Neuropsychological and neuroimaging underpinnings of schizoaffective disorder: a systematic review

Shared and distinct white matter abnormalities in adolescent-onset schizophrenia and adolescent-onset psychotic bipolar disorder

BACKGROUND

While adolescent-onset schizophrenia (ADO-SCZ) and adolescent-onset bipolar disorder with psychosis (psychotic ADO-BPD) present a more severe clinical course than their adult forms, their pathophysiology is poorly understood. Here, we study potentially state- and trait-related white matter diffusion-weighted magnetic resonance imaging (dMRI) abnormalities along the adolescent-onset psychosis continuum to address this need.

METHODS

Forty-eight individuals with ADO-SCZ (20 female/28 male), 15 individuals with psychotic ADO-BPD (7 female/8 male), and 35 healthy controls (HCs, 18 female/17 male) underwent dMRI and clinical assessments. Maps of extracellular free-water (FW) and fractional anisotropy of cellular tissue (FAT) were compared between individuals with psychosis and HCs using tract-based spatial statistics and FSL's Randomise. FAT and FW values were extracted, averaged across all voxels that demonstrated group differences, and then utilized to test for the influence of age, medication, age of onset, duration of illness, symptom severity, and intelligence.

RESULTS

Individuals with adolescent-onset psychosis exhibited pronounced FW and FAT abnormalities compared to HCs. FAT reductions were spatially more widespread in ADO-SCZ. FW increases, however, were only present in psychotic ADO-BPD. In HCs, but not in individuals with adolescent-onset psychosis, FAT was positively related to age.

CONCLUSIONS

We observe evidence for cellular (FAT) and extracellular (FW) white matter abnormalities in adolescent-onset psychosis. Although cellular white matter abnormalities were more prominent in ADO-SCZ, such alterations may reflect a shared trait, i.e. neurodevelopmental pathology, present across the psychosis spectrum. Extracellular abnormalities were evident in psychotic ADO-BPD, potentially indicating a more dynamic, state-dependent brain reaction to psychosis.

Transdiagnostic structural neuroimaging features in depression and psychosis: A systematic review

BACKGROUND

Previous research suggests that there may be similarities in structural brain changes seen in patients with depression and psychosis compared to healthy controls. However, there is yet no systematic review collating studies comparing structural brain changes in depression and psychosis. Establishing shared and specific neuroanatomical features could aid the investigation of underlying biological processes.

AIMS

To identify structural neuroimaging similarities and differences between patients with depression and psychosis.

METHOD

We searched PubMed, PsychInfo, Embase, NICE Evidence, Medline and the Cochrane Library were searched from inception to 30/06/2021 using relevant subject headings (controlled vocabularies) and search syntax. Papers were assessed for quality using the Newcastle-Ottawa Scale.

RESULTS

Five-hundred and twenty papers were retrieved, seven met inclusion criteria. In narrative collation of results, grey matter volume (GMV) reductions were found in the medial frontal gyrus (MFG), hippocampus and left-sided posterior subgenual prefrontal cortex in both psychosis and depression. GMV reductions affected more brain regions in psychosis, including in the insula and thalamus. White matter volume (WMV) decline was found in both depression and psychosis. Reduced fractional anisotropy (FA) was more commonly seen in depression.

CONCLUSIONS

Our results suggest potential transdiagnostic patterns of GMV and WMV reductions in areas including the MFG, hippocampus, and left-sided posterior subgenual prefrontal cortex. These could be investigated as a future biomarker of transdiagnostic signature across mental illnesses. However, due to the limited number and poor quality of studies future research in large samples and harmonised imaging data is first needed.

Dry mouth effects from drugs used for depression, anxiety, schizophrenia and bipolar mood disorder in adults: systematic review

BACKGROUND

Poor oral health is increasingly recognised as an important comorbidity in people with psychiatric illness. One risk factor is psychotropic-induced dry mouth.

AIMS

To perform a systematic review of the severity of dry mouth due to psychotropic drugs in adults (CRD42021239725). Study quality was assessed using the Cochrane risk of bias tool.

METHOD

We searched the following databases: PubMed, EMBASE, PsycINFO, Cochrane Central Register of Controlled Trials, CINAHL and Web of Science. We included randomised controlled trials (RCTs) measuring the severity of drug-induced hyposalivation and xerostomia.

RESULTS

Eighteen RCTs with 605 participants were included. Severity of drug-induced dry mouth was compared among eight drug classes and/or against placebo. All studies were published 20 to 40 years ago and included tricyclic antidepressants (TCAs), serotonin specific reuptake inhibitors (SSRIs) and other drug classes. Meta-analysis was not feasible owing to design heterogeneity. TCAs caused more severe dry mouth, both objectively and subjectively, than placebo or other drug classes. SSRIs were generally associated with less severe symptoms. However, there was no information on antipsychotics or more recently available antidepressants, and there was minimal information on mood stabilisers. Most studies were on healthy subjects, limiting the generalisability of findings. Only one study measured both objective and subjective dry mouth, which have different clinical implications.

