Structural correlates of formal thought disorder in schizophrenia: An ultra-high field multivariate morphometry study

Identify Potential Causal Relationships Between Cortical Thickness, Mismatch Negativity, Neurocognition, and Psychosocial Functioning in Drug-Naïve First-Episode Psychosis Patients

BACKGROUND

Cortical thickness (CT) alterations, mismatch negativity (MMN) reductions, and cognitive deficits are robust findings in first-episode psychosis (FEP). However, most studies focused on medicated patients, leaving gaps in our understanding of the interrelationships between CT, MMN, neurocognition, and psychosocial functioning in unmedicated FEP. This study aimed to employ multiple mediation analysis to investigate potential pathways among these variables in unmedicated drug-naïve FEP.

METHODS

We enrolled 28 drug-naïve FEP and 34 age and sex-matched healthy controls. Clinical symptoms, neurocognition, psychosocial functioning, auditory duration MMN, and T1 structural magnetic resonance imaging data were collected. We measured CT in the superior temporal gyrus (STG), a primary MMN-generating region.

RESULTS

We found a significant negative correlation between MMN amplitude and bilateral CT of STG (CT_STG) in FEP (left: r = -.709, P < .001; right: r = -.612, P = .008). Multiple mediation models revealed that a thinner left STG cortex affected functioning through both direct (24.66%) and indirect effects (75.34%). In contrast, the effects of the right CT_STG on functioning were mainly mediated through MMN and neurocognitive pathways.

CONCLUSIONS

Bilateral CT_STG showed significant association with MMN, and MMN plays a mediating role between CT and cognition. Both MMN alone and its interaction with cognition mediated the effects of structural alterations on psychosocial function. The decline in overall function in FEP may stem from decreased CT_STG, leading to subsequent MMN deficits and neurocognitive dysfunction. These findings underline the crucial role of MMN in elucidating how subtle structural alterations can impact neurocognition and psychosocial function in FEP.

Based on neural network cascade abnormal texture information dissemination of classification of patients with schizophrenia and depression

This study used MRI brain image segmentation to identify novel magnetic resonance imaging (MRI) biomarkers to distinguish patients with schizophrenia (SCZ), major depressive disorder (MD), and healthy control (HC). Brain texture measurements, including entropy and contrast, were calculated to capture variability in adjacent MRI voxel intensity. These measures are then applied to group classification in deep learning techniques and combined with hierarchical correlations to locate results. Texture feature maps were extracted from segmented brain MRI scans of 141 patients with schizophrenia (SCZ), 103 patients with major depressive disorder (MD) and 238 healthy controls (HC). Gray scale coassociation matrix (GLCM) is a monomer matrix calculated in a voxel cube. Deep learning methods were evaluated to determine the application capability of texture feature mapping in binary classification (SCZ vs. HC, MD vs. HC, SCZ vs. MD). The method is implemented by repeated nesting and cross-validation for feature selection. Regions that show the highest correlation (positive or negative). In this study, the authors successfully classified SCZ, MD and HC. This suggests that texture analysis can be used as an effective feature extraction method to distinguish different disease states. Compared with other methods, texture analysis can capture richer image information and improve classification accuracy in some cases. The classification accuracy of SCZ and HC, MD and HC, SCZ and MD reached 84.6%, 86.4% and 76.21%, respectively. Among them, SCZ and HC are the most significant features with high sensitivity and specificity.

Differences in the neural correlates of schizophrenia with positive and negative formal thought disorder in patients with schizophrenia in the ENIGMA dataset

Formal thought disorder (FTD) is a clinical key factor in schizophrenia, but the neurobiological underpinnings remain unclear. In particular, the relationship between FTD symptom dimensions and patterns of regional brain volume loss in schizophrenia remains to be established in large cohorts. Even less is known about the cellular basis of FTD. Our study addresses these major obstacles by enrolling a large multi-site cohort acquired by the ENIGMA Schizophrenia Working Group (752 schizophrenia patients and 1256 controls), to unravel the neuroanatomy of FTD in schizophrenia and using virtual histology tools on implicated brain regions to investigate the cellular basis. Based on the findings of previous clinical and neuroimaging studies, we decided to separately explore positive, negative and total formal thought disorder. We used virtual histology tools to relate brain structural changes associated with FTD to cellular distributions in cortical regions. We identified distinct neural networks positive and negative FTD. Both networks encompassed fronto-occipito-amygdalar brain regions, but positive and negative FTD demonstrated a dissociation: negative FTD showed a relative sparing of orbitofrontal cortical thickness, while positive FTD also affected lateral temporal cortices. Virtual histology identified distinct transcriptomic fingerprints associated for both symptom dimensions. Negative FTD was linked to neuronal and astrocyte fingerprints, while positive FTD also showed associations with microglial cell types. These results provide an important step towards linking FTD to brain structural changes and their cellular underpinnings, providing an avenue for a better mechanistic understanding of this syndrome.

Structural and Functional Brain Patterns Predict Formal Thought Disorder's Severity and Its Persistence in Recent-Onset Psychosis: Results From the PRONIA Study

BACKGROUND

Formal thought disorder (FThD) is a core feature of psychosis, and its severity and long-term persistence relates to poor clinical outcomes. However, advances in developing early recognition and management tools for FThD are hindered by a lack of insight into the brain-level predictors of FThD states and progression at the individual level.

METHODS

Two hundred thirty-three individuals with recent-onset psychosis were drawn from the multisite European Prognostic Tools for Early Psychosis Management study. Support vector machine classifiers were trained within a cross-validation framework to separate two FThD symptom-based subgroups (high vs. low FThD severity), using cross-sectional whole-brain multiband fractional amplitude of low frequency fluctuations, gray matter volume and white matter volume data. Moreover, we trained machine learning models on these neuroimaging readouts to predict the persistence of high FThD subgroup membership from baseline to 1-year follow-up.

RESULTS

Cross-sectionally, multivariate patterns of gray matter volume within the salience, dorsal attention, visual, and ventral attention networks separated the FThD severity subgroups (balanced accuracy [BAC] = 60.8%). Longitudinally, distributed activations/deactivations within all fractional amplitude of low frequency fluctuation sub-bands (BACslow-5 = 73.2%, BACslow-4 = 72.9%, BACslow-3 = 68.0%), gray matter volume patterns overlapping with the cross-sectional ones (BAC = 62.7%), and smaller frontal white matter volume (BAC = 73.1%) predicted the persistence of high FThD severity from baseline to follow-up, with a combined multimodal balanced accuracy of BAC = 77%.

CONCLUSIONS

We report the first evidence of brain structural and functional patterns predictive of FThD severity and persistence in early psychosis. These findings open up avenues for the development of neuroimaging-based diagnostic, prognostic, and treatment options for the early recognition and management of FThD and associated poor outcomes.

Predicting new onset thought disorder in early adolescence with optimized deep learning implicates environmental-putamen interactions

Background

Thought disorder (TD) is a sensitive and specific marker of risk for schizophrenia onset. Specifying factors that predict TD onset in adolescence is important to early identification of youth at risk. However, there is a paucity of studies prospectively predicting TD onset in unstratified youth populations.

Study Design

We used deep learning optimized with artificial intelligence (AI) to analyze 5,777 multimodal features obtained at 9-10 years from youth and their parents in the ABCD study, including 5,014 neural metrics, to prospectively predict new onset TD cases at 11-12 years. The design was replicated for all prevailing TD cases at 11-12 years.

