Stratification and prediction of remission in first-episode psychosis patients: the OPTiMiSE cohort study

Negative symptoms and neurocognition in drug-naïve schizophrenia: moderating role of plasma neutrophil gelatinase-associated lipocalin (NGAL) and interferon-gamma (INF-γ)

Previous studies reported that peripheral inflammation was associated with cognitive performance and brain structure in schizophrenia. However, the moderating effect of inflammation has not been extensively studied. This study investigated whether inflammation markers moderated the association between negative symptoms and neurocognition in schizophrenia. This cross-sectional study included 137 drug-naïve schizophrenia patients (DNS) and 67 healthy controls (HC). We performed the Measurements and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) for cognitive assessment and the Positive and Negative Syndrome Scale (PANSS) for psychiatric symptoms. Plasma concentrations of interferon-gamma (IFN-γ), neutrophil gelatinase-associated lipocalin (NGAL), and nuclear factor kappa B (NF-κB) were measured. The MCCB neurocognition score, social cognition score, and total score; the plasma concentrations of NGAL, IFN-γ, and NF-κB were significantly decreased in DNS than in HC (all P's < 0.001). PANSS negative subscale (PNS), PANSS reduced expressive subdomain (RES) negatively correlated with neurocognition score (P = 0.007; P = 0.011, respectively). Plasma concentrations of IFN-γ and NGAL positively correlated with neurocognition score (P = 0.043; P = 0.008, relatively). The interactions of PNS × NGAL; PNS × IFN-γ; RES × IFN-γ accounted for significant neurocognition variance (P = 0.025; P = 0.029, P = 0.007, respectively). Simple slope analysis showed that all the above moderating effects only occurred in patients with near normal IFN-γ and NGAL levels. Plasma concentrations of IFN-γ and NGAL moderated the relationship between negative symptoms (especially RES) and neurocognition in schizophrenia. Treatment targeting inflammation may contribute to neurocognition improvement in schizophrenia.

Molecular mapping of a core transcriptional signature of microglia-specific genes in schizophrenia

Besides playing a central role in neuroinflammation, microglia regulate synaptic development and is involved in plasticity. Converging lines of evidence suggest that these different processes play a critical role in schizophrenia. Furthermore, previous studies reported altered transcription of microglia genes in schizophrenia, while microglia itself seems to be involved in the etiopathology of the disease. However, the regional specificity of these brain transcriptional abnormalities remains unclear. Moreover, it is unknown whether brain and peripheral expression of microglia genes are related. Thus, we investigated the expression of a pre-registered list of 10 genes from a core signature of human microglia both at brain and peripheral levels. We included 9 independent Gene Expression Omnibus datasets (764 samples obtained from 266 individuals with schizophrenia and 237 healthy controls) from 8 different brain regions and 3 peripheral tissues. We report evidence of a widespread transcriptional alteration of microglia genes both in brain tissues (we observed a decreased expression in the cerebellum, associative striatum, hippocampus, and parietal cortex of individuals with schizophrenia compared with healthy controls) and whole blood (characterized by a mixed altered expression pattern). Our results suggest that brain underexpression of microglia genes may represent a candidate transcriptional signature for schizophrenia. Moreover, the dual brain-whole blood transcriptional alterations of microglia/macrophage genes identified support the model of schizophrenia as a whole-body disorder and lend weight to the use of blood samples as a potential source of biological peripheral biomarkers.

Immunological Biomarkers as Predictors of Treatment Response in Psychotic Disorders

Psychotic disorders, notably schizophrenia, impose a detrimental burden on both an individual and a societal level. The mechanisms leading to psychotic disorders are multifaceted, with genetics and environmental factors playing major roles. Increasing evidence additionally implicates neuro-inflammatory processes within at least a subgroup of patients with psychosis. While numerous studies have investigated anti-inflammatory add-on treatments to current antipsychotics, the exploration of immunological biomarkers as a predictor of treatment response remains limited. This review outlines the current evidence from trials exploring the potential of baseline inflammatory biomarkers as predictors of the treatment effect of anti-inflammatory drugs as add-ons to antipsychotics and of antipsychotics alone. Several of the studies have found correlations between baseline immunological biomarkers and treatment response; however, only a few studies incorporated baseline biomarkers as a primary endpoint, and the findings thus need to be interpreted with caution. Our review emphasizes the need for additional research on the potential of repurposing anti-inflammatory drugs while utilizing baseline inflammatory biomarkers as a predictor of treatment response and to identify subgroups of individuals with psychotic disorders where add-on treatment with immunomodulating agents would be warranted. Future studies investigating the correlation between baseline inflammatory markers and treatment responses can pave the way for personalized medicine approaches in psychiatry centred around biomarkers such as specific baseline inflammatory biomarkers in psychotic disorders.

Altered neutrophil-to-lymphocyte ratio in patients with non-affective first episode psychosis and its relationship with symptom severity and cognitive impairment

Signatures of immune dysregulation as clinical biomarker for psychosis have remained unclear. We aimed to compare the Neutrophil-to-lymphocyte ratio (NLR) of patients with acute non-affective first-episode psychosis (FEP) with healthy controls after accounting for emotional states. We also explored the associations of NLR with symptom severity, onset profile and cognitive functions. The NLR was enumerated from complete blood count taken within a week of assessment. All FEP patients were rated on the Positive and Negative Syndrome Scale (PANSS) and the Clinician Global Impression-Severity (CGI-S) with verbal memory and executive functions assessed with the Cambridge Neuropsychological Test Automated Battery. Prevailing emotional state was measured with Beck Depression Inventory-II and Beck Anxiety Inventory. Out of seventy-nine consecutive FEP patients presenting to the study site, twenty-seven subjects were eligible and recruited. Twenty-seven age-/sex-matched controls were recruited. FEP patients had an NLR of 1.886 over the controls after accounting for scores on emotional states. The NLR of FEP patients was positively associated with CGI-S scores, PANSS positive symptom, disorganization and excitation scores. There was no significant correlation between NLR with the duration of untreated psychosis and cognitive performances. These findings support using NLR as a clinical biomarker in FEP, purporting further prospective study to measure NLR changes in the course of treatment.

Psychotic disorders as a framework for precision psychiatry

People with psychotic disorders can show marked interindividual variations in the onset of illness, responses to treatment and relapse, but they receive broadly similar clinical care. Precision psychiatry is an approach that aims to stratify people with a given disorder according to different clinical outcomes and tailor treatment to their individual needs. At present, interindividual differences in outcomes of psychotic disorders are difficult to predict on the basis of clinical assessment alone. Therefore, current research in psychosis seeks to build models that predict outcomes by integrating clinical information with a range of biological measures. Here, we review recent progress in the application of precision psychiatry to psychotic disorders and consider the challenges associated with implementing this approach in clinical practice.

Methodological and Quality Flaws in the Use of Artificial Intelligence in Mental Health Research: Systematic Review

BACKGROUND

Artificial intelligence (AI) is giving rise to a revolution in medicine and health care. Mental health conditions are highly prevalent in many countries, and the COVID-19 pandemic has increased the risk of further erosion of the mental well-being in the population. Therefore, it is relevant to assess the current status of the application of AI toward mental health research to inform about trends, gaps, opportunities, and challenges.

OBJECTIVE

This study aims to perform a systematic overview of AI applications in mental health in terms of methodologies, data, outcomes, performance, and quality.

METHODS

A systematic search in PubMed, Scopus, IEEE Xplore, and Cochrane databases was conducted to collect records of use cases of AI for mental health disorder studies from January 2016 to November 2021. Records were screened for eligibility if they were a practical implementation of AI in clinical trials involving mental health conditions. Records of AI study cases were evaluated and categorized by the International Classification of Diseases 11th Revision (ICD-11). Data related to trial settings, collection methodology, features, outcomes, and model development and evaluation were extracted following the CHARMS (Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies) guideline. Further, evaluation of risk of bias is provided.

