Brain structure and function changes during the development of schizophrenia: the evidence from studies of subjects at increased genetic risk

Multi-modal deep learning from imaging genomic data for schizophrenia classification

Background

Schizophrenia (SZ) is a psychiatric condition that adversely affects an individual's cognitive, emotional, and behavioral aspects. The etiology of SZ, although extensively studied, remains unclear, as multiple factors come together to contribute toward its development. There is a consistent body of evidence documenting the presence of structural and functional deviations in the brains of individuals with SZ. Moreover, the hereditary aspect of SZ is supported by the significant involvement of genomics markers. Therefore, the need to investigate SZ from a multi-modal perspective and develop approaches for improved detection arises.

Methods

Our proposed method employed a deep learning framework combining features from structural magnetic resonance imaging (sMRI), functional magnetic resonance imaging (fMRI), and genetic markers such as single nucleotide polymorphism (SNP). For sMRI, we used a pre-trained DenseNet to extract the morphological features. To identify the most relevant functional connections in fMRI and SNPs linked to SZ, we applied a 1-dimensional convolutional neural network (CNN) followed by layerwise relevance propagation (LRP). Finally, we concatenated these obtained features across modalities and fed them to the extreme gradient boosting (XGBoost) tree-based classifier to classify SZ from healthy control (HC).

Results

Experimental evaluation on clinical dataset demonstrated that, compared to the outcomes obtained from each modality individually, our proposed multi-modal approach performed classification of SZ individuals from HC with an improved accuracy of 79.01%.

Conclusion

We proposed a deep learning based framework that selects multi-modal (sMRI, fMRI and genetic) features efficiently and fuse them to obtain improved classification scores. Additionally, by using Explainable AI (XAI), we were able to pinpoint and validate significant functional network connections and SNPs that contributed the most toward SZ classification, providing necessary interpretation behind our findings.

Proteomic profiling in the progression of psychosis: Analysis of clinical high-risk, first episode psychosis, and healthy controls

BACKGROUND AND HYPOTHESIS

Recent evidence has highlighted the benefits of early detection and treatment for better clinical outcomes in patients with psychosis. Biological markers of the disease have become a focal point of research. This study aimed to identify protein markers detectable in the early stages of psychosis and indicators of progression by comparing them with those of healthy controls (HC) and first episode psychosis (FEP).

STUDY DESIGN

The participants comprised 28 patients in the clinical high-risk (CHR) group, 49 patients with FEP, and 61 HCs aged 15-35 years. Blood samples were collected and analyzed using multiple reaction monitoring-mass spectrometry to measure the expression of 158 peptide targets. Data were adjusted for age, sex, and use of psychotropic drugs.

STUDY RESULTS

A total of 18 peptides (17 proteins) differed significantly among the groups. The protein PRDX2 was higher in the FEP group than in the CHR and HC groups and showed increased expression according to disease progression. The levels of six proteins were significantly higher in the FEP group than in the CHR group. Nine proteins differed significantly in the CHR group compared to the other groups. Sixteen proteins were significantly correlated with symptom severity. These proteins are primarily related to the coagulation cascade, inflammatory response, brain structure, and synaptic plasticity.

CONCLUSIONS

Our findings suggested that peripheral protein markers reflect disease progression in patients with psychosis. Further longitudinal research is needed to confirm these findings and to identify the specific roles of these markers in the pathogenesis of schizophrenia.

Convergent abnormality in the subgenual anterior cingulate cortex in insomnia disorder: A revisited neuroimaging meta-analysis of 39 studies

The neurobiological underpinnings of insomnia disorder (ID) are still poorly understood. A previous meta-analysis conducted by our research group in 2018 revealed no consistent regional alterations based on the limited number of eligible studies. Given the number of studies published during the last few years, we revisited the meta-analysis to provide an update to the field. Following the best-practice guidelines for conducting neuroimaging meta-analyses, we searched several databases (PubMed, Web of Science, and BrainMap) and identified 39 eligible structural and functional studies, reporting coordinates reflecting significant group differences between ID patients and healthy controls. A significant convergent regional alteration in the subgenual anterior cingulate cortex (sgACC) was observed using the activation likelihood estimation algorithm. Behavioural decoding using the BrainMap database indicated that this region is involved in fear-related emotional and cognitive processing. The sgACC showed robust task-based co-activation in meta-analytic connectivity modelling and task-free functional connectivity in a resting-state functional connectivity analysis with the main hubs of the salience and default mode networks, including the posterior cingulate cortex and dorsal ACC, amygdala, hippocampus, and medial prefrontal cortex. Collectively, the findings from this large-scale meta-analysis suggest a critical role of the sgACC in the pathophysiology of ID.

Functional and structural brain abnormalities in substance use disorder: A multimodal meta-analysis of neuroimaging studies

INTRODUCTION

Numerous neuroimaging studies of resting-state functional imaging and voxel-based morphometry (VBM) have revealed that patients with substance use disorder (SUD) may present brain abnormalities, but their results were inconsistent. This multimodal neuroimaging meta-analysis aimed to estimate common and specific alterations in SUD patients by combining information from all available studies of spontaneous functional activity and gray matter volume (GMV).

METHODS

A whole-brain meta-analysis on resting-state functional imaging and VBM studies was conducted using the Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) software, followed by multimodal overlapping to comprehensively investigate function and structure of the brain in SUD.

RESULTS

In this meta-analysis, 39 independent studies with 47 datasets related to resting-state functional brain activity (1444 SUD patients; 1446 healthy controls [HCs]) were included, as well as 77 studies with 89 datasets for GMV (3457 SUD patients; 3774 HCs). Patients with SUD showed the decreased resting-state functional brain activity in the bilateral anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC). For the VBM meta-analysis, patients with SUD showed the reduced GMV in the bilateral ACC/mPFC, insula, thalamus extending to striatum, and left sensorimotor cortex.

CONCLUSIONS

This multimodal meta-analysis exhibited that SUD shows common impairment in both function and structure in the ACC/mPFC, suggesting that the deficits in functional and structural domains could be correlated together. In addition, a few regions exhibited only structural impairment in SUD, including the insula, thalamus, striatum, and sensorimotor areas.

Co-alteration Network Architecture of Major Depressive Disorder: A Multi-modal Neuroimaging Assessment of Large-scale Disease Effects

Major depressive disorder (MDD) exhibits diverse symptomology and neuroimaging studies report widespread disruption of key brain areas. Numerous theories underpinning the network degeneration hypothesis (NDH) posit that neuropsychiatric diseases selectively target brain areas via meaningful network mechanisms rather than as indistinct disease effects. The present study tests the hypothesis that MDD is a network-based disorder, both structurally and functionally. Coordinate-based meta-analysis and Activation Likelihood Estimation (CBMA-ALE) were used to assess the convergence of findings from 92 previously published studies in depression. An extension of CBMA-ALE was then used to generate a node-and-edge network model representing the co-alteration of brain areas impacted by MDD. Standardized measures of graph theoretical network architecture were assessed. Co-alteration patterns among the meta-analytic MDD nodes were then tested in independent, clinical T1-weighted structural magnetic resonance imaging (MRI) and resting-state functional (rs-fMRI) data. Differences in co-alteration profiles between MDD patients and healthy controls, as well as between controls and clinical subgroups of MDD patients, were assessed. A 65-node 144-edge co-alteration network model was derived for MDD. Testing of co-alteration profiles in replication data using the MDD nodes provided distinction between MDD and healthy controls in structural data. However, co-alteration profiles were not distinguished between patients and controls in rs-fMRI data. Improved distinction between patients and healthy controls was observed in clinically homogenous MDD subgroups in T1 data. MDD abnormalities demonstrated both structural and functional network architecture, though only structural networks exhibited between-groups differences. Our findings suggest improved utility of structural co-alteration networks for ongoing biomarker development.

Detection of advanced brain aging in schizophrenia and its structural underpinning by using normative brain age metrics

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Novel metrics are proposed using the brain age paradigm with normative modeling.

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Normative brain age is validated to reveal advanced aging in schizophrenia.

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Men with schizophrenia have older brain age than women with the disorder.

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The brain age in white matter is positively associated with the negative symptom.

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The precuneus and uncinate fasciculus are markedly related to the advanced aging.

