Schizophrenia is a chronic and complex mental disorder resulting from interactions between cumulative and synergistic genetic and environmental factors. Viral infection during the prenatal stage constitutes one of the most relevant risk factors for the development of schizophrenia later in adulthood.

A narrative review was conducted to explore the link between viral infections and schizophrenia, as well as the neuropsychiatric effects of antiviral drugs, particularly in the context of this specific mental condition. Literature searches were performed using the PubMed, Scopus, and Web of Science databases.

Several viral infections, such as herpesviruses, influenza virus, Borna disease virus, and coronaviruses, can directly or indirectly disrupt normal fetal brain development by modifying gene expression in the maternal immune system, thereby contributing to the pathophysiological symptoms of schizophrenia. In addition, neuropsychiatric effects caused by antiviral drugs are frequent and represent significant adverse outcomes for viral treatment.

Epidemiological evidence suggests a potential relationship between viruses and schizophrenia. Increases in inflammatory cytokine levels and changes in the expression of key genes observed in several viral infections may constitute potential links between these viral infections and schizophrenia. Furthermore, antivirals may affect the central nervous system, although for most drugs, their mechanisms of action are still unclear, and a strong relationship between antivirals and schizophrenia has not yet been established.

There is currently no definitive method for identifying individuals with psychosis in secondary care on a population-level using administrative healthcare data from England.

To develop various algorithms to identify individuals with psychosis in the Mental Health Services Data Set (MHSDS), guided by national estimates of the prevalence of psychosis.

Using a combination of data elements in the MHSDS for financial years 2017–2018 and 2018–2019 (mental health cluster (a way to describe and classify a group of individuals with similar characteristics), Health of the Nation Outcome Scale (HoNOS) scores, reason for referral, primary diagnosis, first-episode psychosis flag, early intervention in psychosis team flag), we developed 12 unique algorithms to detect individuals with psychosis seen in secondary care. The resulting numbers were then compared with national estimates of the prevalence of psychosis to ascertain whether they were reasonable or not.

The 12 algorithms produced 99 204–138 516 and 107 545–134 954 cases of psychosis for financial years 2017–2018 and 2018–2019, respectively, in line with national prevalence estimates. The numbers of cases of psychosis identified by the different algorithms differed according to the type and number (3–6) of data elements used. Most algorithms identified the same core of patients.

The MHSDS can be used to identify individuals with psychosis in secondary care in England. Users can employ several algorithms to do so, depending on the objective of their analysis and their preference regarding the data elements employed. These algorithms could be used for surveillance, research and/or policy purposes.

Patients with schizophrenia experience accelerated aging, accompanied by abnormalities in biomarkers such as shorter telomere length. Brain age prediction using neuroimaging data has gained attention in schizophrenia research, with consistently reported increases in brain-predicted age difference (brain-PAD). However, its associations with clinical symptoms and illness duration remain unclear.

We developed brain age prediction models using structural magnetic resonance imaging (MRI) data from 10,938 healthy individuals. The models were validated on an independent test dataset comprising 79 healthy controls, 57 patients with recent-onset schizophrenia, and 71 patients with chronic schizophrenia. Group comparisons and the clinical associations of brain-PAD were analyzed using multiple linear regression. SHapley Additive exPlanations (SHAP) values estimated feature contributions to the model, and between-group differences in SHAP values and group-by-SHAP value interactions were also examined.

Patients with recent-onset schizophrenia and chronic schizophrenia exhibited increased brain-PAD values of 1.2 and 0.9 years, respectively. Between-group differences in SHAP values were identified in the right lateral prefrontal area (false discovery rate [FDR] p = 0.022), with group-by-SHAP value interactions observed in the left prefrontal area (FDR p = 0.049). A negative association between brain-PAD and Full-scale Intelligence Quotient scores in chronic schizophrenia was noted, which did not remain significant after correction for multiple comparisons.

Brain-PAD increases were pronounced in the early phase of schizophrenia. Regional brain abnormalities contributing to brain-PAD likely vary with illness duration. Future longitudinal studies are required to overcome limitations related to sample size, heterogeneity, and the cross-sectional design of this study.