CONCLUSIONS

Psychotropic-induced dry mouth is a poorly researched area, and well-designed RCTs of newer psychotropic drugs using standardised objective and subjective measures are indicated. Given the ongoing use of TCAs for treatment-resistant depression, prescribers need to remain vigilant for xerostomia.

A meta-analysis comparing cognitive function across the mood/psychosis diagnostic spectrum

BACKGROUND

The nature and degree of cognitive impairments in schizoaffective disorder is not well established. The aim of this meta-analysis was to characterise cognitive functioning in schizoaffective disorder and compare it with cognition in schizophrenia and bipolar disorder. Schizoaffective disorder was considered both as a single category and as its two diagnostic subtypes, bipolar and depressive disorder.

METHODS

Following a thorough literature search (468 records identified), we included 31 studies with a total of 1685 participants with schizoaffective disorder, 3357 with schizophrenia and 1095 with bipolar disorder. Meta-analyses were conducted for seven cognitive variables comparing performance between participants with schizoaffective disorder and schizophrenia, and between schizoaffective disorder and bipolar disorder.

RESULTS

Participants with schizoaffective disorder performed worse than those with bipolar disorder (g = -0.30) and better than those with schizophrenia (g = 0.17). Meta-analyses of the subtypes of schizoaffective disorder showed cognitive impairments in participants with the depressive subtype are closer in severity to those seen in participants with schizophrenia (g = 0.08), whereas those with the bipolar subtype were more impaired than those with bipolar disorder (g = -0.23) and less impaired than those with schizophrenia (g = 0.29). Participants with the depressive subtype had worse performance than those with the bipolar subtype but this was not significant (g = 0.25, p = 0.05).

CONCLUSION

Cognitive impairments increase in severity from bipolar disorder to schizoaffective disorder to schizophrenia. Differences between the subtypes of schizoaffective disorder suggest combining the subtypes of schizoaffective disorder may obscure a study's results and hamper efforts to understand the relationship between this disorder and schizophrenia or bipolar disorder.

Searching for Imaging Biomarkers of Psychotic Dysconnectivity

BACKGROUND

Progress in precision psychiatry is predicated on identifying reliable individual-level diagnostic biomarkers. For psychosis, measures of structural and functional connectivity could be promising biomarkers given consistent reports of dysconnectivity across psychotic disorders using magnetic resonance imaging.

METHODS

We leveraged data from four independent cohorts of patients with psychosis and control subjects with observations from approximately 800 individuals. We used group-level analyses and two supervised machine learning algorithms (support vector machines and ridge regression) to test within-, between-, and across-sample classification performance of white matter and resting-state connectivity metrics.

RESULTS

Although we replicated group-level differences in brain connectivity, individual-level classification was suboptimal. Classification performance within samples was variable across folds (highest area under the curve [AUC] range = 0.30) and across datasets (average support vector machine AUC range = 0.50; average ridge regression AUC range = 0.18). Classification performance between samples was similarly variable or resulted in AUC values of approximately 0.65, indicating a lack of model generalizability. Furthermore, collapsing across samples (resting-state functional magnetic resonance imaging, N = 888; diffusion tensor imaging, N = 860) did not improve model performance (maximal AUC = 0.67). Ridge regression models generally outperformed support vector machine models, although classification performance was still suboptimal in terms of clinical relevance. Adjusting for demographic covariates did not greatly affect results.

CONCLUSIONS

Connectivity measures were not suitable as diagnostic biomarkers for psychosis as assessed in this study. Our results do not negate that other approaches may be more successful, although it is clear that a systematic approach to individual-level classification with large independent validation samples is necessary to properly vet neuroimaging features as diagnostic biomarkers.

Resolving heterogeneity in schizophrenia through a novel systems approach to brain structure: individualized structural covariance network analysis

Reliable mapping of system-level individual differences is a critical first step toward precision medicine for complex disorders such as schizophrenia. Disrupted structural covariance indicates a system-level brain maturational disruption in schizophrenia. However, most studies examine structural covariance at the group level. This prevents subject-level inferences. Here, we introduce a Network Template Perturbation approach to construct individual differential structural covariance network (IDSCN) using regional gray-matter volume. IDSCN quantifies how structural covariance between two nodes in a patient deviates from the normative covariance in healthy subjects. We analyzed T1 images from 1287 subjects, including 107 first-episode (drug-naive) patients and 71 controls in the discovery datasets and established robustness in 213 first-episode (drug-naive), 294 chronic, 99 clinical high-risk patients, and 494 controls from the replication datasets. Patients with schizophrenia were highly variable in their altered structural covariance edges; the number of altered edges was related to severity of hallucinations. Despite this variability, a subset of covariance edges, including the left hippocampus-bilateral putamen/globus pallidus edges, clustered patients into two distinct subgroups with opposing changes in covariance compared to controls, and significant differences in their anxiety and depression scores. These subgroup differences were stable across all seven datasets with meaningful genetic associations and functional annotation for the affected edges. We conclude that the underlying physiology of affective symptoms in schizophrenia involves the hippocampus and putamen/pallidum, predates disease onset, and is sufficiently consistent to resolve morphological heterogeneity throughout the illness course. The two schizophrenia subgroups identified thus have implications for the nosology and clinical treatment.

