Schizophrenia (Heidelberg, Germany)最新文献

Metabolic syndrome (MetS) is highly prevalent among individuals with schizophrenia. However, substantial regional variation exists, and evidence from large samples of hospitalized patients in China remains limited. This study aimed to estimate the prevalence of MetS and to explore its associated factors among individuals with schizophrenia in China. We included 3042 participants with schizophrenia from 25 hospitals in Zhejiang Province from April to December 2022. MetS was defined according to the Chinese Diabetes Society (CDS) criteria, the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) criteria, and the International Diabetes Federation (IDF) criteria. The prevalence of MetS was estimated using the Clopper-Pearson method, and generalized additive models were used to fit smoothed age-specific prevalence curves. Multivariate logistic regression was used to explore potential factors associated with MetS. The overall prevalence of MetS was 34.9% (95% confidence interval [CI]: 33.2-36.7%), 42.6% (40.9-44.4%), and 38.9% (37.2-40.7%) based on the CDS, NCEP ATP III, and IDF criteria, respectively. The prevalence of MetS was significantly higher in female participants with schizophrenia compared to their male counterparts when applying the NCEP ATP III or IDF criteria. In addition, after reaching the age-specific peak, MetS prevalence declined in male participants but stabilized in females. High BMI (OR: 1.30 [1.27-1.33]) and comorbid endocrine diseases (OR: 1.79 [1.48-2.17]) were associated with increased odds of MetS. Metabolic syndrome is highly prevalent among individuals with schizophrenia, regardless of the diagnostic criteria used. Early identification and screening of metabolic abnormalities in individuals with schizophrenia should be considered.

MicroRNAs (miRNAs) are critical regulators of neurodevelopment and are implicated in the pathogenesis of schizophrenia. Schizophrenia is increasingly recognized as a neurodevelopmental disorder, with most cases emerging during late adolescence and early adulthood, which is a critical period of brain maturation. However, the study of miRNAs during this phase has been limited by the challenges of postmortem brain analysis. Neuron-derived extracellular vesicles (NEVs) have recently been proposed for investigating brain-derived molecular profiles. In this study, NEVs were enriched from plasma using the L1CAM antibody in patients with recent-onset schizophrenia (ROS) within 5 years of onsets and chronic-phase schizophrenia (CS). The miRNA profiles of these NEVs in patients with ROS and CS were compared with those of age-and sex-matched healthy controls. Differential expression analysis revealed miRNA changes specific to the recent-onset phase as well as possible pathophysiological mechanisms transitioning from the recent-onset to the chronic phases. These findings provide novel insights into the role of miRNAs in neurodevelopmental abnormalities associated with schizophrenia onset. This study highlights the utility of NEVs as a tool for accessing brain-derived miRNA profiles and diagnostic biomarkers and underscores the importance of an onset period as a critical window for understanding the molecular underpinnings of schizophrenia.

Cognition in schizophrenia is difficult to assess in clinical settings due to the time required to administer traditional pen-and-paper tests, among other factors. Digital remote assessments completed on a smartphone offer an alternative that can reduce the burden on healthcare staff and patients, in addition to providing more nuanced cognitive profiles, especially when used in conjunction with smartphone data such as sleep. Building on previous work using the mindLAMP research app in international contexts, this paper presents a global multi-site pilot study to explore the validity of the app's digital cognitive assessments as proxies for traditional in-person assessments such as the gold standard MATRICS Consensus Battery (MCCB). Across one site in the U.S. (Boston) and two sites in India (Bangalore and Bhopal), a total of 56 participants with diagnoses of early-course schizophrenia or schizoaffective disorder were recruited between September 2024 and March 2025 to engage with the mindLAMP app for 30 days. Participants completed 2-3 different cognitive tasks and surveys each day; at the beginning and the end of this period, participants also took the MCCB and surveys related to their diagnosis. mindLAMP cognitive assessments were scored using different metrics that combine speed and accuracy, and correlation analyses were run on these metrics and MCCB domains. Of the scoring metrics used, the Rate-Correct Score (RCS) most consistently correlates with baseline MCCB domains corrected for age, gender, and education. Moderate test-retest reliability was observed across certain cognitive assessments such as a mobile version of Trails-Making Test A and Symbol Digit Substitution, which agrees with previous research done by Keefe et al.; poor test-retest reliability, in contrast, was observed across assessments such as Spatial Span. Additionally, we conducted exploratory mediation analyses using sleep data to see if sleep mediates between the Ecological Momentary Assessment (EMA) survey scores and performance on select digital cognitive assessments on mindLAMP. Our results support the initial accessibility, validity and reliability of using smartphones to assess cognition in schizophrenia. Future research to develop additional smartphone-based cognitive tests, as well as with larger samples and in other psychiatric populations, is warranted.

We aimed to examine the association between gut permeability biomarkers (LBP, sCD14) and insulin resistance (IR) in schizophrenia. In this cross-sectional study of 91 patients, IR (HOMA-IR ≥ 3.0) was associated with higher LBP, C-reactive protein, body mass index (BMI), and lower physical activity. Logistic regression identified LBP and BMI as independent risk factors, whereas physical activity was protective. These findings suggest altered gut permeability could influence glucose metabolism dysfunction in schizophrenia.

