regions spanning the cortex. Structural connectivity strength between pairs of cortical regions was quantified with structural covariance analysis. Connectivity strength between regions with cortical thickness reductions was compared with connectivity strength between 5,000 sets of randomly chosen regions to establish whether regions with reductions were interconnected more strongly than would be expected by chance., Results: Significant (false discovery rate corrected) and widespread cortical thickness reductions were found in the chronic schizophrenia (79 regions) and treatment-resistant schizophrenia (106 regions) groups, with more circumscribed reductions in the first-episode psychosis group (34 regions). Cortical thickness reductions with the largest effect sizes were found in frontal, temporal, cingulate, and insular regions. In all cohorts, both the patient and healthy control groups showed significantly increased structural covariance between regions with cortical thickness reductions compared with randomly selected regions., Conclusions: Brain network architecture can explain the irregular topographic distribution of cortical thickness reductions in schizophrenia. This finding, replicated in three distinct schizophrenia cohorts, suggests that the effect is robust and independent of illness stage.

Background: The relationship between poor insight and less favorable outcomes in schizophrenia has promoted research efforts to understand its neurobiological basis. Thus far, research on neural correlates of insight has been constrained by small samples, incomplete insight assessments, and a focus on frontal lobes. The purpose of this study was to examine associations of cortical thickness and subcortical volumes, with a comprehensive assessment of clinical insight, in a large sample of enduring schizophrenia patients., Methods: Two dimensions of clinical insight previously identified by a factor analysis of 4 insight assessments were used: Awareness of Illness and Need for Treatment (AINT) and Awareness of Symptoms and Consequences (ASC). T1-weighted structural images were acquired on a 3 T MRI scanner for 110 schizophrenia patients and 69 healthy controls. MR images were processed using CIVET (version 2.0) and MAGeT and quality controlled pre and post-processing. Whole-brain and region-of-interest, vertex-wise linear models were applied between cortical thickness, and levels of AINT and ASC. Partial correlations were conducted between volumes of the amygdala, thalamus, striatum, and hippocampus and insight levels., Results: No significant associations between both insight factors and cortical thickness were observed. Moreover, no significant associations emerged between subcortical volumes and both insight factors., Conclusions: These results do not replicate previous findings obtained with smaller samples using single-item measures of insight into illness, suggesting a limited role of neurobiological factors and a greater role of psychological processes in explaining levels of clinical insight., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background: There is evidence suggesting neuropsychiatric disorders share genomic, cognitive and clinical features. Here, we ask if autism-spectrum disorders (ASD), attention-deficit/hyperactivity disorder (ADHD) and schizophrenia share neuroanatomical variations., Methods: First, we used measures of cortical anatomy to estimate spatial overlap of neuroanatomical variation using univariate methods. Next, we developed a novel methodology to determine whether cortical deficits specifically target or are "enriched" within functional resting-state networks., Results: We found cortical anomalies were preferentially enriched across functional networks rather than clustering spatially. Specifically, cortical thickness showed significant enrichment between patients with ASD and those with ADHD in the default mode network, between patients with ASD and those with schizophrenia in the frontoparietal and limbic networks, and between patients with ADHD and those with schizophrenia in the ventral attention network. Networks enriched in cortical thickness anomalies were also strongly represented in functional MRI results (Neurosynth; r = 0.64, p = 0.032)., Limitations: We did not account for variable symptom dimensions and severity in patient populations, and our cross-sectional design prevented longitudinal analyses of developmental trajectories., Conclusion: These findings suggest that common deficits across neuropsychiatric disorders cannot simply be characterized as arising out of local changes in cortical grey matter, but rather as entities of both local and systemic alterations targeting brain networks.