Neurocognition in Bipolar and Depressive Schizoaffective Disorder: A Comparison with Schizophrenia

INTRODUCTION

Schizoaffective disorder (SA) is classified into bipolar (bSA) and depressive (dSA) subtypes. Although clinical differences between both have been reported, there is no clear information regarding their specific cognitive profile.

OBJECTIVE

To compare neurocognition between SA subtypes and schizophrenia (SC).

METHODS

A total of 61 patients were assessed and divided into 3 groups: 35 SC, 16 bSA, and 10 dSA. All participants signed an informed consent letter. The MATRICS Consensus Cognitive Battery, Central and South American version was used to assess neurocognition. The study was performed at the Instituto Nacional de Psiquiatría "Ramón de la Fuente". Participants were identified by specialized psychiatrists. Trained neuropsychologists carried out the clinical and cognitive assessment, which lasted 2 h approximately.

RESULTS

The cognitive assessment showed a significant difference in Trail Making Test part A subtest (F[2,58] = 4.043; p = 0.023]. Post hoc analyses indicated that dSA obtained a significantly higher score than SC (MD = -11.523; p = 0.018). The f test showed a large effect size (f = 0.401). No statistical differences were observed regarding other cognitive variables.

CONCLUSIONS

The cognitive profile of SA subtypes and SC is similar since no differences were found in most subtests. However, dSA may be less impaired than SC in measures of processing speed. Further research with larger samples must be conducted.

Network analysis of cognitive deficit in patients with schizophrenia spectrum disorders

Background

Cognitive impairments are found in 80% of patients with schizophrenia. The severity of these impairments significantly affects the recovery of patients in terms of social functioning.

Network analysis is the most suitable approach for studying complex relationships among cognitive functions.

Aim

To build a network model of neurocognitive functions for identifying both the severity of impairments in individual functions and the vertices central to the whole model.

Methods

The study included 115 patients with schizophrenia and schizophrenia spectrum disorders and a comparison group, comprising 99 healthy subjects. The severity of clinical symptoms was assessed using the PANSS, CDSS and YMRS, and the SAS and BARS for extrapyramidal symptoms and akathisia. Subjects from the comparison group completed screening questionnaires QIDS-SR and PQ-16. Neurocognitive functions were assessed using the BACS.

Results

The patients performed worse than the healthy subjects on all tests. In the cognitive network models of healthy subjects, fewer connections were revealed and the central place was occupied by working memory, the functioning of which depends upon everyday functioning in the community. In the cognitive models of patients there was a greater connectedness of neurocognitive functions. Furthermore, the central place of the networks in patients is occupied by the processing speed, evaluated primarily using the Symbol Coding test, which reflects the dependence of patient activity on lower-order functions.

Conclusion

The processing speed deficit is key to schizophrenia and it may be considered a potential endophenotype of the disease.

Analysis of the superior temporal gyrus as a possible biomarker in schizophrenia using voxel-based morphometry of the brain magnetic resonance imaging: a comprehensive review

The lack of predictive biomarkers for therapeutic responses to schizophrenia leads clinical procedures to be decided without taking into account the subjects' neuroanatomical features, a consideration, which could help in identifying specific pharmacological treatments for the remission of symptoms. Magnetic resonance imaging (MRI) is a technique widely used for radiological diagnosis and produces 3-dimensional images in excellent anatomical detail, and with a great capacity to differentiate soft tissue. Various MRI techniques of the human brain have emerged as a result of research, enabling structural tests that may help to in consolidate previous findings and lead to the discovery of new patterns of abnormality in schizophrenia. A literature review was undertaken to assess the superior temporal gyrus (STG) as a possible biomarker in schizophrenia with the use of voxel-based morphometry of the brain using MRI. Many findings in studies of schizophrenia using MRI have been inconclusive and, in some cases, conflicting, although interesting results have been obtained when attempting to correlate neuroimaging changes with aspects of clinical features and prognosis of the disease. The individuals affected by this mental illness appear to have smaller STG volumes when compared to healthy controls and also to subjects with a diagnosis of first-episode affective psychosis or groups of individuals at high risk of psychosis. However, the wide variety of definitions surrounding the STG found in a number of studies is a contributing factor to the lack of correlation between brain abnormalities and clinical symptoms. For instance, disagreements have arisen due to studies using regions of interest to analyze the STG whereas other studies prioritize the analysis of only STG subregions or specific supratemporal plane regions. It is necessary to standardize the nomenclature of the areas to be studied in the future, as this will enable more consistent results, allowing higher clinical and morphological correlations.