RESULTS

A total of 429 nonduplicated records were retrieved from the databases and 129 were included for a full assessment-18 of which were manually added. The distribution of AI applications in mental health was found unbalanced between ICD-11 mental health categories. Predominant categories were Depressive disorders (n=70) and Schizophrenia or other primary psychotic disorders (n=26). Most interventions were based on randomized controlled trials (n=62), followed by prospective cohorts (n=24) among observational studies. AI was typically applied to evaluate quality of treatments (n=44) or stratify patients into subgroups and clusters (n=31). Models usually applied a combination of questionnaires and scales to assess symptom severity using electronic health records (n=49) as well as medical images (n=33). Quality assessment revealed important flaws in the process of AI application and data preprocessing pipelines. One-third of the studies (n=56) did not report any preprocessing or data preparation. One-fifth of the models were developed by comparing several methods (n=35) without assessing their suitability in advance and a small proportion reported external validation (n=21). Only 1 paper reported a second assessment of a previous AI model. Risk of bias and transparent reporting yielded low scores due to a poor reporting of the strategy for adjusting hyperparameters, coefficients, and the explainability of the models. International collaboration was anecdotal (n=17) and data and developed models mostly remained private (n=126).

CONCLUSIONS

These significant shortcomings, alongside the lack of information to ensure reproducibility and transparency, are indicative of the challenges that AI in mental health needs to face before contributing to a solid base for knowledge generation and for being a support tool in mental health management.

Education and long-term outcomes in first episode psychosis: 10-year follow-up study of the PAFIP cohort

BACKGROUND

Lower levels of education have been associated with the development of psychosis. Investigating educational achievement in the first episode of psychosis (FEP) patients may shed light on the origins of the alterations and on the variability of outcomes in psychotic disorders.

METHODS

Education achievement was explored in a large sample (n = 659) of FEP patients enrolled in programa de atención a fases iniciales de psicosis (PAFIP), a research and assistance program conducted in Spain. Patients were stratified according to the Spanish educational system according to their attendance in primary (low), secondary (medium) or university studies (high). The three groups were compared on available premorbid, clinical and neuropsychological variables. A subgroup of patients (n = 209), comprising the 10-year follow-up PAFIP cohort, were again compared.

RESULTS

Overall, 49% and 37% of FEP patients had low and medium levels of education, respectively. In total, 13% of the patients with a higher level of education were more frequently women (64%) and older at illness onset (36 years old), reported better premorbid adjustment, presented less severe positive symptoms and better functioning; and showed higher premorbid intelligence quotient and better performance on all the explored cognitive domains. Ten years later the FEP patients in the medium- and high-education groups had good global functioning and a neurocognitive performance within the normal limits.

CONCLUSIONS

Higher education is associated with better initial conditions and more favourable outcomes after an FEP. Sharing this information with the world's educational systems is essential to targeting resources and designing innovative programs or strategies to compensate for student difficulties.

Infections, Inflammation, and Psychiatric Illness: Review of Postmortem Evidence

While there is an abundance of epidemiological evidence implicating infectious agents in the etiology of severe mental illnesses, postmortem studies have not yet detected an increased incidence of microbial nucleic acid or proteins in the brains of people with mental illness. Nevertheless, abnormally expressed immune and inflammatory markers have consistently been found in the postmortem brain of patients with schizophrenia and mood disorders. Some of these abnormalities may be the result of an infection in utero or early in life that not only impacted the developing immune system but also the developing neurons of the brain. Some of the immune markers that are consistently found to be upregulated in schizophrenia implicate a possible viral infection and the blood brain barrier in the etiology and neuropathology of the disorder.

Machine Learning and Non-Affective Psychosis: Identification, Differential Diagnosis, and Treatment

PURPOSE OF REVIEW

This review will cover the most relevant findings on the use of machine learning (ML) techniques in the field of non-affective psychosis, by summarizing the studies published in the last three years focusing on illness detection and treatment.

RECENT FINDINGS

Multiple ML tools that include mostly supervised approaches such as support vector machine, gradient boosting, and random forest showed promising results by applying these algorithms to various sources of data: socio-demographic information, EEG, language, digital content, blood biomarkers, neuroimaging, and electronic health records. However, the overall performance, in the binary classification case, varied from 0.49, which is to be considered very low (i.e., noise), to over 0.90. These results are fully justified by different factors, some of which may be attributable to the preprocessing of the data, the wide variety of the data, and the a-priori setting of hyperparameters. One of the main limitations of the field is the lack of stratification of results based on biological sex, given that psychosis presents differently in men and women; hence, the necessity to tailor identification tools and data analytic strategies. Timely identification and appropriate treatment are key factors in reducing the consequences of psychotic disorders. In recent years, the emergence of new analytical tools based on artificial intelligence such as supervised ML approaches showed promises as a potential breakthrough in this field. However, ML applications in everyday practice are still in its infancy.

Effects of add-on Celecoxib treatment on patients with schizophrenia spectrum disorders and inflammatory cytokine profile trial (TargetFlame): study design and methodology of a multicentre randomized, placebo-controlled trial

Neuroinflammation has been proposed to impact symptomatology in patients with schizophrenia spectrum disorders. While previous studies have shown equivocal effects of treatments with add-on anti-inflammatory drugs such as Aspirin, N-acetylcysteine and Celecoxib, none have used a subset of prospectively recruited patients exhibiting an inflammatory profile. The aim of the study is to evaluate the efficacy and safety as well as the cost-effectiveness of a treatment with 400 mg Celecoxib added to an ongoing antipsychotic treatment in patients with schizophrenia spectrum disorders exhibiting an inflammatory profile. The “Add-on Celecoxib treatment in patients with schizophrenia spectrum disorders and inflammatory cytokine profile trial (TargetFlame)” is a multicentre randomized, placebo-controlled phase III investigator-initiated clinical trial with the following two arms: patients exhibiting an inflammatory profile receiving either add-on Celecoxib 400 mg/day or add-on placebo. A total of 199 patients will be assessed for eligibility by measuring blood levels of three pro-inflammatory cytokines, and 109 patients with an inflammatory profile, i.e. inflamed, will be randomized, treated for 8 weeks and followed-up for additional four months. The primary endpoint will be changes in symptom severity as assessed by total Positive and Negative Syndrome Scale (PANSS) score changes from baseline to week 8. Secondary endpoints include various other measures of psychopathology and safety. Additional health economic analyses will be performed. TargetFlame is the first study aimed at evaluating the efficacy, safety and cost-effectiveness of the antiphlogistic agent Celecoxib in a subset of patients with schizophrenia spectrum disorders exhibiting an inflammatory profile. With TargetFlame, we intended to investigate a novel precision medicine approach towards anti-inflammatory antipsychotic treatment augmentation using drug repurposing.

Clinical trial registration:http://www.drks.de/DRKS00029044 and https://trialsearch.who.int/Trial2.aspx?TrialID=DRKS00029044

Three-year outcomes and predictors for full recovery in patients with early-stage psychosis

In the present study, various outcomes over 3-year period in patients with early stage psychosis including remission, recovery, relapse and medication adherence were investigated. Predictor for full recovery at year 3 was also examined. Three-year follow-up data in 534 patients with schizophrenia spectrum disorders (SSD) and psychotic disorder not otherwise specified (PNOS) were examined for overall outcome trajectories. The data of completers at year 3 (n = 157) were used to identify predictors for recovery using logistic regression. The rates of symptomatic remission and full recovery at 6-, 12-, 24-, and 36-month follow-up were 76.10, 69.20, 79.50, and 79.10%, and 22.80, 26.40, 28.60, and 39.60%, respectively. The rates of drop-out and relapse at 6-, 12-, 24-, and 36-month follow-up were 25.4, 29.5, 38.6, and 51.1%, and 3.7, 8.9, 19.0, and 38.9%, respectively. The rates of good adherence and prescription of Long-Acting Injectable Antipsychotics (LAIA) at 6-, 12-, 24- and 36-month follow-up were 87.8, 88.0, 91.9, and 93.9%, and 18.3, 21.7, 22.0, and 25.5%, respectively. Significant predictors for full recovery were duration of untreated psychosis (DUP), family intimacy and physical activity. We observed similar or better results on remission, recovery, and relapse rates compared to other previous studies. Effective psychosocial intervention should be provided to shorten the gap between remission and recovery rates and to address DUP, family issues, and exercise to enhance recovery.

