Schizoaffective Disorder in the DSM-5

Involvement of the TRPV1 receptor and the endocannabinoid system in schizophrenia

BACKGROUND

Schizophrenia (SCZ) is a severe mental disorder, but its pathogenesis is still unknown, and its clinical treatment effect is very limited. Transient receptor potential vanilloid 1 (TRPV1) channel and the Endocannabinoid System (ECS)have been confirmed to be involved in the pathogenesis of SCZ, although their actions have not been fully clarified yet. The objective is to examine TRPV1 and ECS expression in the blood of schizophrenia patients and investigate their correlation with disease severity.

METHODS

This is a cross-sectional investigation. Peripheral blood samples were gathered from normal controls (NC, n=37), as well as individuals with schizophrenia, including first episode (n=30) and recurrent (n=30) cases. We employed western blot and ELISA techniques to quantify TRPV1, cannabinoid receptors 1(CB1), anandamide (AEA), and 2-arachidonoylglycerol (2-AG), and assess the severity of the patient's symptoms by means of the PANSS scale.

RESULTS

Compared to NC, TRPV1 levels showed a noticeable decrease in both first episode schizophrenia (f-SCZ group) and recurrent schizophrenia (r-SCZ group) subjects. Additionally, CB1 levels appeared increased in f-SCZ group. Furthermore, 2-AG levels were found to be elevated in both f-SCZ group and r-SCZ group compared to NC, whereas AEA levels were decreased in f-SCZ group but increased in r-SCZ group. Moreover, among schizophrenia patients, TRPV1 demonstrated a negative correlation with negative symptoms. Within r-SCZ subjects, CB1 displayed a negative correlation with relapse number, while 2-AG showed a correlation in the opposite direction.

CONCLUSIONS

This study provides initial clinical evidence of changed TRPV1 expression in schizophrenia, potentially linked to negative symptoms. These results suggest a possible dysfunction of TRPV1 and the endocannabinoid system (ECS), which might offer new avenues for medical interventions.

Treatment of a resistant case of schizoaffective disorder with lumateperone: A case report

To this day, there exists skepticism about the reliability and clinical utility of the diagnostic criteria and classification of schizoaffective disorder. In addition, the treatment of schizoaffective disorder, especially of treatment-resistant cases, has been minimally investigated. As a result, formulating official treatment guidelines for schizoaffective disorder has been challenging. We present a case of a 27-year-old female, diagnosed with schizoaffective disorder, bipolar type, for whom, for over 5 years, trials of traditional treatments, to include psychotherapy, pharmacotherapy, and electroconvulsive therapy, were either partially effective or discontinued due to intolerable side effects. The subsequent off-label use of lumateperone led to an adequate response. Lumateperone is an atypical antipsychotic, approved by the Food and Drug Administration for schizophrenia and bipolar depression in adults. Interestingly, it has a similar structure and mechanism of action to paliperidone, the only Food and Drug Administration-approved medication for schizoaffective disorder. Through this case report, as an example of lumateperone's effectiveness and tolerability, as well as a literature review of its pharmacodynamics, we make the case that lumateperone emerges as a promising option for schizoaffective disorder, especially treatment-resistant cases.

The overlap across psychotic disorders: A functional network connectivity analysis

Functional network connectivity (FNC) has previously been shown to distinguish patient groups from healthy controls (HC). However, the overlap across psychiatric disorders such as schizophrenia (SZ), bipolar (BP), and schizoaffective disorder (SAD) is not evident yet. This study focuses on studying the overlap across these three psychotic disorders in both dynamic and static FNC (dFNC/sFNC). We used resting-state fMRI, demographics, and clinical information from the Bipolar-Schizophrenia Network on Intermediate Phenotypes cohort (BSNIP). The data includes three groups of patients with schizophrenia (SZ, N = 181), bipolar (BP, N = 163), and schizoaffective (SAD, N = 130) and HC (N = 238) groups. After estimating each individual's dFNC, we group them into three distinct states. We evaluated two dFNC features, including occupancy rate (OCR) and distance travelled over time. Finally, the extracted features, including both sFNC and dFNC, are tested statistically across patients and HC groups. In addition, we explored the link between the clinical scores and the extracted features. We evaluated the connectivity patterns and their overlap among SZ, BP, and SAD disorders (false discovery rate or FDR corrected p < 0.05). Results showed dFNC captured unique information about overlap across disorders where all disorder groups showed similar pattern of activity in state 2. Moreover, the results showed similar patterns between SZ and SAD in state 1 which was different than BP. Finally, the distance travelled feature of SZ (average R = 0.245, p < 0.01) and combined distance travelled from all disorders was predictive of the PANSS symptoms scores (average R = 0.147, p < 0.01).

Bioinformatics identification of potential biomarkers and therapeutic targets for ischemic stroke and vascular dementia

Ischemic stroke and vascular dementia, as common cerebrovascular diseases, with the former causing irreversible neurological damage and the latter causing cognitive and memory impairment, are closely related and have long received widespread attention. Currently, the potential causative genes of these two diseases have yet to be investigated, and effective early diagnostic tools for the diseases have not yet emerged. In this study, we screened new potential biomarkers and analyzed new therapeutic targets for both diseases from the perspective of immune infiltration. Two gene expression profiles on ischemic stroke and vascular dementia were obtained from the NCBI GEO database, and key genes were identified by LASSO regression and SVM-RFE algorithms, and key genes were analyzed by GO and KEGG enrichment. The CIBERSORT algorithm was applied to the gene expression profile species of the two diseases to quantify the 24 subpopulations of immune cells. Moreover, logistic regression modeling analysis was applied to illustrate the stability of the key genes in the diagnosis. Finally, the key genes were validated using RT-PCR assay. A total of 105 intersecting DEGs genes were obtained in the 2 sets of GEO datasets, and bioinformatics functional analysis of the intersecting DEGs genes showed that GO was mainly involved in the purine ribonucleoside triphosphate metabolic process，respiratory chain complex，DNA-binding transcription factor binding and active transmembrane transporter activity. KEGG is mainly involved in the Oxidative phosphorylation, cAMP signaling pathway. The LASSO regression algorithm and SVM-RFE algorithm finally obtained three genes, GAS2L1, ARHGEF40 and PFKFB3, and the logistic regression prediction model determined that the three genes, GAS2L1 (AUC: 0.882), ARHGEF40 (AUC: 0.867) and PFKFB3 (AUC: 0.869), had good diagnostic performance. Meanwhile, the two disease core genes and immune infiltration were closely related, GAS2L1 and PFKFB3 had the highest positive correlation with macrophage M1 (p < 0.001) and the highest negative correlation with mast cell activation (p = 0.0017); ARHGEF40 had the highest positive correlation with macrophage M1 and B cells naive (p < 0.001), the highest negative correlation with B cell memory highest correlation (p = 0.0047). RT-PCR results showed that the relative mRNA expression levels of GAS2L1, ARHGEF40, and PFKFB3 were significantly elevated in the populations of both disease groups (p < 0.05). Immune infiltration-based models can be used to predict the diagnosis of patients with ischemic stroke and vascular dementia and provide a new perspective on the early diagnosis and treatment of both diseases.