To examine the clinical and demographic profile of inpatient psychosis admissions in Ireland.

Anonymised data was extracted from the Health Research Board (HRB) National Psychiatric Inpatient Reporting System (NPIRS) from 2013–2022. The NPIRS database is maintained by the HRB and records all admissions to inpatient units and hospitals on the register of approved centres under the Mental Health Act 2001. Data was reviewed and analysed using SPSS V26.

There were 43,963 psychosis admissions over the 10-year period corresponding to 26% of all psychiatric admissions. Males accounted for 58% of psychosis admissions. The median age at first admission was 36 years of age for males and 42 years of age for females. Median length of stay in days was longer for psychosis admissions (median = 20 days IQR = 8–43) than for other mental health disorders (median = 13 days IQR = 4.0–33).

Understanding the clinical and demographic profile of psychosis related inpatient psychiatric admissions in Ireland provides insights that can inform effective service planning and care delivery. The findings of this study have particular relevance for the implementation and evolution of the Health Service Executive Early Intervention in Psychosis Clinical Programme.

According to the aberrant salience proposal, reward processing abnormality, specifically erroneous reward prediction error (RPE) signaling due to stimulus-independent release of dopamine, underlies delusions in schizophrenia. However, no studies to date have examined RPE-associated brain activations in relation to this symptom.

Seventy-eight patients with a DSM-5 diagnosis of schizophrenia/schizoaffective disorder and 43 healthy individuals underwent fMRI while they performed a probabilistic monetary reward task designed to generate a measure of RPE. Ratings of delusions and referentiality were made in the patients.

Using whole-brain, voxel-based analysis, schizophrenia patients showed only minor differences in RPE-associated activation compared to healthy controls. Within the patient group, however, severity of delusions was inversely associated with RPE-associated activation in areas including the caudate nucleus, the thalamus and the left pallidum, as well as the lateral frontal cortex bilaterally, the pre- and postcentral gyrus and supplementary motor area, the middle cingulate gyrus, and parts of the temporal and parietal cortex. A broadly similar pattern of association was seen for referentiality.

According to this study, while patients with schizophrenia as a group do not show marked alterations in RPE signaling, delusions and referentiality are associated with reduced activation in parts of the prefrontal cortex and the basal ganglia, though not specifically the ventral striatum. The direction of the changes is on the face of it contrary to that predicted by aberrant salience theory.

Psychosis prediction has been a key focus of psychiatry research for over 20 years. The two dominant approaches to identifying psychosis risk have been the clinical high-risk (CHR) and the familial high-risk (FHR) approaches. To date, the real-world sensitivity of these approaches – that is, the proportion of all future psychotic disorders in the population that they identify – has not been systematically reviewed.

We systematically reviewed and meta-analysed studies in MEDLINE, Embase, PsychINFO, and Web of Science (from inception until September 2024) that reported data on the sensitivity of CHR and FHR approaches – i.e., individuals with a psychosis diagnosis preceded by a CHR diagnosis or a history of parental psychosis (PROSPERO: CRD42024542268).

We identified four CHR studies and four FHR studies reporting relevant data. The pooled estimate of the sensitivity of the CHR approach was 6.7% (95% CI: 1.5–15.0%) and of the FHR approach was 6.5% (95% CI: 4.4–8.9%). There was a high level of heterogeneity between studies. Most FHR studies had a low risk of bias, but most CHR studies had a high risk of bias.

Pooled data suggest that CHR and FHR approaches, each, capture only about 6–7% of future psychotic disorders. These findings demonstrate the need for additional approaches to identify risk for psychosis.

Few studies have examined the long-term outcomes of first-episode psychosis (FEP) among patients beyond symptomatic and functional remission. This study aimed to broaden the scope of outcome indicators by examining the relationships between 12 outcomes of FEP patients at 20.9 years after their initial diagnosis.

At follow-up, 220 out of 550 original patients underwent a new assessment. Twelve outcomes were assessed via semistructured interviews and complementary scales: symptom severity, functional impairment, personal recovery, social disadvantage, physical health, number of suicide attempts, number of episodes, current drug use, dose-years of antipsychotics (DYAps), cognitive impairment, motor abnormalities, and DSM-5 final diagnosis. The relationships between these outcome measures were investigated using Spearman’s correlation analysis and exploratory factor analysis, while the specific connections between outcomes were ascertained using network analysis.

