Schizophrenia (Heidelberg, Germany)最新文献

Cortical excitation-inhibition (E/I) imbalance is a potential model for the pathophysiology of schizophrenia. Previous research using transcranial magnetic stimulation (TMS) and electromyography (EMG) has suggested inhibitory deficits in schizophrenia. In this meta-analysis we assessed the reliability and clinical potential of TMS-EMG paradigms in schizophrenia following the methodological recommendations of the PRISMA guideline and the Cochrane Handbook. The search was conducted in three databases in November 2022. Included articles reported Short-Interval Intracortical Inhibition (SICI), Intracortical Facilitation (ICF), Long-Interval Intracortical Inhibition (LICI) and Cortical Silent Period (CSP) in patients with schizophrenia and healthy controls. Meta-analyses were conducted using a random-effects model. Subgroup analysis and meta-regressions were used to assess heterogeneity. Results of 36 studies revealed a robust inhibitory deficit in schizophrenia with a significant decrease in SICI (Cohen's d: 0.62). A trend-level association was found between SICI and antipsychotic medication. Our findings support the E/I imbalance hypothesis in schizophrenia and suggest that SICI may be a potential pathophysiological characteristic of the disorder.

Phospholipase A2(PLA2) superfamily is recognized as being involved in the pathogenesis of schizophrenia by affecting lipid homeostasis in cell membranes. We hypothesized that PLA2 gene copy number variation (CNV) may affect PLA2 enzyme expression and be associated with schizophrenia risk. This study indicated that in the discovery stage, an increased copy number of PLA2G6 and the deletion of PLA2G3, PLA2G4A, PLA2G4F and PLA2G12F was associated with increased risk of schizophrenia. CNV segments involving six PLA2 genes were detected in publicly available datasets, including two deletion segments specific to the PLA2G4A gene. The relationship between the deletion of PLA2G4A and susceptibility to schizophrenia was then reaffirmed in the validation group of 806 individuals. There was a significant correlation between PLA2G4A deletion and the symptoms of poverty of thought in male patients and erotomanic delusion in females. Furthermore, ELISA results demonstrate a significant decrease in peripheral blood cytosolic PLA2(cPLA2) levels in patients with the PLA2G4A deletion genotype compared to those with normal and copy number duplicate genotypes. These data suggest that the functional copy number deletion in the PLA2G4A gene is associated with the risk of schizophrenia and clinical phenotypes by reducing the expression of cPLA2, which may be an indicator of susceptibility to schizophrenia.

The prospective study of youths at clinical high risk (CHR) for psychosis, including neuroimaging, can identify neural signatures predictive of psychosis outcomes using algorithms that integrate complex information. Here, to identify risk and psychosis conversion, we implemented multiple kernel learning (MKL), a multimodal machine learning approach allowing patterns from each modality to inform each other. Baseline multimodal scans (n = 74, 11 converters) included structural, resting-state functional imaging, and diffusion-weighted data. Multimodal MKL outperformed unimodal models (AUC = 0.73 vs. 0.66 in predicting conversion). Moreover, patterns learned by MKL were robust to training set variations, suggesting it can identify cross-modality redundancies and synergies to stabilize the predictive pattern. We identified many predictors consistent with the literature, including frontal cortices, cingulate, thalamus, and striatum. This highlights the advantage of methods that leverage the complex pathophysiology of psychosis.

We show how acoustic prosodic features, such as pitch and gaps, can be used computationally for detecting symptoms of schizophrenia from a single spoken response. We compare the individual contributions of acoustic and previously-employed text modalities to the algorithmic determination whether the speaker has schizophrenia. Our classification results clearly show that we can extract relevant acoustic features better than those textual ones. We find that, when combined with those acoustic features, textual features improve classification only slightly.

The prolonged usage of atypical antipsychotic drugs (AAPD) among individuals with schizophrenia often leads to metabolic side effects such as dyslipidemia. These effects not only limit one's selection of AAPD but also significantly reduce compliance and quality of life of patients. Recent studies suggest that bilirubin plays a crucial role in maintaining lipid homeostasis and may be a potential pre-treatment biomarker for individuals with dyslipidemia. The present study included 644 schizophrenia patients from two centers. Demographic and clinical characteristics were collected at baseline and 4 weeks after admission to investigate the correlation between metabolites, episodes, usage of AAPDs, and occurrence of dyslipidemia. Besides, we explored the combined predictive value of genotypes and baseline bilirubin for dyslipidemia by employing multiple PCR targeted capture techniques to sequence two pathways: bilirubin metabolism-related genes and lipid metabolism-related genes. Our results indicated that there existed a negative correlation between the changes in bilirubin levels and triglyceride (TG) levels in patients with schizophrenia. Among three types of bilirubin, direct bilirubin in the baseline (DBIL-bl) proved to be the most effective in predicting dyslipidemia in the ROC analysis (AUC = 0.627, p < 0.001). Furthermore, the odds ratio from multinomial logistic regression analysis showed that UGT1A1*6 was a protective factor for dyslipidemia (ß = -12.868, p < 0.001). The combination of baseline DBIL and UGT1A1*6 significantly improved the performance in predicting dyslipidemia (AUC = 0.939, p < 0.001). Schizophrenia patients with UGT1A1*6 mutation and a certain level of baseline bilirubin may be more resistant to dyslipidemia and have more selections for AAPD than other patients.

