Association between symptom dimensions and categorical diagnoses of psychosis: a cross-sectional and longitudinal investigation

Identification of Bipolar Disorder and Schizophrenia Based on Brain CT and Deep Learning Methods

With the increasing prevalence of mental illness, accurate clinical diagnosis of mental illness is crucial. Compared with MRI, CT has the advantages of wide application, low price, short scanning time, and high patient cooperation. This study aims to construct a deep learning (DL) model based on CT images to make identification of bipolar disorder (BD) and schizophrenia (SZ). A total of 506 patients (BD = 227, SZ = 279) and 179 healthy controls (HC) was collected from January 2022 to May 2023 at two hospitals, and divided into an internal training set and an internal validation set according to a ratio of 4:1. An additional 65 patients (BD = 35, SZ = 30) and 40 HC were recruited from different hospitals, and served as an external test set. All subjects accepted the conventional brain CT examination. The DenseMD model for identify BD and SZ using multiple instance learning was developed and compared with other classical DL models. The results showed that DenseMD performed excellently with an accuracy of 0.745 in the internal validation set, whereas the accuracy of the ResNet-18, ResNeXt-50, and DenseNet-121model was 0.672, 0.664, and 0.679, respectively. For the external test set, DenseMD again outperformed other models with an accuracy of 0.724; however, the accuracy of the ResNet-18, ResNeXt-50, and DenseNet-121model was 0.657, 0.638, and 0.676, respectively. Therefore, the potential of DL models for identification of BD and SZ based on brain CT images was established, and identification ability of the DenseMD model was better than other classical DL models.

Interventions targeting emotion regulation: A systematic umbrella review

BACKGROUND

Emotion dysregulation (ED), the difficulty in modulating which emotions are felt, and when and how they are expressed or experienced, has been implicated in an array of psychological disorders. Despite potentially different manifestations depending on the disorder, this symptom is emerging as a transdiagnostic construct that can and should be targeted early, given the associations with various maladaptive behaviors as early as childhood and adolescence. As such, our goal was to investigate the psychotherapeutic interventions used to address ED and gauge their effectiveness, safety, and potential mechanisms across various populations.

METHODS

This umbrella systematic review, pre-registered under PROSPERO (registration: CRD42023411452), consolidates evidence from systematic reviews and meta-analyses on psychotherapeutic interventions targeting ED, in accordance with PRISMA guidelines.

RESULTS

Our synthesis of quantitative and qualitative evidence from 21 systematic reviews (including 11 meta-analyses) points-with moderate overall risk of bias-to the effectiveness of Dialectical Behavior Therapy and Cognitive Behavioral Therapy in reducing ED in a wide range of adult transdiagnostic psychiatric patients and healthy participants. Similar results have emerged in other less extensively researched methods as well. However, results on adolescents and children are sparse, highlighting the need for additional research to tailor these interventions to the unique challenges of ED in younger populations with diverse externalizing and internalizing disorders.

CONCLUSIONS

These demonstrated transdiagnostic advantages of psychotherapy for ED underscore the potential for specifically designed interventions that address this issue directly, particularly for high-risk individuals. In these individuals, early interventions targeting transdiagnostic core dimensions may mitigate the emergence of full-blown disorders. Future research on the mediating factors, the durability of intervention effects, and the exploration of understudied interventions and populations may enhance prevention and treatment efficiency, enhancing the quality of life for those affected by varied manifestations of ED.

Shared and unique characteristics of metabolic syndrome in psychotic disorders: a review

Introduction

People with psychosis spectrum disorders (PSD) face an elevated risk of metabolic syndrome (MetS), which may reduce their life expectancy by nearly 20%. Pinpointing the shared and specific characteristics and clinical implications of MetS in PSD is crucial for designing interventions to reduce this risk, but an up-to-date review on MetS across the psychosis spectrum is lacking.

Methods

This narrative review fills this gap by examining the clinical literature on characteristics and implications of MetS in both distinct PSD and transdiagnostically, i.e., across traditional categorical diagnoses, with a focus on psychiatric and cardio-metabolic management.

Results

We discuss common and specific characteristics of MetS in PSD, as well as factors contributing to MetS development in PSD patients, including unhealthy lifestyle factors, genetic predisposition, pro-inflammatory state, drugs consumption, antipsychotic medication, and psychotic symptoms. We highlight the importance of early identification and management of cardio-metabolic risk in PSD patients, as well as the existing gaps in the literature, for instance in the screening for MetS in younger PSD patients. We compare hypotheses-generating clinical associations and characteristics of MetS in different PSD, concluding by reviewing the existing recommendations and challenges in screening, monitoring, and managing MetS in PSD.

Conclusion

Early identification and management of MetS are crucial to mitigate the long-term cardio-metabolic toll in PSD patients. Interventions should focus on healthy lifestyle and appropriate pharmacological and behavioral interventions. Further translational and clinical research is needed to develop targeted interventions and personalized treatment approaches for this vulnerable population, aiming at improving physical health and overall well-being.

Urban distance to mental healthcare units and public transport increases duration of untreated psychosis in first-episode patients

BACKGROUND

There is a growing interest in environmental and social determinants of mental health. However, how distance to healthcare and public transportation affect illness is neglected in schizophrenia research. Here, we are interested in how the availability of mental healthcare and the ways to reach it may be associated with psychosis.

AIMS

We aim to investigate the association between distances to healthcare units and subway stations and duration of untreated psychosis (DUP) and greater initial severity in an antipsychotic-naïve first episode of psychosis (FEP) sample.

METHOD

Using 212 untreated FEP patients' data, we calculated the distances from their residences to the places of interest. Diagnoses comprehended schizophrenia spectrum disorders, depressive and bipolar affective disorders, and substance-induced disorders. Linear regressions were performed with distances as independent variables, DUP and Positive and Negative Syndrome Scale (PANSS) scores as dependent variables.

RESULTS

Longer distance to emergency mental healthcare was related to longer DUP (95% CI: p = .034, B = 0.152) and higher total PANSS (95% CI: p = .007, B = 0.0189); longer distance to community mental healthcare units was related to longer DUP (95% CI: p = .004, B = 0.0204) and higher total PANSS (95% CI: p = .030, B = 0.152). Moreover, a longer distance to the closest subway station predicted longer DUP (95% CI: p = .019, B = 0.170).

CONCLUSION

Our results indicate that poor healthcare access is related to longer DUP and higher initial PANSS scores. Future research should investigate how investments in mental health access and actions to improve public transport access could impact DUP and treatment outcomes in psychosis patients.

Identification of different MRI atrophy progression trajectories in epilepsy by subtype and stage inference

Artificial intelligence (AI)-based tools are widely employed, but their use for diagnosis and prognosis of neurological disorders is still evolving. Here we analyse a cross-sectional multicentre structural MRI dataset of 696 people with epilepsy and 118 control subjects. We use an innovative machine-learning algorithm, Subtype and Stage Inference, to develop a novel data-driven disease taxonomy, whereby epilepsy subtypes correspond to distinct patterns of spatiotemporal progression of brain atrophy.In a discovery cohort of 814 individuals, we identify two subtypes common to focal and idiopathic generalized epilepsies, characterized by progression of grey matter atrophy driven by the cortex or the basal ganglia. A third subtype, only detected in focal epilepsies, was characterized by hippocampal atrophy. We corroborate external validity via an independent cohort of 254 people and confirm that the basal ganglia subtype is associated with the most severe epilepsy.Our findings suggest fundamental processes underlying the progression of epilepsy-related brain atrophy. We deliver a novel MRI- and AI-guided epilepsy taxonomy, which could be used for individualized prognostics and targeted therapeutics.