Conceptualizing mental disorders as deviations from normative functioning provides a statistical perspective for understanding the individual heterogeneity underlying psychiatric disorders. To broaden the understanding of the idiosyncrasy of brain aging in schizophrenia, we introduced an imaging-derived brain age paradigm combined with normative modeling as novel brain age metrics. We constructed brain age models based on GM, WM, and their combination (multimodality) features of 482 normal participants. The normalized predicted age difference (nPAD) was estimated in 147 individuals with schizophrenia and their 130 demographically matched controls through normative models of brain age metrics and compared between the groups. Regression analyses were also performed to investigate the associations of nPAD with illness duration, onset age, symptom severity, and intelligence quotient. Finally, regional contributions to advanced brain aging in schizophrenia were investigated. The results showed that the individuals exhibited significantly higher nPAD (P < 0.001), indicating advanced normative brain age than the normal controls in GM, WM, and multimodality models. The nPAD measure based on WM was positively associated with the negative symptom score (P = 0.009), and negatively associated with the intelligence quotient (P = 0.039) and onset age (P = 0.006). The imaging features that contributed to nPAD mostly involved the prefrontal, temporal, and parietal lobes, especially the precuneus and uncinate fasciculus. This study demonstrates that normative brain age metrics could detect advanced brain aging and associated clinical and neuroanatomical features in schizophrenia. The proposed nPAD measures may be useful to investigate aberrant brain aging in mental disorders and their brain-phenotype relationships.

Psychosis Associated with Acquired Porencephaly—Cause or Incidental Finding? Case Report and Review of Literature

Porencephaly, a rare disease affecting the central nervous system, is represented by a cerebrospinal fluid-filled cavity in the brain. There are two types of porencephalic cavities: congenital and acquired. Porencephaly is mainly associated with neurological and developmental consequences. Associated psychotic symptoms were reported in a few cases, and due to this fact, there is a knowledge gap regarding the diagnostic and therapeutic approach to such cases. We present the case of a 32-year-old male diagnosed with a psychotic disorder associated with acquired porencephaly. The porencephalic cystic lesions were most probably due to a traumatic brain injury at the age of 6 years old. The psychotic symptomatology consisted of interoceptive/visceral hallucinations, delusions with persecutory and religious/magic content and disorganised behaviour. The porencephalic cavity was confirmed by a computed tomography scan. The patient was treated over the course of time with risperidone, olanzapine and zuclopenthixol. The existing literature regarding other cases of psychosis associated with porencephaly is discussed. In conclusion, even though porencephaly was asymptomatic for a long period of time, we argue that there is a causal relationship between the chronic psychotic symptoms and the porencephalic cyst in our case.

Neurobiology of Schizophrenia: A Comprehensive Review

Schizophrenia is a debilitating disease that presents with both positive and negative symptoms affecting cognition and emotions. Extensive studies have analyzed the different factors that contribute to the disorder. There is evidence of significant genetic etiology involving multiple genes such as dystrobrevin binding protein 1 (DTNBP1) and neuregulin 1 (NRG1). There is no clear link between neurotransmitter changes and the pathophysiology of schizophrenia; however, studies have shown that subcortical dopamine dysfunction is the key mechanism. Specific regions of gray and white matter changes are observed in patients with schizophrenia; gray matter changes being more significant after the onset of psychosis. These pathological changes may be implicated in the impairment of executive functioning, attention, and working memory. The disease can be managed with pharmacological treatments based on individual patient profile, patient compliance, and disease severity. The challenge of disease management sometimes persists due to the side effects. A better understanding of the pathological processes in schizophrenia may lead to more specific and effective therapies.

Serum lipids and suicidal risk among patients with schizophrenia spectrum disorders: Systematic review and meta-analysis

OBJECTIVE

A systematic review of literature was conducted to determine the association between serum lipids and suicidality in people with schizophrenia spectrum disorders.

METHODS

We undertook a systematic search of multiple databases for studies that ascertained an association between serum lipids and suicidality in adult patients with schizophrenia spectrum disorders (18-65 years) from database inception to 2 September 2020. Qualitative analysis was done using National Institute of Health (NIH) scales. The standard mean difference (SMD) and 95% confidence intervals (CI) were calculated for each study and standardized relative to the study. Adjusted p-value, Z-test, and heterogeneity were calculated, as well as testing for publication bias.

RESULTS

Of 1262 records identified, 17 studies (n = 3113) were included in our systematic review, while 11 studies were included in the meta-analysis. The majority of studies (11) rated fair on qualitative analysis. Data from seven studies (n = 1597) revealed a medium effect size for an association between low total cholesterol and suicide attempts (SMD -0.560; 95% CI: 0.949-0.170; p = 0.005). People with history of suicide attempt had a mean cholesterol value 0.56 SD lower than the mean in those without suicide attempts. There were differences in how a suicide attempt was defined and there was high heterogeneity (I² = 83.3%). No significant association was found between any of the serum lipid parameters and suicide ideation. Funnel-plot analysis suggested small study effects with publication bias.

CONCLUSIONS

Suicide attempts in people with schizophrenia spectrum disorders are associated with low mean total cholesterol levels.

Volumetric differences in gray and white matter of cerebellar Crus I/II across the different clinical stages of schizophrenia

AIM

Schizophrenia is considered to be a disorder of progressive structural brain abnormalities. Previous studies have indicated that the cerebellar Crus I/II plays a critical role in schizophrenia. We aimed to investigate how specific morphological features in the Crus I/II at different critical stages of the schizophrenia spectrum contribute to the disease.

METHODS

The study involved 73 participants on the schizophrenia spectrum (28 with ultra-high risk for psychosis [UHR], 17 with first-episode schizophrenia [FES], and 28 with chronic schizophrenia) and 79 healthy controls. We undertook a detailed investigation into differences in Crus I/II volume using a semiautomated segmentation method optimized for the cerebellum. We analyzed the effects of group and sex, as well as their interaction, on Crus I/II volume in gray matter (GM) and white matter (WM).

RESULTS

Significant group × sex interactions were found in WM volumes of the bilateral Crus I/II; the males with UHR demonstrated significantly larger WM volumes compared with the other male groups, whereas no significant group differences were found in the female groups. Additionally, WM and GM volumes of the Crus I/II had positive associations with symptom severity in the UHR group, whereas, in contrast, GM volumes in the FES group were negatively associated with symptom severity.

CONCLUSIONS

The present findings provide evidence that the morphology of Crus I/II is involved in schizophrenia in a sex- and disease stage-dependent manner. Additionally, alterations of WM volumes of Crus I/II may have potential as a biological marker of early detection and treatment for individuals with UHR.

Comparative Study on the Functional Connectivity of Amygdala and Hippocampal Neural Circuits in Patients With First-Episode Schizophrenia and Other High-Risk Populations

Objective: Cortical-limbic system neural circuit abnormalities are closely related to the onset of schizophrenia (SZ). The amygdala, hippocampus, cingulate, and prefrontal lobe are important components of the loop. In this study, we compared resting-state functional connectivity (rs-FC) between the amygdala/hippocampus and cingulate/prefrontal regions among patients with first-episode schizophrenia (FE-SZ), high risk populations with SZ (HR-SZ), and healthy controls (HCs). By discovering the abnormal pattern of the cortical-limbic system of SZ and HR-SZ, we attempted to elucidate the pathophysiological mechanism of SZ. Method: This study collected seventy-five FE-SZ patients, 59 HR-SZ, and 64 HCs. Analysis of variance and chi-square tests were used to analyze their demographic data. Analysis of covariance and post-hoc analysis were performed on the functional connectivity of the three groups. Finally, correlation analysis between the significant brain functional connectivity value and the scale score was performed. Results: The results of the analysis of covariance showed that there were significant differences in rs-FC between the amygdala and the right middle cingulate and between the hippocampus and the bilateral medial superior frontal gyrus among the three groups (Gaussian random field (GRF)-corrected voxel p < 0.001, cluster p < 0.05). Post hoc comparisons showed that the rs-FC of the amygdala-right middle cingulate and the hippocampus-bilateral medial superior frontal gyrus in patients with SZ was significantly lower than that of HR-SZ and HC (Bonferroni corrected p < 0.001). There was no significant difference between the HR-SZ and HC groups. The results of the correlation analysis showed that rs-FC of the hippocampus-medial frontal gyrus in patients with SZ was positively correlated with core depression factor scores on the Hamilton Depression Scale (P = 0.006, R = 0.357). Conclusion: There were different patterns of functional connectivity impairment in the amygdala and hippocampal neural circuits in the schizophrenic cortical-limbic system, and these patterns may be more useful than genetics as state-related imaging changes of the disease.

Multimodal Abnormalities of Brain Structure and Function in Major Depressive Disorder: A Meta-Analysis of Neuroimaging Studies

OBJECTIVE

Imaging studies of major depressive disorder have reported structural and functional abnormalities in a variety of spatially diverse brain regions. Quantitative meta-analyses of this literature, however, have failed to find statistically significant between-study spatial convergence, other than transdiagnostic-only effects. In the present study, the authors applied a novel multimodal meta-analytic approach to test the hypothesis that major depression exhibits spatially convergent structural and functional brain abnormalities.