The outcomes were significantly correlated; specifically, symptom severity, functioning, and personal recovery showed the strongest correlations. Exploratory factor analysis of the 12 outcomes revealed two factors, with 11 of the 12 outcomes loading on the first factor. Network analysis revealed that symptom severity, functioning, social disadvantage, diagnosis, cognitive impairment, DYAps, and number of episodes were the most interconnected outcomes.

Network analysis provided new insights into the heterogeneity between outcomes among patients with FEP. By considering outcomes beyond symptom severity, the rich net of interconnections elucidated herein can facilitate the development of interventions that target potentially modifiable outcomes and generalize their impact on the most interconnected outcomes.

The hypothesized cognitive model of negative symptoms, proposed nearly twenty years ago, is the most prevalent psychological framework for conceptualizing negative symptoms in schizophrenia spectrum disorders (SSDs). The aim of this study was to comprehensively validate the model for the first time, specifically by quantifying the relationships between negative symptom severity and all related dysfunctional beliefs.

A systematic search was conducted using MEDLINE and PsychINFO, supplemented by manual reviews of reference lists and Google Scholar. Eligible studies were peer-reviewed with data on the direct cross-sectional association between negative symptoms and at least one relevant dysfunctional belief in SSD patients. Screening and data extraction were completed by independent reviewers. Random-effects meta-analyses were performed to pool effect size estimates of z-transformed Pearson’s r correlations. Moderators of these relationships, as well as subset analyses for negative symptom domains and measurement instruments, were also assessed.

Significant effects emerged for the relationships between negative symptoms and defeatist performance beliefs (k = 38, n = 2808), r = 0.23 (95% CI, 0.18–0.27), asocial beliefs (k = 8, n = 578), r = 0.21 (95% CI, 0.12–0.28), low expectancies for success (k = 55, n = 5664), r = −0.21 (95% CI, −0.15 – −0.26), low expectancies for pleasure (k = 5, n = 249), r = −0.19 (95% CI, −0.06 – −0.31), and internalized stigma (k = 81, n = 9766), r = 0.17 (95% CI, 0.12–0.22), but not perception of limited resources (k = 10, n = 463), r = 0.08 (95% CI, −0.13 – 0.27).

This meta-analysis provides support for the cognitive model of negative symptoms. The identification of specific dysfunctional beliefs associated with negative symptoms is essential for the development of precision-based cognitive-behavioral interventions.

An accumulating body of evidence indicates that peripheral physiological rhythms help regulate and organize large-scale brain activity. Given that schizophrenia (SZ) is characterized by marked abnormalities in oscillatory cortical activity as well as changes in autonomic function, the present study aimed to identify mechanisms by which central and autonomic nervous system deficits may be related. We evaluated phase-amplitude coupling (PAC) as a physiological mechanism through which autonomic nervous system (ANS) and central nervous system (CNS) activity are integrated and that may be disrupted in SZ.

PAC was measured between high-frequency heart rate variability (HF-HRV) as an index of parasympathetic activity and electroencephalography (EEG) oscillations in 36 individuals with first-episode SZ and 38 healthy comparison participants at rest.

HRV-EEG coupling was lower in SZ in the alpha and theta bands, and HRV-EEG coupling uniquely predicted group membership, whereas HRV and EEG power alone did not. HRV-EEG coupling in the alpha band correlated with measures of sustained attention in SZ. Granger causality analyses indicated a stronger heart-to-brain effect than brain-to-heart effect, consistent across groups.

Lower HRV-EEG coupling provides evidence of deficient autonomic regulation of cortical activity in SZ, suggesting that patterns of dysconnectivity observed in brain networks extend to brain–body interactions. Deficient ANS–CNS integration in SZ may foster a breakdown in the spatiotemporal organization of cortical activity, which may contribute to core cognitive impairments in SZ such as dysregulated attention. These findings encourage pursuit of therapies targeting autonomic function for the treatment of SZ.