Clinical, Brain, and Multilevel Clustering in Early Psychosis and Affective Stages

Importance

Approaches are needed to stratify individuals in early psychosis stages beyond positive symptom severity to investigate specificity related to affective and normative variation and to validate solutions with premorbid, longitudinal, and genetic risk measures.

Objective

To use machine learning techniques to cluster, compare, and combine subgroup solutions using clinical and brain structural imaging data from early psychosis and depression stages.

Design, Setting, and Participants

A multisite, naturalistic, longitudinal cohort study (10 sites in 5 European countries; including major follow-up intervals at 9 and 18 months) with a referred patient sample of those with clinical high risk for psychosis (CHR-P), recent-onset psychosis (ROP), recent-onset depression (ROD), and healthy controls were recruited between February 1, 2014, to July 1, 2019. Data were analyzed between January 2020 and January 2022.

Main Outcomes and Measures

A nonnegative matrix factorization technique separately decomposed clinical (287 variables) and parcellated brain structural volume (204 gray, white, and cerebrospinal fluid regions) data across CHR-P, ROP, ROD, and healthy controls study groups. Stability criteria determined cluster number using nested cross-validation. Validation targets were compared across subgroup solutions (premorbid, longitudinal, and schizophrenia polygenic risk scores). Multiclass supervised machine learning produced a transferable solution to the validation sample.

Results

There were a total of 749 individuals in the discovery group and 610 individuals in the validation group. Individuals included those with CHR-P (n = 287), ROP (n = 323), ROD (n = 285), and healthy controls (n = 464), The mean (SD) age was 25.1 (5.9) years, and 702 (51.7%) were female. A clinical 4-dimensional solution separated individuals based on positive symptoms, negative symptoms, depression, and functioning, demonstrating associations with all validation targets. Brain clustering revealed a subgroup with distributed brain volume reductions associated with negative symptoms, reduced performance IQ, and increased schizophrenia polygenic risk scores. Multilevel results distinguished between normative and illness-related brain differences. Subgroup results were largely validated in the external sample.

Conclusions and Relevance

The results of this longitudinal cohort study provide stratifications beyond the expression of positive symptoms that cut across illness stages and diagnoses. Clinical results suggest the importance of negative symptoms, depression, and functioning. Brain results suggest substantial overlap across illness stages and normative variation, which may highlight a vulnerability signature independent from specific presentations. Premorbid, longitudinal, and genetic risk validation suggested clinical importance of the subgroups to preventive treatments.

The impact of educational attainment, intelligence and intellectual disability on schizophrenia: a Swedish population-based register and genetic study

Schizophrenia (SCZ) is highly heterogenous and no subtypes characterizing treatment response or longitudinal course well. Cognitive impairment is a core clinical feature of SCZ and a determinant of poorer outcome. Genetic overlap between SCZ and cognitive traits is complex, with limited studies of comprehensive epidemiological and genomic evidence. To examine the relation between SCZ and three cognitive traits, educational attainment (EDU), premorbid cognitive ability, and intellectual disability (ID), we used two Swedish samples: a national cohort (14,230 SCZ cases and 3,816,264 controls) and a subsample with comprehensive genetic data (4992 cases and 6009 controls). Population-based analyses confirmed worse cognition as a risk factor for SCZ, and the pedigree and SNP-based genetic correlations were comparable. In the genotyped cases, those with high EDU and premorbid cognitive ability tended to have higher polygenetic risk scores (PRS) of EDU and intelligence and fewer rare exonic variants. Finally, by applying an empirical clustering method, we dissected SCZ cases into four replicable subgroups characterized by EDU and ID. In particular, the subgroup with higher EDU in the national cohort had fewer adverse outcomes including long hospitalization and death. In the genotyped subsample, this subgroup had higher PRS of EDU and no excess of rare genetic burdens than controls. In conclusion, we found extensive evidence of a robust relation between cognitive traits and SCZ, underscoring the importance of cognition in dissecting the heterogeneity of SCZ.

Reduced Serum Levels of Soluble Interleukin-15 Receptor α in Schizophrenia and Its Relationship to the Excited Phenotype

Our previous studies documented that interleukin-15 receptor α (IL-15Rα) knockout (KO) mice exhibited hyperactivity, memory impairment, and desperate behavior, which are core features of schizophrenia and depression. Due to the overlapping symptomology and pathogenesis observed for schizophrenia and depression, the present study attempted to determine whether IL-15Rα was associated with the risk of schizophrenia or depression. One hundred fifty-six participants, including 63 schizophrenia patients, 29 depressive patients, and 64 age-matched healthy controls, were enrolled in the study. We investigated the circulating levels of soluble IL-15Rα and analyzed potential links between the IL-15Rα levels and clinical symptoms present in schizophrenia or depressive patients. We observed reduced serum IL-15Rα levels in schizophrenia patients, but not depressive patients compared with controls. Moreover, a significant negative association was observed between the circulating IL-15Rα levels and excited phenotypes in the schizophrenia patients. The IL-15Rα KO mice displayed pronounced pre-pulse inhibition impairment, which was a typical symptom of schizophrenia. Interestingly, the IL-15Rα KO mice exhibited a remarkable elevation in the startle amplitude in the startle reflex test compared to wild type mice. These results demonstrated that serum levels of soluble IL-15Rα were reduced in schizophrenia and highlighted the relationship of IL-15Rα and the excited phenotype in schizophrenia patients and mice.

Short-chain fatty acids in patients with schizophrenia and ultra-high risk population

BACKGROUND

Individuals who experience the prodromal phase of schizophrenia (SCZ), a common and complex psychiatric disorder, are referred to as ultra-high-risk (UHR) individuals. Short-chain fatty acid (SCFA) is imperative in the microbiota-gut-brain axis and brain function. Accumulating amount of evidence shows the connections between psychiatric disorders and SCFAs. This study aims to explore the underlying roles SCFAs play in SCZ by investigating the association of alterations in SCFAs concentrations with common cognitive functions in both the SCZ and UHR populations.

METHODS

The study recruited 59 SCZ patients (including 15 participants converted from the UHR group), 51 UHR participants, and 40 healthy controls (HC) within a complete follow-up of 2 years. Results of cognitive functions, which were assessed by utilizing HVLT-R and TMT, and serum concentrations of SCFAs were obtained for all participants and for UHR individuals at the time of their conversion to SCZ.

RESULTS

Fifteen UHR participants converted to SCZ within a 2-year follow-up. Valeric acid concentration levels were lower in both the baseline of UHR individuals whom later converted to SCZ (p = 0.046) and SCZ patients (p = 0.036) than the HC group. Additionally, there were lower concentrations of caproic acid in the baseline of UHR individuals whom later transitioned to SCZ (p = 0.019) and the UHR group (p = 0.016) than the HC group. Furthermore, the caproic acid levels in the UHR group are significantly positively correlated with immediate memory (r = 0.355, p = 0.011) and negatively correlated with TMT-B (r = -0.366, p = 0.009). Significant differences in levels of acetic acid, butyric acid and isovaleric acid were absent among the three groups and in UHR individuals before and after transition to SCZ.