Felt presence (FP) - sensing another person without clear sensory evidence - has been described in psychosis for over a century but rarely studied due to challenges in recognition and assessment. Recently FP has been identified as a transdiagnostic phenomenon and highlighted by people with lived experience of psychosis as a clinical priority. Here we describe FP presentation in a first-episode psychosis sample and report preliminary associations with affect, gender, and psychopathology.

Testosterone play an important role in schizophrenia, particularly for impulsive aggressive behaviors. However, there is still unclear how the neurobiological basis and correlates of these risk factors in schizophrenia patients. The schizophrenia patients who visited psychiatric emergency departments (PED) with an acute stage and received an evaluation of aggression and psychotic symptoms by the Positive and Negative Syndrome Scale (PANSS) were included. Blood samples were collected for plasma testosterone measurement. The network analysis and network comparison test were conducted to construct and evaluate whether network characteristics differed by gender. The prevalence of level Ⅱ aggression was 41.4%, level Ⅲ aggression was 33.3%, and level Ⅳ aggression was 8.8% in the SCZ patients visited in PED, respectively. The total score of PANSS, the average level of testosterone, and the proportion of males in the aggressive group were higher than those in the non-aggressive group, respectively. Network analysis identified "Guilt feelings", "Poor impulse control" and "Difficulty in abstract thinking" as the most influential symptoms. "Poor impulse control" appeared to be the bridge symptom linking psychotic symptoms to aggressive behavior. Concurrently, "Poor impulse control" stand as critical bridge symptoms between psychotic symptoms to aggressive behaviors. Moreover, "Blunted affect" exhibited the strongest positive correlation with testosterone levels among SCZ patients in the acute stage. The findings highlight the complex interplay between testosterone and psychotic symptoms of schizophrenia patients, emphasizing the importance of targeting influential symptoms in psychiatric emergency care. The identification of central and bridge symptoms suggests potential pathways for individual interventions for SCZ patients.

Identification of cell type-specific and temporally dynamic regulatory features of schizophrenia (SCZ) risk genes is essential for advancing mechanistic neurobiological studies. This study systematically dissected the genetic architecture and neurodevelopmental mechanisms of SCZ by integrating genome-wide association study (GWAS) data from European (N = 130,644) and East Asian (N = 30,761) population, alongside multi-omics and single-cell sequencing analyses. Cross-method validation identified seven core genes (e.g., MDK, RERE, ERBB4), with RERE exhibiting a notably high eQTL-SCZ colocalization probability of 92.8-93.9%. Single-cell and epigenetic analyses reveal that the spatiotemporal dynamics of RERE may lead to differences in its mediated SCZ disease risk at the levels of genetic variation and transcriptional regulation. Cleavage Under Targets and Tagmentation (CUT&Tag) confirmed that RERE directly regulates synaptic genes such as PPP4R3B and RPS27L, and its co-expression network was found to be strongly linked to SCZ risk. This study unveils a RERE-mediated epigenetic-neurodevelopmental axis and suggests that GABAergic neurons may be a potential new target for the treatment of SCZ. Future validation using organoid models and exploration of clinical translation are warranted.

Understanding neurobiological similarities among individuals with psychosis risk symptoms can improve early identification and intervention strategies. We aimed to (i) identify neurobiologically similar psychosis risk subgroups by integrating resting-state functional connectivity and psychosis risk symptom data and (ii) discern discriminating symptom profiles and brain connectivity patterns in the identified sub-groups. Our sample (N = 922) was extracted from the Philadelphia Neurodevelopmental Cohort, a community group of individuals aged 12-21 years, with fMRI and self-reported psychopathology data. Analyses were conducted separately for youth and early adults. We constructed a two-layer network using pair-wise similarity distances between participants based on resting-state fMRI and psychosis risk symptoms measured with the PRIME screen. We then performed community detection via a multiplex stochastic block model to identify subject clusters. We identified 2 blocks or communities for both the youth (n = 458 and 179) and early adult (n = 173 and 112) groups. Connection parameter estimates of the neuroimaging layer were nearly identical between blocks for both age groups whereas there was significant variation for the symptom layer. Psychopathology symptom and brain system segregation profiles were consistent across age groups. The youth block (n = 458) with higher salience network segregation values had higher mean psychosis risk symptom scores while the early adult block (n = 173) with lower salience network segregation had higher mean psychosis risk symptom scores. By integrating global similarities in brain connectivity and psychosis risk symptoms, we identified distinct subgroups. These groups exhibit different symptom profiles and network segregation in youth and early adults, suggesting variations in developmental paths for psychosis spectrum.

Item Response Theory (IRT) describes a set of statistical models describing how individual items in a test or questionnaire relate to the underlying characteristic or trait that the test claims to measure. Until now IRT models have not been applied to the Positive and Negative Syndrome Scale (PANSS) in forensic and general psychiatric samples to establish its psychometric properties and explore the link between psychotic symptom severity and violent behavior in schizophrenia. This study investigated patients with schizophrenia spectrum disorders and a history of violence from forensic institutions and non-violent patients from general psychiatric settings in five European countries. A total of 398 participants were assessed using the PANSS. IRT analysis revealed a poor model fit for the Partial Credit Model (PCM) with considerably disordered thresholds for most items. Differential item functioning (DIF) revealed significant differences between the two groups, notably for items hypothetically linked to violence risk, such as delusions and hostility. These findings reveal potential limitations when trying to compare PANSS scores across these two clinical populations.