METHODS

This coordinate-based meta-analysis included voxel-based morphometry (VBM) studies and resting-state voxel-based pathophysiology (VBP) studies of blood flow, glucose metabolism, regional homogeneity, and amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF). Input data were grouped into three primary meta-analytic classes: gray matter atrophy, increased function, and decreased function in patients with major depression relative to healthy control subjects. In secondary meta-analyses, the data were grouped across primary categories, and in tertiary analyses, by medication status and absence of psychiatric comorbidity. Activation likelihood estimation was used for all analyses.

RESULTS

A total of 92 publications reporting 152 experiments were identified, collectively representing 2,928 patients with major depressive disorder. The primary analyses detected no convergence across studies. The secondary analyses identified portions of the subgenual cingulate cortex, hippocampus, amygdala, and putamen as demonstrating convergent abnormalities. The tertiary analyses (clinical subtypes) showed improved convergence relative to the secondary analyses.

CONCLUSIONS

Coordinate-based meta-analysis identified spatially convergent structural (VBM) and functional (VBP) abnormalities in major depression. The findings suggest replicable neuroimaging features associated with major depression, beyond the transdiagnostic effects reported in previous meta-analyses, and support a continued research focus on the subgenual cingulate and other selected regions' role in depression.

Anterior cingulate morphology in people at genetic high-risk of schizophrenia

Background

Morphological abnormalities of the anterior cingulate (AC) occur in patients with schizophrenia and in symptomatic high-risk individuals, and may be predictive of subsequent psychosis. We investigated AC sulcal morphology in the Edinburgh High Risk Study cohort to see if such abnormalities are evident and predict psychosis in patients’ relatives. We also investigated the association of the cingulate sulcus (CS) and paracingulate sulcus (PCS) variants with intelligence quotient (IQ).

Patients and methods

We compared cingulate and paracingulate sulcal anatomy, using reliable standardised measurements, blind to group membership, in those at high genetic risk (n = 146), first episode patients (n = 34) and healthy controls (n = 36); and compared high-risk subjects who did (n = 17) or did not develop schizophrenia.

Results

Interruptions of the cingulate sulcus were more common in high-risk individuals and in those with schizophrenia, in both hemispheres, compared to controls. When separated by gender, these results were only present in males in the left hemisphere and only in females in the right hemisphere. A well-formed paracingulate sulcus was less common in high-risk participants and patients with schizophrenia, compared to controls; but this association was only present in males. These morphological variants of the paracingulate sulcus and the continuous cingulate sulcus were also associated with the higher IQ in male high-risk individuals.

Conclusions

An interrupted cingulate sulcus pattern in both males and females and paracingulate morphology in males are associated with increased genetic risk of schizophrenia. Associations between cingulate and paracingulate morphology and premorbid IQ scores provide evidence that intellectual ability could be related to particular cytoarchitectural brain regions. Given that these sulci develop in early fetal life, such findings presumably reflect early neurodevelopmental abnormalities of genetic origin, although environmental effects and interactions cannot be ruled out.

Magnitude and heterogeneity of brain structural abnormalities in 22q11.2 deletion syndrome: a meta-analysis

The 22q11.2 deletion syndrome (22q11.2DS) is a neurodevelopmental disorder associated with a number of volumetric brain abnormalities. The syndrome is also associated with an increased risk for neuropsychiatric disorders including schizophrenia and autism spectrum disorder. An earlier meta-analysis showed reduced grey and white matter volumes in individuals with 22q11.2DS. Since this analysis was conducted, the number of studies has increased markedly, permitting more precise estimates of effects and more regions to be examined. Although 22q11.2DS is clinically heterogeneous, it is not known to what extent this heterogeneity is mirrored in neuroanatomy. The aim of this study was thus to investigate differences in mean brain volume and structural variability within regions, between 22q11.2DS and typically developing controls. We examined studies that reported measures of brain volume using MRI in PubMed, Web of Science, Scopus and PsycINFO from inception to 1 May 2019. Data were extracted from studies in order to calculate effect sizes representing case-control difference in mean volume, and in the variability of volume (as measured using the log variability ratio (lnVR) and coefficient of variation ratio (CVR)). We found significant overall decreases in mean volume in 22q11.2DS compared with control for: total brain (g = -0.96; p < 0.001); total grey matter (g = -0.81, p < 0.001); and total white matter (g = -0.81; p < 0.001). There was also a significant overall reduction of mean volume in 22q11.2DS subjects compared with controls in frontal lobe (g = -0.47; p < 0.001), temporal lobe (g = -0.84; p < 0.001), parietal lobe (g = -0.73; p = 0.053), cerebellum (g = -1.25; p < 0.001) and hippocampus (g = -0.90; p < 0.001). Significantly increased variability in 22q11.2DS individuals compared with controls was found only for the hippocampus (VR, 1.14; p = 0.036; CVR, 1.30; p < 0.001), and lateral ventricles (VR, 1.56; p = 0.004). The results support the notion that structural abnormalities in 22q11.2DS and schizophrenia are convergent, and also to some degree with findings in autism spectrum disorder. Finally, the increased variability seen in the hippocampus in 22q11.2DS may underlie some of the heterogeneity observed in the neuropsychiatric phenotype.

Decreased regional homogeneity and increased functional connectivity of default network correlated with neurocognitive deficits in subjects with genetic high-risk for schizophrenia: A resting-state fMRI study

The complex symptoms of schizophrenia (SCZ) have been associated with dysfunction of the default mode network (DMN). Subjects at genetic high risk (GHR) for SCZ exhibit similar but milder brain abnormalities. This study aimed to investigate functional alterations of DMN from the local to the whole and their relationships with cognitive deficits in GHR subjects. 42 GHR subjects and 38 matched healthy controls (HC) were studied by resting-state functional magnetic resonance imaging (rs-fMRI). Regional homogeneity (ReHo) analysis was performed to measure the local brain function of the DMN, derived by the group independent component analysis, and areas with aberrant ReHo were used as seeds in functional connectivity (FC). Compared with the HC group, the GHR group exhibited significantly decreased ReHo and increased FC in the fronto-limbic-striatal system within the DMN. Furthermore, a significant negative correlation was found between decreased ReHo in the right superior frontal gyrus and the delayed recall in GHR subjects. Our findings revealed decreased local function and hyper-connectivity in the fronto-limbic-striatal system of the DMN in GHR subjects, which is associated with cognitive deficits. This may improve our understanding of the neurophysiological endophenotypes of SCZ and the neural substrate underlying the cognitive deficits of the disease.

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

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

Reading the (functional) writing on the (structural) wall: Multimodal fusion of brain structure and function via a deep neural network based translation approach reveals novel impairments in schizophrenia

This work presents a novel approach to finding linkage/association between multimodal brain imaging data, such as structural MRI (sMRI) and functional MRI (fMRI). Motivated by the machine translation domain, we employ a deep learning model, and consider two different imaging views of the same brain like two different languages conveying some common facts. That analogy enables finding linkages between two modalities. The proposed translation-based fusion model contains a computing layer that learns "alignments" (or links) between dynamic connectivity features from fMRI data and static gray matter patterns from sMRI data. The approach is evaluated on a multi-site dataset consisting of eyes-closed resting state imaging data collected from 298 subjects (age- and gender matched 154 healthy controls and 144 patients with schizophrenia). Results are further confirmed on an independent dataset consisting of eyes-open resting state imaging data from 189 subjects (age- and gender matched 91 healthy controls and 98 patients with schizophrenia). We used dynamic functional connectivity (dFNC) states as the functional features and ICA-based sources from gray matter densities as the structural features. The dFNC states characterized by weakly correlated intrinsic connectivity networks (ICNs) were found to have stronger association with putamen and insular gray matter pattern, while the dFNC states of profuse strongly correlated ICNs exhibited stronger links with the gray matter pattern in precuneus, posterior cingulate cortex (PCC), and temporal cortex. Further investigation with the estimated link strength (or alignment score) showed significant group differences between healthy controls and patients with schizophrenia in several key regions including temporal lobe, and linked these to connectivity states showing less occupancy in healthy controls. Moreover, this novel approach revealed significant correlation between a cognitive score (attention/vigilance) and the function/structure alignment score that was not detected when data modalities were considered separately.