Previous proton magnetic resonance spectroscopy ( 1 H-MRS) studies have reported disrupted levels of various neurometabolites in patients with schizophrenia. An area of particular interest within this patient population is the striatum, which is highly implicated in the pathophysiology of schizophrenia. The present study examined neurometabolite levels in the striatum of 12 patients with schizophrenia receiving antipsychotic treatment for at least 1 year and 11 healthy controls using 3-Tesla 1 H-MRS (PRESS, TE = 35 ms). Glutamate, glutamate+glutamine (Glx), myo-inositol, choline, N-acetylaspartate, and creatine levels were estimated using LCModel, and corrected for fraction of cerebrospinal fluid in the 1 H-MRS voxel. Striatal neurometabolite levels were compared between groups. Multiple study visits permitted a reliability assessment for neurometabolite levels (days between paired 1 H-MRS acquisitions: average = 90.33; range = 7-306). Striatal neurometabolite levels did not differ between groups. Within the whole sample, intraclass correlation coefficients for glutamate, Glx, myo-inositol, choline, and N-acetylaspartate were fair to excellent (0.576-0.847). The similarity in striatal neurometabolite levels between groups implies a marked difference from the antipsychotic-naïve first-episode state, especially in terms of glutamatergic neurometabolites, and might provide insight regarding illness progression and the influence of antipsychotic medication., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Objective: Motivational deficits are prevalent in patients with schizophrenia, persist despite antipsychotic treatment, and predict long-term outcomes. Evidence suggests that patients with greater amotivation have smaller ventral striatum (VS) volumes. We wished to replicate this finding in a sample of older, chronically medicated patients with schizophrenia. Using structural imaging and positron emission tomography, we examined whether amotivation uniquely predicted VS volumes beyond the effects of striatal dopamine D 2/3 receptor (D 2/3 R) blockade by antipsychotics., Methods: Data from 41 older schizophrenia patients (mean age: 60.2 ± 6.7; 11 female) were reanalysed from previously published imaging data. We constructed multivariate linear stepwise regression models with VS volumes as the dependent variable and various sociodemographic and clinical variables as the initial predictors: age, gender, total brain volume, and antipsychotic striatal D 2/3 R occupancy. Amotivation was included as a subsequent step to determine any unique relationships with VS volumes beyond the contribution of the covariates. In a reduced sample (n = 36), general cognition was also included as a covariate., Results: Amotivation uniquely explained 8% and 6% of the variance in right and left VS volumes, respectively (right: β = -.38, t = -2.48, P = .01; left: β = -.31, t = -2.17, P = .03). Considering cognition, amotivation levels uniquely explained 9% of the variance in right VS volumes (β = -.43, t = -0.26, P = .03)., Conclusion: We replicate and extend the finding of reduced VS volumes with greater amotivation. We demonstrate this relationship uniquely beyond the potential contributions of striatal D 2/3 R blockade by antipsychotics. Elucidating the structural correlates of amotivation in schizophrenia may help develop treatments for this presently irremediable deficit., (Copyright © 2017 John Wiley & Sons, Ltd.)