Hypersexuality during treatment with cariprazine in a patient with schizophrenia? A case report

BACKGROUND

Cariprazine is a third-generation antipsychotic with a unique mechanism of action. It functions as a partial agonist with high affinity for dopamine D2 and D3 and serotonin 5-HT1A receptors, an antagonist for 5-HT2A (moderate affinity) and 5-HT2B (high affinity) receptors. It binds to histamine H1 receptors and has a low affinity for 5-HT2C and alpha 1A-adrenergic receptors and no affinity for muscarinic (cholinergic) receptors. Among the troubling side effects, symptoms related to impulse control, such as hypersexuality, pathological gambling, compulsive shopping, compulsive eating etc., have been reported with the use of antipsychotic medications. However, no reports have been published regarding impulse control symptoms associated with cariprazine. We report a case of cariprazine-induced hypersexuality in a patient with schizophrenia, which was resolved by discontinuation of the medication.

CASE PRESENTATION

A 67-year-old Caucasian woman with schizophrenia was admitted to the hospital inpatient unit after she discontinued olanzapine and psychotic symptoms reappeared. Prior to that, she was in remission, taking olanzapine for approximately one year. After discontinuation, she experienced auditory hallucinations with persecutory delusions and became anergic and withdrawn, with blunted affect. Olanzapine was reintroduced, as it was proven successful in her past treatments. However, since there were no changes, especially in negative symptoms, cariprazine was added. Seven days after the introduction of cariprazine, the patient developed compulsive sexual behaviour. Therefore, cariprazine was discontinued, and the hypersexual behaviour was resolved.

CONCLUSIONS

In this case report, we describe hypersexual behaviour that could potentially be induced by cariprazine. As a single case study, conclusions cannot be drawn. Controlled studies are warranted to better determine causality and the significance of this possible side-effect of cariprazine.

Dysregulation of MicroRNAs Derived from Plasma Extracellular Vesicles in Schizoaffective Disorder

The association between peripheral blood extracellular vesicles (EVs)-derived miRNAs (EVs-miRNAs) and neuropsychiatric diseases has been extensively studied. However, it remains largely unclear about the expression profile of EVs-miRNAs in schizoaffective disorder (SAD) patients. In our study, we isolated the EVs from plasma samples of patients and healthy controls, and then analyzed the expression profiles of EVs-miRNAs through small RNA sequencing. Our results identified 32 differentially expressed (DE) miRNAs (25 upregulated and 7 downregulated) in SAD patients. A module containing 42 miRNAs closely related to SAD was identified by weighted gene co-expression network analysis (WGCNA), among which has-miR-15b-5p, has-miR-301a-3p, has-miR-342-3p, has-miR-219b-5p, and has-miR-145-5p were identified as hub miRNAs. The enrichment analysis showed that the target genes of these 42 miRNAs were significantly enriched in multiple pathways related to neuropathology and located at synapses. A total of 6 DE miRNAs (has-miR-7-5p, has-miR-144-3p, has-miR-155-5p, has-miR-342-3p, has-miR-342-5p, and has-miR-487b-3p) associated with SAD were selected for qRT-PCR verification. The level of has-miR-342-3p in SAD patients was downregulated, and hsa-miR-155-5p was upregulated. Our findings support the hypothesis that dysregulation of EVs-miRNAs in plasma might be involved in the underlying neuropathology of SAD through several biological pathways and provide important preliminary evidence supporting the use of EVs-miRNAs as potential novel biomarkers in SAD.

The Course Patterns and Diagnostic Shifts of Patients With Schizoaffective Disorder: A Retrospective Cohort Study

ABSTRACT

Since its introduction, schizoaffective disorder (SAD) has been one of the most controversial diagnoses in psychiatry, both clinically and nosologically. In the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), SAD diagnostic criteria were changed, and instead of a cross-sectional diagnosis, a longitudinal approach covering the life course of the illness was adopted. In this study, the meaning of this conceptual shift in the diagnosis of SAD in clinical practice is investigated throughout the course of the illness for patients with SAD. Sixty-two inpatients diagnosed with SAD according to DSM-5 diagnostic criteria are included in this study. The course of the illness from its onset to the present is investigated retrospectively. The disease duration is 18.3 ± 9.1 years. The most common diagnoses in the first hospitalization are bipolar disorder (manic episodes) and psychotic disorder, not otherwise specified. Furthermore, the time that elapsed between the first psychiatric application of the patients and the diagnosis of SAD is 9.5 ± 7.3 years. Further, when the course of the illness is grouped according to the predominance of affective and psychotic disorders, recurrent affective disorders are observed most frequently (29.3%), followed by mixed-episode disorders and a shift from affective disorders to psychotic disorders (22.4%). It is found that SAD has a heterogeneous course, and affective disorder diagnoses are more dominant during the course of the illness. The clinical relevance of the longitudinal emphasis on the total duration of the illness in the DSM-5 is also demonstrated. The affective and psychotic dichotomy, based on Kraepelin, has failed to elucidate the course of the disease in clinical practice. Therefore, clinicians should meticulously evaluate the entire course of the illness for SAD and avoid conclusive judgments over a single episode.