Study Results

Optimizing performance with AI, we were able to achieve 92% accuracy and F1 and 0.96 AUROC in prospectively predicting the onset of TD in early adolescence. Structural differences in the left putamen, sleep disturbances and the level of parental externalizing behaviors were specific predictors of new onset TD at 11-12 yrs, interacting with low youth prosociality, the total parental behavioral problems and parent-child conflict and whether the youth had already come to clinical attention. More important predictors showed greater inter-individual variability.

Conclusions

This study provides robust person-level, multivariable signatures of early adolescent TD which suggest that structural differences in the left putamen in late childhood are a candidate biomarker that interacts with psychosocial stressors to increase risk for TD onset. Our work also suggests that interventions to promote improved sleep and lessen parent-child psychosocial stressors are worthy of further exploration to modulate risk for TD onset.

Neural Correlates of Positive and Negative Formal Thought Disorder in Individuals with Schizophrenia: An ENIGMA Schizophrenia Working Group Study

Formal thought disorder (FTD) is a key clinical factor in schizophrenia, but the neurobiological underpinnings remain unclear. In particular, relationship between FTD symptom dimensions and patterns of regional brain volume deficiencies in schizophrenia remain to be established in large cohorts. Even less is known about the cellular basis of FTD. Our study addresses these major obstacles based on a large multi-site cohort through the ENIGMA Schizophrenia Working Group (752 individuals with schizophrenia and 1256 controls), to unravel the neuroanatomy of positive, negative and total FTD in schizophrenia and their cellular bases. We used virtual histology tools to relate brain structural changes associated with FTD to cellular distributions in cortical regions. We identified distinct neural networks for positive and negative FTD. Both networks encompassed fronto-occipito-amygdalar brain regions, but negative FTD showed a relative sparing of orbitofrontal cortical thickness, while positive FTD also affected lateral temporal cortices. Virtual histology identified distinct transcriptomic fingerprints associated for both symptom dimensions. Negative FTD was linked to neuronal and astrocyte fingerprints, while positive FTD was also linked to microglial cell types. These findings relate different dimensions of FTD to distinct brain structural changes and their cellular underpinnings, improve our mechanistic understanding of these key psychotic symptoms.

Structural brain networks in schizophrenia based on nonnegative matrix factorization

Schizophrenia is a severe mental disease with significant morphometric reductions in gray matter volume and cortical thickness in a variety of brain regions. However, most studies only focused on the voxel level alterations in specific cerebral regions and ignored the spatial relationship between voxels. In the present study, we used a novel, data-driven technique-nonnegative matrix factorization (NMF) to group voxels with similar information into a network, and studied the structural covariance at the network level in schizophrenia. Our sample included 36 patients with schizophrenia and 21 healthy controls. Compared with healthy controls, patients with schizophrenia showed significant gray matter volume reductions in six structural covariance networks (dorsal striatum, thalamus, hippocampus-parahippocampus, supplementary motor area-fusiform, middle/inferior temporal network, frontal-parietal-occipital network). Our findings confirmed the assumption of a disturbance in the cortical-subcortical circuit in schizophrenia and suggested that NMF is a useful multivariate method to identify brain networks, which provides a new perspective to study the neural mechanism in schizophrenia.

Neural Correlates of Positive and Negative Formal Thought Disorder in Individuals with Schizophrenia: An ENIGMA Schizophrenia Working Group Study

Formal thought disorder (FTD) is a key clinical factor in schizophrenia, but the neurobiological underpinnings remain unclear. In particular, relationship between FTD symptom dimensions and patterns of regional brain volume deficiencies in schizophrenia remain to be established in large cohorts. Even less is known about the cellular basis of FTD. Our study addresses these major obstacles based on a large multi-site cohort through the ENIGMA Schizophrenia Working Group (752 individuals with schizophrenia and 1256 controls), to unravel the neuroanatomy of positive, negative and total FTD in schizophrenia and their cellular bases. We used virtual histology tools to relate brain structural changes associated with FTD to cellular distributions in cortical regions. We identified distinct neural networks for positive and negative FTD. Both networks encompassed fronto-occipito-amygdalar brain regions, but negative FTD showed a relative sparing of orbitofrontal cortical thickness, while positive FTD also affected lateral temporal cortices. Virtual histology identified distinct transcriptomic fingerprints associated for both symptom dimensions. Negative FTD was linked to neuronal and astrocyte fingerprints, while positive FTD was also linked to microglial cell types. These findings relate different dimensions of FTD to distinct brain structural changes and their cellular underpinnings, improve our mechanistic understanding of these key psychotic symptoms.

Ameliorative patterns of grey matter in patients with first-episode and treatment-naïve schizophrenia

BACKGROUND

Grey matter (GM) reduction is a consistent observation in established late stages of schizophrenia, but patients in the untreated early stages of illness display an increase as well as a decrease in GM distribution relative to healthy controls (HC). The relative excess of GM may indicate putative compensatory responses, though to date its relevance is unclear.

METHODS

343 first-episode treatment-naïve patients with schizophrenia (FES) and 342 HC were recruited. Multivariate source-based morphometry was performed to identify covarying 'networks' of grey matter concentration (GMC). Neurocognitive scores using the Cambridge Neuropsychological Test Automated Battery (CANTAB) and symptom burden using the Positive and Negative Symptoms Scale (PANSS) were obtained. Bivariate linear relationships between GMC and cognition/symptoms were studied.

RESULTS

Compared to healthy subjects, FES had prominently lower GMC in two components; the first consists of the anterior insula, inferior frontal gyrus, anterior cingulate and the second component with the superior temporal gyrus, precuneus, inferior/superior parietal lobule, cuneus, and lingual gyrus. Higher GMC was seen in adjacent areas of the middle and superior temporal gyrus, middle frontal gyrus, inferior parietal cortex and putamen. Greater GMC of this component was associated with lower duration of untreated psychosis, less severe positive symptoms and better performance on cognitive tests.

CONCLUSIONS

In untreated stages of schizophrenia, both a distributed lower and higher GMC is observable. While the higher GMC is relatively modest, it occurs across frontoparietal, temporal and subcortical regions in association with reduced illness burden suggesting a compensatory role for higher GMC in the early stages of schizophrenia.

Active Inference, Epistemic Value, and Uncertainty in Conceptual Disorganization in First-Episode Schizophrenia

BACKGROUND AND HYPOTHESIS

Active inference has become an influential concept in psychopathology. We apply active inference to investigate conceptual disorganization in first-episode schizophrenia. We conceptualize speech production as a decision-making process affected by the latent "conceptual organization"-as a special case of uncertainty about the causes of sensory information. Uncertainty is both minimized via speech production-in which function words index conceptual organization in terms of analytic thinking-and tracked by a domain-general salience network. We hypothesize that analytic thinking depends on conceptual organization. Therefore, conceptual disorganization in schizophrenia would be both indexed by low conceptual organization and reflected in the effective connectivity within the salience network.

STUDY DESIGN

With 1-minute speech samples from a picture description task and resting state fMRI from 30 patients and 30 healthy subjects, we employed dynamic causal and probabilistic graphical models to investigate if the effective connectivity of the salience network underwrites conceptual organization.