Paliperidone to Treat Psychotic Disorders

PURPOSE OF REVIEW

This is a comprehensive review of the literature regarding the use of paliperidone in the treatment of schizophrenia and schizoaffective disorder. It covers the background and presentation of schizophrenia and schizoaffective disorder, as well as the mechanism of action and drug information for paliperidone. It covers the existing evidence of the use of paliperidone for the treatment of schizophrenia and schizoaffective disorder.

RECENT FINDINGS

Schizophrenia and schizoaffective disorder lead to significant cognitive impairment. It is thought that dopamine dysregulation is the culprit for the positive symptoms of schizophrenia and schizoaffective disorder. Similar to other second-generation antipsychotics, paliperidone has affinity for dopamine D₂ and serotonin 5-HT_2A receptors. Paliperidone was granted approval in the United States in 2006 to be used in the treatment of schizophrenia and in 2009 for schizoaffective disorder.

SUMMARY

Schizophrenia and schizoaffective disorder have a large impact on cognitive impairment, positive symptoms and negative symptoms. Patients with either of these mental illnesses suffer from impairments in everyday life. Paliperidone has been shown to reduce symptoms of schizophrenia and schizoaffective disorder.

The clinical relevance of gray matter atrophy and microstructural brain changes across the psychosis continuum

Patients with psychotic spectrum disorders (PSD) exhibit similar patterns of atrophy and microstructural changes that may be associated with common symptomatology (e.g., symptom burden and/or cognitive impairment). Gray matter concentration values (proxy for atrophy), fractional anisotropy (FA), mean diffusivity (MD), intracellular neurite density (Vic) and isotropic diffusion volume (Viso) measures were therefore compared in 150 PSD (schizophrenia, schizoaffective disorder, and bipolar disorder Type I) and 63 healthy controls (HC). Additional analyses evaluated whether regions showing atrophy and/or microstructure abnormalities were better explained by DSM diagnoses, symptom burden or cognitive dysfunction. PSD exhibited increased atrophy within bilateral medial temporal lobes and subcortical structures. Gray matter along the left lateral sulcus showed evidence of increased atrophy and MD. Increased MD was also observed in homotopic fronto-temporal regions, suggesting it may serve as a precursor to atrophic changes. Global cognitive dysfunction, rather than DSM diagnoses or psychotic symptom burden, was the best predictor of increased gray matter MD. Regions of decreased FA (i.e., left frontal gray and white matter) and Vic (i.e., frontal and temporal regions and along central sulcus) were also observed for PSD, but were neither spatially concurrent with atrophic regions nor associated with clinical symptoms. Evidence of expanding microstructural spaces in gray matter demonstrated the greatest spatial overlap with current and potentially future regions of atrophy, and was associated with cognitive deficits. These results suggest that this particular structural abnormality could potentially underlie global cognitive impairment that spans traditional diagnostic categories.

Eye Movements and Cognitive Functioning in Patients With Schizophrenia Spectrum Disorders: Network Analysis

Background: Eye movement parameters are often used during cognitive functioning assessments of patients with psychotic spectrum disorders. It is interesting to compare these oculomotor parameters with cognitive functions, as assessed using psychometric cognitive tests. A network analysis is preferable for understanding complex systems; therefore, the aim of this study was to determine the multidimensional relationships that exist between oculomotor reactions and neurocognition in patients with schizophrenia spectrum disorders. Materials and Methods: A total of 134 subjects (93 inpatients with schizophrenia spectrum disorders (ICD-10) and 41 healthy volunteers) participated in this study. Psychiatric symptom severity was assessed using the Positive and Negative Syndrome Scale, the Calgary Depression Scale for Schizophrenia, and the Young Mania Rating Scale. Extrapyramidal symptoms were assessed using the Simpson-Angus Scale, and akathisia was assessed using the Barnes Akathisia Rating Scale. Eye movements were recorded using an eye-tracker SMI RED 500, and cognitive function was assessed using the Brief Assessment of Cognition in Schizophrenia. The statistical analyses were conducted using Minitab 17 Statistical Software, version 17.2.1. Data visualization and additional analyses were performed in the R 4.0.3 environment, using RStudio V 1.3.1093 software. Results: A network model of neurocognitive and oculomotor functions was constructed for the patients. In the full network (which includes all correlations) the median antisaccade latency value is the central element of the oculomotor domain, and the Symbol Coding test, the Digit Sequencing test, and the Verbal Fluency test are central elements in the neurocognitive domain. Additionally, there were connections between other cognitive and oculomotor functions, except for the antisaccade error latency in the oculomotor domain and the Token Motor Task in the neurocognitive domain. Conclusion: Network analysis provides measurable criteria for the assessment of neurophysiological and neurocognitive abnormalities in patients with schizophrenic spectrum disorders and allows to select key targets for their management and cognitive remediation.