Pharmacogenetics of Long-Term Outcomes of Schizophrenia Spectrum Disorders: The Functional Role of CYP2D6 and CYP2C19

Schizophrenia spectrum disorders (SSD) are complex mental disorders, and while treatment with antipsychotics is important, many patients do not respond or develop serious side effects. Genetic variation has been shown to play a considerable role in determining an individual's response to antipsychotic medication. However, previous pharmacogenetic (PGx) studies have been limited by small sample sizes, lack of consensus regarding relevant genetic variants, and cross-sectional designs. The current study aimed to investigate the association between PGx variants and long-term clinical outcomes in 691 patients of European ancestry with SSD. Using evidence from the literature on candidate genes involved in antipsychotic pharmacodynamics, we created a polygenic risk score (PRS) to investigate its association with clinical outcomes. We also created PRS using core variants of psychotropic drug metabolism enzymes CYP2D6 and CYP2C19. Furthermore, the CYP2D6 and CYP2C19 functional activity scores were calculated to determine the relationship between metabolism and clinical outcomes. We found no association for PGx PRSs and clinical outcomes; however, an association was found with CYP2D6 activity scores by the traditional method. Higher CYP2D6 metabolism was associated with high positive and high cognitive impairment groups relative to low symptom severity groups. These findings highlight the need to test PGx efficacy with different symptom domains. More evidence is needed before pharmacogenetic variation can contribute to personalized treatment plans.

Practitioner Review: Psychosis in children and adolescents

Psychotic symptoms, including hallucinations, delusions, and disorganized thinking and behaviors, are the hallmarks of schizophrenia; but may also present in the context of other psychiatric and medical conditions. Many children and adolescents describe psychotic-like experiences, which can be associated with other types of psychopathology and past experiences (e.g., trauma, substance use, and suicidality). However, most youth reporting such experiences do not have, nor will ever develop, schizophrenia or another psychotic disorder. Accurate assessment is critical because these different presentations have different diagnostic and treatment implications. For this review, we focus primarily on the diagnosis and treatment of early onset schizophrenia. In addition, we review the development of community-based first-episode psychosis programming, and the importance of early intervention and coordinated care.

Genetic analysis of a large Han Chinese family line with schizoaffective psychosis

To locate the specific susceptibility genes of a high incidence of schizoaffective disease (SAD) with autonomic dominant inheritance, we recruited a family group from Henan Province with a high incidence of SAD, including 19 individuals sampled from five generations. We used a genome-wide high-density SNP chip to perform genotype detection. The LINKAGE package and MENDEL programs were used for. The two-point and multipoint analyses were calculated by Merlin and SimWalk2 software to obtain the nonparametric linkage (NPL) value, corresponding P value, and parameter linkage limit of detection (LOD) value. Genome-wide linkage analysis yielded a significant linkage signal located on the short arm of chromosome 19. In the dominant genetic model, the LOD of the multipoint parametric analysis was 2.5, and the nonparametric analysis was 19.4 (P < 0.00001). Further haploid genotype analysis localized the candidate region in the 19p13.3-13.2 region, beginning at rs178414 and ending at rs11668751 with a physical length of approximately 4.9 Mb. We believe that the genes responsible for SAD are in this region.

Schizophrenia or schizoaffective disorder? A 50-year assessment of diagnostic stability based on a national case registry

BACKGROUND

Schizoaffective disorder (SAD) remains a controversial diagnosis in terms of necessity and reliability.

OBJECTIVES

We assessed diagnostic patterns of SAD and schizophrenia (SZ) among hospitalized psychiatric patients over a fifty-year period.

METHOD

Data from the Israeli National Psychiatric Registry on 16,341 adults diagnosed with SZ or SAD, hospitalized at least twice in 1963-2017, were analyzed. Stability between most-frequent, first and last diagnosis, and diagnostic-constancy (the same diagnosis in >75 % of a person's hospitalizations) were calculated. Three groups were compared: People with both SAD and SZ diagnoses over the years (SZ-SAD), and people with only one of these diagnoses (SZ-only; SAD-only). The incidence of SAD and SZ before and after DSM-5 publication was compared.

RESULTS

Reliability between last and first diagnosis was 60 % for SAD and 94 % for SZ. Agreement between first and most-frequent diagnosis was 86 % for SAD and 92 % for SZ. Diagnostic shifts differ between persons with SAD and with SZ. Diagnostic-constancy was observed for 50 % of SAD-only patients. In the SZ-SAD group, 9 % had a constant SAD diagnosis. Compared to the other groups, the SZ-SAD group exhibited a higher substance use prevalence, younger age at first-hospitalization, and more hospitalizations/person (p < 0.0001). The incidence of a first-hospitalization SAD diagnosis increased by 2.2 % in the 4-years after vs. prior to DSM-5.

CONCLUSIONS

A SAD diagnosis is less stable than SZ. The incidence of a SAD diagnosis increased after DSM-5, despite stricter diagnostic criteria. The SZ-SAD group exhibited the poorest outcomes. SAD may evolve over time necessitating periodic re-evaluation.

Neuroimaging in schizophrenia: A review article

In this review article we have consolidated the imaging literature of patients with schizophrenia across the full spectrum of modalities in radiology including computed tomography (CT), morphologic magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and magnetoencephalography (MEG). We look at the impact of various subtypes of schizophrenia on imaging findings and the changes that occur with medical and transcranial magnetic stimulation (TMS) therapy. Our goal was a comprehensive multimodality summary of the findings of state-of-the-art imaging in untreated and treated patients with schizophrenia. Clinical imaging in schizophrenia is used to exclude structural lesions which may produce symptoms that may mimic those of patients with schizophrenia. Nonetheless one finds global volume loss in the brains of patients with schizophrenia with associated increased cerebrospinal fluid (CSF) volume and decreased gray matter volume. These features may be influenced by the duration of disease and or medication use. For functional studies, be they fluorodeoxyglucose positron emission tomography (FDG PET), rs-fMRI, task-based fMRI, diffusion tensor imaging (DTI) or MEG there generally is hypoactivation and disconnection between brain regions. However, these findings may vary depending upon the negative or positive symptomatology manifested in the patients. MR spectroscopy generally shows low N-acetylaspartate from neuronal loss and low glutamine (a neuroexcitatory marker) but glutathione may be elevated, particularly in non-treatment responders. The literature in schizophrenia is difficult to evaluate because age, gender, symptomatology, comorbidities, therapy use, disease duration, substance abuse, and coexisting other psychiatric disorders have not been adequately controlled for, even in large studies and meta-analyses.