Background: Patients with schizophrenia (SCZ) tend to sample less information when making a decision, jumping to conclusions (JTC) without sufficient evidence. This "JTC bias" may be a trait marker of the disease and may not improve with antipsychotic treatment. We conducted a double-blind, placebo-controlled trial to test whether intranasal oxytocin could reduce JTC in stable, medicated patients with SCZ and healthy controls (HCs). We also explored whether striatal volume, clinical symptoms, and baseline social functioning (SF) was related to JTC performance., Methods: Forty-three male, medicated SCZ patients (Mean Age: 40.81±11.44) and sixteen HCs (Mean Age: 30.38±9.85) participated in a double-blind, placebo-controlled, cross-over study. Participants completed the Beads Task on two separate visits (minimum 20days apart). Participants were randomized to receive either intranasal oxytocin (50IU in solution) or intranasal placebo (saline). Twenty of the SCZ patients and all sixteen HCs also provided T1 MRIs (3-T)., Results: Patients with SCZ took fewer draws to decision (DTD) than HCs (t(57)=2.78, p=0.007). Oxytocin did not significantly change DTD in patients (t(42)=-1.11, p=0.27), nor in HCs (t(15)=-0.62, p=0.55). Exploratory analyses found ventral caudate volumes were negatively correlated with DTD (r(18)=-0.50, p=0.03) in patients. Moreover, oxytocin was more likely to improve JTC in patients with lower baseline SF. However, these exploratory findings did not survive correction for multiple comparisons., Conclusions: We replicate increased JTC in SCZ. However, acute intranasal oxytocin did not modify JTC. Future studies with larger samples should explore how brain morphology and SF are related to JTC performance in patients with SCZ., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Objective: Suicide is a major concern for those afflicted by schizophrenia. Identifying patients at the highest risk for future suicide attempts remains a complex problem for psychiatric interventions. Machine learning models allow for the integration of many risk factors in order to build an algorithm that predicts which patients are likely to attempt suicide. Currently it is unclear how to integrate previously identified risk factors into a clinically relevant predictive tool to estimate the probability of a patient with schizophrenia for attempting suicide., Methods: We conducted a cross-sectional assessment on a sample of 345 participants diagnosed with schizophrenia spectrum disorders. Suicide attempters and non-attempters were clearly identified using the Columbia Suicide Severity Rating Scale (C-SSRS) and the Beck Suicide Ideation Scale (BSS). We developed four classification algorithms using a regularized regression, random forest, elastic net and support vector machine models with sociocultural and clinical variables as features to train the models., Results: All classification models performed similarly in identifying suicide attempters and non-attempters. Our regularized logistic regression model demonstrated an accuracy of 67% and an area under the curve (AUC) of 0.71, while the random forest model demonstrated 66% accuracy and an AUC of 0.67. Support vector classifier (SVC) model demonstrated an accuracy of 67% and an AUC of 0.70, and the elastic net model demonstrated and accuracy of 65% and an AUC of 0.71., Conclusion: Machine learning algorithms offer a relatively successful method for incorporating many clinical features to predict individuals at risk for future suicide attempts. Increased performance of these models using clinically relevant variables offers the potential to facilitate early treatment and intervention to prevent future suicide attempts., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Kynurenic acid (KYNA) is an endogenous antagonist of N-methyl-D-aspartate and α7 nicotinic acetylcholine receptors that is derived from astrocytes as part of the kynurenine pathway of tryptophan degradation. Evidence suggests that abnormal KYNA levels are involved in the pathophysiology of schizophrenia. However, this has never been assessed through a meta-analysis. A literature search was conducted through Ovid using Embase, Medline, and PsycINFO databases (last search: December 2016) with the search terms: (kynuren* or KYNA) and (schizophreni* or psychosis). English language studies measuring KYNA levels using any method in patients with schizophrenia and healthy controls (HCs) were identified. Standardized mean differences (SMDs) were calculated to determine differences in KYNA levels between groups. Subgroup analyses were separately performed for nonoverlapping participant samples, KYNA measurement techniques, and KYNA sample source. The influences of patients' age, antipsychotic status (%medicated), and sex (%male) on study SMDs were assessed through a meta-regression. Thirteen studies were deemed eligible for inclusion in the meta-analysis. In the main analysis, KYNA levels were elevated in the patient group. Subgroup analyses demonstrated that KYNA levels were increased in nonoverlapping participant samples, and centrally (cerebrospinal fluid and brain tissue) but not peripherally. Patients' age, %medicated, and %male were each positively associated with study SMDs. Overall, KYNA levels are increased in patients with schizophrenia, specifically within the central nervous system. An improved understanding of KYNA in patients with schizophrenia may contribute to the development of novel diagnostic approaches and therapeutic strategies., (© The Author 2017. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Despite being diagnostically associated uniquely with schizophrenia, negative symptoms are also observed in bipolar disorder (BD). Genome-wide association studies (GWAS) have uncovered a number of shared risk genes between schizophrenia and BD. The objectives of this study were to examine whether previously identified risk genes for BD are associated with negative symptom severity within a first-episode schizophrenia (FES) cohort and to examine whether such genes influence brain morphology., Methods: Patients experiencing FES were genotyped for 21 previously identified BD risk genes; a series of univariate analyses of covariance examined the association between negative symptom severity, as measured using the Scale for the Assessment of Negative Symptoms (SANS), and genotype. A subset of participants underwent a structural 1.5 T MRI T 1 scan, analyzed for surface area and cortical thickness changes via the CIVET pipeline and LPBA40 atlas., Results: We included 133 patients with FES in our analysis; 61 of them underwent structural MRI. We observed a significant association between negative symptom severity and the BD risk gene FOXO6 (rs4660531). Individuals with the CC genotype presented significantly higher negative symptoms (Cohen d = 0.46, F = 5.854, p = 0.017) and significantly smaller surface area within the right middle orbitofrontal gyrus (Cohen d = 0.69, F = 7.289, p = 0.009) than carriers of allele A., Limitations: Limitations of this study include its modest sample size and lack of a control sample., Conclusion: Lacking the FOXO6 risk allele was associated with an increase in negative symptoms and surface area reduction in the right orbitofrontal gyrus - an area previously associated with negative symptoms - suggesting that presence of the FOXO6 risk allele confers resistance against negative symptoms and associated neuroanatomical changes in individuals with FES.