Weak dorsolateral prefrontal response to social criticism predicts worsened mood and symptoms following social conflict in people at familial risk for schizophrenia

Understanding the specific mechanisms that explain why people who have relatives with schizophrenia (i.e., people at familial high risk; FHR) are more likely to develop the disorder is crucial for prevention. We investigated a diathesis-stress model of familial risk by testing whether FHR individuals under-recruit brain regions central to emotion regulation when exposed to social conflict, resulting in worse mood and symptoms following conflict. FHR and non-FHR participants listened to critical, neutral, and praising comments in an fMRI scanner before completing 4 weeks of daily-diary records. Compared to non-FHR individuals, FHR individuals under-recruited the bilateral dorsolateral prefrontal cortex (DLPFC)-a region strongly implicated in cognitive emotion regulation-following criticism. Furthermore, within FHR participants, weak DLPFC response to criticism in the laboratory task was associated with elevated negative mood and positive symptoms on days with distressing social conflicts in daily-diary assessments. Results extend diathesis-stress models of schizophrenia by clarifying neural and environmental pathways to dysregulation in FHR individuals.

Imaging and Genetic Biomarkers Predicting Transition to Psychosis

The search for diagnostic and prognostic biomarkers in schizophrenia care and treatment is the focus of many within the research community. Longitudinal cohorts of patients presenting at elevated genetic and clinical risk have provided a wealth of data that has informed our understanding of the development of schizophrenia and related psychotic disorders.Imaging follow-up of high-risk cohorts has demonstrated changes in cerebral grey matter of those that eventually transition to schizophrenia that predate the onset of symptoms and evolve over the course of illness. Longitudinal follow-up studies demonstrate that observed grey matter changes can be employed to differentiate those who will transition to schizophrenia from those who will not prior to the onset of the disorder.In recent years our understanding of the genetic makeup of schizophrenia has advanced significantly. The development of modern analysis techniques offers researchers the ability to objectively quantify genetic risk; these have been successfully applied within a high-risk paradigm to assist in differentiating between high-risk individuals who will subsequently become unwell and those who will not.This chapter will discuss the application of imaging and genetic biomarkers within high-risk groups to predict future transition to schizophrenia and related psychotic disorders. We aim to provide an overview of current approaches focussing on grey matter changes that are predictive of future transition to illness, the developing field of genetic risk scores and other methods being developed to aid clinicians in diagnosis and prognosis.

Deficits in Neurite Density Underlie White Matter Structure Abnormalities in First-Episode Psychosis

BACKGROUND

Structural abnormalities across multiple white matter tracts are recognized in people with early psychosis, consistent with dysconnectivity as a neuropathological account of symptom expression. We applied advanced neuroimaging techniques to characterize microstructural white matter abnormalities for a deeper understanding of the developmental etiology of psychosis.

METHODS

Thirty-five first-episode psychosis patients, and 19 healthy controls, participated in a quantitative neuroimaging study using neurite orientation dispersion and density imaging, a multishell diffusion-weighted magnetic resonance imaging technique that distinguishes white matter fiber arrangement and geometry from changes in neurite density. Fractional anisotropy (FA) and mean diffusivity images were also derived. Tract-based spatial statistics compared white matter structure between patients and control subjects and tested associations with age, symptom severity, and medication.

RESULTS

Patients with first-episode psychosis had lower regional FA in multiple commissural, corticospinal, and association tracts. These abnormalities predominantly colocalized with regions of reduced neurite density, rather than aberrant fiber bundle arrangement (orientation dispersion index). There was no direct relationship with active symptoms. FA decreased and orientation dispersion index increased with age in patients, but not control subjects, suggesting accelerated effects of white matter geometry change.

CONCLUSIONS

Deficits in neurite density appear fundamental to abnormalities in white matter integrity in early psychosis. In the first application of neurite orientation dispersion and density imaging in psychosis, we found that processes compromising axonal fiber number, density, and myelination, rather than processes leading to spatial disruption of fiber organization, are implicated in the etiology of psychosis. This accords with a neurodevelopmental origin of aberrant brain-wide structural connectivity predisposing individuals to psychosis.

Comprehensive review: Computational modelling of schizophrenia

Computational modelling has been used to address: (1) the variety of symptoms observed in schizophrenia using abstract models of behavior (e.g. Bayesian models - top-down descriptive models of psychopathology); (2) the causes of these symptoms using biologically realistic models involving abnormal neuromodulation and/or receptor imbalance (e.g. connectionist and neural networks - bottom-up realistic models of neural processes). These different levels of analysis have been used to answer different questions (i.e. understanding behavioral vs. neurobiological anomalies) about the nature of the disorder. As such, these computational studies have mostly supported diverging hypotheses of schizophrenia's pathophysiology, resulting in a literature that is not always expanding coherently. Some of these hypotheses are however ripe for revision using novel empirical evidence. Here we present a review that first synthesizes the literature of computational modelling for schizophrenia and psychotic symptoms into categories supporting the dopamine, glutamate, GABA, dysconnection and Bayesian inference hypotheses respectively. Secondly, we compare model predictions against the accumulated empirical evidence and finally we identify specific hypotheses that have been left relatively under-investigated.

Sensory integration deficits support a dimensional view of psychosis and are not limited to schizophrenia

Visual dysfunction is commonplace in schizophrenia and occurs alongside cognitive, psychotic and affective symptoms of the disorder. Psychophysical evidence suggests that this dysfunction results from impairments in the integration of low-level neural signals into complex cortical representations, which may also be associated with symptom formation. Despite the symptoms of schizophrenia occurring in a range of disorders, the integration deficit has not been tested in broader patient populations. Moreover, it remains unclear whether such deficits generalize across other sensory modalities. The present study assessed patients with a range of psychotic and nonpsychotic disorders and healthy controls on visual contrast detection, visual motion integration, auditory tone detection and auditory tone integration. The sample comprised a total of 249 participants (schizophrenia spectrum disorder n=98; bipolar affective disorder n=35; major depression n=31; other psychiatric conditions n=31; and healthy controls n=54), of whom 178 completed one or more visual task and 71 completed auditory tasks. Compared with healthy controls and nonpsychotic patients, psychotic patients trans-diagnostically were impaired on both visual and auditory integration, but unimpaired in simple visual or auditory detection. Impairment in visual motion integration was correlated with the severity of positive symptoms, and could not be accounted for by a reduction in processing speed, inattention or medication effects. Our results demonstrate that impaired sensory integration is not specific to schizophrenia, as has previously been assumed. Instead, sensory deficits are closely related to the presence of positive symptoms independent of diagnosis. The finding that equivalent integrative sensory processing is impaired in audition is consistent with hypotheses that propose a generalized deficit of neural integration in psychotic disorders.

Familial and environmental influences on brain volumes in twins with schizophrenia

BACKGROUND

Reductions in whole brain and grey matter volumes are robust features of schizophrenia, yet their etiological influences are unclear.

METHODS

We investigated the association between the genetic and environmental risk for schizophrenia and brain volumes. Whole brain, grey matter and white matter volumes were established from structural MRIs from twins varying in their zygosity and concordance for schizophrenia. Hippocampal volumes were measured manually. We conducted between-group testing and full genetic modelling.

RESULTS

We included 168 twins in our study. Whole brain, grey matter, white matter and right hippocampal volumes were smaller in twins with schizophrenia. Twin correlations were larger for whole brain, grey matter and white matter volumes in monozygotic than dizygotic twins and were significantly heritable, whereas hippocampal volume was the most environmentally sensitive. There was a significant phenotypic correlation between schizophrenia and reductions in all the brain volumes except for that of the left hippocampus. For whole brain, grey matter and the right hippocampus the etiological links with schizophrenia were principally associated with the shared familial environment. Lower birth weight and perinatal hypoxia were both associated with lower whole brain volume and with lower white matter and grey matter volumes, respectively.

LIMITATIONS

Scan data were collected across 2 sites, and some groups were modest in size.

CONCLUSION

Whole brain, grey matter and right hippocampal volume reductions are linked to schizophrenia through correlated familial risk (i.e., the shared familial environment). The degree of influence of etiological factors varies between brain structures, leading to the possibility of a neuroanatomically specific etiological imprint.

Partitioning heritability analysis reveals a shared genetic basis of brain anatomy and schizophrenia

Schizophrenia is a devastating neurodevelopmental disorder with a complex genetic etiology. Widespread cortical gray matter loss has been observed in patients and prodromal samples. However, it remains unresolved whether schizophrenia-associated cortical structure variations arise due to disease etiology or secondary to the illness. Here we address this question using a partitioning-based heritability analysis of genome-wide single-nucleotide polymorphism (SNP) and neuroimaging data from 1750 healthy individuals. We find that schizophrenia-associated genetic variants explain a significantly enriched proportion of trait heritability in eight brain phenotypes (false discovery rate=10%). In particular, intracranial volume and left superior frontal gyrus thickness exhibit significant and robust associations with schizophrenia genetic risk under varying SNP selection conditions. Cross-disorder comparison suggests that the neurogenetic architecture of schizophrenia-associated brain regions is, at least in part, shared with other psychiatric disorders. Our study highlights key neuroanatomical correlates of schizophrenia genetic risk in the general population. These may provide fundamental insights into the complex pathophysiology of the illness, and a potential link to neurocognitive deficits shaping the disorder.