CONCLUSION

Our study suggests that alterations in concentrations of SCFAs may be associated with the pathogenesis and the cognitive impairment of schizophrenia. Further researches are warranted to explore this association. The clinical implications of our findings were discussed.

Inflammation Subtypes and Translating Inflammation-Related Genetic Findings in Schizophrenia and Related Psychoses: A Perspective on Pathways for Treatment Stratification and Novel Therapies

Dysregulation of immunological and inflammatory processes is frequently observed in psychotic disorders. Numerous studies have examined the complex components of innate and adaptive immune processes in schizophrenia and related psychoses. Elevated inflammation in these conditions is related to neurobiological phenotypes and associated with both genetics and environmental exposures. Recent studies have utilized multivariate cytokine approaches to identify what appears to be a subset of individuals with elevated inflammation. The degree to which these findings represent a general process of dysregulated inflammation or whether there are more refined subtypes remains unclear. Brain-imaging studies have attempted to establish the link between peripheral inflammation and gray matter disruption, white matter abnormalities, and neuropsychological phenotypes. However, the interplay between peripheral inflammation and neuroinflammation, as well as the consequences of this interplay, in the context of psychosis remains unclear and requires further investigation. This Perspectives article reviews the following elements of immune dysregulation and its clinical and therapeutic implications: (1) evidence supporting inflammation and immune dysregulation in schizophrenia and related psychoses; (2) recent advances in approaches to characterizing subgroups of patients with elevated inflammation; (3) relationships between peripheral inflammation and brain-imaging indicators of neuroinflammation; (4) convergence of large-scale genetic findings and peripheral inflammation findings; and (5) therapeutic implications: anti-inflammation interventions leveraging genetic findings for drug discovery and repurposing. We offer perspectives and examples of how multiomics technologies may be useful for constructing and studying immunogenetic signatures. Advancing research in this area will facilitate biomarker discovery, disease subtyping, and the development of etiological treatments for immune dysregulation in psychosis.

The poly(I:C)-induced maternal immune activation model; a systematic review and meta-analysis of cytokine levels in the offspring

The maternal polyinosinic:polycytidylic acid (poly(I:C)) animal model is frequently used to study how maternal immune activation may impact neuro development in the offspring. Here, we present the first systematic review and meta-analysis on the effects of maternal poly(I:C) injection on immune mediators in the offspring and provide an openly accessible systematic map of the data including methodological characteristics.

Pubmed and EMBASE were searched for relevant publications, yielding 45 unique papers that met inclusion criteria. We extracted data on immune outcomes and methodological characteristics, and assessed the risk of bias. The descriptive summary showed that most studies reported an absence of effect, with an equal number of studies reporting an increase or decrease in the immune mediator being studied.

Meta-analysis showed increased IL-6 concentrations in the offspring of poly(I:C) exposed mothers. This effect appeared larger prenatally than post-weaning. Furthermore, poly(I:C) administration during mid-gestation was associated with higher IL-6 concentrations in the offspring. Maternal poly(I:C) induced changes in IL-1β, Il-10 and TNF-α concentrations were small and could not be associated with age of offspring, gestational period or sampling location. Finally, quality of reporting of potential measures to minimize bias was low, which stresses the importance of adherence to publication guidelines.

Since neurodevelopmental disorders in humans tend to be associated with lifelong changes in cytokine concentrations, the absence of these effects as identified in this systematic review may suggest that combining the model with other etiological factors in future studies may provide further insight in the mechanisms through which maternal immune activation affects neurodevelopment.

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Long-term effects of maternal poly(I:C) on immune mediators in the offspring appear limited.

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Prenatal measurements and mid gestation poly(I:C) injection are associated with increases in IL-6 concentrations.

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Variety in methodological conduct hampers identification of key elements that affect cytokine concentrations.

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The quality of reporting of potential measures to minimize bias is poor.

PLAN-e-PSY, a mobile application to improve case management and patient's functioning in first episode psychosis: protocol for an open-label, multicentre, superiority, randomised controlled trial

INTRODUCTION

The prognosis of first episode psychosis (FEP), which is a severe disorder, can be notably impaired by patients' disengagement from healthcare providers. Coordinated specialty care with case management is now considered as the gold standard in this population, but there are still challenges for engagement with subsequent functional impairments. Youth-friendly and patient-centred clinical approaches are sought to improve engagement in patients with FEP. Mobile applications are widely used by young people, including patients with FEP, and can increase the youth friendliness of clinical tools. We hypothesise that a co-designed mobile application used during case management can improve functioning in patients with FEP as compared with usual case management practices.

METHODS AND ANALYSIS

A mobile case management application for planning and monitoring individualised care objectives will be co-designed with patients, caregivers and health professionals in a recovery-oriented approach. The application will be compared with usual case management practices in a multicentre, two-arm and parallel groups clinical trial. Patients will be recruited by specialised FEP teams. Impact on functioning will be assessed using the Personal and Social Performance Scale; the variation between baseline and 12 months in each group (control and active) will be the primary outcome.

ETHICS AND DISSEMINATION

This study has been approved by the Inserm Institutional Review Board IRB00003888 (Comité d'évaluation éthique de l'INSERM, reference number 20-647). The results of the study will be published in a peer-reviewed journal and presented at national and international conferences. We will also communicate the results to patients and family representatives' associations. An optimised version of the application will be then disseminated through the French FEP network (Transition Network).

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov: NCT04657380.

Clozapine Response in Schizophrenia and Hematological Changes

BACKGROUND

Clozapine is the only effective medication for treatment-resistant schizophrenia; however, its mechanism of action remains unclear. The present study explored whether its effectiveness is related to changes in hematological measures after clozapine initiation.

METHODS

Patients with treatment-resistant schizophrenia commenced on clozapine between January 2007 and December 2014 by the United Kingdom's largest mental health trust were identified from electronic patient records. Hematological data from these patients were obtained from a monitoring registry. White blood cell, neutrophil, and platelet count were assessed at baseline and during the early phase of clozapine treatment. Clozapine response at 3 months was defined as "much," or "very much" improved on the seven-point Clinical Global Impression-Improvement (CGI-I) subscale.

RESULTS

In the total sample (n = 188), clozapine initiation was associated with a significant transient increase (peaking in weeks 3 to 4) in white blood cell, neutrophil, and platelet count (P < 0.001). There were 112 (59.6%) patients that responded to treatment; however, none of the hematological factors assessed at baseline, nor changes in these factors, were directly associated with treatment response.

IMPLICATIONS

Clozapine treatment is associated with transient hematological changes during the first month of treatment; however, there was no evidence that these were related to the therapeutic response.

The prevention of relapses in first episodes of schizophrenia: The 2EPs Project, background, rationale and study design

Up to 80% of first-episode psychosis patients suffer a relapse within five years of the remission. Relapse should be an important focus of prevention given the potential harm to the patient and family. It threatens to disrupt their psychosocial recovery, increases the risk of resistance to treatment and has been associated with greater direct and indirect costs for society. Based on a previous project entitled "Genotype-phenotype and environment. Application to a predictive model in first psychotic episodes" (PEPs Project), the project "Clinical and neurobiological determinants of second episodes of schizophrenia. Longitudinal study of first episode of psychosis" was designed, also known as the 2EPs Project. It aimed to identify and characterize those factors that predict a relapse within the years immediately following a first episode. This project has focused on following the clinical course, with neuropsychological assessments, biological and neuroanatomical measures, genetic adherence and physical health monitoring in order to compare a subgroup of patients with a second episode to another group of patients which remains in remission. The main objective of the present article is to describe the rationale of the 2EPs Project, explaining the measurement approach adopted and providing an overview of the selected clinical and functional measures. 2EPs Project is a multicenter, coordinated, naturalistic, longitudinal follow-up study over three years in a Spanish sample of patients in remission after a first-psychotic episode of schizophrenia. It is closely monitoring the clinical course of the cases recruited to compare the subgroup of patients with a second episode to that which remains in remission. The sample is composed of 223 subjects recruited from 15 clinical centres in Spain with experience of the preceding PEPs Study project, albeit 2EPs being an expanded version with new basic groups in biological research. From the total sample recruited, 63 patients presented a relapse (44%). 2EPs arose to characterize first episodes in an exhaustive, novel and multimodal way, thus contributing towards the development of a predictive model of relapse. Identifying the characteristics of patients who relapse could improve early detection and intervention.