Current literature suggests that the pathology of schizophrenia (SCZ) has developmental origins. However, the neurodevelopmental theory of SCZ cannot solely explain progressive neurodegenerative processes in the illness. There is evidence of accelerated cognitive decline and increased risk of dementia in elderly patients with SCZ. Investigating β-amyloid (Aβ), we conducted a systematic review focusing on Aβ in patients with SCZ. An OVID literature search using PsychINFO, Medline, and Embase databases was conducted, looking for studies that compared Aβ levels between patients with SCZ and either elderly control subjects, patients with Alzheimer disease (AD), or patients with other psychiatric illnesses. Among 14 identified studies, 11 compared Aβ between SCZ and elderly control subjects, 7 between SCZ and AD, and 3 between SCZ and other psychiatric illnesses. As a result, no evidence was found suggesting that Aβ levels differ in patients with SCZ from elderly control subjects or patients with other psychiatric illnesses. All seven studies reported lower cortical Aβ in patients with SCZ than patients with AD. Furthermore, three of the four studies, which investigated the relationship between Aβ and cognitive impairment in SCZ, observed no association between two factors. The limitations of the included studies are small sample sizes, the inclusion of cerebrospinal fluid Aβ or postmortem plaques rather than cortical Aβ assessment in vivo, and the investigation of different brain regions. In conclusion, Aβ deposition is not associated with cognitive decline in late-life SCZ. Future studies should investigate other neurodegenerative indicators in SCZ to better understand the pathophysiologic mechanisms underlying this illness., (Copyright © 2016 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.)

The glutamic acid decarboxylase 1 (GAD1) gene is a major determinant of γ-aminobutyric acid (GABA), the most abundant inhibitory neurotransmitter modulating local neuronal circuitry. GABAergic dysfunction and expression of GAD1 have been implicated in the pathophysiology of schizophrenia, and in working memory impairment. We examined the influence of the functional GAD1 rs3749034 variant on white matter fractional anisotropy (FA), cortical thickness, and working memory performance in schizophrenia patients and healthy controls (N=197). Using transcranial magnetic stimulation with electroencephalography (TMS-EEG), we subsequently examined the effect of rs3749034 on long-interval cortical inhibition (LICI) in the dorsolateral prefrontal cortex (DLPFC) in schizophrenia patients and healthy controls (N=66). We found that the rs3749034 T-allele carrier risk group had lower voxel-wise FA in the prefrontal cortex region (PFWE-corrected<0.05) but not cortical thickness. Mixed-model regression revealed a significant effect on attentional processing and working memory across four performance measures (F1,182=11.5, P=8 × 10(-4)). FA in the prefrontal cortex was associated with digit-span performance. Voxel-wise mediation analysis revealed that the effect GAD1 on poorer digit-span performance statistically predicted the lower white matter FA (PFWE-corrected<0.05). In exploratory analysis, we found a prominent GAD1 genotype-by-diagnosis interaction on DLPFC LICI (F1,56=14.3, P=4.1 × 10(-4)). Our findings converge on variation in GAD1 gene predicting a susceptibility mechanism that affects white matter FA, GABAergic inhibitory neurotransmission in the DLPFC, and working memory performance. Furthermore, via voxel mediation of FA and TMS-EEG intervention, we provide evidence for a potentially causal mechanism through which aberrant DLPFC GABA signaling may contribute to working memory dysfunction.

