Schizophrenia (Heidelberg, Germany)最新文献

Cognitive deficits and overweight are prominent challenges in the treatment of psychosis, which have a direct impact on patients' quality of life. We aim to determine whether there is an association of overweight with cognitive performance and whether there are sex differences in this association. We included 170 individuals with first-episode psychosis (FEP) (mean age 23.08 years, 32.9% females) attending an early intervention service who underwent clinical, biometric, and cognitive assessments by the MATRICS Consensus Cognitive Battery. A set of two-way analyses of covariance (ANCOVAs) were conducted for each cognitive test. Sex, overweight, and their interaction were included as factors. Nearly 34% of the participants were overweight without differences between males and females. The excess of weight did not exert any main effect on cognition; however, overweight females performed significantly worse than non-overweight females in processing speed, verbal learning and memory, reasoning and problem-solving, and global cognitive function, whereas in males, there were no differences. Our findings highlight that sex matters in the study of metabolic and cognitive factors in FEP to develop targeted interventions based on sex perspectives.

Understanding the role of aberrant salience (AS) in psychosis is crucial for comprehending schizophrenia spectrum disorders (SSDs). Researchers emphasize the importance of salience attribution in schizophrenia, acknowledging its interaction with environmental stressors and multiple neurotransmitter systems. Childhood trauma and adversities (CTA) play a significant role in SSDs, potentially contributing to prodromal symptoms characterized by AS. While empirical evidence supports the relationship between AS and SSD, the interplay between different AS patterns, CTA, and psychotic symptoms remains unclear. Clinical diagnosis followed DSM-5 criteria, and participants completed assessments including the Aberrant Salience Inventory (ASI), Childhood Trauma Questionnaire - Short form (CTQ-SF), and Positive and Negative Symptom Scale (PANSS). Latent profile analysis (LPA) was employed to identify distinct AS profiles within the sample, with subsequent analyses examining differences in psychopathological variables among these profiles. Among 262 participants, four distinct AS profiles emerged from LPA: low AS, high AS with severe symptoms and CTA, intermediate AS with sexual abuse correlation, and chronic AS with specific childhood trauma associations. Profile distinctions included differences in age, hospitalizations, psychotic symptoms, and CTA. Logistic regression analyses showed significant associations between the four profiles and emotional and sexual abuse, physical neglect and clinical variables. Subtyping individuals with SSD based on AS revealed four distinct profiles, each with unique clinical characteristics and associations with CTA. Future studies should investigate whether these profiles correspond to diverse treatment outcomes. These findings highlight the complexity of schizophrenia presentation and underscore the importance of considering individualized diagnostic and therapeutic approaches.

Neuroimaging studies have revealed that the mechanisms of auditory hallucinations are related to morphological changes in multiple cortical regions, but studies on brain network properties are lacking. This study aims to construct intra-individual structural covariance networks and reveal network changes related to auditory hallucinations. T1-weighted MRI images were acquired from 90 schizophrenia patients with persistent auditory hallucinations (pAH group), 55 schizophrenia patients without auditory hallucinations (non-pAH group), and 83 healthy controls (HC group). Networks were constructed using the voxel-based gray matter volume and the intra-individual structural covariance was based on the similarity between the morphological variations of any two regions. One-way ANCOVA was employed to compare global and local network metrics among the three groups, and edge analysis was conducted via network-based statistics. In the pAH group, Pearson correlation analysis between network metrics and clinical symptoms was conducted. Compared with the HC group, both the pAH group (p = 0.01) and the non-pAH group (p = 3.56 × 10^-4) had lower nodal efficiency of the left medial superior frontal gyrus. Compared to the non-pAH group and HC group, the pAH group presented lower nodal efficiency of the temporal pole of the left superior temporal gyrus (p = 1.09 × 10^-3; p = 7.67 × 10^-4) and right insula (p = 0.02; p = 8.99 × 10^-6), and lower degree centrality of the right insula (p = 0.04; p = 1.65 × 10^-5). The pAH group had a subnetwork with reduced structural covariance centered by the left temporal pole of the superior temporal gyrus. In the pAH group, the normalized clustering coefficient (r = -0.36, p = 8.45 × 10^-3) and small-worldness (r = -0.35, p = 9.89 × 10^-3) were negatively correlated with the PANSS positive scale score. This study revealed network changes in schizophrenia patients with persistent auditory hallucinations, and provided new insights into the structural architecture related to auditory hallucinations at the network level.