Predictive processing accounts of psychosis conceptualize delusions as overly strong learned expectations (prior beliefs) that shape cognition and perception. Paranoia, the most prevalent form of delusions, involves threat prior beliefs that are inherently social. Here, we investigated whether paranoia is related to overly strong threat prior beliefs in face perception. Participants with subclinical levels of high (n = 109) versus low (n = 111) paranoia viewed face stimuli paired with written descriptions of threatening versus trustworthy behaviors, thereby activating their threat versus trustworthiness prior beliefs. Subsequently, they completed an established social-psychological reverse correlation image classification (RCIC) paradigm. This paradigm used participants' responses to randomly varying face stimuli to generate individual classification images (ICIs) that intend to visualize either facial prior belief (threat vs. trust). An independent sample (n = 76) rated these ICIs as more threatening in the threat compared to the trust condition, validating the causal effect of prior beliefs on face perception. Contrary to expectations derived from predictive processing accounts, there was no evidence for a main effect of paranoia. This finding suggests that paranoia was not related to stronger threat prior beliefs that directly affected face perception, challenging the assumption that paranoid beliefs operate on a perceptual level.

Schizophrenia, a multifaceted mental disorder characterized by disturbances in thought, perception, and emotion, has been extensively investigated through resting-state fMRI, uncovering changes in spontaneous brain activity among those affected. However, a bibliometric examination regarding publication trends in resting-state fMRI studies related to schizophrenia is lacking. This study obtained relevant publications from the Web of Science Core Collection spanning the period from 1998 to 2022. Data extracted from these publications included information on countries/regions, institutions, authors, journals, and keywords. The collected data underwent analysis and visualization using VOSviewer software. The primary analyses included examination of international and institutional collaborations, authorship patterns, co-citation analyses of authors and journals, as well as exploration of keyword co-occurrence and temporal trend networks. A total of 859 publications were retrieved, indicating an overall growth trend from 1998 to 2022. China and the United States emerged as the leading contributors in both publication outputs and citations, with Central South University and the University of New Mexico being identified as the most productive institutions. Vince D. Calhoun had the highest number of publications and citation counts, while Karl J. Friston was recognized as the most influential author based on co-citations. Key journals such as Neuroimage, Schizophrenia Research, Schizophrenia Bulletin, and Biological Psychiatry played pivotal roles in advancing this field. Recent popular keywords included support vector machine, antipsychotic medication, transcranial magnetic stimulation, and related terms. This study systematically synthesizes the historical development, current status, and future trends in resting-state fMRI research in schizophrenia, offering valuable insights for future research directions.

This systematic review provides a comprehensive overview of the association between premorbid adjustment and social cognition in people with psychotic spectrum disorder. Obtaining evidence of this association will facilitate early detection and intervention before the onset of psychosis. Literature searches were conducted in Scopus, PubMed and PsycINFO. Studies were eligible if they included patients with a psychotic disorder or at a high-risk state; social cognition and premorbid adjustment were measured; and the relationship between premorbid adjustment and social cognition was analysed. The authors independently extracted data from all included articles, and discrepancies were resolved through discussion. Literature searches were conducted in Scopus, PubMed and PsycINFO. Studies were eligible if they included patients with a psychotic disorder or at a high-risk state; social cognition and premorbid adjustment were measured; and the relationship between premorbid adjustment and social cognition was analysed. The authors independently extracted data from all included articles, and discrepancies were resolved through discussion. Of 229 studies identified, 23 met the inclusion criteria. Different methods of assessment were used to measure premorbid adjustment, such as the Premorbid Adjustment Scale or premorbid IQ, among others. Social cognition was assessed as a global measure or by domains using different instruments. A total of 16 articles found a relationship between social cognition (or its domains) and premorbid adjustment: general social cognition (n = 3); Theory of Mind (n  = 12); Emotional Recognition and Social Knowledge (n  = 1). This review shows evidence of a significant relationship between social cognition and premorbid adjustment, specifically between Theory of Mind and premorbid adjustment. Social cognition deficits may already appear in phases prior to the onset of psychosis, so an early individualized intervention with stimulating experiences in people with poor premorbid adjustment can be relevant for prevention. We recommend some future directions, such as carrying out longitudinal studies with people at high-risk of psychosis, a meta-analysis study, broadening the concept of premorbid adjustment, and a consensual assessment of social cognition and premorbid adjustment variables. PROSPERO registration number: CRD42022333886.