Poor insight is a common, multidimensional phenomenon in patients with schizophrenia, associated with poorer outcomes and treatment non-adherence. Yet scant research has investigated the neuronal correlates of insight into symptoms (IS), a dimension of insight that may be particularly significant in enduring schizophrenia. Sixty-six patients with enduring schizophrenia (duration >4years) and 33 healthy controls completed MRI scanning and IQ, depression, and anxiety assessments. The Scale to Assess Insight-Expanded (SAI-E) measured insight into patients' four most prominent symptoms and patients were classified into two groups: low IS (0-2; n=33), and high IS (>2; n=33). We evaluated the association between cortical thickness (CT) and insight into symptoms using two methods: (1) a between-patients region-of-interest analysis in the insula, superior temporal gyrus (STG) and frontal lobe; and (2) a whole-brain exploratory regression between patient and controls. Brain regions were segmented using a neuroanatomical atlas and vertex-wise CT analyses were conducted with CIVET, covaried for age and sex. ROI analysis revealed thinner insula cortex in patients with low IS (p<0.05, surviving FDR correction). Patients with low IS also showed significantly thinner right insula, STG, and parahippocampal cortex compared to healthy controls (p<0.05, surviving FDR correction). Regions of observed CT reductions have been hypothesized to subserve self-monitoring, error awareness, and ability to identify hallucinations. Results highlight an important association between right insula abnormalities and impaired IS in schizophrenia. The diverse clinical presentation of patients further suggests an independent relationship between symptomology and insight-related differences in CT that has been previously unexplored in enduring schizophrenia., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Verbal memory (VM) represents one of the most affected cognitive domains in schizophrenia. Multiple studies have shown that schizophrenia is associated with cortical abnormalities, but it remains unclear whether these are related to VM impairments. Considering the vast literature demonstrating the role of the frontal cortex, the parahippocampal cortex, and the hippocampus in VM, we examined the cortical thickness/volume of these regions. We used a categorical approach whereby 27 schizophrenia patients with 'moderate to severe' VM impairments were compared to 23 patients with 'low to mild' VM impairments and 23 healthy controls. A series of between-group vertex-wise GLM on cortical thickness were performed for specific regions of interest defining the parahippocampal gyrus and the frontal cortex. When compared to healthy controls, patients with 'moderate to severe' VM impairments revealed significantly thinner cortex in the left frontal lobe, and the parahippocampal gyri. When compared to patients with 'low to mild' VM impairments, patients with 'moderate to severe' VM impairments showed a trend of thinner cortex in similar regions. Virtually no differences were observed in the frontal area of patients with 'low to mild' VM impairments relative to controls. No significant group differences were observed in the hippocampus. Our results indicate that patients with greater VM impairments demonstrate significant cortical thinning in regions known to be important in VM performance. Treating VM deficits in schizophrenia could have a positive effect on the brain; thus, subgroups of patients with more severe VM deficits should be a prioritized target in the development of new cognitive treatments.

Purpose: Studies show that deficit syndrome schizophrenia patients, characterized by primary negative symptoms and poor functional outcome, have impairment in specific neural circuits. We assessed whether these same neural circuits are directly linked to functional outcomes across schizophrenia patients., Methods: T1- and diffusion-weighted MR images were obtained for schizophrenia (n=30) and matched healthy control participants (n=30). Negative symptoms and functional outcome were assessed at baseline and 6-month follow-up. Cortical thickness and tract-wise fractional anisotropy (FA) were compared between groups. To assess relationships of neuroimaging measures with functional outcome, principal component analysis (PCA) was performed on tract-wise FA values and components were entered into a multiple regression model for schizophrenia participants., Results: Consistent with the literature, schizophrenia participants showed frontotemporal reductions in cortical thickness and tract-wise FA compared to controls. The top two components from PCA explained 71% of the variance in tract-wise FA values. The second component (associated with inferior longitudinal and arcuate fasciculus FA) was significantly correlated with functional outcome (baseline: β=0.54, p=0.03; follow-up: β=0.74, p=0.047); further analysis revealed this effect was mediated by negative symptoms. Post-hoc network analysis revealed increased cortical coupling between right inferior frontal and supramarginal gyri (connected by the arcuate fasciculus) in schizophrenia participants with poorer functional outcome., Conclusions: Our findings indicate that impairment in the same neural circuitry susceptible in deficit syndrome schizophrenia predicts functional outcome in a continuous manner in schizophrenia participants. This relationship was mediated by negative symptom burden. Our findings provide novel evidence for brain-based biomarkers of longitudinal functional outcome in people with schizophrenia., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Importance: The clinical heterogeneity of schizophrenia has hindered neurobiological investigations aimed at identifying neural correlates of the disorder., Objective: To identify network-based biomarkers across the spectrum of impairment present in schizophrenia by separately evaluating individuals with deficit and nondeficit subtypes of this disorder., Design, Setting, and Participants: A university hospital network-based neuroimaging study was conducted between February 1, 2007, and February 28, 2012. Participants included patients with schizophrenia (n = 128) and matched healthy controls (n = 130) from two academic centers and patients with bipolar I disorder (n = 39) and matched healthy controls (n = 43) from a third site. Patients with schizophrenia at each site in the top quartile on the proxy scale for the deficit syndrome were classified as having deficit schizophrenia and those in the bottom quartile were classified as having nondeficit schizophrenia., Exposure: All participants underwent magnetic resonance brain imaging., Main Outcomes and Measures: Network-level properties of cortical thickness were assessed in each group. Interregional cortexwide coupling was compared among the groups, and graph theoretical approaches were used to assess network density and node degree, betweenness, closeness, and eigenvector centrality., Results: Stronger frontoparietal and frontotemporal coupling was found in patients with deficit schizophrenia compared with those with nondeficit schizophrenia (17 of 1326 pairwise relationships were significantly different, P < .05; 5% false discovery rate) and in patients with deficit schizophrenia compared with healthy controls (49 of 1326 pairwise relationships were significantly different, P < .05; 5% false discovery rate). Participants with nondeficit schizophrenia and bipolar I disorder did not show significant differences in coupling relative to those in the control groups (for both comparisons, 0 of 1326 pairwise relationships were significantly different, P > .05; 5% false discovery rate). The networks formed from patients with deficit schizophrenia demonstrated increased density of connections relative to controls and nondeficit patients (range, 0.07-0.45 in controls, 0.09-0.43 in the nondeficit group, and 0.18-0.67 in the deficit group). High centrality nodes were identified in the supramarginal, middle, and superior temporal and inferior frontal regions in deficit schizophrenia networks based on ranking of 4 centrality metrics. High centrality regions were identified as those that ranked in the top 10 in 50% or more of the thresholded networks in 3 or more of the centrality measures. Network properties were similar in patients with deficit schizophrenia from both study sites., Conclusions and Relevance: Patients with schizophrenia at one end of a spectrum show characteristic signatures of altered intracortical relationships compared with those at the other end of that spectrum, patients with bipolar I disorder, and healthy individuals. Cortical connectomic approaches can be used to reliably identify neural signatures in clinically heterogeneous groups of patients.