Aberrant functional connectivity within the salience network is related to cognitive deficits and disorganization in psychosis

In schizophrenia and schizoaffective disorder cognitive deficits are a reliable characteristic predicting a poor functional outcome. It has been theorized that both the default mode network (DMN) and the salience network (SN) play a crucial role in cognitive processes and aberrant functional connectivity within these networks in psychotic patients has been reported. The goal of this study was to reveal potential links between aberrant functional connectivity within these networks and impaired cognitive performance in psychosis. We chose two approaches for cognitive assessment, first the MATRICS Consensus Cognitive Battery (MCCB) combined into a global score and second the disorganization factor derived from a five-factor model of the Positive and Negative Syndrome Scale (PANSS) known to be relevant for cognitive performance. DMN and SN were identified using independent component analysis on resting-state functional magnetic resonance imaging data. We found significantly decreased connectivity within the right supplementary motor area (SMA) and bilateral putamen in patients with psychosis (n = 70; 27F/43M) compared to healthy controls (n = 72; 28F/44M). Within patients, linear regression analysis revealed that aberrant SMA connectivity was associated with impaired global cognition, while dysfunctional bilateral putamen connectivity predicted disorganization. There were no significant changes in connectivity within the DMN. Results support the hypothesis that SN dysfunctional connectivity is important in the pathobiology of cognitive deficits in psychosis. For the first time we were able to show the involvement of dysfunctional SMA connectivity in this context. We interpret the decreased SN connectivity as evidence of reduced functionality in recruiting brain areas necessary for cognitive processing.

Mapping relationships among schizophrenia, bipolar and schizoaffective disorders: A deep classification and clustering framework using fMRI time series

BACKGROUND

Psychiatric disorders are categorized using self-report and observational information rather than biological data. There is also considerable symptomatic overlap between different types of psychiatric disorders, which makes diagnostic categorization and multi-class classification challenging.

METHODS

In this work, we propose a unified framework for supervised classification and unsupervised clustering of psychotic disorders using brain imaging data. A new multi-scale recurrent neural network (MsRNN) model was developed and applied to fMRI time courses (TCs) for multi-class classification. The high-level representations of the original TCs were then submitted to a tSNE clustering model for visualizing the group differences between disorders. A leave-one-feature-out approach was used for disorder-related biomarker identification.

RESULTS

When studying fMRI from schizophrenia, psychotic bipolar disorder, schizoaffective disorder, and healthy individuals, the accuracy of a 4-class classification reached 46%, significantly above chance. The hippocampus, supplementary motor area and paracentral lobule were discovered as the most contributing regional TCs in the multi-class classification. Beyond this, visualization of the tSNE clustering suggested that the disease severity can be captured and schizoaffective disorder (SAD) may be separated into two subtypes. SAD cluster1 has significantly higher Positive And Negative Syndrome Scale (PANSS) scores than SAD cluster2 in PANSS negative2 (emotional withdrawal), general2 (anxiety), general3 (guilt feelings), general4 (tension).

CONCLUSIONS

The proposed deep classification and clustering framework is not only able to identify psychiatric disorders with high accuracy, but also interpret the correlation between brain networks and specific psychiatric disorders, and reveal the relationship between them. This work provides a promising way to investigate a spectrum of similar disorders using neuroimaging-based measures.

Large-scale real-world data analysis identifies comorbidity patterns in schizophrenia

Schizophrenia affects >3.2 million people in the USA. However, its comorbidity patterns have not been systematically characterized in real-world populations. To address this gap, we conducted an observational study using a cohort of 86 million patients in a nationwide health insurance dataset. We identified participants with schizophrenia and those without schizophrenia matched by age, sex, and the first three digits of zip code. For each phenotype encoded in phecodes, we compared their prevalence in schizophrenia patients and the matched non-schizophrenic participants, and we performed subgroup analyses stratified by age and sex. Results show that anxiety, posttraumatic stress disorder, and substance abuse commonly occur in adolescents and young adults prior to schizophrenia diagnoses. Patients aged 60 and above are at higher risks of developing delirium, alcoholism, dementia, pelvic fracture, and osteomyelitis than their matched controls. Type 2 diabetes, sleep apnea, and eating disorders were more prevalent in women prior to schizophrenia diagnosis, whereas acute renal failure, rhabdomyolysis, and developmental delays were found at higher rates in men. Anxiety and obesity are more commonly seen in patients with schizoaffective disorders compared to patients with other types of schizophrenia. Leveraging a large-scale insurance claims dataset, this study identified less-known comorbidity patterns of schizophrenia and confirmed known ones. These comorbidity profiles can guide clinicians and researchers to take heed of early signs of co-occurring diseases.

Guidelines for the management of psychosis in the context of mood disorders

Psychotic episodes occur in a substantial proportion of patients suffering from major mood disorders (both unipolar and bipolar) at some point in their lives. The nature of these episodes is less well understood than the more common, non-psychotic periods of illness and hence their management is also less sophisticated. This is a concern because the risk of suicide is particularly high in this subtype of mood disorder and comorbidity is far more common. In some cases psychotic symptoms may be signs of a comorbid illness but the relationship of psychotic mood to other forms of psychosis and in particular its interactions with schizophrenia is poorly understood. Therefore, our targeted review draws upon extant research and our combined experience to provide clinical context and a framework for the management of these disorders in real-world practice - taking into consideration both biological and psychological interventions.