Predictive value of oxidative stress biomarkers in drug‑free patients with schizophrenia and schizo-affective disorder

Several studies have suggested that oxidative stress may represent one of the primary etiological mechanisms of schizophrenia (SZ) and schizoaffective disorder (SAD) which can be targeted by therapeutic intervention. The present study was conducted over a period of 24 months, between June 2016 and June 2018. All enrolled subjects were Tunisian, forty five drug‑free male patients with SZ (mean age: 37.6 years), twenty one drug‑free male patients with SAD (mean age: 28.8 years) and hundred and one age and gender matched controls (mean age: 34.2 years) were enrolled in the study. Plasma reduced glutathione (GSH) and Total thiols levels were significantly decreased in patients compared to controls (respectively p<0.001; p=0.050). In addition, malondialdehyde (MDA), advanced oxidation protein products (AOPP) and protein carbonyls (PC) concentrations and glutathione peroxidase (GSH-Px) activity were significantly increased in patients compared to controls (p<0.001; p<0.001; p<0.001 and p=0.003 respectively). The binary logistic regression analysis revealed that MDA, AOPP, PC and GSH-Px could be considered as independent risk factors for SZ and SAD. When using ROC analysis, a remarkable increase in the area under the curve (AUC) with higher sensitivity (Se) and specificity (Sp) for MDA, AOPP, PC and GSH-Px combined markers was observed. The present study indicated that the identification of the predictive value of this four-selected biomarkers related to oxidative stress in drug free patients should lead to a better identification of the etiological mechanism of SZ or SAD.

Quantifying the Core Deficit in Classical Schizophrenia

In the classical descriptions of schizophrenia, Kraepelin and Bleuler recognized disorganization and impoverishment of mental activity as fundamental symptoms. Their classical descriptions also included a tendency to persisting disability. The psychopathological processes underlying persisting disability in schizophrenia remain poorly understood. The delineation of a core deficit underlying persisting disability would be of value in predicting outcome and enhancing treatment. We tested the hypothesis that mental disorganization and impoverishment are associated with persisting impairments of cognition and role function, and together reflect a latent core deficit that is discernible in cases diagnosed by modern criteria. We used Confirmatory Factor Analysis to determine whether measures of disorganization, mental impoverishment, impaired cognition, and role functioning in 40 patients with schizophrenia represent a single latent variable. Disorganization scores were computed from the variance shared between disorganization measures from 3 commonly used symptom scales. Mental impoverishment scores were computed similarly. A single factor model exhibited a good fit, supporting the hypothesis that these measures reflect a core deficit. Persisting brain disorders are associated with a reduction in post-movement beta rebound (PMBR), the characteristic increase in electrophysiological beta amplitude that follows a motor response. Patients had significantly reduced PMBR compared with healthy controls. PMBR was negatively correlated with core deficit score. While the symptoms constituting impoverished and disorganized mental activity are dissociable in schizophrenia, nonetheless, the variance that these 2 symptom domains share with impaired cognition and role function, appears to reflect a pathophysiological process that might be described as the core deficit of classical schizophrenia.

Neurodevelopmental pathways in bipolar disorder

Aberrations in neurodevelopmental trajectories have been implicated in the neurobiology of several mental disorders and evidence indicates a pathophysiological and genetic overlap of schizophrenia and bipolar disorder (BD). In this narrative review, we summarize findings related to developmental and perinatal factors as well as epidemiological, clinical, neuropsychological, brain imaging, postmortem brain and genomic studies that provide evidence for a putative neurodevelopmental pathogenesis and etiology of BD. Overall, aberrations in neurodevelopmental pathways have been more consistently implicated in the pathophysiology of schizophrenia compared to BD. Nevertheless, an accumulating body of evidence indicates that dysfunctional neurodevelopmental pathways may be implicated in the underlying pathophysiology of at least a subset of individuals with BD particularly those with an early age of illness onset and those exhibiting psychotic symptoms. A heuristic neurodevelopmental model for the pathophysiology of BD based on the findings of this review is proposed. Furthermore, we critically discuss clinical and research implications of this model. Finally, further research directions for this emerging field are provided.

Current Challenges in Translational and Clinical fMRI and Future Directions

Translational neuroscience is an important field that brings together clinical praxis with neuroscience methods. In this review article, the focus will be on functional neuroimaging (fMRI) and its applicability in clinical fMRI studies. In the light of the "replication crisis," three aspects will be critically discussed: First, the fMRI signal itself, second, current fMRI praxis, and, third, the next generation of analysis strategies. Current attempts such as resting-state fMRI, meta-analyses, and machine learning will be discussed with their advantages and potential pitfalls and disadvantages. One major concern is that the fMRI signal shows substantial within- and between-subject variability, which affects the reliability of both task-related, but in particularly resting-state fMRI studies. Furthermore, the lack of standardized acquisition and analysis methods hinders the further development of clinical relevant approaches. However, meta-analyses and machine-learning approaches may help to overcome current shortcomings in the methods by identifying new, and yet hidden relationships, and may help to build new models on disorder mechanisms. Furthermore, better control of parameters that may have an influence on the fMRI signal and that can easily be controlled for, like blood pressure, heart rate, diet, time of day, might improve reliability substantially.