Balanced translocation linked to psychiatric disorder, glutamate, and cortical structure/function

Rare genetic variants of large effect can help elucidate the pathophysiology of brain disorders. Here we expand the clinical and genetic analyses of a family with a (1;11)(q42;q14.3) translocation multiply affected by major psychiatric illness and test the effect of the translocation on the structure and function of prefrontal, and temporal brain regions. The translocation showed significant linkage (LOD score 6.1) with a clinical phenotype that included schizophrenia, schizoaffective disorder, bipolar disorder, and recurrent major depressive disorder. Translocation carriers showed reduced cortical thickness in the left temporal lobe, which correlated with general psychopathology and positive psychotic symptom severity. They showed reduced gyrification in prefrontal cortex, which correlated with general psychopathology severity. Translocation carriers also showed significantly increased activation in the caudate nucleus on increasing verbal working memory load, as well as statistically significant reductions in the right dorsolateral prefrontal cortex glutamate concentrations. These findings confirm that the t(1;11) translocation is associated with a significantly increased risk of major psychiatric disorder and suggest a general vulnerability to psychopathology through altered cortical structure and function, and decreased glutamate levels.

Functional brain substrate of quality of life in patients with schizophrenia: A brain SPECT multidimensional analysis

The aim of this study was to investigate the functional brain substrate of quality of life (QoL) in patients with schizophrenia. Participants comprised 130 right-handed patients with schizophrenia who underwent whole-brain single photon emission computed tomography (SPECT) with (99m)Tc-labeled ethylcysteinate dimer ((99m)Tc-ECD) for exploring correlations of regional cerebral blood flow (rCBF) with the eight dimensions score of the Schizophrenia Quality of Life questionnaire (S-QoL 18). A significant positive correlation was found between the global index of the S-QoL 18 and rCBF in the right superior temporal sulcus and between psychological well-being dimension and rCBF in Brodmann area (BA)6, BA8, BA9, and BA10 and between self-esteem dimension and rCBF in striatum and between family relationship dimension and rCBF in BA1, BA2, BA3, BA4, BA8, BA22, BA40, BA42 and BA44 and between relationship with friends dimension and rCBF in BA44 and between physical well-being dimension and rCBF in parahippocampal gyrus, and finally between autonomy dimension and rCBF in cuneus and precuneus. A significant negative correlation was found between resilience dimension and rCBF in precuneus and between sentimental life dimension and rCBF in BA10. Our findings provide neural correlates of QoL. Brain regions involved in cognitions, emotional information processing and social cognition underlie the different QoL dimensions.

Childhood adversity and cortical thickness and surface area in a population at familial high risk of schizophrenia

BACKGROUND

There is now a well-established link between childhood adversity (CA) and schizophrenia. Similar structural abnormalities to those found in schizophrenia including alterations in grey-matter volume have also been shown in those who experience CA.

METHOD

We examined whether global estimates of cortical thickness or surface area were altered in those familial high-risk subjects who had been referred to a social worker or the Children's Panel compared to those who had not.

RESULTS

We found that the cortical surface area of those who were referred to the Children's Panel was significantly smaller than those who had not been referred, but cortical thickness was not significantly altered. There was also an effect of social work referral on cortical surface area but not on thickness.

CONCLUSIONS

Cortical surface area increases post-natally more than cortical thickness. Our findings suggest that CA can influence structural changes in the brain and it is likely to have a greater impact on cortical surface area than on cortical thickness.

Maturation- and sex-sensitive depression of hippocampal excitatory transmission in a rat schizophrenia model

Schizophrenia is associated with behavioral and brain structural abnormalities, of which the hippocampus appears to be one of the most consistent region affected. Previous studies performed on the poly I:C model of schizophrenia suggest that alterations in hippocampal synaptic transmission and plasticity take place in the offspring. However, these investigations yielded conflicting results and the neurophysiological alterations responsible for these deficits are still unclear. Here we performed for the first time a longitudinal study examining the impact of prenatal poly I:C treatment and of gender on hippocampal excitatory neurotransmission. In addition, we examined the potential preventive/curative effects of risperidone (RIS) treatment during the peri-adolescence period. Excitatory synaptic transmission was determined by stimulating Schaffer collaterals and monitoring fiber volley amplitude and slope of field-EPSP (fEPSP) in CA1 pyramidal neurons in male and female offspring hippocampal slices from postnatal days (PNDs) 18-20, 34, 70 and 90. Depression of hippocampal excitatory transmission appeared at juvenile age in male offspring of the poly I:C group, while it expressed with a delay in female, manifesting at adulthood. In addition, a reduced hippocampal size was found in both adult male and female offspring of poly I:C treated dams. Treatment with RIS at the peri-adolescence period fully restored in males but partly repaired in females these deficiencies. A maturation- and sex-dependent decrease in hippocampal excitatory transmission occurs in the offspring of poly I:C treated pregnant mothers. Pharmacological intervention with RIS during peri-adolescence can cure in a gender-sensitive fashion early occurring hippocampal synaptic deficits.

Association between genetic risk scoring for schizophrenia and bipolar disorder with regional subcortical volumes

Previous research has shown coincident abnormal regional brain volume in patients with schizophrenia (SCZ) and bipolar disorder (BD) compared with controls. Whether these abnormalities are genetically driven or explained by secondary effects of the disorder or environmental factors is unknown. We aimed to investigate the association between genetic risk scoring (GRS) for SCZ and BD with volume of brain areas previously shown to be different between these clinical groups and healthy controls. We obtained subcortical brain volume measures and GRS for SCZ and BD from a sample of 274 healthy volunteers (71.4% females, mean age 24.7 (s.d. 6.9)). Volume of the globus pallidus was associated with the shared GRS between SCZ and BD, and also with the independent GRS for each of these disorders. Volume of the amygdala was associated with the non-shared GRS between SCZ and BD, and with the independent GRS for BD. Our results for volume of the globus pallidus support the idea of SCZ and BD sharing a common underlying neurobiological abnormality associated with a common genetic risk for both these disorders. Results for volume of the amygdala, though, would suggest the existence of a distinct mechanism only associated with genetic risk for BD. Finally, the lack of association between genetic risk and volume of most subcortical structures suggests that the volumetric differences reported in patient-control comparisons may not be genetically driven, but a consequence of the disorder or co-occurring environmental factors.

Baseline putamen volume as a predictor of positive symptom reduction in patients at clinical high risk for psychosis: A preliminary study

OBJECTIVES

Illness course in individuals at clinical high risk (CHR) status for psychosis is heterogeneous, which limits effective treatment for all CHR subgroups. Baseline predictors of positive symptom trajectory in the CHR group will reduce such limitations. We singled out the putamen, thought to be involved in the generation of the key schizophrenia symptoms early in the course of disease, as a potential predictor of positive symptom trajectory in CHR patients.

METHOD

We recruited 45 CHR patients and 29 age- and gender-matched healthy controls (HC). The CHR group was divided into patients with positive symptom reduction (CHR-R) and patients without positive symptom reduction (CHR-NR) at 6 months. Comparisons were made between the baseline putamen volumes of CHR-R, CHR-NR and HC groups. The relationship between baseline putamen volumes and clinical measures was investigated.

RESULTS

Left putamen volumes of CHR-R patients were significantly smaller than those of HCs (p=0.002) and of CHR-NR patients (p=0.024). CHR-R patients had significantly reduced leftward laterality compared to HCs (p=0.007). In the CHR-R group, bilateral putamen volumes were correlated with positive symptom severity at baseline (r=-0.552, p=0.001) and at 6 months (r=-0.360, p=0.043), and predicted positive symptom score change in 6 months at a trend level (p=0.092).

CONCLUSION

Smaller left putamen volumes in CHR-R patients, and the correlation between positive symptom severity and putamen volumes suggest that putamen volume is a possible risk-stratifier and predictor of clinical course in the CHR population.

Grey matter networks in people at increased familial risk for schizophrenia

Grey matter brain networks are disrupted in schizophrenia, but it is still unclear at which point during the development of the illness these disruptions arise and whether these can be associated with behavioural predictors of schizophrenia. We investigated if single-subject grey matter networks were disrupted in a sample of people at familial risk of schizophrenia. Single-subject grey matter networks were extracted from structural MRI scans of 144 high risk subjects, 32 recent-onset patients and 36 healthy controls. The following network properties were calculated: size, connectivity density, degree, path length, clustering coefficient, betweenness centrality and small world properties. People at risk of schizophrenia showed decreased path length and clustering in mostly prefrontal and temporal areas. Within the high risk sample, the path length of the posterior cingulate cortex and the betweenness centrality of the left inferior frontal operculum explained 81% of the variance in schizotypal cognitions, which was previously shown to be the strongest behavioural predictor of schizophrenia in the study. In contrast, local grey matter volume measurements explained 48% of variance in schizotypy. The present results suggest that single-subject grey matter networks can quantify behaviourally relevant biological alterations in people at increased risk for schizophrenia before disease onset.