The Role of Cytokines in the Pathogenesis of Schizophrenia

Schizophrenia is a chronic mental illness of unknown etiology. A growing and compelling body of evidence implicates immunologic dysfunction as the key element in its pathomechanism. Cytokines, whose altered levels have been increasingly reported in various patient populations, are the major mediators involved in the coordination of the immune system. The available literature reports both elevated levels of proinflammatory as well as reduced levels of anti-inflammatory cytokines, and their effects on clinical status and neuroimaging changes. There is evidence of at least a partial genetic basis for the association between cytokine alterations and schizophrenia. Two other factors implicated in its development include early childhood trauma and disturbances in the gut microbiome. Moreover, its various subtypes, characterized by individual symptom severity and course, such as deficit schizophrenia, seem to differ in terms of changes in peripheral cytokine levels. While the use of a systematic review methodology could be difficult due to the breadth and diversity of the issues covered in this review, the applied narrative approach allows for a more holistic presentation. The aim of this narrative review was to present up-to-date evidence on cytokine dysregulation in schizophrenia, its effect on the psychopathological presentation, and links with antipsychotic medication. We also attempted to summarize its postulated underpinnings, including early childhood trauma and gut microbiome disturbances, and propose trait and state markers of schizophrenia.

Multivariate relationships between peripheral inflammatory marker subtypes and cognitive and brain structural measures in psychosis

Elevations in peripheral inflammatory markers have been reported in patients with psychosis. Whether this represents an inflammatory process defined by individual or subgroups of markers is unclear. Further, relationships between peripheral inflammatory marker elevations and brain structure, cognition, and clinical features of psychosis remain unclear. We hypothesized that a pattern of plasma inflammatory markers, and an inflammatory subtype established from this pattern, would be elevated across the psychosis spectrum and associated with cognition and brain structural alterations. Clinically stable psychosis probands (Schizophrenia spectrum, n = 79; Psychotic Bipolar disorder, n = 61) and matched healthy controls (HC, n = 60) were assessed for 15 peripheral inflammatory markers, cortical thickness, subcortical volume, cognition, and symptoms. A combination of unsupervised exploratory factor analysis and hierarchical clustering was used to identify inflammation subtypes. Levels of IL6, TNFα, VEGF, and CRP were significantly higher in psychosis probands compared to HCs, and there were marker-specific differences when comparing diagnostic groups. Individual and/or inflammatory marker patterns were associated with neuroimaging, cognition, and symptom measures. A higher inflammation subgroup was defined by elevations in a group of 7 markers in 36% of Probands and 20% of HCs. Probands in the elevated inflammatory marker group performed significantly worse on cognitive measures of visuo-spatial working memory and response inhibition, displayed elevated hippocampal, amygdala, putamen and thalamus volumes, and evidence of gray matter thickening compared to the proband group with low inflammatory marker levels. These findings specify the nature of peripheral inflammatory marker alterations in psychotic disorders and establish clinical, neurocognitive and neuroanatomic associations with increased inflammatory activation in psychosis. The identification of a specific subgroup of patients with inflammatory alteration provides a potential means for targeting treatment with anti-inflammatory medications.

A Meta-Analysis of the Influence of Antipsychotics on Cytokines Levels in First Episode Psychosis

Background: Cytokines have a major impact on the neurotransmitter networks that are involved in schizophrenia pathophysiology. First Episode Psychosis (FEP) patients exhibit abnormalities in cytokines levels prior to the start of treatment. Previous studies showed that antipsychotic treatment modulates cytokines levels. The aim of this meta-analysis is to further investigate this relationship. Methods: Several online databases were searched. For meta-analysis of selected studies, we analysed variables containing the number of cases, mean and standard deviation of IL-1β, IL-2, IL-4, IL-6, IL-10, IL-17, TNF-α, IFN-γ levels before, and after, antipsychotic treatment. Results: 12 studies were included in the meta-analysis. Our main results demonstrate that, in FEP patients, antipsychotic treatment is related to decreased concentrations of pro-inflammatory IL-1β, IL-6, IFN-γ, TNF-α and anti-inflammatory IL-4, IL-10 cytokines. On the other hand, levels of pro-inflammatory IL-2 and IL-17 remain unaffected. Conclusions: When compared with other meta-analyses of studies involving FEP individuals, results we obtained are consistent regarding decrease in IL-1β, IL-6. Comparing outcomes of our study with meta-analyses of schizophrenic subjects, in general, our results are consistent in IL-1β, IL-6, TNF-α, IFN-γ, IL-2. Our meta-analysis is the only one which indicates a decrease in anti-inflammatory IL-10 in FEP patients after antipsychotic treatment.

Dopamine and Glutamate in Antipsychotic-Responsive Compared With Antipsychotic-Nonresponsive Psychosis: A Multicenter Positron Emission Tomography and Magnetic Resonance Spectroscopy Study (STRATA)

The variability in the response to antipsychotic medication in schizophrenia may reflect between-patient differences in neurobiology. Recent cross-sectional neuroimaging studies suggest that a poorer therapeutic response is associated with relatively normal striatal dopamine synthesis capacity but elevated anterior cingulate cortex (ACC) glutamate levels. We sought to test whether these measures can differentiate patients with psychosis who are antipsychotic responsive from those who are antipsychotic nonresponsive in a multicenter cross-sectional study. 1H-magnetic resonance spectroscopy (1H-MRS) was used to measure glutamate levels (Glucorr) in the ACC and in the right striatum in 92 patients across 4 sites (48 responders [R] and 44 nonresponders [NR]). In 54 patients at 2 sites (25 R and 29 NR), we additionally acquired 3,4-dihydroxy-6-[18F]fluoro-l-phenylalanine (18F-DOPA) positron emission tomography (PET) to index striatal dopamine function (Kicer, min-1). The mean ACC Glucorr was higher in the NR than the R group after adjustment for age and sex (F1,80 = 4.27; P = .04). This was associated with an area under the curve for the group discrimination of 0.59. There were no group differences in striatal dopamine function or striatal Glucorr. The results provide partial further support for a role of ACC glutamate, but not striatal dopamine synthesis, in determining the nature of the response to antipsychotic medication. The low discriminative accuracy might be improved in groups with greater clinical separation or increased in future studies that focus on the antipsychotic response at an earlier stage of the disorder and integrate other candidate predictive biomarkers. Greater harmonization of multicenter PET and 1H-MRS may also improve sensitivity.

Changes in peripheral blood compounds following psychopharmacological treatment in drug-naïve first-episode patients with either schizophrenia or major depressive disorder: a meta-analysis

BACKGROUND

This meta-analysis on peripheral blood compounds in drug-naïve first-episode patients with either schizophrenia or major depressive disorder (MDD) examined which compounds change following psychopharmacological treatment.

METHODS

The Embase, PubMed and PsycINFO databases were systematically searched for longitudinal studies reporting measurements of blood compounds in drug-naïve first-episode schizophrenia or MDD.