STUDY RESULTS

Low analytic thinking scores index low conceptual organization which affects diagnostic status. The influence of the anterior insula on the anterior cingulate cortex and the self-inhibition within the anterior cingulate cortex are elevated given low conceptual organization (ie, conceptual disorganization).

CONCLUSIONS

Conceptual organization, a construct that explains formal thought disorder, can be modeled in an active inference framework and studied in relation to putative neural substrates of disrupted language in schizophrenia. This provides a critical advance to move away from rating-scale scores to deeper constructs in the pursuit of the pathophysiology of formal thought disorder.

Language Network Dysfunction and Formal Thought Disorder in Schizophrenia

BACKGROUND

Pathophysiological inquiries into schizophrenia require a consideration of one of its most defining features: disorganization and impoverishment in verbal behavior. This feature, often captured using the term Formal Thought Disorder (FTD), still remains to be one of the most poorly understood and understudied dimensions of schizophrenia. In particular, the large-scale network level dysfunction that contributes to FTD remains obscure to date.

STUDY DESIGN

In this narrative review, we consider the various challenges that need to be addressed for us to move towards mapping FTD (construct) to a brain network level account (circuit).

STUDY RESULTS

The construct-to-circuit mapping goal is now becoming more plausible than it ever was, given the parallel advent of brain stimulation and the tools providing objective readouts of human speech. Notwithstanding this, several challenges remain to be overcome before we can decisively map the neural basis of FTD. We highlight the need for phenotype refinement, robust experimental designs, informed analytical choices, and present plausible targets in and beyond the Language Network for brain stimulation studies in FTD.

CONCLUSIONS

Developing a therapeutically beneficial pathophysiological model of FTD is a challenging endeavor, but holds the promise of improving interpersonal communication and reducing social disability in schizophrenia. Addressing the issues raised in this review will be a decisive step in this direction.

Language abnormalities in schizophrenia: binding core symptoms through contemporary empirical evidence

Both the ability to speak and to infer complex linguistic messages from sounds have been claimed as uniquely human phenomena. In schizophrenia, formal thought disorder (FTD) and auditory verbal hallucinations (AVHs) are manifestations respectively relating to concrete disruptions of those abilities. From an evolutionary perspective, Crow (1997) proposed that "schizophrenia is the price that Homo sapiens pays for the faculty of language". Epidemiological and experimental evidence points to an overlap between FTD and AVHs, yet a thorough investigation examining their shared neural mechanism in schizophrenia is lacking. In this review, we synthesize observations from three key domains. First, neuroanatomical evidence indicates substantial shared abnormalities in language-processing regions between FTD and AVHs, even in the early phases of schizophrenia. Second, neurochemical studies point to a glutamate-related dysfunction in these language-processing brain regions, contributing to verbal production deficits. Third, genetic findings further show how genes that overlap between schizophrenia and language disorders influence neurodevelopment and neurotransmission. We argue that these observations converge into the possibility that a glutamatergic dysfunction in language-processing brain regions might be a shared neural basis of both FTD and AVHs. Investigations of language pathology in schizophrenia could facilitate the development of diagnostic tools and treatments, so we call for multilevel confirmatory analyses focused on modulations of the language network as a therapeutic goal in schizophrenia.

Structural network alterations and their association with neurological soft signs in schizophrenia: Evidence from clinical patients and unaffected siblings

BACKGROUND

Grey matter abnormalities and neurological soft signs (NSS) have been found in schizophrenia patients and their unaffected relatives. Evidence suggested that NSS are associated with grey matter morphometrical alterations in multiple regions in schizophrenia. However, the association between NSS and structural abnormalities at network level remains largely unexplored, especially in the schizophrenia and unaffected siblings.

METHOD

We used source-based morphometry (SBM) to examine the association of structural brain network characteristics with NSS in 62 schizophrenia patients, 25 unaffected siblings, and 60 healthy controls.

RESULTS

Two components, namely the IC-5 (superior temporal gyrus, inferior frontal gyrus and insula network) and the IC-10 (parahippocampal gyrus, fusiform, thalamus and insula network) showed significant grey matter reductions in schizophrenia patients compared to healthy controls and unaffected siblings. Further association analysis demonstrated separate NSS-related grey matter covarying patterns in schizophrenia, unaffected siblings and healthy controls. Specifically, NSS were negatively associated with IC-1 (hippocampus, caudate and thalamus network) and IC-5 in schizophrenia, but with IC-3 (caudate, superior and middle frontal cortices network) in unaffected siblings and with IC-5 in healthy controls.

CONCLUSION

Our results confirmed the key cortical and subcortical network abnormalities and NSS-related grey matter covarying patterns in the schizophrenia and unaffected siblings. Our findings suggest that brain regions implicating genetic liability to schizophrenia are partly separated from brain regions implicating neural abnormalities.

Flights and Perchings of the BrainMind: A Temporospatial Approach to Psychotherapy

This article introduces a process-oriented approach for improving present moment conceptualization in psychotherapy that is in alignment with neuroscience: the Temporospatial movements of mind (TSMM) model. We elaborate on seven temporal movements that describe the moment-to-moment morphogenesis of emotional feelings and thoughts from inception to maturity. Temporal refers to the passage of time through which feelings and thoughts develop, and electromagnetic activity, that among other responsibilities, bind information across time. Spatial dynamics extend from an undifferentiated to three dimensional experiences of emotional and cognitive processes. Neurophysiologically, spatial refers to structures within the brain and their varying interactions with one another. This article culminates in the development of an atheoretical temporospatial grid that may help clinicians conceptualize where patients are in their cognitive and emotional development to further guide technique.

Structural covariance networks in schizophrenia: A systematic review Part I

BACKGROUND

Schizophrenia is proposed as a disorder of dysconnectivity. However, examination of complexities of dysconnectivity has been challenging. Structural covariance networks (SCN) provide important insights into the nature of dysconnectivity. This systematic review examines the SCN studies that employed statistical approaches to elucidate covariation of regional morphometric variations.

METHODS

A systematic search of literature was conducted for peer-reviewed publications using different keywords and keyword combinations for schizophrenia. Fifty-two studies met the criteria.

RESULTS

Early SCN studies began using correlational structure of selected regions. Over the last 3 decades, methodological approaches have grown increasingly sophisticated from examining selected brain regions using correlation tests on small sample sizes to recent approaches that use advanced statistical methods to examine covariance structure of whole-brain parcellations on larger samples. Although the results are not fully consistent across all studies, a pattern of fronto-temporal, fronto-parietal and fronto-thalamic covariation is reported. Attempts to associate SCN alterations with functional connectivity, to differentiate between disease-related and neurodevelopment-related morphometric changes, and to develop "causality-based" models are being reported. Clinical correlation with outcome, psychotic symptoms, neurocognitive and social cognitive performance are also reported.

CONCLUSIONS

Application of advanced statistical methods are beginning to provide insights into interesting patterns of regional covariance including correlations with clinical and cognitive data. Although these findings appear similar to morphometric studies, SCNs have the advantage of highlighting topology of these regions and their relationship to the disease and associated variables. Further studies are needed to investigate neurobiological underpinnings of shared covariance, and causal links to clinical domains.