The Perspectives of Early Diagnosis of Schizophrenia Through the Detection of Epigenomics-Based Biomarkers in iPSC-Derived Neurons

The lack of early diagnostic biomarkers for schizophrenia greatly limits treatment options that deliver therapeutic agents to affected cells at a timely manner. While previous schizophrenia biomarker research has identified various biological signals that are correlated with certain diseases, their reliability and practicality as an early diagnostic tool remains unclear. In this article, we discuss the use of atypical epigenetic and/or consequent transcriptional alterations (ETAs) as biomarkers of early-stage schizophrenia. Furthermore, we review the viability of discovering and applying these biomarkers through the use of cutting-edge technologies such as human induced pluripotent stem cell (iPSC)-derived neurons, brain models, and single-cell level analyses.

Systematic Review of Functional MRI Applications for Psychiatric Disease Subtyping

Background: Psychiatric disorders have been historically classified using symptom information alone. Recently, there has been a dramatic increase in research interest not only in identifying the mechanisms underlying defined pathologies but also in redefining their etiology. This is particularly relevant for the field of personalized medicine, which searches for data-driven approaches to improve diagnosis, prognosis, and treatment selection for individual patients. Methods: This review aims to provide a high-level overview of the rapidly growing field of functional magnetic resonance imaging (fMRI) from the perspective of unsupervised machine learning applications for disease subtyping. Following the PRISMA guidelines for protocol reproducibility, we searched the PubMed database for articles describing functional MRI applications used to obtain, interpret, or validate psychiatric disease subtypes. We also employed the active learning framework ASReview to prioritize publications in a machine learning-guided way. Results: From the 20 studies that met the inclusion criteria, five used functional MRI data to interpret symptom-derived disease clusters, four used it to interpret clusters derived from biomarker data other than fMRI itself, and 11 applied clustering techniques involving fMRI directly. Major depression disorder and schizophrenia were the two most frequently studied pathologies (35% and 30% of the retrieved studies, respectively), followed by ADHD (15%), psychosis as a whole (10%), autism disorder (5%), and the consequences of early exposure to violence (5%). Conclusions: The increased interest in personalized medicine and data-driven disease subtyping also extends to psychiatric disorders. However, to date, this subfield is at an incipient exploratory stage, and all retrieved studies were mostly proofs of principle where further validation and increased sample sizes are craved for. Whereas results for all explored diseases are inconsistent, we believe this reflects the need for concerted, multisite data collection efforts with a strong focus on measuring the generalizability of results. Finally, whereas functional MRI is the best way of measuring brain function available to date, its low signal-to-noise ratio and elevated monetary cost make it a poor clinical alternative. Even with technology progressing and costs decreasing, this might incentivize the search for more accessible, clinically ready functional proxies in the future.

Shared decision making in a semi-secluded chronic psychiatric ward: The reflective lifeworld experiences of patients with schizophrenia or schizoaffective disorders and nursing staff

BACKGROUND

Shared decision making (SDM) enhances recovery-oriented mental healthcare, but literature predominately focuses on doctor-patient collaboration leaving the role of mental health nurses (MHN's) underexposed.

AIM

This study describes the experiences of patients with schizophrenia or schizoaffective disorder with SDM in a semi-secluded psychiatric facility, and the attitudes toward SDM by MHN's.

METHOD

A hermeneutic phenomenological design.

RESULTS

Seven patients and six MHN's were interviewed. Although MHNs were skeptical to utilize SDM, and patients often feel omitted, investing in inter-human contact increased the therapeutic alliance.

CONCLUSION

Tailored plan making and attainable goal setting, building trust, and providing hope are important incentives to enhance SDM.

A Misdiagnosed Case of Schizoaffective Disorder With Bipolar Manifestations

Bipolar and schizoaffective disorders are both psychiatric illnesses that share common traits, but also significant differences. Due to the close overlap in symptoms, obtaining the correct diagnosis can be difficult. The management of these patients often poses a challenge to clinicians.

Five years ago, our patient was misdiagnosed with bipolar disorder with psychotic features. It was later discovered that she was suffering from schizoaffective disorder, bipolar type. The schizoaffective disorder involves symptoms of both schizophrenia and mood disorder.

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.

Schizophrenia-schizoaffective-bipolar spectra: an epistemological perspective

For decades clinicians and researchers have been thinking and writing about the spectrum of schizophrenia disorders. Indeed both Kraepelin and Bleuler believed in schizophrenia as a spectrum, both in a clinical (individual) and hereditary (family) continuum, from just some exquisite personality traits to unquestionable chronic and debilitating psychosis. Other authors would put the schizophrenia spectrum disorders on different levels of continuum: developmental, psychofunctional, existential, and genetic. Here, we would like to present an historical chronology for the schizophrenia-schizoaffective-bipolar spectra plus a tridimensional model for these spectra: the first axis for categories (affective versus nonaffective psychoses), the second axis for dimensions (personality versus full blown psychosis), and a third axis for biomarkers (remission versus relapse). We believe that without the schizophrenia-schizoaffective-bipolar spectra concept in our minds all our efforts will keep failing one the hardest quest: searching for biomarkers in schizophrenia and related disorders.

Risk Factors, Clinical Features, and Polygenic Risk Scores in Schizophrenia and Schizoaffective Disorder Depressive-Type

There is controversy about the status of schizoaffective disorder depressive-type (SA-D), particularly whether it should be considered a form of schizophrenia or a distinct disorder. We aimed to determine whether individuals with SA-D differ from individuals with schizophrenia in terms of demographic, premorbid, and lifetime clinical characteristics, and genetic liability to schizophrenia, depression, and bipolar disorder. Participants were from the CardiffCOGS sample and met ICD-10 criteria for schizophrenia (n = 713) or SA-D (n = 151). Two samples, Cardiff Affected-sib (n = 354) and Cardiff F-series (n = 524), were used for replication. For all samples, phenotypic data were ascertained through structured interview, review of medical records, and an ICD-10 diagnosis made by trained researchers. Univariable and multivariable logistic regression models were used to compare individuals with schizophrenia and SA-D for demographic and clinical characteristics, and polygenic risk scores (PRS). In the CardiffCOGS, SA-D, compared to schizophrenia, was associated with female sex, childhood abuse, history of alcohol dependence, higher functioning Global Assessment Scale (GAS) score in worst episode of psychosis, lower functioning GAS score in worst episode of depression, and reduced lifetime severity of disorganized symptoms. Individuals with SA-D had higher depression PRS compared to those with schizophrenia. PRS for schizophrenia and bipolar disorder did not significantly differ between SA-D and schizophrenia. Compared to individuals with schizophrenia, individuals with SA-D had higher rates of environmental and genetic risk factors for depression and a similar genetic liability to schizophrenia. These findings are consistent with SA-D being a sub-type of schizophrenia resulting from elevated liability to both schizophrenia and depression.