There are varying, often conflicting, reports with respect to altered striatal volume and morphometry in the major psychoses due to the influences of antipsychotic medications on striatal volume. Thus, disassociating disease effects from those of medication become exceedingly difficult. For the first time, using a longitudinally studied sample of structural magnetic resonance images from patients with childhood onset schizophrenia (COS; neurobiologically contiguous with the adult onset form of schizophrenia), their nonpsychotic siblings (COSSIBs), and novel shape mapping algorithms that are volume independent, we report the familial contribution of striatal morphology in schizophrenia. The results of our volumetric analyses demonstrate age-related increases in overall striatal volumes specific only to COS. However, both COS and COSSIBs showed overlapping shape differences in the striatal head, which normalized in COSSIBs by late adolescence. These results mirror previous studies from our group, demonstrating cortical thickness deficits in COS and COSSIBs as these deficits normalize in COSSIBs in the same age range as our striatal findings. Finally, there is a single region of nonoverlapping outward displacement in the dorsal aspect of the caudate body, potentially indicative of a response to medication. Striatal shape may be considered complimentary to volume as an endophenotype, and, in some cases may provide information that is not detectable using standard volumetric techniques. Our striatal shape findings demonstrate the striking localization of abnormalities in striatal the head. The neuroanatomical localization of these findings suggest the presence of abnormalities in the striatal-prefrontal circuits in schizophrenia and resilience mechanisms in COSSIBs with age dependent normalization., (© 2014 Wiley Periodicals, Inc.)

Impaired illness awareness or anosognosia is a common, but poorly understood feature of schizophrenia that contributes to medication nonadherence and poor treatment outcomes. Here we present a functional imaging study to measure brain activity at the moment of illness denial. To accomplish this, participants with schizophrenia (n = 18) with varying degrees of illness awareness were confronted with their illness beliefs while undergoing functional MRI. To link structure with function, we explored the relationships among impaired illness awareness and brain activity during the illness denial task with cortical thickness. Impaired illness awareness was associated with increased brain activity in the left temporoparieto-occipital junction (TPO) and left medial prefrontal cortex (mPFC) at the moment of illness denial. Brain activity in the left mPFC appeared to be a function of participants' degree of self-reflectiveness, while the activity in the left TPO was associated with cortical thinning in this region and more specific to illness denial. Participants with impaired illness awareness had slower response times to illness related stimuli than those with good illness awareness. Increased left hemisphere brain activity in association with illness denial is consistent with the literature in other neuropsychiatric conditions attributing anosognosia or impaired illness awareness to left hemisphere dominance. The TPO and mPFC may represent putative targets for noninvasive treatment interventions, such as transcranial magnetic or direct current stimulation., (© 2014 Wiley Periodicals, Inc.)