Dimensions of Formal Thought Disorder and Their Relation to Gray- and White Matter Brain Structure in Affective and Psychotic Disorders

Factorial dimensions and neurobiological underpinnings of formal thought disorders (FTD) have been extensively investigated in schizophrenia spectrum disorders (SSD). However, FTD are also highly prevalent in other disorders. Still, there is a lack of knowledge about transdiagnostic, structural brain correlates of FTD. In N = 1071 patients suffering from DSM-IV major depressive disorder, bipolar disorder, or SSD, we calculated a psychopathological factor model of FTD based on the SAPS and SANS scales. We tested the association of FTD dimensions with 3 T MRI measured gray matter volume (GMV) and white matter fractional anisotropy (FA) using regression and interaction models in SPM12. We performed post hoc confirmatory analyses in diagnostically equally distributed, age- and sex-matched sub-samples to test whether results were driven by diagnostic categories. Cross-validation (explorative and confirmatory) factor analyses revealed three psychopathological FTD factors: disorganization, emptiness, and incoherence. Disorganization was negatively correlated with a GMV cluster comprising parts of the middle occipital and angular gyri and positively with FA in the right posterior cingulum bundle and inferior longitudinal fascicle. Emptiness was negatively associated with left hippocampus and thalamus GMV. Incoherence was negatively associated with FA in bilateral anterior thalamic radiation, and positively with the hippocampal part of the right cingulum bundle. None of the gray or white matter associations interacted with diagnosis. Our results provide a refined mapping of cross-disorder FTD phenotype dimensions. For the first time, we demonstrated that their neuroanatomical signatures are associated with language-related gray and white matter structures independent of diagnosis.

Ultra-high field neuroimaging in psychosis: A narrative review

Schizophrenia and related psychoses are complex neuropsychiatric diseases representing dysconnectivity across multiple scales, through the micro (cellular), meso (brain network), manifest (behavioral), and social (interpersonal) levels. In vivo human neuroimaging, particularly at ultra-high field (UHF), offers unprecedented opportunity to examine multiscale dysconnectivity in psychosis. In this review, we provide an overview of the literature to date on UHF in psychosis, focusing on microscale findings from magnetic resonance spectroscopy (MRS), mesoscale studies on structural and functional magnetic resonance imaging (fMRI), and multiscale studies assessing multiple neuroimaging modalities and relating UHF findings to behavior. We highlight key insights and considerations from multiscale and longitudinal studies and provide recommendations for future research on UHF neuroimaging in psychosis.

Structural Covariance of Depth-Dependent Intracortical Myelination in the Human Brain and Its Application to Drug-Naïve Schizophrenia: A T1w/T2w MRI Study

Aberrations in intracortical myelination are increasingly being considered as a cardinal feature in the pathophysiology of schizophrenia. We investigated the network-level distribution of intracortical myelination across various cortex depths. We enrolled 126 healthy subjects and 106 first-episode drug-naïve schizophrenia patients. We used T1w/T2w ratio as a proxy of intracortical myelination, parcellated cortex into several equivolumetric surfaces based on cortical depths and mapped T1w/T2w ratios to each surface. Non-negative matrix factorization was used to generate depth-dependent structural covariance networks (dSCNs) of intracortical myelination from 2 healthy controls datasets-one from our study and another from 100-unrelated dataset of the Human Connectome Project. For patient versus control comparisons, partial least squares approach was used; we also related myelination to clinical features of schizophrenia. We found that dSCNs were highly reproducible in 2 independent samples. Network-level myelination was reduced in prefrontal and cingulate cortex and increased in perisylvian cortex in schizophrenia. The abnormal network-level myelination had a canonical correlation with symptom burden in schizophrenia. Moreover, myelination of prefrontal cortex correlated with duration of untreated psychosis. In conclusion, we offer a feasible and sensitive framework to study depth-dependent myelination and its relationship with clinical features.

Dissecting the neurobiology of linguistic disorganisation and impoverishment in schizophrenia

Schizophrenia provides a quintessential disease model of how disturbances in the molecular mechanisms of neurodevelopment lead to disruptions in the emergence of cognition. The central and often persistent feature of this illness is the disorganisation and impoverishment of language and related expressive behaviours. Though clinically more prominent, the periodic perceptual distortions characterised as psychosis are non-specific and often episodic. While several insights into psychosis have been gained based on study of the dopaminergic system, the mechanistic basis of linguistic disorganisation and impoverishment is still elusive. Key findings from cellular to systems-level studies highlight the role of ubiquitous, inhibitory processes in language production. Dysregulation of these processes at critical time periods, in key brain areas, provides a surprisingly parsimonious account of linguistic disorganisation and impoverishment in schizophrenia. This review links the notion of excitatory/inhibitory (E/I) imbalance at cortical microcircuits to the expression of language behaviour characteristic of schizophrenia, through the building blocks of neurochemistry, neurophysiology, and neurocognition.

Acute conceptual disorganization in untreated first-episode psychosis: a combined magnetic resonance spectroscopy and diffusion imaging study of the cingulum

BACKGROUND

Disorganized thinking is a core feature of acute psychotic episodes that is linked to social and vocational functioning. Several lines of evidence implicate disrupted cognitive control, excitatory overdrive and oxidative stress relating to the anterior cingulate cortex as mechanisms of conceptual disorganization (CD). We examined 3 candidate mechanistic markers related to CD in firstepisode psychosis: glutamate excess, cortical antioxidant (glutathione) status and the integrity of the cingulum bundle that connects regions implicated in cognitive control.

METHODS

We used fractional anisotropy maps from 7 T diffusion-weighted imaging to investigate the bilateral cingulum based on a probabilistic white matter atlas. We compared high CD, low CD and healthy control groups and performed probabilistic fibre tracking from the identified clusters (regions of interest within the cingulum) to the rest of the brain. We quantified glutamate and glutathione using magnetic resonance spectroscopy (MRS) in the dorsal anterior cingulate cortex.

RESULTS

We found a significant fractional anisotropy reduction in a cluster in the left cingulum in the high CD group compared to the low CD group (Cohen's d = 1.39; p < 0.001) and controls (Cohen's d = 0.86; p = 0.009). Glutamate levels did not vary among groups, but glutathione levels were higher in the high CD group than in the low CD group. We also found higher glutathione related to lower fractional anisotropy in the cingulum cluster in the high CD group.

LIMITATIONS

The MRS measures of glutamine were highly uncertain, and MRS was acquired from a single voxel only.

CONCLUSION

Acute CD relates to indicators of oxidative stress, as well as reduced white matter integrity of the cingulum, but not to MRI-based glutamatergic excess. We propose that both oxidative imbalance and structural dysconnectivity underlie acute disorganization.

Systemic inflammation and grey matter volume in schizophrenia and bipolar disorder: Moderation by childhood trauma severity

BACKGROUND

Elevated levels of systemic inflammation are consistently reported in both schizophrenia (SZ) and bipolar-I disorder (BD), and are associated with childhood trauma exposure. We tested whether childhood trauma exposure moderates associations between systemic inflammation and brain morphology in people with these diagnoses.

METHODS

Participants were 55 SZ cases, 52 BD cases and 59 healthy controls (HC) who underwent magnetic resonance imaging. Systemic inflammation was measured using a composite z-score derived from serum concentrations of interleukin 6, tumor necrosis factor alpha and C-reactive protein. Indices of grey matter volume covariation (GMC) were derived from independent component analysis. Childhood trauma was measured using the Childhood Trauma Questionnaire (CTQ Total score).