Methamphetamine use can produce psychotic symptoms almost indistinguishable from schizophrenia (SCZ). Variation in DNA methylation may be closely implicated in the etiology and longitudinal development of psychiatric disorders. However, the relationship between psychotic symptoms, functional disability, and DNA methylation is still unclear. This study consists of three periods: discovery, validation, and follow-up. In the discovery stage, we employed genome-wide DNA methylation profiling (Illumina 450K) in peripheral blood mononuclear cells to test whether DNA methylation associates with psychotic symptoms and function state in representative SCZ and methamphetamine-induced psychotic disorder (MIP) patients. Then, we found seven differentially methylated regions/genes (DMRs, in UBA6, APOL3, KIF17, MLLT3, GRM8, CSNK1E, SETDB1) overlapping with genetic variants reported in previous studies of psychosis. In the validation stage, we compared the above-mentioned seven genes by MethLight qPCR method in Chinese Han males (N = 109 SCZ patients, N = 99 methamphetamine use disorder with MIP patients, N = 150 methamphetamine use disorder without MIP patients, N = 282 normal controls, age range: 18-50 years). GRM8 showed robustly altered methylation, which has passed rigorous filtration in subsequent validation, suggesting a remarkable contribution to SCZ and MIP. In addition, hypermethylation of GRM8 showed a significant association with the total scores of the Positive Negative Syndrome Scale and WHO disability assessment schedule II in both baseline and follow-up periods. Our findings suggest that increased CpG methylation in the promoter of GRM8 is a potential candidate epigenetic biomarker of psychotic symptoms in transdiagnostic samples of SCZ and MIP.

Hyperactivity of the human anterior hippocampus has been reported to spread from its CA1 subfield to the subiculum around the onset of first-episode psychosis and could be a cellular target for early therapeutic intervention in the schizophrenia prodrome. However, to what extent CA1 hyperactivity actually causes schizophrenia-related symptoms remains unknown. Here, we mimic this endophenotype by direct optogenetic activation of excitatory cells in the homologous mouse region, ventral CA1 (vCA1) and assess its consequence in multiple schizophrenia-related behavioural tests. We find that hyperactivity of vCA1 causes hyperlocomotion and impairments of spatial and object-related short-term habituation (spatial novelty-preference and novel-object recognition memory) and spatial working memory, whereas social interaction, spatial exploration, and anxiety remain unaltered. Stimulation of the ventral subiculum, in contrast, only increased locomotion and exploration. In conclusion, CA1 hyperactivity may be a direct driver of prodromal cognitive symptoms and of aberrant salience assignment leading to psychosis.

Several multivariate prognostic models have been published to predict outcomes in patients with first episode psychosis (FEP), but it remains unclear whether those predictions generalize to independent populations. Using a subset of demographic and clinical baseline predictors, we aimed to develop and externally validate different models predicting functional outcome after a FEP in the context of a schizophrenia-spectrum disorder (FES), based on a previously published cross-validation and machine learning pipeline. A crossover validation approach was adopted in two large, international cohorts (EUFEST, n = 338, and the PSYSCAN FES cohort, n = 226). Scores on the Global Assessment of Functioning scale (GAF) at 12 month follow-up were dichotomized to differentiate between poor (GAF current < 65) and good outcome (GAF current ≥ 65). Pooled non-linear support vector machine (SVM) classifiers trained on the separate cohorts identified patients with a poor outcome with cross-validated balanced accuracies (BAC) of 65-66%, but BAC dropped substantially when the models were applied to patients from a different FES cohort (BAC = 50-56%). A leave-site-out analysis on the merged sample yielded better performance (BAC = 72%), highlighting the effect of combining data from different study designs to overcome calibration issues and improve model transportability. In conclusion, our results indicate that validation of prediction models in an independent sample is essential in assessing the true value of the model. Future external validation studies, as well as attempts to harmonize data collection across studies, are recommended.