Findings from neuroimaging studies in patients with schizophrenia suggest widespread structural changes although the mechanisms through which these changes occur are currently unknown. Glutamatergic activity appears to be increased in the early phases of schizophrenia and may contribute to these structural alterations through an excitotoxic effect. The primary aim of this review was to describe the possible role of glutamate-mediated excitotoxicity in explaining the presence of neuroanatomical changes within schizophrenia. A Medline(®) literature search was conducted, identifying English language studies on the topic of glutamate-mediated excitotoxicity in schizophrenia, using the terms "schizophreni" and "glutam" and (("MRS" or "MRI" or "magnetic resonance") or ("computed tomography" or "CT")). Studies concomitantly investigating glutamatergic activity and brain structure in patients with schizophrenia were included. Results are discussed in the context of findings from preclinical studies. Seven studies were identified that met the inclusion criteria. These studies provide inconclusive support for the role of glutamate-mediated excitotoxicity in the occurrence of structural changes within schizophrenia, with the caveat that there is a paucity of human studies investigating this topic. Preclinical data suggest that an excitotoxic effect may occur as a result of a paradoxical increase in glutamatergic activity following N-methyl-D-aspartate receptor hypofunction. Based on animal literature, glutamate-mediated excitotoxicity may account for certain structural changes present in schizophrenia, but additional human studies are required to substantiate these findings. Future studies should adopt a longitudinal design and employ magnetic resonance imaging techniques to investigate whether an association between glutamatergic activity and structural changes exists in patients with schizophrenia., (Copyright © 2014 Elsevier B.V. and ECNP. All rights reserved.)

Background: Prominent regional cortical thickness reductions have been shown in schizophrenia. In contrast, little is known regarding alterations of structural coupling between regions in schizophrenia and how these alterations may be related to cognitive impairments in this disorder., Methods: T1-weighted magnetic resonance images were acquired in 54 patients with schizophrenia and 68 healthy control subjects aged 18-55 years. Cortical thickness was compared between groups using a vertex-wise approach. To assess structural coupling, seeds were selected within regions of reduced thickness, and brain-wide cortical thickness correlations were compared between groups. The relationships between identified patterns of circuit structure disruption and cognitive task performance were then explored., Results: Prominent cortical thickness reductions were found in patients compared with controls at a 5% false discovery rate in a predominantly frontal and temporal pattern. Correlations of the left dorsolateral prefrontal cortex (DLPFC) with right prefrontal regions were significantly different in patients and controls. The difference remained significant in a subset of 20 first-episode patients. Participants with stronger frontal interhemispheric thickness correlations had poorer working memory performance., Conclusions: We identified structural impairment in a left-right DLPFC circuit in patients with schizophrenia independent of illness stage or medication exposure. The relationship between left-right DLPFC thickness correlations and working memory performance implicates prefrontal interhemispheric circuit impairment as a vulnerability pathway for poor working memory performance. Our findings could guide the development of novel therapeutic interventions aimed at improving working memory performance in patients with schizophrenia., (© The Author 2013. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Oligodendrocyte genes and white matter tracts have been implicated in the pathophysiology of schizophrenia and may play an important etiopathogenic role in cognitive dysfunction in schizophrenia. The objective of the present study in 60 chronic schizophrenia patients individually matched to 60 healthy controls was to determine whether 1) white matter tract integrity influences cognitive performance, 2) oligodendrocyte gene variants influence white matter tract integrity and cognitive performance, and 3) effects of oligodendrocyte gene variants on cognitive performance are mediated via white matter tract integrity. We used the partial least-squares multivariate approach to ascertain relationships among oligodendrocyte gene variants, integrity of cortico-cortical and subcortico-cortical white matter tracts, and cognitive performance. Robust relationships among oligodendrocyte gene variants, white matter tract integrity, and cognitive performance were found in both patients and controls. We also showed that effects of gene variants on cognitive performance were mediated by the integrity of white matter tracts. Our results were strengthened by bioinformatic analyses of gene variant function. To our knowledge, this is the first study that has brought together these lines of investigation in the same population and highlights the importance of the oligodendrocyte/white matter pathway in schizophrenia, particularly as it pertains to cognitive function.