RESULTS

For this random-effects meta-analysis, we retrieved a total of 31 studies comprising 1818 schizophrenia patients, and 14 studies comprising 469 MDD patients. Brain-derived neurotrophic factor (BDNF) increased following treatment in schizophrenia (Hedges' g (g): 0.55; 95% confidence interval (CI) 0.39-0.70; p < 0.001) and MDD (g: 0.51; CI 0.06-0.96; p = 0.027). Interleukin (IL)-6 levels decreased in schizophrenia (g: -0.48; CI -0.85 to -0.11; p = 0.011), and for MDD a trend of decreased IL-6 levels was observed (g: -0.39; CI -0.87 to 0.09; p = 0.115). Tumor necrosis factor alpha (TNFα) also decreased in schizophrenia (g: -0.34; CI -0.68 to -0.01; p = 0.047) and in MDD (g: -1.02; CI -1.79 to -0.25; p = 0.009). Fasting glucose levels increased only in schizophrenia (g: 0.26; CI 0.07-0.44; p = 0.007), but not in MDD. No changes were found for C-reactive protein, IL-1β, IL-2 and IL-4.

CONCLUSIONS

Psychopharmacological treatment has modulating effects on BDNF and TNFα in drug-naïve first-episode patients with either schizophrenia or MDD. These findings support efforts for further research into transdiagnostic preventive strategies and augmentation therapy for those with immune dysfunctions.

General Functioning in Patients With First-Episode Psychosis After the First 18 Months of Treatment

BACKGROUND

One of the main goals in the treatment of first-episode psychosis (FEP) is achieving functional remission. This study aims to analyze whether initial neurocognitive status and the use of specific pharmacological and psychosocial treatment options in FEP can predict general functioning after 18 months of treatment.

METHODS

We conducted a longitudinal naturalistic study with a sample of 129 patients with FEP treated at 2 Croatian psychiatric clinics from 2016until 2018. Ordinal regression was used to predict the global level of functioning assessed with the Global Assessment of Functioning scale (GAF) at the 18th month of treatment from the baseline symptoms (assessed with a set of neurocognitive tests) and different treatment options.

RESULTS

Higher score on GAF at the 18th month was significantly predicted by female sex, better baseline verbal memory and GAF scores, and the type of treatment. Group multimodal psychosocial treatment, antipsychotic polytherapy, and not being treated with sedatives at baseline predicted better GAF scores at follow-up. In the exploratory analysis, taking sedatives in the final assessment and being rehospitalized due to relapse predicted worse GAF scores at the end of follow-up.

CONCLUSIONS

Although baseline neurocognitive features and baseline general functioning seem to influence the overall long-term functioning of persons with FEP, addition of a multimodal group psychosocial treatment program and appropriate medication seem to be equally important for improving the patients' level of functioning after the FEP.

Topology predicts long-term functional outcome in early psychosis

Early intervention in psychosis is crucial to improving patient response to treatment and the functional deficits that critically affect their long-term quality of life. Stratification tools are needed to personalize functional deficit prevention strategies at an early stage. In the present study, we applied topological tools to analyze symptoms of early psychosis patients, and detected a clear stratification of the cohort into three groups. One of the groups had a significantly better psychosocial outcome than the others after a 3-year clinical follow-up. This group was characterized by a metabolic profile indicative of an activated antioxidant response, while that of the groups with poorer outcome was indicative of oxidative stress. We replicated in a second cohort the finding that the three distinct clinical profiles at baseline were associated with distinct outcomes at follow-up, thus validating the predictive value of this new stratification. This approach could assist in personalizing treatment strategies.

Real-World Functioning in Patients With Schizophrenia: Beyond Negative and Cognitive Symptoms

Introduction: Interest in the idea of recovery for certain patients with schizophrenia has been growing over the last decade. Improving symptomatology and functioning is crucial for achieving this. Our study aims to identify those factors that substantially contribute to real-world functioning in these patients. Methods: We carried out a cross-sectional study in stable outpatients with schizophrenia on maintenance antipsychotic monotherapy. Patients: We studied 144 outpatients with schizophrenia (DSM-IV-TR criteria) meeting the following criteria: (1) 18-65 years of age; (2) being clinically stable for at least the previous three months; (3) on maintenance antipsychotic monotherapy (prescriptions ≤ 10 mg olanzapine, ≤200 mg quetiapine, or ≤100 mg levomepromazine as hypnotics were also allowed); and (4) written informed consent. Assessment: We collected information on demographic and clinical variables by using an ad hoc questionnaire. For psychopathology, we employed the Spanish versions of the following psychometric instruments: the Positive and Negative Syndrome Scale (PANSS), the Brief Negative Symptom Scale (BNSS-Sp), and the Calgary Depression Scale (CDS). In addition, cognitive domains were assessed using the Verbal Fluency Test (VFT), the Digit Symbol Substitution Test (DSST), and the Trail Making Test, parts A and B (TMT-A and TMT-B). Finally, we employed the Spanish versions of the University of California San Diego Performance-based Skills Assessment (Sp-UPSA) and the Personal and Social Performance (PSP) for assessing functional capacity and real-world functioning, respectively. Statistical analysis: A forward stepwise regression was conducted by entering those variables significantly associated with PSP total score into the univariate analyses (Student's t-test, ANOVA with Duncan's post-hoc test, or bivariate Pearson correlation). Results: A total of 144 patients; mean age 40 years, 64% males, mean length of illness 12.4 years, PSP total score 54.3. The final model was a significant predictor of real-world functioning [F _{(7, 131)} = 36.371, p < 0.001] and explained 66.0% of the variance. Variables retained in the model: BNSS-Sp abulia, asociality, and blunted affect, PANSS general psychopathology, Sp-UPSA transportation, TMT-B, and heart rate. Conclusion: Our model will contribute to a more efficient and personalized daily clinical practice by assigning specific interventions to each patient based on specific impaired factors in order to improve functioning.

Präzisionspsychiatrie und der Beitrag von Brain Imaging und anderen Biomarkern

'Precision Psychiatry' as the psychiatric variant of 'Precision Medicine' aims to provide high-level diagnosis and treatment based on robust biomarkers and tailored to the individual clinical, neurobiological, and genetic constitution of the patient. The specific peculiarity of psychiatry, in which disease entities are normatively defined based on clinical experience and are also significantly influenced by contemporary history, society and philosophy, has so far made the search for valid and reliable psychobiological connections difficult. Nevertheless, considerable progress has now been made in all areas of psychiatric research, made possible above all by the critical review and renewal of previous concepts of disease and psychopathology, the increased orientation towards neurobiology and genetics, and in particular the use of machine learning methods. Notably, modern machine learning methods make it possible to integrate high-dimensional and multimodal data sets and generate models which provide new psychobiological insights and offer the possibility of individualized, biomarker-driven single-subject prediction of diagnosis, therapy response and prognosis. The aim of the present review is therefore to introduce the concept of 'Precision Psychiatry' to the interested reader, to concisely present modern, machine learning methods required for this, and to clearly present the current state and future of biomarker-based 'precision psychiatry'.

Effects of Antipsychotic Drugs: Cross Talk Between the Nervous and Innate Immune System

Converging lines of evidence suggest that activation of microglia (innate immune cells in the central nervous system [CNS]) is present in a subset of patients with schizophrenia. The extent to which antipsychotic drug treatment contributes to or combats this effect remains unclear. To address this question, we reviewed the literature for evidence that antipsychotic exposure influences brain microglia as indexed by in vivo neuroimaging and post-mortem studies in patients with schizophrenia and experimental animal models. We found no clear evidence from clinical studies for an effect of antipsychotics on either translocator protein (TSPO) radioligand binding (an in vivo neuroimaging measure of putative gliosis) or markers of brain microglia in post-mortem studies. In experimental animals, where drug and illness effects may be differentiated, we also found no clear evidence for consistent effects of antipsychotic drugs on TSPO radioligand binding. By contrast, we found evidence that chronic antipsychotic exposure may influence central microglia density and morphology. However, these effects were dependent on the dose and duration of drug exposure and whether an immune stimulus was present or not. In the latter case, antipsychotics were generally reported to suppress expression of inflammatory cytokines and inducible inflammatory enzymes such as cyclooxygenase and microglia activation. No clear conclusions could be drawn with regard to any effect of antipsychotics on brain microglia from current clinical data. There is evidence to suggest that antipsychotic drugs influence brain microglia in experimental animals, including possible anti-inflammatory actions. However, we lack detailed information on how these drugs influence brain microglia function at the molecular level. The clinical relevance of the animal data with regard to beneficial treatment effects and detrimental side effects of antipsychotic drugs also remains unknown, and further studies are warranted.