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.

Misdiagnosis, detection rate, and associated factors of severe psychiatric disorders in specialized psychiatry centers in Ethiopia

BACKGROUND

There are limited studies on the prevalence of misdiagnosis as well as detection rates of severe psychiatric disorders in specialized and non-specialized healthcare settings. To the best of our knowledge, this is the first study to determine the prevalence of misdiagnosis and detection rates of severe psychiatric disorders including schizophrenia, schizoaffective, bipolar, and depressive disorders in a specialized psychiatric setting.

METHOD

In this cross-sectional study, a random sample of 309 patients with severe psychiatric disorders was selected by systematic sampling technique. Severe psychiatric disorders were assessed using the Structured Clinical Interview for DSM-IV (SCID). The potential determinates of misdiagnosis were explored using univariable and multivariable logistic regression models, adjusting for the potential confounding factors.

RESULT

This study revealed that more than a third of patients with severe psychiatric disorders were misdiagnosed (39.16%). The commonly misdiagnosed disorder was found to be a schizoaffective disorder (75%) followed by major depressive disorder (54.72%), schizophrenia (23.71%), and bipolar disorder (17.78%). Among the patients detected with the interview by SCID criteria, the highest level of the correct diagnosis was recorded in the medical record for schizophrenia (76.29%) followed by bipolar (72.22%), depressive (42.40%), and schizoaffective (25%) disorders with detection rate (sensitivity) of 0.76 (95% CI 0.69-0.84), 0.42 (95% CI 0.32-0.53), 0.72 (95% CI 0.60-0.84), and 0.25 (95% CI 0.09-0.41), respectively for schizophrenia, depressive, bipolar, and schizoaffective disorders. Patients with bipolar disorder were more likely to be misdiagnosed as having schizophrenia (60%), whereas schizophrenic patients were more likely to be misdiagnosed as having bipolar disorder (56.25%) and patients with depressive disorders were more likely to be misdiagnosed as having schizophrenia (54.72%). Having a diagnosis of schizoaffective and depressive disorders, as well as suicidal ideation, was found to be significant predictors of misdiagnosis.

CONCLUSION

This study showed that roughly four out of ten patients with severe psychiatric disorders had been misdiagnosed in a specialized psychiatric setting in Ethiopia. The highest rate of misdiagnosis was observed for schizoaffective disorder (3 out of 4), followed by major depressive disorder (1 out of 2), schizophrenia (1 out of 4), and bipolar disorders (1 in 5). The detection rates were highest for schizophrenia, followed by bipolar, depressive, and schizoaffective disorders. Having a diagnosis of schizoaffective and depressive disorders as well as suicidal ideation was found to be significant predictors of misdiagnosis.

In Vivo Amygdala Nuclei Volumes in Schizophrenia and Bipolar Disorders

Abnormalities in amygdala volume are well-established in schizophrenia and commonly reported in bipolar disorders. However, the specificity of volumetric differences in individual amygdala nuclei is largely unknown. Patients with schizophrenia disorders (SCZ, N = 452, mean age 30.7 ± 9.2 [SD] years, females 44.4%), bipolar disorders (BP, N = 316, 33.7 ± 11.4, 58.5%), and healthy controls (N = 753, 34.1 ± 9.1, 40.9%) underwent T1-weighted magnetic resonance imaging. Total amygdala, nuclei, and intracranial volume (ICV) were estimated with Freesurfer (v6.0.0). Analysis of covariance and multiple linear regression models, adjusting for age, age2, ICV, and sex, were fitted to examine diagnostic group and subgroup differences in volume, respectively. Bilateral total amygdala and all nuclei volumes, except the medial and central nuclei, were significantly smaller in patients relative to controls. The largest effect sizes were found for the basal nucleus, accessory basal nucleus, and cortico-amygdaloid transition area (partial η2 > 0.02). The diagnostic subgroup analysis showed that reductions in amygdala nuclei volume were most widespread in schizophrenia, with the lateral, cortical, paralaminar, and central nuclei being solely reduced in this disorder. The right accessory basal nucleus was marginally smaller in SCZ relative to BP (t = 2.32, P = .05). Our study is the first to demonstrate distinct patterns of amygdala nuclei volume reductions in a well-powered sample of patients with schizophrenia and bipolar disorders. Volume differences in the basolateral complex (lateral, basal, and accessory basal nuclei), an integral part of the threat processing circuitry, were most prominent in schizophrenia.

Electroconvulsive Therapy in a Renal Transplantation Patient: A Rare Combination of Disease and Treatment

The safety and efficacy of electroconvulsive therapy (ECT) for the treatment of psychiatric disorders have been demonstrated in a wide variety of patients, including postoperative patients and those who are pregnant. While several reports highlight the safety of this treatment in heart and liver transplantation patients, there is a relative lack of literature detailing the safety profile of ECT in an individual with recent kidney transplantation. Here, we explore the case of a patient with a recent renal transplant secondary to diabetes-related end-stage renal disease (ESRD) who underwent a successful course of ECT treatment. A 57-year-old Caucasian male with a past psychiatric history of schizoaffective disorder, bipolar type, and a past medical history of end-stage renal disease with recent right renal transplantation was admitted to the inpatient psychiatry unit. The admission was via a temporary detention order (TDO) for suicidality and auditory hallucinations promoting self-harm. The patient's depressive and delusional history was well-documented and had been refractory to several courses of psychotherapeutic and pharmacologic management. Electroconvulsive therapy was subsequently initiated and was well-tolerated. Treatments progressively alleviated his depressive and psychotic symptoms and did not adversely affect the function of his transplanted kidney, which was closely monitored throughout the treatment process. This case demonstrated the safety and efficacy of ECT treatment in an individual with recent renal transplant and may prompt further trials into establishing safety and efficacy in larger study populations.