Post-mortem studies have demonstrated alterations in superficial white matter (SWM) in schizophrenia patients. Diffusion tensor imaging (DTI) can be used to assess SWM in vivo, and compare SWM fractional anisotropy (FA) in schizophrenia patients vs healthy controls. The assessment of SWM in vivo also provides an opportunity to identify novel neural correlates of cognitive performance, and potential cognitive impairment in schizophrenia patients. Forty-four patients with schizophrenia and 44 matched healthy controls underwent neuroimaging and cognitive protocols. Using an SWM mask and tract-based spatial statistics, differences in SWM-FA were examined between groups. SWM-FA clusters different between groups were then used to predict cognitive performance with multiple linear regression. The relative contribution of SWM fiber subtypes (deep white matter extensions vs U-fibers and intraregional fibers) from significantly different clusters was examined. Compared to controls, patients with schizophrenia had reduced FA in five SWM clusters: the largest a left posterior parieto-occipital cluster, followed by four clusters in the left frontal lobe. SWM-FA in the frontal lobe clusters predicted attention, working memory, and processing speed performance in healthy controls, but not in patients with schizophrenia. The majority of streamlines tracked from these clusters were restricted to U-fibers and intraregional fibers, rather than deep white matter extensions. Our analyses revealed prominent SWM disruption in patients with schizophrenia compared to controls. SWM-cognition relationships shown in healthy individuals were disrupted in patients with schizophrenia. SWM may be an important neurobiological substrate of cognitive performance and a novel cortical treatment target for cognitive deficits in schizophrenia patients.

Introduction: Lack of illness awareness or anosognosia occurs in both schizophrenia and right hemisphere lesions due to stroke, dementia, and traumatic brain injury. In the latter conditions, anosognosia is thought to arise from unilateral hemispheric dysfunction or interhemispheric disequilibrium, which provides an anatomical model for exploring illness unawareness in other neuropsychiatric disorders, such as schizophrenia., Methods: Both voxel-based morphometry using Diffeomorphic Anatomical Registration through Exponentiated Lie Algebra (DARTEL) and a deformation-based morphology analysis of hemispheric asymmetry were performed on 52 treated schizophrenia subjects, exploring the relationship between illness awareness and gray matter volume. Analyses included age, gender, and total intracranial volume as covariates., Results: Hemispheric asymmetry analyses revealed illness unawareness was significantly associated with right < left hemisphere volumes in the anteroinferior temporal lobe (t = 4.83, P = 0.051) using DARTEL, and the dorsolateral prefrontal cortex (t = 5.80, P = 0.003) and parietal lobe (t = 4.3, P = 0.050) using the deformation-based approach. Trend level associations were identified in the right medial prefrontal cortex (t = 4.49, P = 0.127) using DARTEL. Lack of illness awareness was also strongly associated with reduced total white matter volume (r = 0.401, P < 0.01) and illness severity (r = 0.559, P < 0.01)., Conclusion: These results suggest a relationship between anosognosia and hemispheric asymmetry in schizophrenia, supporting previous volume-based MRI studies in schizophrenia that found a relationship between illness unawareness and reduced right hemisphere gray matter volume. Functional imaging studies are required to examine the neural mechanisms contributing to these structural observations., (Copyright © 2012 Wiley Periodicals, Inc.)

We examined the influence of the genome-wide significant schizophrenia risk variant rs1625579 near the microRNA (miRNA)-137 (MIR137) gene on well-established sources of phenotypic variability in schizophrenia: age-at-onset of psychosis and brain structure. We found that the MIR137 risk genotype strongly predicts an earlier age-at-onset of psychosis across four independently collected samples of patients with schizophrenia (n=510; F1,506=17.7, P=3.1 × 10(-5)). In an imaging-genetics subsample that included additional matched controls (n=213), patients with schizophrenia who had the MIR137 risk genotype had reduced white matter integrity (F3,209=13.6, P=3.88 × 10(-8)) throughout the brain as well as smaller hippocampi and larger lateral ventricles; the brain structure of patients who were carriers of the protective allele was no different from healthy control subjects on these neuroimaging measures. Our findings suggest that MIR137 substantially influences variation in phenotypes that are thought to have an important role in clinical outcome and treatment response. Finally, the possible consequences of genetic risk factors may be distinct in patients with schizophrenia compared with healthy controls.

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.