Unlocking Neural Function with 3D In Vitro Models: A Technical Review of Self-Assembled, Guided, and Bioprinted Brain Organoids and Their Applications in the Study of Neurodevelopmental and Neurodegenerative Disorders

Understanding the complexities of the human brain and its associated disorders poses a significant challenge in neuroscience. Traditional research methods have limitations in replicating its intricacies, necessitating the development of in vitro models that can simulate its structure and function. Three-dimensional in vitro models, including organoids, cerebral organoids, bioprinted brain models, and functionalized brain organoids, offer promising platforms for studying human brain development, physiology, and disease. These models accurately replicate key aspects of human brain anatomy, gene expression, and cellular behavior, enabling drug discovery and toxicology studies while providing insights into human-specific phenomena not easily studied in animal models. The use of human-induced pluripotent stem cells has revolutionized the generation of 3D brain structures, with various techniques developed to generate specific brain regions. These advancements facilitate the study of brain structure development and function, overcoming previous limitations due to the scarcity of human brain samples. This technical review provides an overview of current 3D in vitro models of the human cortex, their development, characterization, and limitations, and explores the state of the art and future directions in the field, with a specific focus on their applications in studying neurodevelopmental and neurodegenerative disorders.

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.

Psychopathological networks in psychosis: Changes over time and clinical relevance. A long-term cohort study of first-episode psychosis

BACKGROUND

First-episode psychosis is a critical period for early interventions to reduce the risk of poor outcomes and relapse as much as possible. However, uncertainties about the long-term outcomes of symptomatology remain to be ascertained.

METHODS

The aim of the present study was to use network analysis to investigate first-episode and long-term stages of psychosis at three levels of analysis: micro, meso and macro. The sample was a cohort of 510 patients with first-episode psychoses from the SEGPEP study, who were reassessed at the long-term follow-up (n = 243). We used the Comprehensive Assessment of Symptoms and History for their assessments and lifetime outcome variables of clinical relevance.

RESULTS

Our results showed a similar pattern of clustering between first episodes and long-term follow-up in seven psychopathological dimensions at the micro level, 3 and 4 dimensions at the meso level, and one at the macro level. They also revealed significant differences between first-episode and long-term network structure and centrality measures at the three levels, showing that disorganization symptoms have more influence in long-term stabilized patients.

CONCLUSIONS

Our findings suggest a relative clustering invariance at all levels, with the presence of two domains of disorganization as the most notorious difference over time at micro level. The severity of disorganization at the follow-up was associated with a more severe course of the psychosis. Moreover, a relative stability in global strength of the interconnections was found, even though the network structure varied significantly in the long-term follow-up. The macro level was helpful in the integration of all dimensions into a common psychopathology factor, and in unveiling the strong relationships of psychopathological dimensions with lifetime outcomes, such as negative with poor functioning, disorganization with high antipsychotic dose-years, and delusions with poor adherence to treatment. These results add evidence to the hierarchical, dimensional and longitudinal structure of psychopathological symptoms and their clinical relevance in first-episode psychoses.

Affective symptom dimensions in early-onset psychosis over time: a principal component factor analysis of the Young Mania Rating Scale and the Hamilton Depression Rating Scale

Early-onset psychosis (EOP) is a complex disorder characterized by a wide range of symptoms, including affective symptoms. Our aim was to (1) examine the dimensional structure of affective symptoms in EOP, (2) evaluate the predominance of the clinical dimensions and (3) assess the progression of the clinical dimensions over a 2-year period. STROBE-compliant prospective principal component factor analysis of Young Mania Rating Scale (YMRS) and Hamilton Depression Rating Scale-21 (HDRS-21) at baseline, 6-months, 1-year and 2-year follow-up. We included 108 EOP individuals (mean age = 15.5 ± 1.8 years, 68.5% male). The factor analysis produced a four-factor model including the following dimensions: mania, depression/anxiety, sleep and psychosis. It explained 47.4% of the total variance at baseline, 60.6% of the total variance at 6-months follow-up, 54.5% of the total variance at 1-year follow-up and 49.5% of the total variance at 2-year follow-up. According to the variance explained, the mania factor was predominant at baseline (17.4%), 6-month follow-up (23.5%) and 2-year follow-up (26.1%), while the depression/anxiety factor was predominant at 1-year follow-up (23.1%). The mania factor was the most stable; 58.3% items that appeared in this factor (with a load > 0.4) at any time point appeared in the same factor at ≥ 3/4 time points. Affective symptoms are frequent and persistent in EOP. Mania seems to be the most predominant and stable affective dimension. However, depression and anxiety may gain predominance with time. A comprehensive evaluation of the dimensional structure and the progression of affective symptoms may offer clinical and therapeutic advantages.

Emerging evidence for astrocyte dysfunction in schizophrenia

Schizophrenia is a complex, chronic mental health disorder whose heterogeneous genetic and neurobiological background influences early brain development, and whose precise etiology is still poorly understood. Schizophrenia is not characterized by gross brain pathology, but involves subtle pathological changes in neuronal populations and glial cells. Among the latter, astrocytes critically contribute to the regulation of early neurodevelopmental processes, and any dysfunctions in their morphological and functional maturation may lead to aberrant neurodevelopmental processes involved in the pathogenesis of schizophrenia, such as mitochondrial biogenesis, synaptogenesis, and glutamatergic and dopaminergic transmission. Studies of the mechanisms regulating astrocyte maturation may therefore improve our understanding of the cellular and molecular mechanisms underlying the pathogenesis of schizophrenia.

The Important Role of Motivation and Pleasure Deficits on Social Functioning in Patients With Schizophrenia: A Network Analysis

Negative symptoms, particularly the motivation and pleasure (MAP) deficits, are associated with impaired social functioning in patients with schizophrenia (SCZ). However, previous studies seldom examined the role of the MAP on social functioning while accounting for the complex interplay between other psychopathology. This network analysis study examined the network structure and interrelationship between negative symptoms (at the "symptom-dimension" and "symptom-item" levels), other psychopathology and social functioning in a sample of 269 patients with SCZ. The psychopathological symptoms were assessed using the Clinical Assessment Interview for Negative Symptoms (CAINS) and the Positive and Negative Syndrome Scale (PANSS). Social functioning was evaluated using the Social and Occupational Functioning Assessment Scale (SOFAS). Centrality indices and relative importance of each node were estimated. The network structures between male and female participants were compared. Our resultant networks at both the "symptom-dimension" and the "symptom-item" levels suggested that the MAP factor/its individual items were closely related to social functioning in SCZ patients, after controlling for the complex interplay between other nodes. Relative importance analysis showed that MAP factor accounted for the largest proportion of variance of social functioning. This study is among the few which used network analysis and the CAINS to examine the interrelationship between negative symptoms and social functioning. Our findings supported the pivotal role of the MAP factor to determine SCZ patients' social functioning, and as a potential intervention target for improving functional outcomes of SCZ.

Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study

How individual differences in brain network organization track behavioral variability is a fundamental question in systems neuroscience. Recent work suggests that resting-state and task-state functional connectivity can predict specific traits at the individual level. However, most studies focus on single behavioral traits, thus not capturing broader relationships across behaviors. In a large sample of 1858 typically developing children from the Adolescent Brain Cognitive Development (ABCD) study, we show that predictive network features are distinct across the domains of cognitive performance, personality scores and mental health assessments. On the other hand, traits within each behavioral domain are predicted by similar network features. Predictive network features and models generalize to other behavioral measures within the same behavioral domain. Although tasks are known to modulate the functional connectome, predictive network features are similar between resting and task states. Overall, our findings reveal shared brain network features that account for individual variation within broad domains of behavior in childhood.

The benefit of diagnostic whole genome sequencing in schizophrenia and other psychotic disorders

Schizophrenia has a multifactorial etiology, involving a polygenic architecture. The potential benefit of whole genome sequencing (WGS) in schizophrenia and other psychotic disorders is not well studied. We investigated the yield of clinical WGS analysis in 251 families with a proband diagnosed with schizophrenia (N = 190), schizoaffective disorder (N = 49), or other conditions involving psychosis (N = 48). Participants were recruited in Israel and USA, mainly of Jewish, Arab, and other European ancestries. Trio (parents and proband) WGS was performed for 228 families (90.8%); in the other families, WGS included parents and at least two affected siblings. In the secondary analyses, we evaluated the contribution of rare variant enrichment in particular gene sets, and calculated polygenic risk score (PRS) for schizophrenia. For the primary outcome, diagnostic rate was 6.4%; we found clinically significant, single nucleotide variants (SNVs) or small insertions or deletions (indels) in 14 probands (5.6%), and copy number variants (CNVs) in 2 (0.8%). Significant enrichment of rare loss-of-function variants was observed in a gene set of top schizophrenia candidate genes in affected individuals, compared with population controls (N = 6,840). The PRS for schizophrenia was significantly increased in the affected individuals group, compared to their unaffected relatives. Last, we were also able to provide pharmacogenomics information based on CYP2D6 genotype data for most participants, and determine their antipsychotic metabolizer status. In conclusion, our findings suggest that WGS may have a role in the setting of both research and genetic counseling for individuals with schizophrenia and other psychotic disorders and their families.

