Increased circulating IL-18 levels in severe mental disorders indicate systemic inflammasome activation.

BACKGROUND: Schizophrenia (SCZ) and bipolar disorder (BD) are severe mental illnesses (SMI) that are part of a psychosis continuum, and dysregulated innate immune responses have been suggested to be involved in their pathophysiology. However, disease-specific immune mechanisms in SMI are not known yet. Recently, dyslipidemia has been linked to systemic inflammasome activation, and elevated atherogenic lipid ratios have been shown to correlate with circulating levels of inflammatory biomarkers in SMI. It is, however, not yet known if increased systemic cholesterol load leads to inflammasome activation in these patients. METHODS: We tested the hypothesis that patients with SCZ and BD display higher circulating levels compared to healthy individuals of key members of the IL-18 system using a large patient cohort (n = 1632; including 737 SCZ and 895 BD), and healthy controls (CTRL; n = 1070). In addition, we assessed associations with coronary artery disease risk factors in SMI, focusing on relevant inflammasome-related, neuroendocrine, and lipid markers. RESULTS: We report higher baseline levels of circulating IL-18 system components (IL-18, IL-18BPA, IL-18R1), and increased expression of inflammasome-related genes (NLRP3 and NLRC4) in the blood of patients relative to CTRL. We demonstrate a cholesterol dyslipidemia pattern in psychotic disorders, and report correlations between levels of blood cholesterol types and the expression of inflammasome system elements in SMI. CONCLUSIONS: Based on these results, we suggest a role for inflammasome activation/dysregulation in SMI. Our findings further the understanding of possible underlying inflammatory mechanisms and may expose important therapeutic targets in SMI.

Do sleep disturbances contribute to cognitive impairments in schizophrenia spectrum and bipolar disorders?

Sleep disturbances and cognitive impairments are both frequent across psychotic disorders, with debilitating effects on functioning and quality of life. This study aims to investigate if sleep disturbances are related to cognitive impairments in schizophrenia spectrum (SCZ) and bipolar disorders (BD), if this relationship varies between different sleep disturbances (insomnia, hypersomnia or delayed sleep phase (DSP)) and lastly, if this relationship differs between clinical groups and healthy controls (HC). We included 797 patients (SCZ = 457, BD = 340) from the Norwegian Centre for Mental Disorders Research (NORMENT) study in Norway. Sleep disturbances were based on items from the Inventory of Depressive Symptoms-Clinician rated scale (IDS-C). Their relationship with several cognitive domains was tested using separate ANCOVAs. A three-way between-groups ANOVA was conducted to test if the relationship with cognitive impairments varies between different sleep disturbances. These analyses revealed significantly poorer processing speed and inhibition in those with any sleep disturbance versus those without, also after adjusting for several covariates. The relationship between sleep disturbances and cognition was similar across SCZ and BD, and there were significant effects of insomnia and hypersomnia on both processing speed and inhibition. No association between sleep disturbances and cognition was found in HC. Sleep disturbances contribute to cognitive impairments in psychotic disorders. Processing speed and inhibition is poorer in patients with sleep disturbances. Impairments in these domains are related to insomnia and hypersomnia. These findings suggest that treating sleep disturbances is important to protect cognitive functioning, alongside cognitive remediation in psychotic disorders.

Comorbidity of Physical Disorders Among Patients With Severe Mental Illness With and Without Substance Use Disorders: A Systematic Review and Meta-Analysis.

Objective: Physical disorders in patients with severe mental illness (SMI) are common and they tend to be underdiagnosed by clinicians, which might lead to negative treatment outcomes. The presence of substance use disorders could further aggravate the situation. There are existing systematic reviews on physical disorders among individuals with SMI in general but none of these previous reviews stratified their findings by substance use disorder status. This study aimed to synthesize the evidence on the frequency of comorbid physical disorders among patients with SMI with or without substance use disorders. Methods: We searched for studies published in English between 1988 and 2017 in MEDLINE, Embase, CINAHL, PsycINFO, Global Health, Web of Science, Scopus, WHO Global Health Library (Global Index Medicus), Google Scholar, OpenGrey, the Grey Literature Report, Cochrane Library, International Standardized Randomized Controlled Trial Number Registry, WHO International Clinical Trials Registry Platform, ClinicalTrials.gov, Australian and New Zealand Clinical Trials Registry, and PROSPERO. There was no geographical restriction and the target population was adults (≥18 years) with diagnosed SMI including schizophrenia, bipolar disorder, and other psychotic illnesses. The outcome of interest was physical disorder. Results: A total of 6,994 records were retrieved. Only 30 papers (representing 24 studies) met our inclusion criteria and 13 studies were included in the meta-analysis. The prevalence of most of the reported physical disorders was higher in SMI patients with substance use disorders than in those without substance use disorders. When ranked according to pooled prevalence level, hypertension (35.6%), tardive dyskinesia (35.4%), and hepatitis C (26.9%) were the most prevalent physical disorders among SMI patients with substance use disorders. For SMI patients without substance use disorders, hypertension (32.5%), tardive dyskinesia (25.1%), and endocrine disease (19.0%) were more common. Estimates for diabetes (7.5% vs. 7.5%) and cardiovascular diseases (11.8% vs. 11.3%) were similar across groups. Conclusions: Physical disorders among SMI patients vary by substance use disorder status. Clinicians managing SMI in patients should screen for physical disorders and substance use disorders and provide treatment or referral. Registration: International Prospective Register of Systematic Reviews (PROSPERO) registration number CRD42017072286.

Developing "MinDag" - an app to capture symptom variation and illness mechanisms in bipolar disorder.

Introduction: The illness course of bipolar disorder (BD) is highly heterogeneous with substantial variation between individuals with the same BD subtype and within individuals over time. This heterogeneity is not well-delineated and hampers the development of more targeted treatment. Furthermore, although lifestyle-related behaviors are believed to play a role in the illness course, such mechanisms are poorly understood. To address some of these knowledge gaps, we aimed to develop an app for collection of multi-dimensional longitudinal data on BD-relevant symptoms and lifestyle-related behaviors. Methods: An app named MinDag was developed at the Norwegian Center for Mental Disorders Research in Oslo, Norway. The app was designed to tap into selected areas: mood, sleep, functioning/activities (social, occupational, physical exercise, leisure), substance use, emotional reactivity, and psychotic experiences. Ethical, security and usability issues were highly prioritized throughout the development and for the final app solution. We conducted beta- and pilot testing to eliminate technical problems and enhance usability and acceptability. Results: The final version of MinDag comprises six modules; three which are presented for the user once daily (the Sleep module in the morning and the Mood and Functoning/Activities modules in the evening) and three which are presented once weekly (Substance Use, Emotional Reactivity, and Psychotic Experiences modules). In general, MinDag was well received in both in the beta-testing and the pilot study, and the participants provided valuable feedback that was taken into account in the final development. MinDag is now in use as part of the research protocol at the NORMENT center and in a specialized treatment unit for BD at Oslo University Hospital in Norway. Discussion: We believe that MinDag will generate unique longitudinal data well suited for capturing the heterogeneity of BD and clarifying important unresolved issues such as how life-style related behavior may influence BD symptoms. Also, the experiences and knowledge derived from the development of MinDag may contribute to improving the security, acceptability, and benefit of digital tools in mental health.