RESULTS

A series of moderated moderation analyses indicated that increased systemic inflammation were associated with increased GMC in the striatum and cerebellum among all participants. Severity of childhood trauma exposure moderated the relationship between systemic inflammation and GMC in one component, differently among the groups. Specifically, decreased GMC in the PCC/precuneus, parietal lobule and postcentral gyrus, and increased GMC in the left middle temporal gyrus was associated with increased systemic inflammation in HC individuals exposed to high (but not low or average) levels of trauma and in SZ cases exposed to low (but not average or high) levels of trauma, but not in BD cases.

CONCLUSIONS

Increased systemic inflammation is associated with grey matter changes in people with psychosis, and these relationships may be partially and differentially moderated by childhood trauma exposure according to diagnosis.

Conceptual disorganization and redistribution of resting-state cortical hubs in untreated first-episode psychosis: A 7T study

Network-level dysconnectivity has been studied in positive and negative symptoms of schizophrenia. Conceptual disorganization (CD) is a symptom subtype that predicts impaired real-world functioning in psychosis. Systematic reviews have reported aberrant connectivity in formal thought disorder, a construct related to CD. However, no studies have investigated whole-brain functional correlates of CD in psychosis. We sought to investigate brain regions explaining the severity of CD in patients with first-episode psychosis (FEPs) compared with healthy controls (HCs). We computed whole-brain binarized degree centrality maps of 31 FEPs, 25 HCs, and characterized the patterns of network connectivity in the 2 groups. In FEPs, we related these findings to the severity of CD. We also studied the effect of positive and negative symptoms on altered network connectivity. Compared to HCs, reduced centrality of a right superior temporal gyrus (rSTG) cluster was observed in the FEPs. In patients exhibiting high CD, increased centrality of a medial superior parietal (mSPL) cluster was observed, compared to patients exhibiting low CD. This cluster was strongly correlated with CD scores but not with other symptom scores. Our observations are congruent with previous findings of reduced but not increased centrality. We observed increased centrality of mSPL suggesting that cortical reorganization occurs to provide alternate routes for information transfer. These findings provide insight into the underlying neural processes mediating the presentation of symptoms in untreated FEP. Longitudinal tracking of the symptom course will be useful to assess the mechanisms underlying these compensatory changes.

Understanding Language Abnormalities and Associated Clinical Markers in Psychosis: The Promise of Computational Methods

The language and speech of individuals with psychosis reflect their impairments in cognition and motor processes. These language disturbances can be used to identify individuals with and at high risk for psychosis, as well as help track and predict symptom progression, allowing for early intervention and improved outcomes. However, current methods of language assessment-manual annotations and/or clinical rating scales-are time intensive, expensive, subject to bias, and difficult to administer on a wide scale, limiting this area from reaching its full potential. Computational methods that can automatically perform linguistic analysis have started to be applied to this problem and could drastically improve our ability to use linguistic information clinically. In this article, we first review how these automated, computational methods work and how they have been applied to the field of psychosis. We show that across domains, these methods have captured differences between individuals with psychosis and healthy controls and can classify individuals with high accuracies, demonstrating the promise of these methods. We then consider the obstacles that need to be overcome before these methods can play a significant role in the clinical process and provide suggestions for how the field should address them. In particular, while much of the work thus far has focused on demonstrating the successes of these methods, we argue that a better understanding of when and why these models fail will be crucial toward ensuring these methods reach their potential in the field of psychosis.

Cortical thickness and formal thought disorder in schizophrenia: An ultra high-field network-based morphometry study

BACKGROUND

Persistent formal thought disorder (FTD) is a core feature of schizophrenia. Recent cognitive and neuroimaging studies indicate a distinct mechanistic pathway underlying the persistent positive FTD (pFTD or disorganized thinking), though its structural determinants are still elusive. Using network-based cortical thickness estimates from ultra-high field 7-Tesla Magnetic Resonance Imaging (7T MRI), we investigated the structural correlates of pFTD.

METHODS

We obtained speech samples and 7T MRI anatomical scans from medicated clinically stable patients with schizophrenia (n = 19) and healthy controls (n = 20). Network-based morphometry was used to estimate the mean cortical thickness of 17 functional networks covering the entire cortical surface from each subject. We also quantified the vertexwise variability of thickness within each network to quantify the spatial coherence of the 17 networks, estimated patients vs. controls differences, and related the thickness of the affected networks to the severity of pFTD.

RESULTS

Patients had reduced thickness of the frontoparietal and default mode networks, and reduced spatial coherence affecting the salience and the frontoparietal control network. A higher burden of positive FTD related to reduced frontoparietal thickness and reduced spatial coherence of the salience network. The presence of positive FTD, but not its severity, related to the reduced thickness of the language network comprising of the superior temporal cortex.

CONCLUSIONS

These results suggest that cortical thickness of both cognitive control and language networks underlie the positive FTD in schizophrenia. The structural integrity of cognitive control networks is a critical determinant of the expressed severity of persistent FTD in schizophrenia.

Effects of age and sex on clinical high-risk for psychosis in the community

BACKGROUND

Recent reports of both heightened prevalence rates and limited clinical relevance of clinical high-risk (CHR) criteria and their relevant symptoms in children and adolescents indicate an important role of neurodevelopment in the early detection of psychoses. Furthermore, sex effects in CHR symptoms have been reported, though studies were inconclusive. As sex also impacts on neurodevelopment, we expected that sex might have an additional contribution to age in the prevalence and clinical relevance of CHR symptoms and criteria.

AIM

To investigate age and sex effects on CHR criteria and symptoms and their association with psychosocial impairment and mental disorder.

METHODS

In this cross-sectional cohort study, n = 2916 8- to 40-year-olds, randomly drawn from the population register of the Swiss canton Bern, were assessed in semi-structured interviews by phone or face-to-face for CHR symptoms and criteria using the Structured Interview for Psychosis-Risk Syndromes and the Schizophrenia Proneness Instrument in its child and youth, and adult version, respectively. Furthermore, social and occupational functioning and DSM-IV axis I disorders were assessed. Simple and interaction effects of age and sex on CHR symptoms and criteria, and interaction effects of age, sex, and CHR symptoms and criteria on presentation of functional impairment and of non-psychotic disorder were investigated using logistic regression analyses.

RESULTS

Altogether, 542 (18.6%) participants reported any CHR symptom; of these, 261 (9.0%) participants reported any one of the 11 criteria relevant cognitive and perceptual basic symptoms, and 381 (13.1%) any one of the five attenuated or transient psychotic symptoms (attenuated psychotic symptoms/brief intermittent psychotic symptoms). Fewer participants met any one of the CHR criteria (n = 82, 2.8%) or any one of the three recently recommended CHR criteria (n = 38, 1.3%). Both age and sex were significantly (P < 0.05) associated with CHR symptoms and criteria, mostly by younger age and female sex. Though slightly differing between symptom groups, age thresholds were detected around the turn from adolescence to adulthood; they were highest for cognitive basic symptoms and CHR criteria. With the exception of the infrequent speech disorganization attenuated psychotic symptom, the interaction of age with CHR symptoms and criteria predicted functional impairment; whereas, independent of each other, sex and CHR symptoms mostly predicted mental disorders.