Social disconnection, including objective social isolation and subjective loneliness, is linked to substantial health risks. Yet, little is known about the predictors of social disconnection in individuals with mental illness. Here, we used machine learning to identify predictors of social isolation and loneliness in schizophrenia (N = 72), a psychiatric condition associated with social disconnection. For comparison, we also included two other groups: a psychiatric comparison sample of bipolar disorder (N = 48) and a community sample enriched for social isolation (N = 151). We fitted statistical models of social isolation and loneliness within and across groups. Each model included five candidate predictors: social avoidance motivation, depression, nonsocial cognition, social anhedonia, and social cognition. The results showed that social anhedonia explained unique variance in social isolation and loneliness in all samples, suggesting that it contributes to social isolation and loneliness broadly. However, nonsocial cognition explained unique variance in social isolation only within schizophrenia. Thus, social anhedonia could be a potential intervention target across populations, whereas nonsocial cognition may play a unique role in determining social disconnection in schizophrenia.

Schizophrenia and schizoaffective disorder present burdens to patients and health systems through elevated healthcare resource utilization (HCRU) and costs. However, there is a paucity of evidence describing these burdens across payor types. To identify unmet needs, this study characterized patients with schizophrenia or schizoaffective disorder by payor type. We identified patients aged 12-94 years with newly diagnosed schizophrenia or schizoaffective disorder (index date) between 01/01/2014 and 08/31/2020 with continuous enrollment for 12 months before and after index date from the Healthcare Integrated Research Database. After stratifying by post-index relapse frequency (0, 1, or ≥2) and payor type (commercial, Medicare Advantage/Supplemental (Medigap)/Part D, or managed Medicaid), we examined patient characteristics, treatment patterns, HCRU, costs, and relapse patterns and predictors. During follow-up, 25% of commercial patients, 29% of Medicare patients, and 37% of Medicaid patients experienced relapse. Atypical antipsychotic discontinuation was most common among Medicaid patients, with 65% of these patients discontinuing during follow-up. Compared to commercial patients, Medicare and Medicaid patients had approximately half as many psychotherapy visits during follow-up (12 vs. 5 vs. 7 visits, respectively). Relative to baseline, average unadjusted all-cause costs during follow-up increased by 105% for commercial patients, 66% for Medicare patients, and 77% for Medicaid patients. Patients with schizophrenia or schizoaffective disorder had high HCRU and costs but consistently low psychotherapy utilization, and they often discontinued pharmacologic therapy and experienced relapse. These findings illustrate the high burden and unmet need for managing these conditions and opportunities to improve care for underserved patients.

Distinguishing stable and fluctuating psychopathological features in young individuals at Ultra High Risk (UHR) for psychosis is challenging, but critical for building robust, accurate, early clinical detection and prevention capabilities. Over a 24-month period, 159 UHR individuals were assessed using the Positive and Negative Symptom Scale (PANSS). Generalisability Theory was used to validate the PANSS with this population and to investigate stable and fluctuating features, by estimating the reliability and generalisability of three factor (Positive, Negative, and General) and five factor (Positive, Negative, Cognitive, Depression, and Hostility) symptom models. Acceptable reliability and generalisability of scores across occasions and sample population were demonstrated by the total PANSS scale (Gr = 0.85). Fluctuating symptoms (delusions, hallucinatory behaviour, lack of spontaneity, flow in conversation, emotional withdrawal, and somatic concern) showed high variability over time, with 50-68% of the variance explained by individual transient states. In contrast, more stable symptoms included excitement, poor rapport, anxiety, guilt feeling, uncooperativeness, and poor impulse control. The 3-factor model of PANSS and its subscales showed robust reliability and generalisability of their assessment scores across the UHR population and evaluation periods (G = 0.77-0.93), offering a suitable means to assess psychosis risk. Certain subscales within the 5-factor PANSS model showed comparatively lower reliability and generalisability (G = 0.33-0.66). The identified and investigated fluctuating symptoms in UHR individuals are more amendable by means of intervention, which could have significant implications for preventing and addressing psychosis. Prioritising the treatment of fluctuating symptoms could enhance intervention efficacy, offering a sharper focus in clinical trials. At the same time, using more reliable total scale and 3 subscales can contribute to more accurate assessment of enduring psychosis patterns in clinical and experimental settings.