Converting scores between the PANSS and SAPS/SANS beyond the positive/negative dichotomy

Previous work provided conversion equations for overall indices of positive and negative symptomatology between the Positive and Negative Syndrome Scale (PANSS) and the Scales for the Assessment of Positive/Negative Symptoms (SAPS/SANS). Our objective was to provide such conversion equations for subdomains of positive and negative symptomatology in order to better account for the diversity of symptom profiles in schizophrenia. Symptoms severity was assessed using both the PANSS and SAPS/SANS in 205 patients with schizophrenia. Two exploratory factor analyses combining items from both scales were first performed separately in the positive and negative symptom domains. Positive factors were termed 'Hallucinations', 'Delusions' and 'Disorganization', while negative factors were associated with 'Expressivity', 'Amotivation' and 'Cognition', consistent with current descriptions of symptom dimensions in schizophrenia. For each factor, linear regression analyses were conducted on 80% of the data to obtain conversion equations from the PANSS to the SAPS/SANS and vice versa. Reliability was then evaluated on the 20% remaining data, with good to excellent intra-class correlation coefficients between the original and predicted scores for all but the cognition factor. These findings show that symptom severity scores can be converted with good accuracy between clinical scales beyond the positive/negative symptom dichotomy.

Appraisal of patient-level health economic models of severe mental illness: systematic review

BACKGROUND

Healthcare decision makers require accurate long-term economic models to evaluate the cost-effectiveness of new mental health interventions.

AIMS

To assess the suitability of current patient-level economic models to estimate long-term economic outcomes in severe mental illness.

METHOD

We undertook pre-specified systematic searches in MEDLINE, Embase and PsycINFO to identify reviews and stand-alone publications of economic models of interventions for schizophrenia, bipolar disorder and major depressive disorder (PROSPERO: CRD42020158243). We screened paper titles and abstracts to identify unique patient-level economic models. We conducted a structured extraction of identified models, recording the presence of key predefined model features. Model quality and validation were appraised using the 2014 ISPOR and 2016 AdViSHE model checklists.

RESULTS

We identified 15 unique patient-level models for psychosis and major depressive disorder from 1481 non-duplicate records. Models addressed schizophrenia (n = 6), bipolar disorder (n = 2) and major depressive disorder (n = 7). The predominant model type was discrete event simulation (n = 9). Model complexity and incorporation of patient heterogeneity varied considerably, and only five models extrapolated costs and outcomes over a lifetime horizon. Key model parameters were often based on low-quality evidence, and checklist quality assessment revealed weak model verification procedures.

CONCLUSIONS

Existing patient-level economic models of interventions for severe mental illness have considerable limitations. New modelling efforts must be supplemented by the generation of good-quality, contemporary evidence suitable for model building. Combined effort across the research community is required to build and validate economic extrapolation models suitable for accurately assessing the long-term value of new interventions from short-term clinical trial data.

Precursors of self-reported subclinical hypomania in adolescence: A longitudinal general population study

Symptoms of subclinical hypomania (SHM) are common in the general population of adolescents and young adults. SHM are most often transient yet might be risk markers of later bipolar disorder. The current study aimed to assess the clinical correlates of SHM at age 11 in the general population, examine the continuity of SHM from age 11-age 16 and explore the clinical precursors of age 16 SHM. As part of the Copenhagen Child Cohort 2000, 1,632 preadolescents participated in the examination of SHM and various clinical correlates at age 11, 893 were re-assessed for SHM at age 16 years. At age 11, SHM, psychotic experiences and depressive symptoms were assessed by semi-structured psychopathological interviews. Furthermore, the participants were diagnostically assessed by the Development and Well-Being Assessment and interviewed about sleep length. At age 16, SHM was assessed by self-report, using the Hypomania Checklist-32. Cannabis use occurring at age 15 or earlier was assessed at age 16. At age 11, SHM was associated with depressive disorders (Relative Risk [RR] = 2.96 [95% CI 1.26–6.96]), interview-based depressive symptoms (RR = 9.22 [5.93–14.34]), neurodevelopmental disorders (RR = 2.94 [1.66–5.20]), psychotic experiences (RR = 4.51 [2.90–7.01]) and insufficient sleep (RR = 2.10 [1.28–3.43]. In the longitudinal analyses, age 16 SHM was preceded by age 11 SHM (RR = 1.89 [1.02–3.49]), psychotic experiences (RR = 2.06, [1.28–3.33]), emotional disorders (RR = 1.77, [1.02–3.09]) and cannabis use (RR = 3.14, [1.93–5.10]), after mutual adjustment and adjustment for sex, and sociodemographic factors. In conclusion, age 11 SHM was statistically significantly associated with other types of psychopathology in cross-sectional analyses and showed some continuity with later self-reported SHM at age 16. Particularly early psychotic experiences and cannabis use stood out as independent precursors of self-reported SHM and might constitute important risk markers for the development of future SHM and bipolar disorder. An important potential caveat of the current study includes the self-report assessment of SHM.

Inferior frontal gyrus seed-based resting-state functional connectivity and sustained attention across manic/hypomanic, euthymic and depressive phases of bipolar disorder

OBJECTIVE

Seed-based resting-state functional connectivity (rs-FC) of inferior frontal gyrus (IFG), as well as sustained attention cognitive deficit are consistently reported to be impaired in bipolar disorders. However, whether these deficits exist across mood states and euthymic state are lacking. We compared rs-FC of IFG and sustained attention of bipolar patients in (hypo) mania, depression and euthymia, with controls. We also explored the interrelationships between clinical, cognitive, and imaging measurements.

METHODS

Participants included 110 bipolar subjects: 46 manic/hypomanic, 35 euthymic, and 29 depressed, matched with 41 healthy controls (HCs) underwent structural magnetic resonance imaging (MRI) and resting-state functional MRI scans. Seed-based functional connectivity analyses were performed focused on bilateral IFG seeds. Clinical symptoms and sustained attention function were measured. Stepwise linear regression analysis was conducted to explore predictors of sustained attention measurements.

RESULTS

Increased rs-FC between right IFG and bilateral frontal pole/superior frontal gyrus, precuneus, and posterior cingulate gyrus, as well as decreased rs-FC between right IFG and sensorimotor areas, anterior middle cingulate gyrus were found in all three bipolar subgroups compared with HCs. Impaired sustained attention measurement was found in bipolar manic/hypomanic and depressive subgroups compared with HCs. Linear regression analyses revealed a significant impact of the manic symptoms and psychotic symptoms on the performance of sustained attention task.

CONCLUSIONS

Our results revealed that IFG seed-based resting-state functional networks involved in emotion regulation and cognitive function were trait-like deficit in bipolar patients. Higher manic levels and psychotic symptoms were predictors of a worse sustained attention performance.

Dynamic functional connectome predicts individual working memory performance across diagnostic categories

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We created transdiagnostic predictive working memory models using connectome-based predictive modeling (CPM).

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Dynamic functional connectivity-based CPM models successfully predicted working memory.

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Static functional connectivity-based CPM models fell short in prediction.

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Frontoparietal, somato-motor, default mode and visual networks contributed most to prediction.