CONCLUSION

Age and sex differentially impact on CHR symptoms and criteria; these differences may support better understanding of causal pathways. Thus, future CHR studies should consider effects of sex and age.

Genetic Intersections of Language and Neuropsychiatric Conditions

PURPOSE OF REVIEW

To better understand the shared basis of language and mental health, this review examines the behavioral and neurobiological features of aberrant language in five major neuropsychiatric conditions. Special attention is paid to genes implicated in both language and neuropsychiatric disorders, as they reveal biological domains likely to underpin the processes controlling both.

RECENT FINDINGS

Abnormal language and communication are common manifestations of neuropsychiatric conditions, and children with impaired language are more likely to develop psychiatric disorders than their peers. Major themes in the genetics of both language and psychiatry include master transcriptional regulators, like FOXP2; key developmental regulators, like AUTS2; and mediators of neurotransmission, like GRIN2A and CACNA1C.

Source-based morphometry: a decade of covarying structural brain patterns

In this paper, we review and discuss brain imaging studies which have used the source-based morphometry (SBM) approach over the past decade. SBM is a data-driven linear multivariate approach for decomposing structural brain imaging data into commonly covarying imaging components and subject-specific loading parameters. It is a well-established technique which has predominantly been used to study neuroanatomic differences between healthy controls and patients with neuropsychiatric diseases. We start by discussing the advantages of this technique over univariate analysis for imaging studies, followed by a discussion of results from recent studies which have successfully applied this methodology. We also present recent extensions of this framework including nonlinear SBM, biclustered independent component analysis (B-ICA) and conclude with the possible directions of work for future.

Neurocognitive and linguistic correlates of positive and negative formal thought disorder: A meta-analysis

Executive dysfunction and language impairment are the most prominent neuropsychological models of formal thought disorder (FTD) in schizophrenia. However, available studies have provided contradictory findings regarding the accuracy of these models. Furthermore, specific neurocognitive underpinnings of positive FTD (PosFTD) and negative FTD (NegFTD) are not clear. Following the systematic review of schizophrenia studies, a random-effects meta-analysis of the relationship between FTD and neurocognition/language in schizophrenia was conducted in 52 reports including 2805 patients. Neurocognition was significantly associated with both PosFTD (r = -0.21, CI = -0.14 to -0.27) and NegFTD (r = -0.24, CI = -0.18 to -0.30). Both PosFTD (r = ranged from -0.18 to -0.27) and NegFTD (r = ranged from -0.19 to -0.23) were significantly correlated with verbal memory, visual memory, attention, and processing speed. In meta-analyses of executive functions, PosFTD was significantly associated with working memory (r = -0.21), planning (r = -0.19), and inhibition (r = -0.21) and NegFTD was significantly associated with planning (r = -0.27), fluency (r = -0.27), and working memory (r = -0.24). In meta-analyses of linguistic variables, PosFTD was associated with deficits in syntactic comprehension (r = -0.27) and semantic processing (r = -0.18). In contrast, NegFTD was associated only with semantic comprehension (r = -0.21). Both PosFTD and NegFTD were significantly associated with executive dysfunction, neurocognitive deficits and semantic dysfunction but syntactic deficits were more specific to PosFTD. There were also some distinct patterns of relationships between the pattern of executive dysfunction and types of FTD. Fluency deficit was associated more strongly with NegFTD and poor inhibition was more specifically related to PosFTD. Current findings suggest that neurocognitive and linguistic correlates of PosFTD and NegFTD might be partly different.

Thought disorder in atypical schizophrenia-like psychosis after stroke: analysis of clinical cases

Formal thought disorder refers to disorganized thinking and it represents a hallmark of schizophrenia and psychosis. Psychosis is a rare complication after stroke. We described two cases of female patients, who developed an atypical schizophrenia-like psychosis post-stroke, characterized by formal thought disorder, hallucinations, and delusion. Cerebrovascular disease affected the right temporal lobe, areas devoted to modulation of higher order cognitive processes. To date, the relation between stroke and psychosis remain unclear, maybe due to the involvement of a complex brain networks. However, the high impact of this disorder on physical, psychological and social wellbeing suggests the importance of improving specific treatments.

Identifying Brain Abnormalities with Schizophrenia Based on a Hybrid Feature Selection Technology

Many medical imaging data, especially the magnetic resonance imaging (MRI) data, usually have a small sample size, but a large number of features. How to reduce effectively the data dimension and locate accurately the biomarkers from such kinds of data are quite crucial for diagnosis and further precision medicine. In this paper, we propose a hybrid feature selection method based on machine learning and traditional statistical approaches and explore the brain abnormalities of schizophrenia by using the functional and structural MRI data. The results show that the abnormal brain regions are mainly distributed in the supramarginal gyrus, cingulate gyrus, frontal gyrus, precuneus and caudate, and the abnormal functional connections are related to the caudate nucleus, insula and rolandic operculum. In addition, some complex network analyses based on graph theory are utilized on the functional connection data, and the results demonstrate that the located abnormal functional connections in brain can distinguish schizophrenia patients from healthy controls. The identified abnormalities in brain with schizophrenia by the proposed hybrid feature selection method show that there do exist some abnormal brain regions and abnormal disruption of the network segregation and network integration for schizophrenia, and these changes may lead to inaccurate and inefficient information processing and synthesis in the brain, which provide further evidence for the cognitive dysmetria of schizophrenia.

Structural similarity networks predict clinical outcome in early-phase psychosis

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

Prognostic Utility of Multivariate Morphometry in Schizophrenia

Background: Voxel-based morphometry studies have repeatedly highlighted the presence of distributed gray matter changes in schizophrenia, but to date, it is not clear if clinically useful prognostic information can be gleaned from structural imaging. The suspected association between gray matter volume (GMV) and duration of psychotic illness, antipsychotic exposure, and symptom severity also limits the prognostic utility of morphometry. We address the question of whether morphometric information from patients with drug-naive first-episode psychosis can predict the linear trajectory of symptoms following early antipsychotic intervention using a longitudinal design. Method: Sixty-two first-episode, drug-naive patients with schizophrenia underwent brain magnetic resonance imaging scans at baseline, treated with antipsychotics, and rescanned after 1-year follow-up. Positive and Negative Syndrome Scale (PANSS) was used to assess their clinical manifestations. A multivariate approach to detect covariance-based network-like spatial components [Source Based Morphometry (SBM)] was performed to analyze the GMV. Paired t tests were used to study changes in the loading coefficients of GMV in the spatial components between two time points. The reduction in PANSS scores between the baseline (T0) and 1-year follow-up (T1) expressed as a ratio of the baseline scores (reduction ratio) was computed for positive, negative, and disorganization symptoms. Separate multiple regression analyses were conducted to predict the longitudinal change in symptoms (treatment response) using the loading coefficients of spatial components that differed between T0 and T1 with age, gender, duration of illness, and antipsychotic dose as covariates. We also tested the putative "toxicity" effects of baseline symptom severity on the GMV at 1 year using multiple regression analysis. Results: Of the 30 spatial components of gray matter extracted using SBM, loading coefficients of anterior cingulate cortex (ACC), insula and inferior frontal gyrus (IFG), superior temporal gyrus (STG), middle temporal gyrus (MTG), precuenus, and dorsolateral prefrontal cortex (DLPFC) reduced with time in patients. Specifically, the lower volume of insula and IFG at baseline predicted a lack of improvement in positive and disorganization symptoms. None of the symptom severity scores (positive, negative, or disorganization) at baseline independently predicted the reduced GMV at 1 year. Conclusions: The baseline deficit in a covariance-based network-like spatial component comprising of insula and IFG is predictive of the clinical course of schizophrenia. We do not find any evidence to support the notion of symptoms per se being neurotoxic to gray matter tissue. If judiciously combined with other available predictors of clinical outcome, multivariate morphometric information can improve our ability to predict prognosis in schizophrenia.