Brain structural and clinical changes after first episode psychosis: Focus on cannabinoid receptor 1 polymorphisms

Cannabinoid receptor 1 (CNR1) gene polymorphisms have been associated with central and peripheral effects of cannabis and schizophrenia pathophysiology. Here, we have tested whether three CNR1 variants (rs1049353, rs1535255 and rs2023239) are associated with changes in brain volumes, body mass index (BMI) or psychopathological scores in a 3-year longitudinal study of 65 first-episode psychosis patients. The rs1049353 at-risk allele was significantly associated with a greater reduction of caudate volume, and the rs2023239 T/C polymorphism showed a significant decrease in thalamic volume after the 3-year period. For those who were not cannabis users, the rs1535255 and rs2023239 polymorphisms had effects in lateral ventricle (LV), and LV and white matter, respectively. The rs2023239 variant also was associated with significant improvements in positive and negative symptoms of schizophrenia. There was no significant effect of any of the variants on changes in BMI over the 3-year study. Finally, an interaction between all three polymorphisms was found involving evolution of positive symptoms. These findings suggest that the cannabinoid pathway is associated with schizophrenia evolution over time. However, further studies using larger cohorts are needed to confirm these results. If confirmed, the present findings could lead in subsequent investigations for identification of novel drug targets for improved treatment of patients suffering from schizophrenia.

The cortical thickness phenotype of individuals with DISC1 translocation resembles schizophrenia

BACKGROUND. The disrupted in schizophrenia 1 (DISC1) gene locus was originally identified in a Scottish pedigree with a high incidence of psychiatric disorders that is associated with a balanced t(1;11)(q42.1;q14.3) chromosomal translocation. Here, we investigated whether members of this family carrying the t(1;11)(q42.1;q14.3) translocation have a common brain-related phenotype and whether this phenotype is similar to that observed in schizophrenia (SCZ), using multivariate pattern recognition techniques.

METHODS. We measured cortical thickness, cortical surface area, subcortical volumes, and regional cerebral blood flow (rCBF) in healthy controls (HC) (n = 24), patients diagnosed with SCZ (n = 24), patients diagnosed with bipolar disorder (BP) (n = 19), and members of the original Scottish family (n = 30) who were either carriers (T+) or noncarriers (T–) of the DISC1 translocation. Binary classification models were developed to assess the differences and similarities across groups.

RESULTS. Based on cortical thickness, 72% of the T– group were assigned to the HC group, 83% of the T+ group were assigned to the SCZ group, and 45% of the BP group were classified as belonging to the SCZ group, suggesting high specificity of this measurement in predicting brain-related phenotypes. Shared brain-related phenotypes between SCZ and T+ individuals were found for cortical thickness only. Finally, a classification accuracy of 73% was achieved when directly comparing the pattern of cortical thickness of T+ and T– individuals.

CONCLUSION. Together, the results of this study suggest that the DISC1 translocation may increase the risk of psychiatric disorders in this pedigree by affecting neurostructural phenotypes such as cortical thickness.

FUNDING. This work was supported by the National Health Service Research Scotland, the Scottish Translational Medicine Research Collaboration, the Innovative Medicines Initiative (IMI), the Engineering and Physical Sciences Research Council (EPSRC), The Wellcome Trust, the National Institute of Health Research (NIHR), and Pfizer.

Psychotic Experiences, Working Memory, and the Developing Brain: A Multimodal Neuroimaging Study

Psychotic experiences (PEs) occur in the general population, especially in children and adolescents, and are associated with poor psychosocial outcomes, impaired cognition, and increased risk of transition to psychosis. It is unknown how the presence and persistence of PEs during early adulthood affects cognition and brain function. The current study assessed working memory as well as brain function and structure in 149 individuals, with and without PEs, drawn from a population cohort. Observer-rated PEs were classified as persistent or transient on the basis of longitudinal assessments. Working memory was assessed using the n-back task during fMRI. Dynamic causal modeling (DCM) was used to characterize frontoparietal network configuration and voxel-based morphometry was utilized to examine gray matter. Those with persistent, but not transient, PEs performed worse on the n-back task, compared with controls, yet showed no significant differences in regional brain activation or brain structure. DCM analyses revealed greater emphasis on frontal connectivity within a frontoparietal network in those with PEs compared with controls. We propose that these findings portray an altered configuration of working memory function in the brain, potentially indicative of an adaptive response to atypical development associated with the manifestation of PEs.

Hippocampal, amygdala and nucleus accumbens volume in first-episode schizophrenia patients and individuals at high familial risk: A cross-sectional comparison

It is unknown whether brain changes occur prior to onset of schizophrenia or after it develops. Prospective familial high risk studies provide a good method to investigate this. In the Edinburgh High Risk Study, structural MRI scans of 150 young individuals at familial high risk of schizophrenia, 34 patients with first-episode schizophrenia and 36 matched controls were obtained. Of the high risk participants with scans suitable for analysis, 17 developed schizophrenia after the scans were taken, whilst 57 experienced isolated or sub-clinical psychotic symptoms, and 70 remained well. We used Freesurfer to extract volumetric measurements of the hippocampus, amygdala and nucleus accumbens with the aim of assessing whether any alterations found were present in all those at high risk, or selectively in the high risk cohort based on future clinical outcome, or only in those experiencing their first-episode of psychosis. We found no significant differences in any examined regions between controls and those at high risk, or between those at high risk who later developed schizophrenia and those who remained well. However, patients with first-episode schizophrenia demonstrated significant volumetric reductions in the bilateral hippocampus, left amygdala, and right nucleus accumbens compared to high risk individuals and healthy controls, which were not significantly associated with the intake of anti-psychotic medication or duration of illness. We found that patients had significantly smaller left amygdalae and bilateral hippocampus compared to HR[ill]. Our findings suggest that volumetric reductions of the hippocampus, amygdala and nucleus accumbens occur early in the first-episode of psychosis. The apparent absence of high risk versus control differences we found using Freesurfer is at odds with our previous studies conducted on the same sample, and possible methodological reasons for these apparent discrepancies are discussed.

Compromised small-world efficiency of structural brain networks in schizophrenic patients and their unaffected parents

Several lines of evidence suggest that efficient information integration between brain regions is disrupted in schizophrenia. Abnormalities in white matter tracts that interconnect brain regions may be directly relevant to this pathophysiological process. As a complex mental disorder with high heritability, mapping abnormalities in patients and their first-degree relatives may help to disentangle the risk factors for schizophrenia. We established a weighted network model of white matter connections using diffusion tensor imaging in 25 nuclear families with schizophrenic probands (19 patients and 41 unaffected parents) and two unrelated groups of normal controls (24 controls matched with patients and 26 controls matched with relatives). The patient group showed lower global efficiency and local efficiency. The decreased regional efficiency was localized in hubs such as the bilateral frontal cortices, bilateral anterior cingulate cortices, and left precuneus. The global efficiency was negatively correlated with cognition scores derived from a 5-factor model of schizophrenic psychopathology. We also found that unaffected parents displayed decreased regional efficiency in the right temporal cortices, left supplementary motor area, left superior temporal pole, and left thalamus. The global efficiency tended to be lower in unaffected parents. Our data suggest that (1) the global efficiency loss in neuroanatomical networks may be associated with the cognitive disturbances in schizophrenia; and (2) genetic vulnerability to schizophrenia may influence the anatomical organization of an individual's brain networks.

Regional white matter abnormalities in drug-naive, first-episode schizophrenia patients and their healthy unaffected siblings

OBJECTIVE

Shared neuropathological features between schizophrenia patients and their siblings may represent intermediate phenotypes of schizophrenia and can be used to investigate genetic susceptibility to the illness. This study aimed to discover regional white matter abnormalities in first-episode schizophrenia (FES) patients and their unaffected siblings compared to healthy subjects in the Chinese Han population using optimized Voxel-Based Morphometry (VBM).

METHOD

A total of 51 drug-naive, FES patients, 45 of their unaffected siblings and 59 healthy comparisons were studied with magnetic resonance imaging (MRI).