Treatment Capacity and Clinical Outcomes for Patients With Schizophrenia Who Were Treated With Electroconvulsive Therapy: A Retrospective Cohort Study

BACKGROUND

Patients with schizophrenia are often found incapable to consent to psychiatric treatment. We evaluated clinical outcomes for incapable and capable patients with schizophrenia treated with electroconvulsive therapy (ECT).

METHODS

We conducted a chart review of all inpatients treated with an acute course of ECT between 2010 and 2018 at the Centre for Addiction and Mental Health, Toronto, Canada. Short-term outcomes included treatment response and cognitive impairment. We assessed whether incapable patients regained the capacity to consent to treatment. Long-term outcomes included readmissions and subsequent courses of acute or maintenance ECT.

RESULTS

A total of 159 (67%) incapable and 79 (33%) capable patients were included. Patients experienced treatment response (incapable, n = 108, 67.9%; capable, n = 52, 65.8%; P = .771) and few experienced cognitive impairment (incapable, n = 21, 13.2%; capable, n = 19, 24.1%; P = .043). A minority of patients were treated with a subsequent course of acute ECT (incapable, n = 46, 28.9%; capable, n = 16, 20.3%; P = .162). Incapable patients were more likely to be treated with maintenance ECT for at least 6 months (incapable, n = 46, 28.9%; capable, n = 13, 16.5%; P = .039). Both groups had similar readmission rates (incapable, n = 70, 44.0%; capable, n = 35, 44.3%; P = 1.000). Eight (5.0%) incapable patients regained capacity and 7 consented to further treatment.

CONCLUSIONS

Irrespective of treatment capacity, the majority of patients demonstrated clinical improvement. Incapable patients experienced less cognitive side effects when compared with capable patients, though they had fewer treatments overall. This study informs clinicians, patients, and substitute decision-makers about the outcomes and challenges of ECT in patients with schizophrenia.

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.

Identifying commonality and specificity across psychosis sub-groups via classification based on features from dynamic connectivity analysis

It is difficult to distinguish schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar disorder with psychosis (BPP) as their clinical diagnoses rely on symptoms that overlap. In this paper, we investigate if there is biological evidence to support the symptom-based clinical categories by looking across the three disorders using dynamic connectivity measures, and provide meaningful characteristics on which brain functional connectivity measures are commonly or uniquely impaired. Large-sample functional magnetic resonance image (fMRI) datasets from 623 subjects including 238 healthy controls (HCs), 113 SZ patients, 132 SAD patients, and 140 BPP patients were analyzed. First, we computed whole-brain dynamic functional connectivity (DFC) using a sliding-window technique, and then extracted the individual connectivity states by applying our previously proposed decomposition-based DFC analysis method. Next, with the features from the dominant connectivity state, we assessed the clinical categories by performing both four-group (SZ, SAD, BPP and healthy control groups) and pair-wise classification using a support vector machine within cross-validation. Furthermore, we comprehensively summarized the shared and unique connectivity alterations among the disorders. In terms of the classification performance, our method achieved 69% in the four-group classification and >80% in the between-group classifications for the mean overall accuracy; and yielded 66% in the four-group classification and >80% in the between-group classifications for the mean balanced accuracy. Through summarizing the features that were automatically selected in the classifications, we found that among the three symptom-related disorders, their disorder-common impairments primarily included the decreased connectivity strength between thalamus and cerebellum and the increased strength between postcentral gyrus and thalamus. The disorder-unique changes included more various brain regions, mainly in the temporal and frontal gyrus. Our work demonstrates that dynamic functional connectivity provides biological evidence that both common and unique impairments exist in psychosis sub-groups.

Transcriptional changes in the stress pathway are related to symptoms in schizophrenia and to mood in schizoaffective disorder

Altered levels of stress-signalling transcripts have been identified in post-mortem brains of people with schizophrenia, and since stress effects may be expressed throughout the body, there should be similar changes in peripheral cells. However, the extent to which these markers are altered in peripheral white blood cells of people with schizophrenia is not known. Furthermore, how peripheral cortisol and stress-related mRNA are associated with negative symptom severity and emotional states in people with schizophrenia versus schizoaffective disorder has not been determined. Whole blood samples were collected from 86 patients with either schizophrenia or schizoaffective disorder (56 people with schizophrenia and 30 people with schizoaffective disorder), and 77 healthy controls. Total RNA was isolated, cDNA was synthesized, and stress-signalling mRNA levels (for NR3C1, FKBP5, FKBP4, PTGES3 and BAG1) were determined. Stress and symptom severity scores were measured by the Depression, Anxiety and Stress Scale, and the Positive and Negative Syndrome Scale, respectively. We found increased FKBP5 mRNA, Z(156) = 2.5, p = 0.01, decreased FKBP4 mRNA, t(155) = 3.5, p ≤ 0.001, and decreased PTGES3 mRNA, t(153) = 3.0, p ≤ 0.01, in schizophrenia and schizoaffective disorder cohorts combined compared to healthy controls. Stress-related peripheral mRNA levels were differentially correlated with negative emotional states and symptom severity in schizoaffective disorder (β's = -0.45-0.56, p's = 0.05-0.001) and schizophrenia (β's = -0.34-0.38, p's = 0.04-0.03), respectively. Therefore, molecules of the stress-signalling pathway appear to differentially contribute to clinical features of schizophrenia versus schizoaffective disorder.

How Well Does the DSM-5 Capture Schizoaffective Disorder?

