The high centrality of functional capacity and everyday life skills in the network suggests that improving the ability to perform tasks relevant to everyday life is critical for any therapeutic intervention in schizophrenia. The pattern of network node connections supports the implementation of personalized interventions.

Improving real‐life functioning is the main goal of the most advanced integrated treatment programs in people with schizophrenia. The Italian Network for Research on Psychoses previously explored, by using network analysis, the interplay among illness‐related variables, personal resources, context‐related factors and real‐life functioning in a large sample of patients with schizophrenia. The same research network has now completed a 4‐year follow‐up of the original sample. In the present study, we used network analysis to test whether the pattern of relationships among all variables investigated at baseline was similar at follow‐up. In addition, we compared the network structure of patients who were classified as recovered at follow‐up versus those who did not recover. Six hundred eighteen subjects recruited at baseline could be assessed in the follow‐up study. The network structure did not change significantly from baseline to follow‐up, and the overall strength of the connections among variables increased slightly, but not significantly. Functional capacity and everyday life skills had a high betweenness and closeness in the network at follow‐up, as they had at baseline, while psychopathological variables remained more peripheral. The network structure and connectivity of non‐recovered patients were similar to those observed in the whole sample, but very different from those in recovered subjects, in which we found few connections only. These data strongly suggest that tightly coupled symptoms/dysfunctions tend to maintain each other's activation, contributing to poor outcome in schizophrenia. Early and integrated treatment plans, targeting variables with high centrality, might prevent the emergence of self‐reinforcing networks of symptoms and dysfunctions in people with schizophrenia.

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The kynurenine pathway of tryptophan metabolism has been implicated in the pathophysiology of psychiatric disorders, including schizophrenia. We report here that the kynurenine metabolite, xanturenic acid (XA), interacts with, and activates mGlu2 and mGlu3 metabotropic glutamate receptors in heterologous expression systems. However, the molecular nature of this interaction is unknown, and our data cannot exclude that XA acts primarily on other targets, such as the vesicular glutamate transporter, in the CNS. Systemic administration of XA in mice produced antipsychotic-like effects in the MK-801-induced model of hyperactivity. This effect required the presence of mGlu2 receptors and was abrogated by the preferential mGlu2/3 receptor antagonist, LY341495. Because the mGlu2 receptor is a potential drug target in the treatment of schizophrenia, we decided to measure serum levels of XA and other kynurenine metabolites in patients affected by schizophrenia. Serum XA levels were largely reduced in a large cohort of patients affected by schizophrenia, and, in patients with first-episode schizophrenia, levels remained low after 12 months of antipsychotic medication. As opposed to other kynurenine metabolites, XA levels were also significantly reduced in first-degree relatives of patients affected by schizophrenia. We suggest that lowered serum XA levels might represent a novel trait marker for schizophrenia.

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IntroductionA specific clinically relevant staging model for schizophrenia has not yet been developed. The aim of the current study was to evaluate the factor structure of the PANSS and develop such a staging method.MethodsTwenty-nine centers from 25 countries contributed 2358 patients aged 37.21 ± 11.87 years with schizophrenia. Analysis of covariance, Exploratory Factor Analysis, Discriminant Function Analysis, and inspection of resultant plots were performed.ResultsExploratory Factor Analysis returned 5 factors explaining 59% of the variance (positive, negative, excitement/hostility, depression/anxiety, and neurocognition). The staging model included 4 main stages with substages that were predominantly characterized by a single domain of symptoms (stage 1: positive; stages 2a and 2b: excitement/hostility; stage 3a and 3b: depression/anxiety; stage 4a and 4b: neurocognition). There were no differences between sexes. The Discriminant Function Analysis developed an algorithm that correctly classified >85% of patients.DiscussionThis study elaborates a 5-factor solution and a clinical staging method for patients with schizophrenia. It is the largest study to address these issues among patients who are more likely to remain affiliated with mental health services for prolonged periods of time.

We performed a retrospective study from January to May 2020 to establish the sociodemographic and clinical characteristics of patients with mental health problems who arrived at an Italian emergency department during the COVID-19 outbreak. We divided the sample into two groups taking as a watershed March 11, when the World Health Organization announced COVID-19 outbreak as a pandemic. Chi-square/t-tests, adjusted p values (Bonferroni method), and regression analysis were performed. Patients who arrived at the emergency department during the lockdown decreased by 56%; showed greater active suicidal ideation, more tension, and more severe psychopathological state; were living alone more frequently; and were taking home treatment mainly based on second-generation antipsychotics. According to our study, it seems that patients with mental disorders have consulted psychiatric services less frequently during the pandemic, but the economic, health, and social distress may be linked with an increase in suicidal risk and the severity of the psychopathological state.

The relationships of personal resources with symptom severity and psychosocial functioning have never been tested systematically in a large sample of people with schizophrenia. We applied structural equation models to a sample of 921 patients with schizophrenia collected in a nationwide Italian study, with the aim to identify, among a large set of personal resources, those that may have an association with symptom severity or psychosocial functioning. Several relevant demographic and clinical variables were considered concurrently. Poor service engagement and poor recovery style, as well as older age and younger age at onset, were related to greater symptom severity and poorer social functioning. Higher resilience and higher education were related to better social functioning only. Poor problem-focused coping and internalized stigma, as well as male gender and depression, were related to symptom severity only. The explored variables showed distinctive and partially independent associations with symptom severity and psychosocial functioning. A deeper understanding of these relationships may inform treatment decisions.