Formal thought disorder is related to aberrations in language-related white matter tracts in patients with schizophrenia

This study examined the hypothesis that a fronto-temporal disconnection in the language network underpins formal thought disorder (FTD) in schizophrenia. Forty-nine patients with a schizophrenia spectrum disorder (27 with mild FTD, 22 with severe FTD) and 26 healthy controls (HC) were included. Overall psychopathology and FTD were assessed by the Positive and Negative Syndrome Scale and the Thought, Language, and Communication scale, respectively. White matter (WM) microstructure was analysed using Tract-Based Spatial Statistics. In patients, severity of overall FTD (TLC Sum Score) was predicted by decreased fractional anisotropy (FA) in the right superior longitudinal fasciculus (SLF), and severity of negative FTD (TLC Emptiness subscale) was predicted by increased FA in the left SLF and arcuate fasciculus (AF). Notably, these results were no longer significant after correction for multiple comparisons. Compared with HC, patients showed lower FA in all the investigated language-related WM tracts as well as across the whole WM skeleton. No difference in FA was found between patients with severe and patients with mild FTD. Our results are compatible with earlier studies reporting impairments in widely spread WM tracts including those related to language processing in patients with schizophrenia.

Is formal thought disorder in schizophrenia related to structural and functional aberrations in the language network? A systematic review of neuroimaging findings

Formal thought disorder (FTD) is a core feature of schizophrenia, a marker of illness severity and a predictor of outcome. The underlying neural mechanisms are still a matter of debate. This study aimed at 1) reviewing the literature on the neural correlates of FTD in schizophrenia, and 2) testing the hypothesis that FTD correlates with structural and functional aberrations in the language network. Medline, PsychInfo, and Embase were searched for neuroimaging studies, which applied a clinical measure to assess FTD in adults with schizophrenia and were published in English or German in peer-reviewed journals until December 2016. Of 412 articles identified, 61 studies were included in the review. Volumetric studies reported bilateral grey matter deficits (L > R) to be associated with FTD in the inferior frontal gyrus, the superior temporal gyrus and the inferior parietal lobe. The same regions showed hyperactivity in resting state functional magnetic resonance imaging (fMRI) studies and both hyper- and hypoactivity in fMRI studies that employed semantic processing or free speech production tasks. Diffusion tensor imaging studies demonstrated white matter aberrations in fibre tracts that connect the frontal and temporo-parietal regions. FTD in schizophrenia was found to be associated with structural and functional aberrations in the language network. However, there are studies that did not find an association between FTD and neural aberrations of the language network and regions not included in the language network have been associated with FTD. Thus, future research is needed to clarify the specificity of the language network for FTD in schizophrenia.

Systems Neuroscience of Psychosis: Mapping Schizophrenia Symptoms onto Brain Systems

Schizophrenia research has been in a deadlock for many decades. Despite important advances in clinical treatment, there are still major concerns regarding long-term psychosocial reintegration and disease management, biological heterogeneity, unsatisfactory predictors of individual course and treatment strategies, and a confusing variety of controversial theories about its etiology and pathophysiological mechanisms. In the present perspective on schizophrenia research, we first discuss a methodological pitfall in contemporary schizophrenia research inherent in the attempt to link mental phenomena with the brain: we claim that the time-honored phenomenological method of defining mental symptoms should not be contaminated with the naturalistic approach of modern neuroscience. We then describe our Systems Neuroscience of Psychosis (SyNoPsis) project, which aims to overcome this intrinsic problem of psychiatric research. Considering schizophrenia primarily as a disorder of interindividual communication, we developed a neurobiologically informed semiotics of psychotic disorders, as well as an operational clinical rating scale. The novel psychopathology allows disentangling the clinical manifestations of schizophrenia into behavioral domains matching the functions of three well-described higher-order corticobasal brain systems involved in interindividual human communication, namely, the limbic, associative, and motor loops, including their corticocortical sensorimotor connections. The results of several empirical studies support the hypothesis that the proposed three-dimensional symptom structure, segregated into the affective, the language, and the motor domain, can be specifically mapped onto structural and functional abnormalities of the respective brain systems. New pathophysiological hypotheses derived from this brain system-oriented approach have helped to develop and improve novel treatment strategies with noninvasive brain stimulation and practicable clinical parameters. In clinical practice, the novel psychopathology allows confining the communication deficits of the individual patient, shifting attention from the symptoms to the intact resources. We have studied this approach and observed important advantages for therapeutic alliances, personalized treatment, and de-escalation strategies. Future studies will further conjoin clinical definitions of psychotic symptoms with brain structures and functions, and disentangle structural and functional deficit patterns within these systems to identify neurobiologically distinct subsyndromes. Neurobiologically homogeneous patient groups may provide new momentum for treatment research. Finally, lessons learned from schizophrenia research may contribute to developing a comprehensive perspective on human experience and behavior that integrates methodologically distinct, but internally consistent, insights from humanities and neuroscience.

Thought disorder

We review thought disorder in psychopathology, including how one can assess it clinically, useful psychometric measures and its clinical importance. In the final section we discuss how recent studies in neuropsychology and neuroimaging have helped understand the mechanisms of abnormal speech and languages in psychotic illnesses.

Common variation in ZNF804A (rs1344706) is not associated with brain morphometry in schizophrenia or healthy participants

BACKGROUND

The single nucleotide polymorphism (SNP) rs1344706 [A>C] within intron 2 of the zinc finger protein 804A gene (ZNF804A) is associated with schizophrenia at the genome-wide level, but its function in relation to the development of psychotic disorders, including its influence on brain morphology remains unclear.

METHODS

Using both univariate (voxel-based morphometry, VBM; cortical thickness) and multivariate (source-based morphometry, SBM) approaches, we examined the effects of variation of the rs1344706 polymorphism on grey matter integrity in 214 Caucasian schizophrenia cases and 94 Caucasian healthy individuals selected from the Australian Schizophrenia Research Bank.

RESULTS

Neither univariate nor multivariate analyses showed any associations between indices of grey matter and rs1344706 variation in schizophrenia or healthy participants. This was revealed in the context of the typical pattern of decreased grey matter integrity in schizophrenia compared to healthy individuals, including: (1) large grey matter volume reductions in the orbitofrontal and anterior cingulate cortices and the left fusiform/inferior temporal gyri; (2) decreased cortical thickness in the left inferior temporal and fusiform gyri, the left orbitofrontal gyrus, as well as in the right pars opercularis/precentral gyrus; and (3) decreased covariation of grey matter concentration in frontal and limbic brain regions emerging from the SBM analyses.