Schizoaffective disorder has long been recognized and quite variably defined. It has been variably positioned as a discrete entity, a variant of either schizophrenia or of a mood disorder, as simply reflecting the co-occurrence of schizophrenia and a mood disorder, and effectively reflecting a diagnosis along a continuum linking schizophrenia and bipolar disorder. This article considers historical views, some empirical data that advance consideration of its status, and focuses on its classification in the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5). DSM-5 criteria seemingly weight it in the direction of a schizophrenic illness, as do some empirical studies, whereas the empirical literature examining the response to lithium links it more closely to bipolar disorder. It is suggested that DSM-5's B and C criteria are operationally unfeasible. Some suggestions are provided for a simpler definition.

MMPs in learning and memory and neuropsychiatric disorders

Matrix metalloproteinases (MMPs) are a group of over twenty proteases, operating chiefly extracellularly to cleave components of the extracellular matrix, cell adhesion molecules as well as cytokines and growth factors. By virtue of their expression and activity patterns in animal models and clinical investigations, as well as functional studies with gene knockouts and enzyme inhibitors, MMPs have been demonstrated to play a paramount role in many physiological and pathological processes in the brain. In particular, they have been shown to influence learning and memory processes, as well as major neuropsychiatric disorders such as schizophrenia, various kinds of addiction, epilepsy, fragile X syndrome, and depression. A possible link connecting all those conditions is either physiological or aberrant synaptic plasticity where some MMPs, e.g., MMP-9, have been demonstrated to contribute to the structural and functional reorganization of excitatory synapses that are located on dendritic spines. Another common theme linking the aforementioned pathological conditions is neuroinflammation and MMPs have also been shown to be important mediators of immune responses.

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.

The reliability and clinical utility of ICD-11 schizoaffective disorder: A field trial

A major goal for the revision of the International Classification of Diseases and Related Health Problems, Tenth Edition (ICD-10) is to increase the clinical utility of the diagnostic system. Schizoaffective disorder has a history of poor diagnostic reliability due to the similarities and overlap in symptoms that it shares with other disorders, especially primary psychotic and mood disorders. The present study was part of the case-controlled field trials for ICD-11 and examines how the proposed changes for schizoaffective disorder may improve differential diagnosis and diagnostic accuracy. Clinicians from around the globe (n = 873) were provided with either ICD-10 or ICD-11 diagnostic guidelines and asked to apply them to case vignettes comparing schizoaffective disorder to schizophrenia and mood disorders with psychotic symptoms. Participants were asked to respond to follow-up diagnostic questions to determine which components of the diagnostic guidelines affected diagnostic accuracy. Overall, clinicians showed small improvements in accurately diagnosing vignettes using ICD-11 over ICD-10. Results suggest the discrepancy in diagnosing schizoaffective disorder is related primarily to the presence of mood symptoms and discrepancies about whether those symptoms are more consistent with schizoaffective disorder or a mood disorder diagnosis. Continuing to identify ways to more accurately capture this symptom picture will be important in the future as well as systematic efforts to educate clinicians about differential diagnosis.

Classification and Prediction of Brain Disorders Using Functional Connectivity: Promising but Challenging

Brain functional imaging data, especially functional magnetic resonance imaging (fMRI) data, have been employed to reflect functional integration of the brain. Alteration in brain functional connectivity (FC) is expected to provide potential biomarkers for classifying or predicting brain disorders. In this paper, we present a comprehensive review in order to provide guidance about the available brain FC measures and typical classification strategies. We survey the state-of-the-art FC analysis methods including widely used static functional connectivity (SFC) and more recently proposed dynamic functional connectivity (DFC). Temporal correlations among regions of interest (ROIs), data-driven spatial network and functional network connectivity (FNC) are often computed to reflect SFC from different angles. SFC can be extended to DFC using a sliding-window framework, and intrinsic connectivity states along the time-varying connectivity patterns are typically extracted using clustering or decomposition approaches. We also briefly summarize window-less DFC approaches. Subsequently, we highlight various strategies for feature selection including the filter, wrapper and embedded methods. In terms of model building, we include traditional classifiers as well as more recently applied deep learning methods. Moreover, we review representative applications with remarkable classification accuracy for psychosis and mood disorders, neurodevelopmental disorder, and neurological disorders using fMRI data. Schizophrenia, bipolar disorder, autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), Alzheimer's disease and mild cognitive impairment (MCI) are discussed. Finally, challenges in the field are pointed out with respect to the inaccurate diagnosis labeling, the abundant number of possible features and the difficulty in validation. Some suggestions for future work are also provided.

Functional outcome and service engagement in major depressive disorder with psychotic features: comparisons with schizophrenia, schizoaffective disorder and bipolar disorder in a 6-year follow-up of the Cavan-Monaghan First Episode Psychosis Study (CAMFEPS)

OBJECTIVE

While long-term outcome following a first psychotic episode is well studied in schizophrenia (SZ), schizoaffective disorder (SA), and bipolar disorder (BD), major depressive disorder with psychotic features (MDDP) has received less investigation. This study compares MDDP with SZ, SA, and BD at 6-year follow-up.

METHODS

At 6 years after a first psychotic episode, follow-up data on psychopathology, functioning, quality of life, and service engagement were obtained for 27 cases of MDDP in comparison to 60 SZ, 27 SA, and 35 BD.

RESULTS

Positive psychotic symptoms were less prominent in MDDP and BD than in SZ and SA. Negative symptoms, impaired functioning, and reduction in objectively determined quality of life were less prominent in MDDP and BD, intermediate in SA and most prominent in SZ. However, subjectively determined quality of life was indistinguishable across diagnoses. Service engagement was highest for MDDP, intermediate for SA and BD, and lowest for SZ.

CONCLUSIONS

At 6-year follow-up, these diagnoses are characterized by quantitative rather than qualitative differences in psychopathology, functionality, quality of life, and service engagement, with considerable overlap between them. These findings suggest that MDDP should join SZ, SA, and BD in a milieu of psychosis that transcends arbitrary boundaries.

Interactions between cannabis and schizophrenia in humans and rodents

In this review, we provide an overview of the relationship between cannabis use and the development of schizophrenia, using both animal and human studies. We further discuss the potential neural mechanism that may mediate the relationship between cannabis use and schizophrenia symptoms. We finally provide clinical implications and future studies that can further elucidate the relationship between cannabis and schizophrenia.