Effective connectivity within a triple network brain system discriminates schizophrenia spectrum disorders from psychotic bipolar disorder at the single-subject level

OBJECTIVE

Schizophrenia spectrum disorders (SSD) and psychotic bipolar disorder share a number of genetic and neurobiological features, despite a divergence in clinical course and outcome trajectories. We studied the diagnostic classification potential that can be achieved on the basis of the structure and connectivity within a triple network system (the default mode, salience and central executive network) in patients with SSD and psychotic bipolar disorder.

METHODS

Directed static connectivity and its dynamic variance was estimated among 8 nodes of the three large-scale networks. Multivariate autoregressive models of deconvolved resting state functional magnetic resonance imaging time series were obtained from 57 patients (38 with SSD and 19 with bipolar disorder and psychosis). We used 2/3 of the patients for training and validation of the classifier and the remaining 1/3 as an independent hold-out test data for performance estimation.

RESULTS

A high level of discrimination between bipolar disorder with psychosis and SSD (combined balanced accuracy = 96.2%; class accuracies 100% for bipolar and 92.3% for SSD) was achieved when effective connectivity and morphometry of the triple network nodes was combined with symptom scores. Patients with SSD were discriminated from patients with bipolar disorder and psychosis as showing higher clinical severity of disorganization and higher variability in the effective connectivity between salience and executive networks.

CONCLUSIONS

Our results support the view that the study of network-level connectivity patterns can not only clarify the pathophysiology of SSD but also provide a measure of excellent clinical utility to identify discrete diagnostic/prognostic groups among individuals with psychosis.

A symptom-based continuum of psychosis explains cognitive and real-world functional deficits better than traditional diagnoses

BACKGROUND

Patients with psychotic spectrum disorders share overlapping clinical/biological features, making it often difficult to separate them into a discrete nosology (i.e., Diagnostic and Statistical Manual of Mental Disorders [DSM]).

METHODS

The current study investigated whether a continuum classification scheme based on symptom burden would improve conceptualizations for cognitive and real-world dysfunction relative to traditional DSM nosology. Two independent samples (New Mexico [NM] and Bipolar and Schizophrenia Network on Intermediate Phenotypes [B-SNIP]) of patients with schizophrenia (NM: N = 93; B-SNIP: N = 236), bipolar disorder Type I (NM: N = 42; B-SNIP: N = 195) or schizoaffective disorder (NM: N = 15; B-SNIP: N = 148) and matched healthy controls (NM: N = 64; B-SNIP: N = 717) were examined. Linear regressions examined how variance differed as a function of classification scheme (DSM diagnosis, negative and positive symptom burden, or a three-cluster solution based on symptom burden).

RESULTS

Symptom-based classification schemes (continuous and clustered) accounted for a significantly larger portion of captured variance of real-world functioning relative to DSM diagnoses across both samples. The symptom-based classification schemes accounted for large percentages of variance for general cognitive ability and cognitive domains in the NM sample. However, in the B-SNIP sample, symptom-based classification schemes accounted for roughly equivalent variance as DSM diagnoses. A potential mediating variable across samples was the strength of the relationship between negative symptoms and impaired cognition.

CONCLUSIONS

Current results support suggestions that a continuum perspective of psychopathology may be more powerful for explaining real-world functioning than the DSM diagnostic nosology, whereas results for cognitive dysfunction were sample dependent.

Schizoaffective disorder comorbid with type 2 diabetes mellitus accompanied by frontotemporal atrophy and impaired cognition: A CARE compliant case report

RATIONALE

Brain atrophy coupled with impaired cognition may be a sign of dementia. However, growing evidence indicates that schizoaffective disorder (SAD) and type 2 diabetes mellitus (T2DM) play roles in the processes of frontotemporal atrophy and cognitive decline. Few cases of frontotemporal atrophy and impaired cognition have been reported in young adult patients with SAD and T2DM.

PATIENT CONCERNS

A 34-year-old man was admitted for his 19th rehospitalization due to auditory verbal hallucinations (AVHs), delusions of persecution, mania, and fluctuating blood sugar levels. After admission, a brain computed tomography (CT) scan revealed that the patient's frontotemporal atrophy, which was first found in 2014, had gradually degenerated over time. The Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) revealed cognitive impairments. Based on the clinical assessment, his cognition and social function impairments were determined to mainly result from SAD and T2DM because the clinical characteristics and course of the disease did not coincide with the features of progressive aggravation of dementia.

DIAGNOSES

Diagnoses include the following: SAD-mania and T2DM.