The prevention of relapses in first episodes of schizophrenia: The 2EPs Project, background, rationale and study design

Up to 80% of first-episode psychosis patients suffer a relapse within five years of the remission. Relapse should be an important focus of prevention given the potential harm to the patient and family. It threatens to disrupt their psychosocial recovery, increases the risk of resistance to treatment and has been associated with greater direct and indirect costs for society. Based on a previous project entitled "Genotype-phenotype and environment. Application to a predictive model in first psychotic episodes" (PEPs Project), the project "Clinical and neurobiological determinants of second episodes of schizophrenia. Longitudinal study of first episode of psychosis" was designed, also known as the 2EPs Project. It aimed to identify and characterize those factors that predict a relapse within the years immediately following a first episode. This project has focused on following the clinical course, with neuropsychological assessments, biological and neuroanatomical measures, genetic adherence and physical health monitoring in order to compare a subgroup of patients with a second episode to another group of patients which remains in remission. The main objective of the present article is to describe the rationale of the 2EPs Project, explaining the measurement approach adopted and providing an overview of the selected clinical and functional measures. 2EPs Project is a multicenter, coordinated, naturalistic, longitudinal follow-up study over three years in a Spanish sample of patients in remission after a first-psychotic episode of schizophrenia. It is closely monitoring the clinical course of the cases recruited to compare the subgroup of patients with a second episode to that which remains in remission. The sample is composed of 223 subjects recruited from 15 clinical centres in Spain with experience of the preceding PEPs Study project, albeit 2EPs being an expanded version with new basic groups in biological research. From the total sample recruited, 63 patients presented a relapse (44%). 2EPs arose to characterize first episodes in an exhaustive, novel and multimodal way, thus contributing towards the development of a predictive model of relapse. Identifying the characteristics of patients who relapse could improve early detection and intervention.

Blood tests to diagnose schizophrenia: self-imposed limits in psychiatry

The naturalisation of mental disorders-ie, their translation into measurable and preferably molecular variables-has not progressed despite breath-taking discoveries in the neurosciences. We ask whether self-inflicted limits exist among psychiatrists that would prevent them from supporting an imaginary perfect blood test with diagnostic specificity, sensitivity, and validity, which was able to replace clinical diagnosis completely. Although relevant for many mental disorders, we use the clinical disease category schizophrenia here as an example to discuss factors that oppose the naturalisation of clinical disease categories. We defend the provocative position that a complete substitution of the clinical diagnosis by a blood test is generally not desired among clinicians because various factors perpetuate the current diagnostic culture. These are (1) methodological problems, such as a falsely presumed homogeneity of biological causes under the umbrella of one clinical diagnosis that prevents efficient subset identification, (2) professional fears, such as loss of importance of interview-diagnostic expert skills, and (3) conceptual problems, such as a dualistic mindset. We posit that doubts regarding the possibility of a blood test for diagnosing schizophrenia can subtly result in a negative self-fulfilling prophecy, discouraging serious scientific efforts to develop one. We give historical examples of how some of these problems have been solved in other medical disciplines. We predict that only blood tests that improve diagnostic accuracy but do not displace the primacy of clinical diagnosis will be successful. In the future, novel professional expertise for orchestrating various biological variables together with clinical criteria will be needed.

Dissimilarity in Sulcal Width Patterns in the Cortex can be Used to Identify Patients With Schizophrenia With Extreme Deficits in Cognitive Performance

Schizophrenia is a biologically complex disorder with multiple regional deficits in cortical brain morphology. In addition, interindividual heterogeneity of cortical morphological metrics is larger in patients with schizophrenia when compared to healthy controls. Exploiting interindividual differences in the severity of cortical morphological deficits in patients instead of focusing on group averages may aid in detecting biologically informed homogeneous subgroups. The person-based similarity index (PBSI) of brain morphology indexes an individual's morphometric similarity across numerous cortical regions amongst a sample of healthy subjects. We extended the PBSI such that it indexes the morphometric similarity of an independent individual (eg, a patient) with respect to healthy control subjects. By employing a normative modeling approach on longitudinal data, we determined an individual's degree of morphometric dissimilarity to the norm. We calculated the PBSI for sulcal width (PBSI-SW) in patients with schizophrenia and healthy control subjects (164 patients and 164 healthy controls; 656 magnetic resonance imaging scans) and associated it with cognitive performance and cortical sulcation index. A subgroup of patients with markedly deviant PBSI-SW showed extreme deficits in cognitive performance and cortical sulcation. Progressive reduction of PBSI-SW in the schizophrenia group relative to healthy controls was driven by these deviating individuals. By explicitly leveraging interindividual differences in the severity of PBSI-SW deficits, neuroimaging-driven subgrouping of patients is feasible. As such, our results pave the way for future applications of morphometric similarity indices for subtyping of clinical populations.

Altered peripheral blood compounds in drug-naïve first-episode patients with either schizophrenia or major depressive disorder: a meta-analysis

IMPORTANCE

Schizophrenia and major depressive disorder (MDD) are associated with increased risks of immunologic disease and metabolic syndrome. It is unclear to what extent growth, immune or glucose dysregulations are similarly present in these disorders without the influence of treatment or chronicity.

OBJECTIVE

To conduct a meta-analysis investigating whether there are altered peripheral growth, immune or glucose metabolism compounds in drug-naïve first-episode patients with schizophrenia or MDD compared with controls.

DATA SOURCES AND STUDY SELECTION

Case-control studies reporting compound measures in drug-naïve first-episode patients with schizophrenia or MDD compared with controls in the Embase, PubMed and PsycINFO databases.

DATA EXTRACTION AND SYNTHESIS

Two independent authors extracted data for a random-effects meta-analysis.

MAIN OUTCOMES AND MEASURES

Peripheral growth, immune or glucose metabolism compounds in schizophrenia or MDD compared with controls. Standardized mean differences were quantified with Hedges' g (g).

RESULTS

74 studies were retrieved comprising 3453 drug-naïve first-episode schizophrenia patients and 4152 controls, and 29 studies were retrieved comprising 1095 drug-naïve first-episode MDD patients and 1399 controls. Growth factors: brain-derived neurotrophic factor (BDNF) (g = -0.77, P < .001) and nerve growth factor (NGF) (g = -2.51, P = .03) were decreased in schizophrenia. For MDD, we observed a trend toward decreased BDNF (g = -0.47, P = .19) and NGF (g = -0.33, P = .08) levels, and elevated vascular endothelial growth factor levels (g = 0.40, P = .03). Immune factors: interleukin (IL)-6 (g = 0.95, P < .001), IL-8 (g = 0.59, P = .001) and tumor necrosis factor alpha (TNFα) (g = 0.48, P = .002) were elevated in schizophrenia. For C-reactive protein (CRP) (g = 0.57, P = .09), IL-4 (g = 0.44, P = .10) and interferon gamma (g = 0.33, P = .11) we observed a trend toward elevated levels in schizophrenia. In MDD, IL-6 (g = 0.62, P = .007), TNFα (g = 1.21, P < .001), CRP (g = 0.53, P < .001), IL-1β (g = 1.52, P = .009) and IL-2 (g = 4.41, P = .04) were elevated, whereas IL-8 (g = -0.84, P = .01) was decreased. The fasting glucose metabolism factors glucose (g = 0.24, P = .003) and insulin (g = 0.38, P = .003) were elevated in schizophrenia.