The development of guidelines is time-consuming and cost-intensive. The heterogeneity of clinical practice, evidence, and patients’ needs is an issue across Europe. An European core guidance for a specific psychiatric disorder may help to overcome this issue. Here, we present a progress report on the European Psychiatric Association (EPA) proof-of-concept approach to develop a European consensus guidance on the pharmacological treatment of schizophrenia.

All national psychiatric associations in Europe were contacted to provide their schizophrenia guidelines. Six guidelines were rated by three experts, experienced in the development of national and international guidelines, from three different countries (Italy, Hungary, and Germany), and the German schizophrenia guideline published in 2019 was found to have the highest quality. For this proof-of-concept approach, 45 recommendations on the pharmacological treatment of schizophrenia from the German guideline were evaluated in a two-step Delphi process to determine their acceptability throughout the European continent.

44 experts participated in the first round and 40 experts in the second round of the Delphi process. Agreement among the involved experts was reached for 75% of the presented recommendations from the German schizophrenia guidelines. 11 out of 45 recommendations (24.4%) did not reach this level of agreement.

This progress report highlights the possibility of developing a pan-European core guidance on the pharmacological treatment of schizophrenia by adapting national guidelines and reconciling their recommendations. However, several barriers in this adaptation process, such as non-agreement in recommendations with strong scientific evidence in the reconciling process, were identified and must be considered when developing the final guidance.

Accelerated ageing indexed by telomere attrition is suggested in schizophrenia spectrum- (SCZ) and bipolar disorders (BD). While inflammation may promote telomere shortening, few studies have investigated the association between telomere length (TL) and markers of immune activation and inflammation in severe mental disorders.

Leucocyte TL defined as telomere template/amount of single-copy gene template (T/S ratio), was determined in participants with SCZ (N = 301) or BD (N = 211) and a healthy control group (HC, N = 378). TL was analysed with linear regressions for associations with levels of 12 immune markers linked to SCZ or BD. Adjustments were made for a broad range of potential confounding variables. TL was measured by quantitative polymerase chain reaction (qPCR) and the immune markers were measured by enzyme immunoassays.

A positive association between levels of soluble tumour necrosis factor receptor 1A (sTNF-R1) and TL in SCZ (β = 0.191, p = 0.012) was observed. Plasma levels of the other immune markers were not significantly associated with TL in the BD, SCZ or HC groups.

There was limited evidence of association between immune markers and TL in SCZ and BD. The results provide little support for involvement of immune dysregulation, as reflected by current systemic markers, in telomere attrition-related accelerated ageing in severe mental disorders.

Women with schizophrenia frequently discontinue antipsychotic medications during pregnancy. However, evidence on the risk of postpartum relapse associated with antipsychotic use during pregnancy is lacking.

To investigate the within-individual association between antipsychotic continuation during pregnancy and postpartum relapse in women with schizophrenia.

This retrospective cohort study used data of women with schizophrenia who gave live birth between 2007 and 2018 identified from the National Health Information Database of South Korea. Women were classified according to antipsychotic use patterns during the 12 months before delivery as non-users, discontinuers and continuers. Relapse was defined as admission for psychosis (ICD-10, F20–29). The incidence rate ratio (IRR) for admission for psychosis in the 6-month postpartum period was estimated using conditional Poisson regression, with the reference period set between 2 and 1 years before delivery. Additionally, we calculated the relative risk ratios (RRRs) for the IRRs of different antipsychotic use patterns.

Among the 3026 women included in the analysis (median age 34 years, interquartile range 31–37), the within-individual risk of admission for psychosis in the 6-month postpartum period was 0.56 times (RRR, 95% CI 0.36–0.87) lower in continuers (IRR = 1.31, 95% CI 0.89–1.72) than in discontinuers (IRR = 2.34, 95% CI 1.87–2.91). Among discontinuers, the IRRs of admission for psychosis in the 6-month postpartum period did not change significantly with the timing of discontinuation (trend P = 0.946).

Antipsychotic continuation during pregnancy was associated with a reduced risk of postpartum relapse in women with schizophrenia. Continuing antipsychotics during pregnancy would be recommended after a risk–benefit assessment.