Working memory impairment is a common feature of psychiatric disorders. Although its neural mechanisms have been extensively examined in healthy subjects or individuals with a certain clinical condition, studies investigating neural predictors of working memory in a transdiagnostic sample are scarce. The objective of this study was to create a transdiagnostic predictive working memory model from whole-brain functional connectivity using connectome-based predictive modeling (CPM), a recently developed machine learning approach. Resting-state functional MRI data from 242 subjects across 4 diagnostic categories (healthy controls and individuals with schizophrenia, bipolar disorder, and attention deficit/hyperactivity) were used to construct dynamic and static functional connectomes. Spatial working memory was assessed by the spatial capacity task. CPM was conducted to predict individual working memory from dynamic and static functional connectivity patterns. Results showed that dynamic connectivity-based CPM models successfully predicted overall working memory capacity and accuracy as well as mean reaction time, yet their static counterparts fell short in the prediction. At the neural level, we found that dynamic connectivity of the frontoparietal and somato-motor networks were negatively correlated with working memory capacity and accuracy, and those of the default mode and visual networks were positively associated with mean reaction time. Moreover, different feature selection thresholds, parcellation strategies and model validation methods as well as diagnostic categories did not significantly influence the prediction results. Our findings not only are coherent with prior reports that dynamic functional connectivity encodes more behavioral information than static connectivity, but also help advance the translation of cognitive “connectome fingerprinting” into real-world application.

Inter-relationships among psychopathology, premorbid adjustment, cognition and psychosocial functioning in first-episode psychosis: a network analysis approach

BACKGROUND

Better understanding of interplay among symptoms, cognition and functioning in first-episode psychosis (FEP) is crucial to promoting functional recovery. Network analysis is a promising data-driven approach to elucidating complex interactions among psychopathological variables in psychosis, but has not been applied in FEP.

METHOD

This study employed network analysis to examine inter-relationships among a wide array of variables encompassing psychopathology, premorbid and onset characteristics, cognition, subjective quality-of-life and psychosocial functioning in 323 adult FEP patients in Hong Kong. Graphical Least Absolute Shrinkage and Selection Operator (LASSO) combined with extended Bayesian information criterion (BIC) model selection was used for network construction. Importance of individual nodes in a generated network was quantified by centrality analyses.

RESULTS

Our results showed that amotivation played the most central role and had the strongest associations with other variables in the network, as indexed by node strength. Amotivation and diminished expression displayed differential relationships with other nodes, supporting the validity of two-factor negative symptom structure. Psychosocial functioning was most strongly connected with amotivation and was weakly linked to several other variables. Within cognitive domain, digit span demonstrated the highest centrality and was connected with most of the other cognitive variables. Exploratory analysis revealed no significant gender differences in network structure and global strength.

CONCLUSION

Our results suggest the pivotal role of amotivation in psychopathology network of FEP and indicate its critical association with psychosocial functioning. Further research is required to verify the clinical significance of diminished motivation on functional outcome in the early course of psychotic illness.

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum

The Hierarchical Taxonomy of Psychopathology (HiTOP) is a scientific effort to address shortcomings of traditional mental disorder diagnoses, which suffer from arbitrary boundaries between psychopathology and normality, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. This paper synthesizes evidence on the validity and utility of the thought disorder and detachment spectra of HiTOP. These spectra are composed of symptoms and maladaptive traits currently subsumed within schizophrenia, other psychotic disorders, and schizotypal, paranoid and schizoid personality disorders. Thought disorder ranges from normal reality testing, to maladaptive trait psychoticism, to hallucinations and delusions. Detachment ranges from introversion, to maladaptive detachment, to blunted affect and avolition. Extensive evidence supports the validity of thought disorder and detachment spectra, as each spectrum reflects common genetics, environmental risk factors, childhood antecedents, cognitive abnormalities, neural alterations, biomarkers, and treatment response. Some of these characteristics are specific to one spectrum and others are shared, suggesting the existence of an overarching psychosis superspectrum. Further research is needed to extend this model, such as clarifying whether mania and dissociation belong to thought disorder, and explicating processes that drive development of the spectra and their subdimensions. Compared to traditional diagnoses, the thought disorder and detachment spectra demonstrated substantially improved utility: greater reliability, larger explanatory and predictive power, and higher acceptability to clinicians. Validated measures are available to implement the system in practice. The more informative, reliable and valid characterization of psychosis-related psychopathology offered by HiTOP can make diagnosis more useful for research and clinical care.

Dimensional structure of first episode psychosis

AIM

Current diagnostic systems, DSM-5 and ICD-10, still adopt a categorical approach to classify psychotic disorders. The present study was aimed at investigating the structure of psychotic symptomatology in both affective and non-affective psychosis from a dimensional approach.

METHODS

Participants with a first episode psychosis (FEP) were recruited from a cluster-randomized controlled trial (GET-UP PIANO TRIAL), offered to all Community Mental Health Centres (CMHCs) located across two northern Italian regions. After clinical stabilization, patients were assessed with a comprehensive set of psychopathological measures including the Positive and Negative Syndrome Scale, the Hamilton Depression Rating Scale and the Bech-Rafaelsen Mania Rating Scale. A two-step cluster analysis was performed.

RESULTS

Overall, 257 FEP patients (male, n = 171, 66.5%; mean age = 24.96 ± 4.56) were included in the study. The cluster analysis revealed a robust four-cluster solution: delusional-persecutory (n = 82; 31.9%), depressed (n = 95; 37%), excited (n = 26; 10.1%) and negative-disorganized (n = 54; 21%), thus suggesting a quadripartite structure with both affective and non-affective dimensions. Among non-affective dimensions, negative and disorganization symptoms constituted a unique construct apart from positive symptoms.

CONCLUSIONS

Symptom dimensions may represent a useful tool for dissecting the indistinct and non-specific psychopathology of FEP in order to better target specific interventions.

Somatosensory-Motor Dysconnectivity Spans Multiple Transdiagnostic Dimensions of Psychopathology

BACKGROUND

There is considerable interest in a dimensional transdiagnostic approach to psychiatry. Most transdiagnostic studies have derived factors based only on clinical symptoms, which might miss possible links between psychopathology, cognitive processes, and personality traits. Furthermore, many psychiatric studies focus on higher-order association brain networks, thereby neglecting the potential influence of huge swaths of the brain.

METHODS

A multivariate data-driven approach (partial least squares) was used to identify latent components linking a large set of clinical, cognitive, and personality measures to whole-brain resting-state functional connectivity patterns across 224 participants. The participants were either healthy (n = 110) or diagnosed with bipolar disorder (n = 40), attention-deficit/hyperactivity disorder (n = 37), schizophrenia (n = 29), or schizoaffective disorder (n = 8). In contrast to traditional case-control analyses, the diagnostic categories were not used in the partial least squares analysis but were helpful for interpreting the components.

RESULTS

Our analyses revealed three latent components corresponding to general psychopathology, cognitive dysfunction, and impulsivity. Each component was associated with a unique whole-brain resting-state functional connectivity signature and was shared across all participants. The components were robust across multiple control analyses and replicated using independent task functional magnetic resonance imaging data from the same participants. Strikingly, all three components featured connectivity alterations within the somatosensory-motor network and its connectivity with subcortical structures and cortical executive networks.

CONCLUSIONS

We identified three distinct dimensions with dissociable (but overlapping) whole-brain resting-state functional connectivity signatures across healthy individuals and individuals with psychiatric illness, providing potential intermediate phenotypes that span diagnostic categories. Our results suggest expanding the focus of psychiatric neuroscience beyond higher-order brain networks.

How would patients with psychosis like to be in contact with a volunteer: Face-to-face or digitally?

Introduction

Volunteer befriending can be used to address social isolation in patients with psychosis. Traditionally this involves face-to-face encounters between a volunteer and a patient, but modern digital technology also makes it possible to have these interactions remotely. This study aimed to explore the views and interests of patients with psychosis about different formats of volunteering, face-to-face or digitally.

Methods

A survey was conducted with patients with psychotic disorders in community mental health teams in London. Questions covered socio-demographic characteristics, quality of life, loneliness, views on the different formats of volunteering and types of volunteers, and their interest in getting volunteering support, face-to-face or digitally. Binary logistic regressions were used to investigate potential predictors of interest in getting volunteering support face-to-face or digitally.