INTERVENTIONS

Paliperidone and sodium valproate coupled with quetiapine add-on treatment were prescribed for the patient.

OUTCOMES

The therapeutic strategy had a limited effect on the patient.

LESSONS

Early onset of SAD and T2DM, as well as irregular treatment, resulting in brain atrophy coupled with cognitive impairments, may be the main causes of the patient's treatment resistance and poor outcome. The risks and benefits of treatment strategies should be individually assessed. Further neuroimaging, pertinent biomarkers, and genetic tests along with long-term follow-up are needed for precise evaluation of the patient's condition.

The continuing story of schizophrenia and schizoaffective disorder: One condition or two?

Although schizophrenia and schizoaffective disorder remain separable in diagnostic systems, the validity of the distinction is uncertain. This study asked whether schizophrenia and schizoaffective disorder are distinguishable on selected cognitive, social cognitive and structural social brain measures. Outpatients with a diagnosis of schizophrenia (n = 44) or schizoaffective disorder (n = 29) and non-psychiatric control participants (n = 62) were studied. Patients were assessed clinically (Positive and Negative Syndrome Scale) and all participants were administered a battery of cognitive (MATRICS Consensus Cognitive Battery; Wechsler Abbreviated Scale of Intelligence, Wide Range Achievement Reading) and social cognitive (Reading the Mind in the Eyes, Mayer-Salovey-Caruso Emotional Intelligence Test; MSCEIT) tasks. In addition, participants underwent structural magnetic resonance imaging (MRI) to yield cortical thickness data for 42 regions associated with the social brain network. Results showed no significant differences between patient groups on 17/18 cognitive/social cognitive and social brain cortical thickness measures. In contrast, schizophrenia and schizoaffective disorder patients differed from controls on 16/18 and 11/18 measures respectively. Schizoaffective disorder patients outperformed schizophrenia patients on an emotion regulation task (MSCEIT). Schizophrenia and schizoaffective disorder are largely indistinguishable on key cognitive, social cognitive and neural measures. The continuing separation of these syndromes in diagnostic systems and disease models requires is questionable and requires further attention.

Could schizoaffective disorder, schizophrenia and bipolar I disorder be distinguishable using cognitive profiles?

This study seeks to determine whether the cognition profiles of patients with schizoaffective disorder (SAD), schizophrenia and bipolar I disorder (BD) are distinguishable. A total of 227 participants, comprising 88 healthy control subjects, 50 patients with SAD, 48 patients with schizophrenia and 41 patients with BD, were recruited. The participants' cognitive functions were evaluated using the Brief Assessment of Cognition in Schizophrenia (BACS). A discriminant functions analysis (DFA) was conducted to determine whether using cognitive performance can be used to distinguish these participant groups. Relative to healthy control subjects, patients with SAD, schizophrenia and BD exhibited significant deficits in all cognitive domains (verbal memory, working memory, motor speed, verbal fluency, attention and processing speed, executive function and a composite BACS score). Among the three patient groups, the schizophrenia group exhibited particularly impaired motor speed, and the BD group performed best in attention, processing speed, executive function and the composite BACS score. The classification accuracy rates of patients with SAD, schizophrenia and BD in the DFA model were 38%, 47.9% and 46.3%, respectively. These findings suggest that the impairments of some cognitive domains were less severe in patients with BD than in patients with schizophrenia or SAD.

Multivariate Relationships Between Cognition and Brain Anatomy Across the Psychosis Spectrum

BACKGROUND

Cognitive and structural brain abnormalities range from mild to severe in psychosis. The relationships of specific cognitive functions to specific brain structures across the psychosis spectrum is less certain.

METHODS

Participants (n = 678) with bipolar, schizoaffective, or schizophrenia psychoses and healthy control subjects were recruited via the Bipolar-Schizophrenia Network for Intermediate Phenotypes. The Schizo-Bipolar Scale was used to create a psychosis continuum (from purely affective to purely nonaffective). Canonical correlation between 14 cognitive measures and structural brain measures (gray matter volume, cortical thickness, cortical surface area, and local gyrification indices) for 68 neocortical regions yielded constructs that defined shared cognition-brain structure relationships. Canonical discriminant analysis was used to integrate these constructs and efficiently summarize cognition-brain structure relationships across the psychosis continuum.

RESULTS

General cognition was associated with larger gray matter volumes and thicker cortices but smaller cortical surface area in frontoparietal regions. Working memory was associated with larger volume and surface area in frontotemporal regions. Faster response speed was associated with thicker frontal cortices. Constructs that captured general cognitive ability and working memory and their relationship to cortical volumes primarily defined an ordered psychosis spectrum (purely affective, least abnormal through purely nonaffective, and most abnormal). A construct that captured general cognitive ability and its relationship to cortical surface area differentiated purely affective cases from other groups.