CONCLUSIONS AND RELEVANCE

Both schizophrenia and MDD show alterations in growth and immune factors from disease onset. An altered glucose metabolism seems to be present from onset in schizophrenia. These findings support efforts for further research into transdiagnostic preventive strategies and augmentation therapy for those with immune or metabolic dysfunctions.

Testing Psychosis Phenotypes From Bipolar-Schizophrenia Network for Intermediate Phenotypes for Clinical Application: Biotype Characteristics and Targets

BACKGROUND

Psychiatry aspires to the molecular understanding of its disorders and, with that knowledge, to precision medicine. Research supporting such goals in the dimension of psychosis has been compromised, in part, by using phenomenology alone to estimate disease entities. To this end, we are proponents of a deep phenotyping approach in psychosis, using computational strategies to discover the most informative phenotypic fingerprint as a promising strategy to uncover mechanisms in psychosis.

METHODS

Doing this, the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has used biomarkers to identify distinct subtypes of psychosis with replicable biomarker characteristics. While we have presented these entities as relevant, their potential utility in clinical practice has not yet been demonstrated.

RESULTS

Here we carried out an analysis of clinical features that characterize biotypes. We found that biotypes have unique and defining clinical characteristics that could be used as initial screens in the clinical and research settings. Differences in these clinical features appear to be consistent with biotype biomarker profiles, indicating a link between biological features and clinical presentation. Clinical features associated with biotypes differ from those associated with DSM diagnoses, indicating that biotypes and DSM syndromes are not redundant and are likely to yield different treatment predictions. We highlight 3 predictions based on biotype that are derived from individual biomarker features and cannot be obtained from DSM psychosis syndromes.

CONCLUSIONS

In the future, biotypes may prove to be useful for targeting distinct molecular, circuit, cognitive, and psychosocial therapies for improved functional outcomes.

Normalizing the Abnormal: Do Antipsychotic Drugs Push the Cortex Into an Unsustainable Metabolic Envelope?

The use of antipsychotic medication to manage psychosis, principally in those with a diagnosis of schizophrenia or bipolar disorder, is well established. Antipsychotics are effective in normalizing positive symptoms of psychosis in the short term (delusions, hallucinations and disordered thought). Their long-term use is, however, associated with side effects, including several types of movement (extrapyramidal syndrome, dyskinesia, akathisia), metabolic and cardiac disorders. Furthermore, higher lifetime antipsychotic dose-years may be associated with poorer cognitive performance and blunted affect, although the mechanisms driving the latter associations are not well understood. In this article, we propose a novel model of the long-term effects of antipsychotic administration focusing on the changes in brain metabolic homeostasis induced by the medication. We propose here that the brain metabolic normalization, that occurs in parallel to the normalization of psychotic symptoms following antipsychotic treatment, may not ultimately be sustainable by the cerebral tissue of some patients; these patients may be characterized by already reduced oxidative metabolic capacity and this may push the brain into an unsustainable metabolic envelope resulting in tissue remodeling. To support this perspective, we will review the existing data on the brain metabolic trajectories of patients with a diagnosis of schizophrenia as indexed using available neuroimaging tools before and after use of medication. We will also consider data from pre-clinical studies to provide mechanistic support for our model.

A proteomic signature associated to atypical antipsychotic response in schizophrenia patients: a pilot study

A major hurdle faced by most schizophrenia patients is the poor efficacy of current antipsychotic medications. This stems from a poor understanding of the underlying pathophysiology and the lack of biomarkers for the prediction of a positive medication response. By employing state-of-the-art proteomic analysis of blood plasma from 58 patients who were either drug-naive or drug-free at the time of sample collection, we identified potential biomarkers that were predictive of a positive response after 6 weeks of treatment with antipsychotics. Complement and coagulation cascades were the most over-represented biological pathways among these proteins, consistent with the importance of these processes in schizophrenia. Although preliminary, these findings are novel and may drive future efforts in the development of predictive tests for medication efficacy and thereby have a positive influence on disease outcome.

Lipid alterations in adolescents with early-onset psychosis may be independent of antipsychotic medication

BACKGROUND

Dyslipidemia and insulin resistance (HOMA-IR) are cardiovascular risk factors prevalent in patients with psychosis. Whether these factors are intrinsic or affected by lifestyle or antipsychotic medication (AP) is unclear. Therefore, we investigated lipid profiles, HOMA-IR, and psychotic phenotypes in patients aged 12-18 years with early-onset psychosis (EOP) with and without AP exposure.

METHOD

We measured fasting total cholesterol (TC), high-density lipoprotein cholesterol (HDLC), triglycerides (TG), insulin, and glucose in patients with EOP (n = 39) and healthy controls (HC) (n = 66). Diet information was not available. Negative symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS). We used univariate analysis of variance to compare TC/HDL-C ratios and TG and HOMA-IR values, controlling for body mass index (BMI) and AP exposure. We assessed the explained variance of having EOP using multiple regression analysis.

RESULTS

Patients with and without AP exposure had significantly higher TC/HDL-C (p = 0.003, p = 0.029) and TG values (p < 0.001, p = 0.021) than HC. Significantly increased HOMA-IR scores were found only in AP-exposed patients (p = 0.037). EOP significantly increased the explained variance for TC/HDL-C and TG, but not for HOMA-IR. Patients with a PANSS negative score > 21 had significantly higher levels of TG than those with low scores (p = 0.032).

CONCLUSION

Our results suggest that lipid alterations predate AP treatment in adolescents with EOP. Higher levels of negative symptoms and AP further increase metabolic risk. The preliminary findings propose that subclinical dyslipidemia may be intrinsic to EOP.

[Evidence-based treatment of acute psychotic episode and schizophrenia in children and adolescents]

Children and adolescents are a special group in the context of psychopharmacotherapy. Given the limited choice of registered antipsychotics permitted in childhood, caution should be exercised in the choice of medication. This literature review reviews the current evidence base for pharmacotherapy of acute psychotic episode and schizophrenia in children and adolescents. The results of major systematic reviews and meta-analyses are compared. Meta-analyses of pharmacotherapy studies of the first psychotic episode are considered separately. Antipsychotics of the first and second generation are comparable in effectiveness for children and adolescents with acute psychotic episode. Olanzapine demonstrates higher efficacy in reducing negative symptoms. Ziprasidone and asenapine are less effective in treating schizophrenia in children and adolescents than other antipsychotics. Compared to adults, children and adolescents are at higher risk of metabolic impairments when taking antipsychotics.

Schizophrenia Patient Shows a Rare Interleukin 15 Receptor alpha Variant Disrupting Signal Transduction

BACKGROUND

Schizophrenia is a complex and debilitating mental disorder with strong heritability. Its pathogenesis involves immune dysregulation. Interleukin 15 and interleukin 15 receptor alpha(IL-15Rα) are classical immune molecules. They also help maintain normal brain function, leading to our hypothesis that IL-15Rα gene(IL- 15RA) variants contribute to the pathogenesis of schizophrenia.

OBJECTIVE

We determine whether the genetic variants of IL-15RA are associated with the development and progression of schizophrenia and whether IL-15RA single nucleotide polymorphism(SNP) plays a key role in downstream signaling transduction.

METHODS AND RESULTS

We sequenced IL-15RA exon from 132 Chinese schizophrenic patients and identified a rare variant(rs528238821) in a patient diagnosed with catatonic schizophrenia and ankylosing spondylitis(AS). We overexpressed this missense variant in cells driven by pBI-CMV vector. The cells showed attenuated STAT3 phosphorylation in response to interleukin15.

CONCLUSION

IL-15RA mutation is rare in schizophrenic patients but interfered with IL- 15Rα intracellular signal transduction. Given the similarity of symptoms of catatonic schizophrenia and the known phenotype of IL-15Rα knockout mice, gene variation might offer diagnostic value for sub-types of schizophrenia.