Results

A total of 151 patients with psychotic disorders were included in this study. More than half of the patients (n = 87, 57.6%) had not heard about these volunteering programs. Many were interested in getting face-to-face (n = 87, 57.6%) and digital (n = 56, 37.1%) volunteering. For the face-to-face encounters, most preferred them to be weekly (n = 36, 41.4%), for one-hour (n = 32, 36.8%), and with an open-ended relationship (n = 45, 51.7%). For the digital contacts, most preferred them to be weekly (n = 17, 30.9%) and through text messages (n = 26, 46.4%). A minority of patients (n = 20, 13.2%) did not use digital technology. Patients with lower quality of life were significantly more likely to prefer face-to-face volunteering (p < .05). Younger patients and with fewer years of diagnosis were significantly more likely to prefer digital volunteering (p < .05).

Conclusions

The variability in patients’ interests suggests that different formats of volunteer support should be offered. Digital volunteering may become more important in the future, since many younger patients are interested in it.

Handwriting movements for assessment of motor symptoms in schizophrenia spectrum disorders and bipolar disorder

The main aim of the present study was to explore the value of several measures of handwriting in the study of motor abnormalities in patients with bipolar or psychotic disorders. 54 adult participants with a schizophrenia spectrum disorder or bipolar disorder and 44 matched healthy controls, participated in the study. Participants were asked to copy a handwriting pattern consisting of four loops, with an inking pen on a digitizing tablet. We collected a number of classical, non-linear and geometrical measures of handwriting. The handwriting of patients was characterized by a significant decrease in velocity and acceleration and an increase in the length, disfluency and pressure with respect to controls. Concerning non-linear measures, we found significant differences between patients and controls in the Sample Entropy of velocity and pressure, Lempel-Ziv of velocity and pressure, and Higuchi Fractal Dimension of pressure. Finally, Lacunarity, a measure of geometrical heterogeneity, was significantly greater in handwriting patterns from patients than from controls. We did not find differences in any handwriting measure on function of the specific diagnosis or the antipsychotic dose. Results indicate that participants with a schizophrenia spectrum disorder or bipolar disorder exhibit significant motor impairments and that these impairments can be readily quantified using measures of handwriting movements. Besides, they suggest that motor abnormalities are a core feature of several mental disorders and they seem to be unrelated to the pharmacological treatment.

Transdiagnostic dimensions of psychosis in the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP)

The validity of the classification of non-affective and affective psychoses as distinct entities has been disputed, but, despite calls for alternative approaches to defining psychosis syndromes, there is a dearth of empirical efforts to identify transdiagnostic phenotypes of psychosis. We aimed to investigate the validity and utility of general and specific symptom dimensions of psychosis cutting across schizophrenia, schizoaffective disorder and bipolar I disorder with psychosis. Multidimensional item-response modeling was conducted on symptom ratings of the Positive and Negative Syndrome Scale, Young Mania Rating Scale, and Montgomery-Åsberg Depression Rating Scale in the multicentre Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium, which included 933 patients with a diagnosis of schizophrenia (N=397), schizoaffective disorder (N=224), or bipolar I disorder with psychosis (N=312). A bifactor model with one general symptom dimension, two distinct dimensions of non-affective and affective psychosis, and five specific symptom dimensions of positive, negative, disorganized, manic and depressive symptoms provided the best model fit. There was further evidence on the utility of symptom dimensions for predicting B-SNIP psychosis biotypes with greater accuracy than categorical DSM diagnoses. General, positive, negative and disorganized symptom dimension scores were higher in African American vs. Caucasian patients. Symptom dimensions accurately classified patients into categorical DSM diagnoses. This study provides evidence on the validity and utility of transdiagnostic symptom dimensions of psychosis that transcend traditional diagnostic boundaries of psychotic disorders. Findings further show promising avenues for research at the interface of dimensional psychopathological phenotypes and basic neurobiological dimensions of psychopathology.

Resting-state network connectivity and metastability predict clinical symptoms in schizophrenia

BACKGROUND

The functional architecture of resting-state networks (RSNs) is defined by their connectivity and metastability. Disrupted RSN connectivity has been amply demonstrated in schizophrenia while the role of metastability remains poorly defined. Here, we undertake a comprehensive characterisation of RSN organization in schizophrenia and test its contribution to the clinical profile of this disorder.

METHODS

We extracted RSNs representing the default mode (DMN), central executive (CEN), salience (SAL), language (LAN), sensorimotor (SMN), auditory (AN) and visual (VN) networks from resting-state functional magnetic resonance imaging data obtained from patients with schizophrenia (n = 85) and healthy individuals (n = 48). For each network, we computed its functional cohesiveness and integration and used the Kuramoto order parameter to compute metastability. We used stepwise multiple regression analyses to test these RSN features as predictors of symptom severity in patients.

RESULTS

RSN features respectively explained 14%, 17%, 12% and 5% of the variance in positive, negative, anxious/depressive and agitation/disorganization symptoms. Lower functional integration between the DMN, CEN and SMN primarily contributed to positive symptoms. The functional properties of the SAL network were key predictors of all other symptom dimensions; specifically, lower cohesiveness of the SAL, lower integration of this network with the LAN and higher integration with the CEN respectively contributed to negative, anxious/depressive and disorganization symptoms. Increased SAL metastability was associated with negative symptoms.

CONCLUSIONS

These results confirm the primacy of the SAL network for schizophrenia and demonstrate that abnormalities in RSN connectivity and metastability are significant predictors of schizophrenia-related psychopathology.

Baseline brain structural and functional predictors of clinical outcome in the early course of schizophrenia

Although schizophrenia is considered a brain disorder, the role of brain organization for symptomatic improvement remains inadequately defined. We investigated the relationship between baseline brain morphology, resting-state network connectivity and clinical response after 24-weeks of antipsychotic treatment in patients with schizophrenia (n = 95) using integrated multivariate analyses. There was no significant association between clinical response and measures of cortical thickness (r = 0.37, p = 0.98) and subcortical volume (r = 0.56, p = 0.15). By contrast, we identified a strong mode of covariation linking functional network connectivity to clinical response (r = 0.70; p = 0.04), and particularly to improvement in positive (weight = 0.62) and anxious/depressive symptoms (weight = 0.49). Higher internal cohesiveness of the default mode network was the single most important positive predictor. Key negative predictors involved the functional cohesiveness of central executive subnetworks anchored in the frontoparietal cortices and subcortical regions (including the thalamus and striatum) and the inter-network integration between the default mode and sensorimotor networks. The present findings establish links between clinical response and the functional organization of brain networks involved both in perception and in spontaneous and goal-directed cognition, thereby advancing our understanding of the pathophysiology of schizophrenia.

The factor structure of the short form of the Wisconsin schizotypy scales

The Chapman psychosis-proneness scales-also known as Wisconsin schizotypy scales (WSS)-are among the most used tools to measure schizotypy. The factor structure of the short-form WSS was investigated in a mixed sample of patients with chronic mental disorders and of healthy subjects from the general population. One hundred patients with a chronic mental disorder were enrolled over a 6-month period. For each patient, two controls of same sex and similar age (±5 years) were enrolled; 131 accepted to take part in the study. The unidimensional, the correlated four-factor, the second-order two-factor models, and the bifactor model with two or four orthogonally independent factors of the short-form WSS were tested with confirmatory factor analysis. Good reliability of the short-form WSS was confirmed, as its capacity of differentiating people with and without schizotypy. The bifactor models were superior to other models. However, in both bifactor models the explained common variance (ECV) attributable to the general factor and the percentage of uncontaminated correlations (PUC) were too low to use a general summary score as a measure of a single latent schizotypy variable. Symptoms scores derived from the short-form WSS can be better appreciated within a multidimensional model of schizotypy.

Multivariate Associations Among Behavioral, Clinical, and Multimodal Imaging Phenotypes in Patients With Psychosis

IMPORTANCE

Alterations in multiple neuroimaging phenotypes have been reported in psychotic disorders. However, neuroimaging measures can be influenced by factors that are not directly related to psychosis and may confound the interpretation of case-control differences. Therefore, a detailed characterization of the contribution of these factors to neuroimaging phenotypes in psychosis is warranted.

OBJECTIVE

To quantify the association between neuroimaging measures and behavioral, health, and demographic variables in psychosis using an integrated multivariate approach.