RESULTS

FES patients exhibited significant regional white matter deficits in the left inferior frontal gyrus and left joint of external capsule and internal capsule compared with healthy subjects (corrected FDR, p<0.005). The sibling group also showed significant white matter deficits in these two regions compared with the healthy comparison group (uncorrected, p<0.001). White matter deficits with a less stringent threshold for significance in the left cerebellum anterior lobe, left middle frontal gyrus, left hippocampus, right anterior cingulate and right internal capsule were observed in patients compared to their siblings.

CONCLUSIONS

Our findings extend those from previous VBM analyses showing that FES patients and their unaffected siblings may share white matter deficits in the left inferior frontal gyrus and the left joint of external capsule and internal capsule. These regional white matter deficits may be related to genetic factors related to schizophrenia susceptibility.

Fetal programming of schizophrenia: select mechanisms

Mounting evidence indicates that schizophrenia is associated with adverse intrauterine experiences. An adverse or suboptimal fetal environment can cause irreversible changes in brain that can subsequently exert long-lasting effects through resetting a diverse array of biological systems including endocrine, immune and nervous. It is evident from animal and imaging studies that subtle variations in the intrauterine environment can cause recognizable differences in brain structure and cognitive functions in the offspring. A wide variety of environmental factors may play a role in precipitating the emergent developmental dysregulation and the consequent evolution of psychiatric traits in early adulthood by inducing inflammatory, oxidative and nitrosative stress (IO&NS) pathways, mitochondrial dysfunction, apoptosis, and epigenetic dysregulation. However, the precise mechanisms behind such relationships and the specificity of the risk factors for schizophrenia remain exploratory. Considering the paucity of knowledge on fetal programming of schizophrenia, it is timely to consolidate the recent advances in the field and put forward an integrated overview of the mechanisms associated with fetal origin of schizophrenia.

Brain structure in people at ultra-high risk of psychosis, patients with first-episode schizophrenia, and healthy controls: a VBM study

Early intervention research in schizophrenia has suggested that brain structural alterations might be present in subjects at high risk of developing psychosis. The heterogeneity of regional effects of these changes, which is established in schizophrenia, however, has not been explored in prodromal or high-risk populations. We used high-resolution MRI and voxel-based morphometry (VBM8) to analyze grey matter differences in 43 ultra high-risk subjects for psychosis (meeting ARMS criteria, identified through CAARMS interviews), 24 antipsychotic-naïve first-episode schizophrenia patients and 49 healthy controls (groups matched for age and gender). Compared to healthy controls, resp., first-episode schizophrenia patients had reduced regional grey matter in left prefrontal, insula, right parietal and left temporal cortices, while the high-risk group showed reductions in right middle temporal and left anterior frontal cortices. When dividing the ultra-high-risk group in those with a genetic risk vs. those with attenuated psychotic symptoms, the former showed left anterior frontal, right caudate, as well as a smaller right hippocampus, and amygdala reduction, while the latter subgroup showed right middle temporal cortical reductions (each compared to healthy controls). Our findings in a clinical psychosis high-risk cohort demonstrate variability of brain structural changes according to subgroup and background of elevated risk, suggesting frontal and possibly also hippocampal/amygdala changes in individuals with genetic susceptibility. Heterogeneity of structural brain changes (as seen in schizophrenia) appears evident even at high-risk stage, prior to potential onset of psychosis.

Using Machine Learning to Estimate Global PM2.5 for Environmental Health Studies

With the increasing awareness of health impacts of particulate matter, there is a growing need to comprehend the spatial and temporal variations of the global abundance of ground-level airborne particulate matter (PM2.5). Here we use a suite of remote sensing and meteorological data products together with ground based observations of PM2.5 from 8,329 measurement sites in 55 countries taken between 1997 and 2014 to train a machine learning algorithm to estimate the daily distributions of PM2.5 from 1997 to the present. We demonstrate that the new PM2.5 data product can reliably represent global observations of PM2.5 for epidemiological studies. An analysis of Baltimore schizophrenia emergency room admissions is presented in terms of the levels of ambient pollution. PM2.5 appears to have an impact on some aspects of mental health.

Changes in the adolescent brain and the pathophysiology of psychotic disorders

Adolescence is a time of extensive neuroanatomical, functional, and chemical reorganisation of the brain which parallels substantial maturational changes in cognition and affect regulation. This period is characterised by stabilisation of synapses to diminish redundancy and increase efficiency of neural function, fine-tuning of excitatory and inhibitory neurotransmitter systems, beginning of integration between late maturing and early maturing brain structures, and development of effective connections. In effect, these so-called moving parts create a state of dynamic change that might underlie adolescent behaviours. Imbalances or changes in timing of these developmental processes clearly increase the risk for psychiatric disorders. Genetic, environmental, and epigenetic factors that shape brain development and hormonal changes that affect stress reactivity could be reasons why some, but not all, adolescents are at a heightened risk of developing a psychopathological disorder. In this Series paper, we assess the neurobiology of the changing adolescent brain, implications of this knowledge, and future research in major psychiatric disorders, particularly for psychotic disorders.

Facial emotion identification in early-onset and first-episode psychosis: a systematic review with meta-analysis

OBJECTIVE

Patients with chronic schizophrenia are characterized by deficits in identifying facial expressions of emotion, and these deficits relate to impaired social and occupational function. It is not yet known if these deficits are trait-like and present at the onset of psychosis, preceding a subsequent diagnosis of schizophrenia. Our objective was to systematically review and analyze the extant literature to assess if there is a consistent profile of emotion identification problems in early-onset and first-episode psychosis.

METHODS

We conducted a systematic review and meta-analysis of 12 peer-reviewed studies of facial emotion identification in early-onset and first-episode psychosis, published between 1980 and March 2013. We examined the average mean difference between patients and controls on measures of facial emotion identification.

RESULTS

Findings suggest that patients with early-onset and first-episode psychosis have impairment in identifying facial expressions of biologically salient emotion. Across the 12 studies, the onset of psychosis was distinguished by a generalized effect of significantly poorer accuracy for identifying facial expressions of emotion than healthy controls, and this difference had a substantial effect size (d=-0.88, N=378, 95% CI=-1.42 to -0.32). Within this general effect some emotions were also harder for patients to identify than others, with the magnitude of impairment found to be (i) large for disgust, fear and surprise, and (ii) medium for sadness, and happiness. No between groups mean differences were found for anger or neutral facial expressions.

CONCLUSIONS

Deficits in facial emotion identification are evident at first onset of a psychotic episode. The findings suggest that, over and above a generalized deficit in identifying facial emotion, patients may find some emotions harder to identifying than others. This reflects findings with chronic schizophrenia populations and suggests that emotion identification impairment represents a trait susceptibility marker, rather than a sequeale of illness. They signal the urgent need to treat emotion identification deficits at the onset of illness, which could improve functional outcomes.

Partial genetic deletion of neuregulin 1 and adolescent stress interact to alter NMDA receptor binding in the medial prefrontal cortex

Schizophrenia is thought to arise due to a complex interaction between genetic and environmental factors during early neurodevelopment. We have recently shown that partial genetic deletion of the schizophrenia susceptibility gene neuregulin 1 (Nrg1) and adolescent stress interact to disturb sensorimotor gating, neuroendocrine activity and dendritic morphology in mice. Both stress and Nrg1 may have converging effects upon N-methyl-D-aspartate receptors (NMDARs) which are implicated in the pathogenesis of schizophrenia, sensorimotor gating and dendritic spine plasticity. Using an identical repeated restraint stress paradigm to our previous study, here we determined NMDAR binding across various brain regions in adolescent Nrg1 heterozygous (HET) and wild-type (WT) mice using [³H] MK-801 autoradiography. Repeated restraint stress increased NMDAR binding in the ventral part of the lateral septum (LSV) and the dentate gyrus (DG) of the hippocampus irrespective of genotype. Partial genetic deletion of Nrg1 interacted with adolescent stress to promote an altered pattern of NMDAR binding in the infralimbic (IL) subregion of the medial prefrontal cortex. In the IL, whilst stress tended to increase NMDAR binding in WT mice, it decreased binding in Nrg1 HET mice. However, in the DG, stress selectively increased the expression of NMDAR binding in Nrg1 HET mice but not WT mice. These results demonstrate a Nrg1-stress interaction during adolescence on NMDAR binding in the medial prefrontal cortex.

A review of structural neuroimaging in schizophrenia: from connectivity to connectomics

In patients with schizophrenia neuroimaging studies have revealed global differences with some brain regions showing focal abnormalities. Examining neurocircuitry, diffusion-weighted imaging studies have identified altered structural integrity of white matter in frontal and temporal brain regions and tracts such as the cingulum bundles, uncinate fasciculi, internal capsules and corpus callosum associated with the illness. Furthermore, structural co-variance analyses have revealed altered structural relationships among regional morphology in the thalamus, frontal, temporal and parietal cortices in schizophrenia patients. The distributed nature of these abnormalities in schizophrenia suggests that multiple brain circuits are impaired, a neural feature that may be better addressed with network level analyses. However, even with the advent of these newer analyses, a large amount of variability in findings remains, likely partially due to the considerable heterogeneity present in this disorder.