CONCLUSIONS

Contrary to some - but not all - previous findings, this study of a large sample of schizophrenia cases and healthy controls reveals no evidence for association between grey matter alterations and variation in rs1344706 (ZNF804A). Differences in sample sizes and ethnicities may account for discrepant findings between the present and previous studies.

White matter correlates of the disorganized speech dimension in schizophrenia

Disorganized speech is related to functional abnormalities in schizophrenia. To test the association between formal thought disorders (FTDs) and white matter microstructure, we applied a behavioral rating and diffusion tensor imaging in 61 patients with schizophrenia spectrum disorders. The Bern Psychopathology Scale was used to rate the dimension of language abnormalities ranging from negative FTDs, basically unaltered speech, to positive FTDs. Tract-based spatial statistics indicated increased fractional anisotropy in left hemispheric pathways of the language system in patients with negative FTDs. Thus, altered white matter properties in relevant fiber tracts may represent vulnerability to specific formal thought disorders.

Formal thought disorder in people at ultra-high risk of psychosis

BACKGROUND

Formal thought disorder is a cardinal feature of psychosis. However, the extent to which formal thought disorder is evident in ultra-high-risk individuals and whether it is linked to the progression to psychosis remains unclear.

AIMS

Examine the severity of formal thought disorder in ultra-high-risk participants and its association with future psychosis.

METHOD

The Thought and Language Index (TLI) was used to assess 24 ultra-high-risk participants, 16 people with first-episode psychosis and 13 healthy controls. Ultra-high-risk individuals were followed up for a mean duration of 7 years (s.d.=1.5) to determine the relationship between formal thought disorder at baseline and transition to psychosis.

RESULTS

TLI scores were significantly greater in the ultra-high-risk group compared with the healthy control group (effect size (ES)=1.2), but lower than in people with first-episode psychosis (ES=0.8). Total and negative TLI scores were higher in ultra-high-risk individuals who developed psychosis, but this was not significant. Combining negative TLI scores with attenuated psychotic symptoms and basic symptoms predicted transition to psychosis (P=0.04; ES=1.04).

CONCLUSIONS

TLI is beneficial in evaluating formal thought disorder in ultra-high-risk participants, and complements existing instruments for the evaluation of psychopathology in this group.

DECLARATION OF INTERESTS

None.

COPYRIGHT AND USAGE

© The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license.

Formal thought disorder in schizophrenia and bipolar disorder: A systematic review and meta-analysis

Historically, formal thought disorder has been considered as one of the distinctive symptoms of schizophrenia. However, research in last few decades suggested that there is a considerable clinical and neurobiological overlap between schizophrenia and bipolar disorder (BP). We conducted a meta-analysis of studies comparing positive (PTD) and negative formal thought disorder (NTD) in schizophrenia and BP. We included 19 studies comparing 715 schizophrenia and 474 BP patients. In the acute inpatient samples, there was no significant difference in the severity of PTD (d=-0.07, CI=-0.22-0.09) between schizophrenia and BP. In stable patients, schizophrenia was associated with increased PTD compared to BP (d=1.02, CI=0.35-1.70). NTD was significantly more severe (d=0.80, CI=0.52-0.1.08) in schizophrenia compared to BP. Our findings suggest that PTD is a shared feature of both schizophrenia and BP but persistent PTD or NTD can distinguish subgroups of schizophrenia from BP and schizophrenia patients with better clinical outcomes.

Brain Structural Networks Associated with Intelligence and Visuomotor Ability

Increasing evidence indicates that multiple structures in the brain are associated with intelligence and cognitive function at the network level. The association between the grey matter (GM) structural network and intelligence and cognition is not well understood. We applied a multivariate approach to identify the pattern of GM and link the structural network to intelligence and cognitive functions. Structural magnetic resonance imaging was acquired from 92 healthy individuals. Source-based morphometry analysis was applied to the imaging data to extract GM structural covariance. We assessed the intelligence, verbal fluency, processing speed, and executive functioning of the participants and further investigated the correlations of the GM structural networks with intelligence and cognitive functions. Six GM structural networks were identified. The cerebello-parietal component and the frontal component were significantly associated with intelligence. The parietal and frontal regions were each distinctively associated with intelligence by maintaining structural networks with the cerebellum and the temporal region, respectively. The cerebellar component was associated with visuomotor ability. Our results support the parieto-frontal integration theory of intelligence by demonstrating how each core region for intelligence works in concert with other regions. In addition, we revealed how the cerebellum is associated with intelligence and cognitive functions.

Meta-analysis of the Brief Psychiatric Rating Scale - Expanded (BPRS-E) structure and arguments for a new version

The factor structure of the 24 item BPRS-E was examined to determine the effect of additional items on consensus scales derived primarily from the 18 item BPRS. A meta-analysis (k = 32, n = 10,084) of previous factor analyses of the BPRS-E was conducted using both a co-occurrence similarity matrix and reproduced correlations. Components generally supporting the consensus scales were found suggesting four relatively invariant subscales: Affect (defined by the core items: anxiety, guilt, depression, suicidality), Positive Symptoms (hallucinations, unusual thought content, suspiciousness, grandiosity), Negative Symptoms (blunted affect, emotional withdrawal, motor retardation) and Activation (excitement, motor hyperactivity, elevated mood, distractibility). The additional BPRS-E items primarily contribute directly to a clear Activation dimension which expands and clarifies the traditional 18 item BPRS structure. Though not statistically supported in this meta-analysis, a fifth factor describing disorganization (conceptual disorganization, disorientation, self-neglect, mannerisms-posturing) was present in some analyses and should be considered. The five factor solution including a disorganization factor has theoretical validity based on the pentagonal model of schizophrenia while also containing the same four primary dimensions that were statistically supported in this meta-analysis. A new version of the BPRS (BPRS-26) with modified and additional items is presented. BPRS-26 is supposed to enhance the stability and the comprehensiveness of the scale and to more closely measure this five factor model.

Patterns of Co-Occurring Gray Matter Concentration Loss across the Huntington Disease Prodrome

Huntington disease (HD) is caused by an abnormally expanded cytosine-adenine-guanine (CAG) trinucleotide repeat in the HTT gene. Age and CAG-expansion number are related to age at diagnosis and can be used to index disease progression. However, observed onset-age variability suggests that other factors also modulate progression. Indexing prodromal (pre-diagnosis) progression may highlight therapeutic targets by isolating the earliest-affected factors. We present the largest prodromal HD application of the univariate method voxel-based morphometry (VBM) and the first application of the multivariate method source-based morphometry (SBM) to, respectively, compare gray matter concentration (GMC) and capture co-occurring GMC patterns in control and prodromal participants. Using structural MRI data from 1050 (831 prodromal, 219 control) participants, we characterize control-prodromal, whole-brain GMC differences at various prodromal stages. Our results provide evidence for (1) regional co-occurrence and differential patterns of decline across the prodrome, with parietal and occipital differences commonly co-occurring, and frontal and temporal differences being relatively independent from one another, (2) fronto-striatal circuits being among the earliest and most consistently affected in the prodrome, (3) delayed degradation in some movement-related regions, with increasing subcortical and occipital differences with later progression, (4) an overall superior-to-inferior gradient of GMC reduction in frontal, parietal, and temporal lobes, and (5) the appropriateness of SBM for studying the prodromal HD population and its enhanced sensitivity to early prodromal and regionally concurrent differences.