DESIGN, SETTING, AND PARTICIPANTS

This imaging study was conducted at a university research hospital from June 26, 2014, to March 9, 2017. High-resolution multimodal magnetic resonance imaging data were obtained from 100 patients with schizophrenia, 40 patients with bipolar disorder, and 50 healthy volunteers; computed were cortical thickness, subcortical volumes, white matter fractional anisotropy, task-related brain activation (during working memory and emotional recognition), and resting-state functional connectivity. Ascertained in all participants were nonimaging measures pertaining to clinical features, cognition, substance use, psychological trauma, physical activity, and body mass index. The association between imaging and nonimaging measures was modeled using sparse canonical correlation analysis with robust reliability testing.

MAIN OUTCOMES AND MEASURES

Multivariate patterns of the association between nonimaging and neuroimaging measures in patients with psychosis and healthy volunteers.

RESULTS

The analyses were performed in 92 patients with schizophrenia (23 female [25.0%]; mean [SD] age, 27.0 [7.6] years), 37 patients with bipolar disorder (12 female [32.4%]; mean [SD] age, 27.5 [8.1] years), and 48 healthy volunteers (20 female [41.7%]; mean [SD] age, 29.8 [8.5] years). The imaging and nonimaging data sets showed significant covariation (r = 0.63, P < .001), which was independent of diagnosis. Among the nonimaging variables examined, age (r = -0.53), IQ (r = 0.36), and body mass index (r = -0.25) were associated with multiple imaging phenotypes; cannabis use (r = 0.23) and other substance use (r = 0.33) were associated with subcortical volumes, and alcohol use was associated with white matter integrity (r = -0.15). Within the multivariate models, positive symptoms retained associations with the global neuroimaging (r = -0.13), the cortical thickness (r = -0.22), and the task-related activation variates (r = -0.18); negative symptoms were mostly associated with measures of subcortical volume (r = 0.23), and depression/anxiety was associated with measures of white matter integrity (r = 0.12).

CONCLUSIONS AND RELEVANCE

Multivariate analyses provide a more accurate characterization of the association between brain alterations and psychosis because they enable the modeling of other key factors that influence neuroimaging phenotypes.

Validating dimensions of psychosis symptomatology: Neural correlates and 20-year outcomes

Heterogeneity of psychosis presents significant challenges for classification. Between 2 and 12 symptom dimensions have been proposed, and consensus is lacking. The present study sought to identify uniquely informative models by comparing the validity of these alternatives. An epidemiologic cohort of 628 first-admission inpatients with psychosis was interviewed 6 times over 2 decades and completed an electrophysiological assessment of error processing at year 20. We first analyzed a comprehensive set of 49 symptoms rated by interviewers at baseline, progressively extracting from 1 to 12 factors. Next, we compared the ability of resulting factor solutions to (a) account for concurrent neural dysfunction and (b) predict 20-year role, social, residential, and global functioning, and life satisfaction. A four-factor model showed incremental validity with all outcomes, and more complex models did not improve explanatory power. The 4 dimensions-reality distortion, disorganization, inexpressivity, and apathy/asociality-were replicable in 5 follow-ups, internally consistent, stable across assessments, and showed strong discriminant validity. These results reaffirm the value of separating disorganization and reality distortion, are consistent with recent findings distinguishing inexpressivity and apathy/asociality, and suggest that these 4 dimensions are fundamental to understanding neural abnormalities and long-term outcomes in psychosis. (PsycINFO Database Record

Imaging Habenula Volume in Schizophrenia and Bipolar Disorder

The habenula (Hb), a bilateral nucleus located next to the dorsomedial thalamus, is of particular relevance to psychiatric disorders based on preclinical evidence linking the Hb to depressive and amotivational states. However, studies in clinical samples are scant because segmentation of the Hb in neuroimaging data is challenging due to its small size and low contrast from the surrounding tissues. Negative affective states dominate the clinical course of schizophrenia and bipolar disorder and represent a major cause of disability. Diagnosis-related alterations in the volume of Hb in these disorders have therefore been hypothesized but remain largely untested. To probe this question, we used a recently developed objective and reliable semi-automated Hb segmentation method based on myelin-sensitive magnetic resonance imaging (MRI) data. We ascertained case-control differences in Hb volume from high resolution structural MRI data obtained from patients with schizophrenia (n = 95), bipolar disorder (n = 44) and demographically matched healthy individuals (n = 52). Following strict quality control of the MRI data, the final sample comprised 68 patients with schizophrenia, 32 with bipolar disorder and 40 healthy individuals. Regardless of diagnosis, age, sex, and IQ were not correlated with Hb volume. This was also the case for age of illness onset and medication (i.e., antipsychotic dose and lithium-treatment status). Case-control differences in Hb volume did not reach statistical significance; their effect size (Cohen's d) was negligible on the left (schizophrenia: 0.14; bipolar disorder: -0.03) and small on the right (schizophrenia: 0.34; bipolar disorder: 0.26). Nevertheless, variability in the volume of the right Hb was associated with suicidality in the entire patient sample (ρ = 0.29, p = 0.004) as well as in each patient group (bipolar disorder: ρ = 0.34, p = 0.04; schizophrenia: ρ = 0.25, p = 0.04). These findings warrant replication in larger samples and longitudinal designs and encourage more comprehensive characterization of Hb connectivity and function in clinical populations.

The slow death of the concept of schizophrenia and the painful birth of the psychosis spectrum

The concept of schizophrenia only covers the 30% poor outcome fraction of a much broader multidimensional psychotic syndrome, yet paradoxically has become the dominant prism through which everything 'psychotic' is observed, even affective states with mild psychosis labelled 'ultra-high risk' (for schizophrenia). The inability of psychiatry to frame psychosis as multidimensional syndromal variation of largely unpredictable course and outcome - within and between individuals - hampers research and recovery-oriented practice. 'Psychosis' remains firmly associated with 'schizophrenia', as evidenced by a vigorous stream of high-impact but non-replicable attempts to 'reverse-engineer' the hypothesized biological disease entity, using case-control paradigms that cannot distinguish between risk for illness onset and risk for poor outcome. In this paper, the main issues surrounding the concept of schizophrenia are described. We tentatively conclude that with the advent of broad spectrum phenotypes covering autism and addiction in DSM5, the prospect for introducing a psychosis spectrum disorder - and modernizing psychiatry - appears to be within reach.

Retrospective study of first episode psychosis in the Dublin Southwest Mental Health Service: demographics, clinical profile and service evaluation of treatment

OBJECTIVE

In Ireland, National Clinical Programmes are being established to improve and standardise patient care throughout the Health Service Executive. In line with internationally recognised guidelines on the treatment of first episode psychosis the Early Intervention in Psychosis (EIP) programme is being drafted with a view to implementation by mental health services across the country. We undertook a review of patients presenting with a first episode of psychosis to the Dublin Southwest Mental Health Service before the implementation of the EIP. This baseline information will be used to measure the efficacy of our EIP programme.

METHODS

Patients who presented with a first episode psychosis were retrospectively identified through case note reviews and consultation with treating teams. We gathered demographic and clinical information from patients as well as data on treatment provision over a 2-year period from the time of first presentation. Data included age at first presentation, duration of untreated psychosis, diagnosis, referral source, antipsychotic prescribing rates and dosing, rates of provision of psychological interventions and standards of physical healthcare monitoring. Outcome measures with regards to rates of admission over a 2-year period following initial presentation were also recorded.

RESULTS

In total, 66 cases were identified. The majority were male, single, unemployed and living with their family or spouse. The mean age at first presentation was 31 years with a mean duration of untreated psychosis of 17 months. Just under one-third were diagnosed with schizophrenia. Approximately half of the patients had no contact with a health service before presentation. The majority of patients presented through the emergency department. Two-thirds of all patients had a hospital admission within 2 years of presentation and almost one quarter of patients had an involuntary admission. The majority of patients were prescribed antipsychotic doses within recommended British National Formulary guidelines. Most patients received individual support through their keyworker and family intervention was provided in the majority of cases. Only a small number received formal Cognitive-Behavioural Therapy. Physical healthcare monitoring was insufficiently recorded in the majority of patients.