CONCLUSIONS

General cognition and working memory with cortical volume deviations characterized more nonaffective psychoses. Alternatively, affective psychosis cases with general cognitive deficits had deviations in cortical surface area, perhaps accounting for heterogeneous findings across previous studies.

Cognitive Remediation Interventions in Schizoaffective Disorder: A Systematic Review

Background: Patients with schizoaffective disorder (SAD) suffer from cognitive impairment, which negatively influences their functionality. Cognitive remediation (CR) interventions have been shown to be effective in patients with schizophrenia (SZ) and bipolar disorder (BD), but evidence in SAD is limited so far. The aim of this study is to systematically review the published data on CR interventions, either in neurocognition or social cognition, in patients with SAD. Methods: We conducted a comprehensive, computerized literature search using terms related to CR interventions in psychotic and affective disorders, and particularly in SAD. Pubmed, Embase, and Web of Knowledge databases were used up to February 28th, 2018 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The search returned 2672 articles of which four were finally selected meeting the inclusion criteria. Results: Cognitive Enhancement Therapy, computerized Cognitive Remediation Therapy and Cognitive Training showed positive results in subsamples of patients with SAD regarding neurocognition and functioning in comparable terms to patients with schizophrenia as well as in a greater extent in quality of life. Benefits in social cognition were also described when Social Cognition Interaction Training was considered in patients with SAD. Conclusions: CR interventions seem to improve neurocognition and social cognition in patients with SAD as well as functioning and quality of life. However, further randomized controlled trials on CR interventions with an optimized design focusing on selected sample of patients with SAD are imperative.

Neurocognition in patients with psychotic and non-psychotic bipolar I disorder. A comparative study with individuals with schizophrenia

BACKGROUND

It has been suggested that patients with bipolar disorder with psychotic symptoms (BD-P) have larger neurocognitive impairment than patients with bipolar disorder without a history of psychotic symptoms (BD-NP). The objective of this study was to compare neurocognitive performance of BD-P and BD-NP relative to a group of patients with schizophrenia (SZ), and healthy controls (HC).

METHODS

Neurocognitive function was examined in 100 subjects with bipolar I disorder (50 BD-P, 50 BD-NP), 50 SZ, and 51 HC. All patients with BD fulfilled criteria for euthymia, while all SZ patients were stabilised for at least the previous 3 months.

RESULTS

Patients with BD-P and BD-NP performed worse than HC in all neurocognitive measures, except for sustained attention. Differences between BD-P and BD-NP were subtle and circumscribed to the working memory domain (effect size: 0.29). SZ performed worse than BD-NP in the neurocognitive composite index (NCI) and in the working memory domain. There were no differences between SZ and BD-P in any neurocognitive measure.

LIMITATIONS

The relatively small sample size, the cross-sectional design and, that patients were receiving pharmacological treatment are the main limitations of this study.

CONCLUSIONS

Our findings show that the three groups of patients have a large neurocognitive impairment. Differences are quantitative and only present in some neurocognitive domains, such as working memory. These results suggest that patients with BD and SZ can benefit from the same strategies of cognitive remediation.

Safety, tolerability, and risks associated with first- and second-generation antipsychotics: a state-of-the-art clinical review

Since the discovery of chlorpromazine (CPZ) in 1952, first-generation antipsychotics (FGAs) have revolutionized psychiatric care in terms of facilitating discharge from hospital and enabling large numbers of patients with severe mental illness (SMI) to be treated in the community. Second-generation antipsychotics (SGAs) ushered in a progressive shift from the paternalistic management of SMI symptoms to a patient-centered approach, which emphasized targets important to patients - psychosocial functioning, quality of life, and recovery. These drugs are no longer limited to specific Diagnostic and Statistical Manual of Mental Disorders (DSM) categories. Evidence indicates that SGAs show an improved safety and tolerability profile compared with FGAs. The incidence of treatment-emergent extrapyramidal side effects is lower, and there is less impairment of cognitive function and treatment-related negative symptoms. However, treatment with SGAs has been associated with a wide range of untoward effects, among which treatment-emergent weight gain and metabolic abnormalities are of notable concern. The present clinical review aims to summarize the safety and tolerability profile of selected FGAs and SGAs and to link treatment-related adverse effects to the pharmacodynamic profile of each drug. Evidence, predominantly derived from systematic reviews, meta-analyses, and clinical trials of the drugs amisulpride, aripiprazole, asenapine, brexpiprazole, cariprazine, clozapine, iloperidone, lurasidone, olanzapine, paliperidone, quetiapine, risperidone, sertindole, ziprasidone, CPZ, haloperidol, loxapine, and perphenazine, is summarized. In addition, the safety and tolerability profiles of antipsychotics are discussed in the context of the "behavioral toxicity" conceptual framework, which considers the longitudinal course and the clinical and therapeutic consequences of treatment-emergent side effects. In SMI, SGAs with safer metabolic profiles should ideally be prescribed first. However, alongside with safety, efficacy should also be considered on a patient-tailored basis.