Hippocampal atrophy and subsequent depressive symptoms in older men and women: results from a 10-year prospective cohort

Several studies have reported smaller hippocampal volume in patients with depression. However, the temporality of the association is undetermined. One hypothesis is that hippocampal atrophy might be a susceptibility factor for depression. In the present study, we assessed whether hippocampal atrophy was associated with subsequent depressive symptoms in a cohort of older French adults (n = 1,309) who were 65-80 years of age and enrolled into the study in 1999-2001 in Dijon, France. Subjects were followed for more than 10 years. Participants underwent 2 cerebral magnetic resonance imaging scans, one at baseline and one at the 4-year follow-up. We used linear mixed models to estimate the associations of hippocampal atrophy with 1) the average depressive symptom scores over follow-up (using the Center for Epidemiologic Studies-Depression scale) measured biennially over the subsequent 6 years and 2) changes in symptom scores over follow-up. In women, a 2-standard-deviation increase in annual hippocampal atrophy was associated with a 1.67-point (95% confidence interval: 0.59, 2.77) increase in the average depressive symptom score over follow-up and with a 1.97-point (95% confidence interval: 0.68, 3.24) increase in scores over the 2 subsequent years but not with later changes in symptoms. No association was detected in men. Accounting for potential selective attrition (using inverse probability weights) did not alter results. Hippocampal atrophy was associated with more subsequent depressive symptoms and with shorter-term worsening of symptoms in women.

Hippocampus and amygdala volumes in children and young adults at high-risk of schizophrenia: research synthesis

BACKGROUND

Studies have reported hippocampal and amygdala volume abnormalities in schizophrenic patients. It is necessary to explore the potential for these structures as early disease markers in subjects at high risk (HR) of schizophrenia.

METHODS

We performed a review of 29 magnetic resonance imaging (MRI) studies measuring hippocampal and amygdala volumes in subjects at HR for schizophrenia. We reclassified subjects in 3 new HR categories: presence of only risk symptoms (psychotic moderate symptoms), presence of only risk factors (genetic, developmental or environmental), and presence of combined risk symptoms/factors.

RESULTS

Hippocampal volume reductions were detected in subjects with first episode (FE) of psychosis, in all young adults and in adolescents at HR of schizophrenia. The loss of tissue was mainly located in the posterior part of hippocampus and the right side seems more vulnerable in young adults with only risk symptoms. Instead, the anterior sector seems more involved in HR subjects with genetic risks. Abnormal amygdala volumes were found in FE subjects, in children with combined risk symptoms/factors and in older subjects using different inclusion criteria, but not in young adults.

CONCLUSION

Hippocampal and amygdala abnormalities may be present before schizophrenia onset. Further studies should be conducted to clarify whether these abnormalities are causally or effectually related to neurodevelopment. Shape analysis could clarify the impact of environmental, genetic, and developmental factors on the medial temporal structures during the evolution of this disease.

Chronic exposure of mutant DISC1 mice to lead produces sex-dependent abnormalities consistent with schizophrenia and related mental disorders: a gene-environment interaction study

The glutamatergic hypothesis of schizophrenia suggests that hypoactivity of the N-methyl-D-aspartate receptor (NMDAR) is an important factor in the pathophysiology of schizophrenia and related mental disorders. The environmental neurotoxicant, lead (Pb(2+)), is a potent and selective antagonist of the NMDAR. Recent human studies have suggested an association between prenatal Pb(2+) exposure and the increased likelihood of schizophrenia later in life, possibly via interacting with genetic risk factors. In order to test this hypothesis, we examined the neurobehavioral consequences of interaction between Pb(2+) exposure and mutant disrupted in schizophrenia 1 (mDISC1), a risk factor for major psychiatric disorders. Mutant DISC1 and control mice born by the same dams were raised and maintained on a regular diet or a diet containing moderate levels of Pb(2+). Chronic, lifelong exposure of mDISC1 mice to Pb(2+) was not associated with gross developmental abnormalities but produced sex-dependent hyperactivity, exaggerated responses to the NMDAR antagonist, MK-801, mildly impaired prepulse inhibition of the acoustic startle, and enlarged lateral ventricles. Together, these findings support the hypothesis that environmental toxins could contribute to the pathogenesis of mental disease in susceptible individuals.

Associations of white matter integrity and cortical thickness in patients with schizophrenia and healthy controls

Typical brain development includes coordinated changes in both white matter (WM) integrity and cortical thickness (CT). These processes have been shown to be disrupted in schizophrenia, which is characterized by abnormalities in WM microstructure and by reduced CT. The aim of this study was to identify patterns of association between WM markers and cortex-wide CT in healthy controls (HCs) and patients with schizophrenia (SCZ). Using diffusion tensor imaging and structural magnetic resonance imaging data of the Mind Clinical Imaging Consortium study (130 HC and 111 SCZ), we tested for associations between (a) fractional anisotropy in selected manually labeled WM pathways (corpus callosum, anterior thalamic radiation, and superior longitudinal fasciculus) and CT, and (b) the number of lesion-like WM regions ("potholes") and CT. In HC, but not SCZ, we found highly significant negative associations between WM integrity and CT in several pathways, including frontal, temporal, and occipital brain regions. Conversely, in SCZ the number of WM potholes correlated with reduced CT in the left lateral temporal gyrus, left fusiform, and left lateral occipital brain area. Taken together, we found differential patterns of association between WM integrity and CT in HC and SCZ. Although the pattern in HC can be explained from a developmental perspective, the reduced gray matter CT in SCZ patients might be the result of focal but spatially heterogeneous disruptions of WM integrity.

Neuroanatomical markers of genetic liability to psychosis and first episode psychosis: a voxelwise meta-analytical comparison

OBJECTIVES

To address at a meta-analytical level the neuroanatomical markers of genetic liability to psychosis and a of first episode of psychosis.

METHODS

Fifteen voxel-based morphometry (VBM) studies of antipsychotic-naive subjects at genetic high-risk (HR) for psychosis or with a first-episode psychosis (FEP) were included in a Signed Differential Mapping (SDM) meta-analysis. Publication bias was assessed with funnel plots and Egger's intercept. Heterogeneity was assessed with Q statistics and I (2) index.

RESULTS

The database comprised 458 HR and 206 antipsychotic-naïve FEP subjects, matched with controls. Gray matter (GM) reductions as compared to controls, were observed in the left parahippocampal gyrus and in the bilateral anterior cingulate gyrus in the HR group, and in the right superior temporal gyrus, in the left insula and in the left cerebellum in the FEP group. Further GM decreases were observed in the FEP group as compared to the HR group in the left anterior cingulate, in the right precuneus, in the left cerebellum and in the right superior temporal gyrus. Limitations. The cross-sectional nature of the included studies prevented the comparison of high risk subjects who later did or did not develop a psychotic episode. Other caveats are based on the methodological heterogeneity across individual imaging studies.

CONCLUSIONS

GM reductions in the anterior cingulate are markers of genetic liability to psychosis while reductions in the superior temporal gyrus and cerebellum can be interpreted as markers of a first onset of the illness.

Brain structure in different psychosis risk groups in the Northern Finland 1986 birth cohort

We tested the hypothesis that family risk for psychosis (FR) and clinical risk for psychosis (CR) are associated with structural brain abnormalities, with increased deficits in those at both family risk and clinical risk for psychosis (FRCR). The study setting was the Oulu Brain and Mind Study, with subjects drawn from the Northern Finland 1986 Birth Cohort (n=9479) using register and questionnaire based screening, and interviews using the Structured Interview for Prodromal Symptoms. After this procedure, 172 subjects were included in the study, classified as controls (n=73) and three risk groups: FR excluding CR (FR, n=60), CR without FR (CR, n=26), and individuals at both FR and CR (FRCR, n=13). T1-weighted brain scans were acquired and processed in a voxel-based analysis using permutation-based statistics. In the comparison between FRCR versus controls, we found lower grey matter volume (GMV) in a cluster (1689 voxels at -4.00, -72.00, -18.00mm) covering both cerebellar hemispheres and the vermis. This cluster was subsequently used as a mask to extract mean GMV in all four groups: FR had a volume intermediate between controls and FRCR. Within FRCR there was an association between cerebellar cluster brain volume and motor function. These findings are consistent with an evolving pattern of cerebellar deficits in psychosis risk with the most pronounced deficits in those at highest risk of psychosis.