CONCLUSIONS

There is a shortage of information on the profile and treatment of patients presenting with a first episode of psychosis in Ireland. This baseline information is important in evaluating the efficacy of any new programme for this patient group. Many aspects of good practice were identified within the service in particular with regards to the appropriate prescribing of antipsychotic medication and the rates of family intervention. Deficiencies remain however in the monitoring of physical health and the provision of formal psychological interventions to patients. With the implementation of an EIP programme it is hoped that service provision would improve nationwide and to internationally recognised standards.

Auditory verbal hallucinations and continuum models of psychosis: A systematic review of the healthy voice-hearer literature

Recent decades have seen a surge of research interest in the phenomenon of healthy individuals who experience auditory verbal hallucinations, yet do not exhibit distress or need for care. The aims of the present systematic review are to provide a comprehensive overview of this research and examine how healthy voice-hearers may best be conceptualised in relation to the diagnostic versus ‘quasi-‘ and ‘fully-dimensional’ continuum models of psychosis. A systematic literature search was conducted, resulting in a total of 398 article titles and abstracts that were scrutinised for appropriateness to the present objective. Seventy articles were identified for full-text analysis, of which 36 met criteria for inclusion. Subjective perceptual experience of voices, such as loudness or location (i.e., inside/outside head), is similar in clinical and non-clinical groups, although clinical voice-hearers have more frequent voices, more negative voice content, and an older age of onset. Groups differ significantly in beliefs about voices, control over voices, voice-related distress, and affective difficulties. Cognitive biases, reduced global functioning, and psychiatric symptoms such as delusions, appear more prevalent in healthy voice-hearers than in healthy controls, yet less than in clinical samples. Transition to mental health difficulties is increased in HVHs, yet only occurs in a minority and is predicted by previous mood problems and voice distress. Whilst healthy voice-hearers show similar brain activity during hallucinatory experiences to clinical voice-hearers, other neuroimaging measures, such as mismatch negativity, have been inconclusive. Risk factors such as familial and childhood trauma appear similar between clinical and non-clinical voice-hearers. Overall the results of the present systematic review support a continuum view rather than a diagnostic model, but cannot distinguish between ‘quasi’ and ‘fully’ dimensional models. Healthy voice-hearers may be a key resource in informing transdiagnostic approaches to research of auditory hallucinations.

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Subjective perceptual experiences of voices appear similar in clinical and non-clinical groups.

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Healthy voice-hearers hear voices less frequently, with less negative content, more perceived control and from an earlier age.

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Healthy and clinical voice-hearers differ in beliefs about voices, voice-related distress, and affective difficulties.

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Healthy voice-hearers show more cognitive biases, psychiatric symptoms and functional impairments than healthy controls.

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Risk factors such as familial and childhood trauma appear similar between clinical and non-clinical voice-hearers.

Evaluation of the validity and utility of a transdiagnostic psychosis dimension encompassing schizophrenia and bipolar disorder

BACKGROUND

In recent years, the Kraepelinian dichotomy has been challenged in light of evidence on shared genetic and environmental factors for schizophrenia and bipolar disorder, but empirical efforts to identify a transdiagnostic phenotype of psychosis remain remarkably limited.

AIMS

To investigate whether schizophrenia spectrum and bipolar disorder lie on a transdiagnostic spectrum with overlapping non-affective and affective psychotic symptoms.

METHOD

Multidimensional item-response modelling was conducted on symptom ratings of the OPerational CRITeria (OPCRIT) system in 1168 patients with schizophrenia spectrum and bipolar disorder.

RESULTS

A bifactor model with one general, transdiagnostic psychosis dimension underlying affective and non-affective psychotic symptoms and five specific dimensions of positive, negative, disorganised, manic and depressive symptoms provided the best model fit and diagnostic utility for categorical classification.

CONCLUSIONS

Our findings provide support for including dimensional approaches into classification systems and a directly measurable clinical phenotype for cross-disorder investigations into shared genetic and environmental factors of psychosis.

Dimensional approaches to schizophrenia: A comparison of the Bern Psychopathology scale and the five-factor model of the Positive and Negative Syndrome Scale

The aim was to examine to what extent the dimensions of the BPS map the five factors derived from the PANSS in order to explore the level of agreement of these alternative dimensional approaches in patients with schizophrenia. 149 inpatients with schizophrenia spectrum disorders were recruited. Psychopathological symptoms were assessed with the Bern Psychopathology Scale (BPS) and the Positive and Negative Syndrome Scale (PANSS). Linear regression analyses were conducted to explore the association between the factors and the items of the BPS. The robustness of patterns was evaluated. An understandable overlap of both approaches was found for positive and negative symptoms and excitement. The PANSS positive factor was associated with symptoms of the affect domain in terms of both inhibition and disinhibition, the PANSS negative factor with symptoms of all three domains of the BPS as an inhibition and the PANSS excitement factor with an inhibition of the affect domain and a disinhibition of the language and motor domains. The results show that here is only a partial overlap between the system-specific approach of the BPS and the five-factor PANSS model. A longitudinal assessment of psychopathological symptoms would therefore be of interest.

A virtue analysis of recreational marijuana use

Several empirical studies suggest that recreational marijuana is popularly perceived as an essentially harmless rite of passage that ends as young people settle into their careers and their adult intimate relationships. Is this perception accurate? To answer this question, we evaluate the morality of recreational marijuana use from a virtue perspective guided by the theological synthesis of St. Thomas Aquinas. Since the medical data reveals that recreational marijuana use is detrimental to the well-being of the user, we conclude that it is a vicious activity, an instance of the vice of intoxication, and as such would be morally illicit.

LAY SUMMARY

In contrast to its medical use, the recreational use of marijuana cannot be justified for at least three reasons. First, as scientists have amply documented, it harms the organic functioning of the human body. Second, it impedes our ability to reason and in so doing does harm to us. Finally, it has lasting detrimental effects on the user and his neighbor, even when it occurs in a casual setting. Intoxication is always contrary to the integral good of the person. Thus, the use of marijuana is never warranted even for good, non-medical reasons.

Focus on psychosis

The concept of psychosis has been shaped by traditions in the concepts of mental disorders during the last 170 years. The term "psychosis" still lacks a unified definition, but denotes a clinical construct composed of several symptoms. Delusions, hallucinations, and thought disorders are the core clinical features. The search for a common denominator of psychotic symptoms points toward combinations of neuropsychological mechanisms resulting in reality distortion. To advance the elucidation of the causes and the pathophysiology of the symptoms of psychosis, a deconstruction of the term into its component symptoms is therefore warranted. Current research is dealing with the delineation from "normality", the genetic underpinnings, and the causes and pathophysiology of the symptoms of psychosis.

Individualized covariance profile of cortical morphology for auditory hallucinations in first-episode psychosis

Neocortical phenotype of cortical surface area (CSA) and thickness (CT) are influenced by distinctive genetic factors and undergo differential developmental trajectories, which could be captured using the individualized cortical structural covariance (ISC). Disturbed patterns of neocortical development and maturation underlie the perceptual disturbance of psychosis including auditory hallucination (AH). To demonstrate the utility of selected ISC features as primal biomarker of AH in first-episode psychosis (FEP) subjects experiencing AH (FEP-AH), we employed herein a support vector machine (SVM). A total of 147 subjects (FEP-AH, n = 27; FEP-NAH, n = 24; HC, n = 96) underwent T1 -weighted magnetic resonance imaging at 3T. The FreeSurfer software suite was used for cortical parcellation, with the CSA-ISC and CT-ISC then calculated. The most informative ISCs showing statistical significance (P < 0.001) across every run of leave-one-out group-comparison were aligned according to the absolute value of averaged t-statistics and were packaged into candidate feature sets for classification analysis using the SVM. An optimal feature set comprising three CSA-ISCs, including the intraparietal sulcus, Broca's complex, and the anterior insula, distinguished FEP-AH from FEP-NAH subjects with 83.6% accuracy (sensitivity = 82.8%; specificity = 85.7%). Furthermore, six CT-ISCs encompassing the executive control network and Wernicke's module classified FEP-AH from FEP-NAH subjects with 82.3% accuracy (sensitivity = 79.5%; specificity = 88.6%). Finally, extended sets of ISCs related to the default-mode network distinguished FEP-AH or FEP-NAH from HC subjects with 89.0-93.0% accuracy (sensitivity = 88.4-93.4%; specificity = 89.0-94.1%). This study established a distinctive intermediate phenotype of biological proneness for AH in FEP using CSA-ISCs as well as a state marker of disease progression using CT-ISCs.

A dimensional comparison between delusional disorder, schizophrenia and schizoaffective disorder

INTRODUCTION

Since the early description of paranoia, the nosology of delusional disorder has always been controversial. The old idea of unitary psychosis has now gained some renewed value from the dimensional continuum model of psychotic symptoms.

AIMS

1. To study the psychopathological dimensions of the psychosis spectrum; 2. to explore the association between psychotic dimensions and categorical diagnoses; 3. to compare the different psychotic disorders from a psychopathological and functional point of view.

MATERIAL AND METHODS

This is an observational study utilizing a sample of some 550 patients with a psychotic disorder. 373 participants had a diagnosis of schizophrenia, 137 had delusional disorder and 40 with a diagnosis of schizoaffective disorder. The PANSS was used to elicit psychopathology and global functioning was ascertained using the GAF measure. Both exploratory and confirmatory factor analyses of the PANSS items were performed to extract psychopathological dimensions. Associations between diagnostic categories and dimensions were subsequently studied using ANOVA tests.

RESULTS

5 dimensions - manic, negative symptoms, depression, positive symptoms and cognitive - emerged. The model explained 57.27% of the total variance. The dimensional model was useful to explained differences and similarities between all three psychosis spectrum categories. The potential clinical usefulness of this dimensional model within and between clinical psychosis spectrum categories is discussed.

A Danish Twin Study of Schizophrenia Liability: Investigation from Interviewed Twins for Genetic Links to Affective Psychoses and for Cross-Cohort Comparisons

We studied schizophrenia liability in a Danish population-based sample of 44 twin pairs (13 MZ, 31 DZ, SS plus OS) in order to replicate previous twin study findings using contemporary diagnostic criteria, to examine genetic liability shared between schizophrenia and other disorders, and to explore whether variance in schizophrenia liability attributable to environmental factors may have decreased with successive cohorts exposed to improvements in public health. ICD-10 diagnoses were determined by clinical interview. Although the best-fitting, most parsimonious biometric model of schizophrenia liability specified variance attributable to additive genetic and non-shared environmental factors, this model did not differ significantly from a model that also included non-additive genetic factors, consistent with recent interview-based twin studies. Schizophrenia showed strong genetic links to other psychotic disorders but much less so for the broader category of psychiatric disorders in general. We also observed a marginally significant decline in schizophrenia variance attributable to environmental factors over successive Western European cohorts, consistent perhaps with improvements in diagnosis and in prenatal and perinatal care and with a secular decline in the prevalence of schizophrenia in that region.

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

BACKGROUND

Persistent formal thought disorder (FTD) is one of the most characteristic features of schizophrenia. Several neuroimaging studies report spatially distinct neuroanatomical changes in association with FTD. Given that most studies so far have employed a univariate localisation approach that obscures the study of covarying interregional relationships, the present study focussed on the multivariate systemic pattern of anatomical changes that contribute to FTD.

METHODS

Speech samples from nineteen medicated clinically stable schizophrenia patients and 20 healthy controls were evaluated for subtle formal thought disorder. Ultra high-field (7T) anatomical Magnetic Resonance Imaging scans were obtained from all subjects. Multivariate morphometric patterns were identified using an independent component approach (source based morphometry). Using multiple regression analysis, the morphometric patterns predicting positive and negative FTD scores were identified.

RESULTS

Morphometric variations in grey matter predicted a substantial portion of inter-individual variance in negative but not positive FTD. A pattern of concomitant striato-insular/precuneus reduction along with frontocingular grey matter increase had a significant association with negative FTD.

CONCLUSIONS

These results suggest that concomitant increase and decrease in grey matter occur in association with persistent negative thought disorder in clinically stable individuals with schizophrenia.

Neurosis Meets Psychosis: Case Series from a Tertiary Care Center in South India

The utility of the terms psychosis and neurosis in psychiatry have maintained their dichotomous stance since ages. Clinical observations and etiological hypothesis of psychiatric disorders have kept this polarity intact since the times of Freud and Jung. This case series attempts to revisit this perennial psychiatric controversy.

Metacognitive training for delusions (MCTd): effectiveness on data-gathering and belief flexibility in a Chinese sample

Metacognitive training (MCT) was developed to promote awareness of reasoning biases among patients with schizophrenia. While MCT has been translated into 31 languages, most MCT studies were conducted in Europe, including newer evidence recommending an individualized approach of delivery. As reasoning biases covered in MCT are separable processes and are associated with different symptoms, testing the effect of selected MCT modules would help to develop a targeted and cost-effective intervention for specific symptoms and associated mechanisms. This study tested the efficacy of a four-session metacognitive training for delusions, MCTd (in Traditional Chinese with cultural adaptations, provided individually), as an adjunct to antipsychotics in reducing severity and conviction of delusions, jumping to conclusions (JTC) bias and belief inflexibility. Forty-four patients with delusions were randomized into the MCTd or the wait-list control condition. Patients on wait-list received the same MCTd after 4 weeks of treatment as usual (TAU). Assessment interviews took place before and after the treatment, and at 4-week follow-up. There was an additional baseline assessment for the controls. JTC and belief flexibility were measured by the beads tasks and the Maudsley Assessment of Delusions Scale. Attendance rate of the MCTd was satisfactory (84.5%). Compared to TAU, there was a greater reduction in psychotic symptoms, delusional severity and conviction following MCTd. There was a large treatment effect size in improvement in belief flexibility. Improvement in reaction to hypothetical contradiction predicted treatment effect in positive symptoms and delusions. JTC bias was reduced following MCTd, although the treatment effect was not significantly larger than TAU. Our results support the use of process-based interventions that target psychological mechanisms underlying specific psychotic symptoms as adjuncts to more conventional approaches.

The independence of schizotypy from affective temperaments--a combined confirmatory factor analysis of SPQ and the short TEMPS-A

Sparse evidence of a co-aggregation of the risk of schizophrenia and bipolar disorder provides support for a shared but nonspecific genetic etiology of bipolar disorder and schizophrenia. Temperaments are conceptualized as trait sub-syndromic conditions of major pathologies. This study set out to test the hypothesis of a continuum between schizotypy and affective temperaments versus the alternative hypothesis of their independence based on a cross-sectional, survey design involving 649 (males: 47%) college students. The short 39-item TEMPS-A and the SPQ were used as measures of the affective temperaments and of schizotypy, respectively. Confirmatory factor analyses were applied to a unidimensional model, to a standard correlate traits model, to second-order representations of a common latent structure, and to a bifactor model. Confirmatory bifactor modeling provided evidence against a complete independence of the dimensions subsumed by the affective and the schizotypal traits. The best solution distinguished between two sub-domains grouping positive symptoms and negative symptoms as measured by the SPQ subscales, and a sub-domain related to the affective temperaments as measured by the TEMPS-A. Limitations due to the use of subscales from two different tools should be taken into account.

A cross-national factor analytic comparison of three models of PANSS symptoms in schizophrenia

The 30-item Positive and Negative Syndrome Scale (PANSS) is used worldwide in the assessment of symptom severity in schizophrenia. The present study uses confirmatory factor analysis (CFA) to compare three different factorial models and to evaluate the best-fitting representation of schizophrenia symptom structure on the PANSS across four samples of patients diagnosed with schizophrenia from the US (the CATIE schizophrenia trial), São Paulo, Brazil, and from Beijing and Changsha, China. We examine the goodness of fit of several previously proposed models. The traditional trifactorial model for the PANSS and two five-factor models were evaluated using absolute and incremental indices. Single group CFA found that the five-factor model proposed by NIMH researchers based on an extensive literature review demonstrates the best fit in each of the four samples. This model used 20 of the 30 PANSS items grouped into five factors: positive, negative, disorganized, excited, and depressed symptoms. Subgroups defined by age, gender, nationality, hospitalization status, and severity of illness also did not differ in overall symptom structure as assessed by several standard indices. Our findings suggest that the five factor NIMH model showed the best representation among all four samples from different countries and potentially contrasting cultures.