Schizophrenia (Heidelberg, Germany)最新文献

Second-generation antipsychotics (SGAs) were found to have varying metabolic side-effects for patients with schizophrenia, while no studies have examined the associations between adding or switching low-risk SGAs and metabolic outcomes. This real-world observational study aimed to examine the association of adding or switching to low-risk SGAs with metabolic syndrome and metabolic abnormalities for patients with schizophrenia from 25 healthcare organizations across Zhejiang Province, China. Participants were dichotomized into the low-risk SGAs group and the high/intermediate SGAs group according to whether adding or switching to low-risk SGAs. A 1:1 propensity score matching (PSM) using a nearest-neighbor method was conducted to balance the baseline characteristics between groups. The mean [standard deviation (SD)] age of included patients was 50.0 (12.4) years, and 288 (37.7%) were women. The PSM yielded 223 matched pairs, with no between-group differences in baseline characteristics. Compared to the high/intermediate SGAs group, the low-risk SGAs group showed consistent decreases in the proportion of participants with metabolic syndrome [e.g., at 6 months: risk differences = 19.28%, 95% confidence interval (CI) = -28.19% to -10.38%; odds ratio = 0.47, 95% CI = 0.30 to 0.72] and the number of metabolic abnormalities [e.g., at 6 months: mean difference (MD) = -0.52, 95% CI = -0.75 to -0.29; relative risk = 0.79, 95% CI = 0.71 to 0.87]. The low-risk SGAs group presented significant improvement in metabolic parameters, including lower levels of weight, glucose and triglyceride (e.g., for triglycerise, (MD = -0.41 mmol/L, 95% CI = -0.61 to -0.21 mmol/L at 6 months), compared to the high/intermediate risk SGAs group. These assocaitions were more pronounced in those with no comorbid physical conditions, lower BMI, shorter duration and reporting smoking or drinking. Adding or switching to low-risk antipsychotics was associated with a decrease in metabolic outcomes, which can be considered as an appropriate secondary prevention strategy for patients with both schizophrenia and metabolic abnormalities.

Stigma substantially contributes to the burden of psychotic disorders such as schizophrenia. Previous attempts to reduce stigma based on neurobiological illness models were unsuccessful. In this Perspective article, we argue that these models may have failed to reduce stigma in schizophrenia because of their lack of explanatory power and their connotations of biological otherness and determinism. We suggest that recent developments in the realm of computational psychiatry may help to remedy this situation. In particular, we discuss the potential of predictive processing, a highly influential computational framework of brain function, to reduce the stigma associated with schizophrenia. We argue that predictive processing accounts may do so by bridging the explanatory gap between biology and psychotic experiences within a normative theory of brain function, thus offering a normalizing perspective on the neural underpinnings of schizophrenia. This may facilitate not only a better understanding of psychotic experiences but also counteract connotations of biological determinism and foster belief in change. Viewing schizophrenia through the lens of predictive processing may thus pave the way for the integration of neurobiologically grounded models into the communication with patients, their relatives, and the public, which have the potential to reduce stigma.

Schizophrenia is highly heritable, and polygenic risk score for schizophrenia (PRS_SCZ) has been associated with brain and behavior in healthy populations. However, the full associations of PRS_SCZ with brain white matter microstructure and cognitive and mental health outcomes, the potential effects of sex and areal deprivation on these associations, and the mediation of white matter microstructure for the associations between PRS_SCZ and behavioral outcomes remain largely unknown. In up to 300,000 participants from the UK Biobank, we investigated the associations of PRS_SCZ with eight white matter microstructure metrics of 48 tracts and 14 cognitive and mental health phenotypes, and we further tested the moderation of sex and index of multiple deprivation (IMD) on these associations and the mediation of brain white matter phenotypes for the associations between PRS_SCZ and behavioral outcomes. We found that higher PRS_SCZ was associated with decreased white matter integrity in 26 tracts, such as cingulum, corona radiata, and fornix. We also found that higher PRS_SCZ was associated with poorer mental health and worse cognitive performance. These associations were not significantly moderated by sex and IMD. Causal mediation analyses revealed that these adverse effects of PRS_SCZ on cognitive and mental health outcomes were partially mediated by brain white matter phenotypes. These results indicate that genetic risk for schizophrenia affects the integrity of white matter tracts, which may account for its adverse effects on cognitive and mental health outcomes.

Brain activity undergoes intrinsic fluctuations with complexities specific to both the resting state and the task state. However, in patients with schizophrenia (SZ), where the boundary between internal and external realms is blurred, optimal modulation of these complexities between rest and stimulus phases is likely disrupted. Here, we present a frequency-dependent rest-task shift in electroencephalography (EEG) complexity in normal controls (NCs) and the associated abnormal patterns in patients with SZ. Specifically, we examined EEG complexity in different frequency bands, quantified by multiscale entropy (MSE), during the resting state and a 40 Hz auditory steady-state response (ASSR) task in 77 normal controls (NCs) and 103 patients with SZ. We compared the ASSR/resting MSE ratio between the NC and SZ groups. In the NC group, transitioning from the resting state to the ASSR state caused increased alpha-band entropy and decreased gamma-band entropy, whereas no such shifts were observed in patients with SZ. This study suggests that in NCs, alpha-band oscillatory complexity, which influences cortical response properties, increases during the transition from intrinsic to extrinsic information processing, while gamma-band oscillatory complexity decreases, likely due to concentration on auditory processing of a temporal enriching stimulation with high salience. Patients with SZ, which are marked by impaired neural synchrony, lacked the NCs' pronounced changes in neural complexity across frequency bands. This indicates that in patients with SZ, disruptions in the spontaneous activity that shapes the internal mental state may alter the properties of cortical responses and entrainment to external stimuli.

The default position in the treatment of psychotic conditions is that lifelong treatment is required after multiple episodes, with some portion of patients able to stop after a single episode. However, there are reasons to question this consensus, including that not everyone who stops antipsychotics relapses, the protective effects of antipsychotics may have been exaggerated due to the possibility that withdrawal itself is associated with adverse effects, including relapse, there is little evidence that antipsychotics target a pathological mechanism and their adverse effects may outweigh their benefits for some users. Recent pragmatic trials that employ a gradual reduction strategy give mixed results. They highlight that relapse is still a potential risk, but there may be gains in terms of social functioning in the long-term. There are no consistent factors that enable identification of people who might be able to discontinue antipsychotics more successfully, suggesting this option should be more widely offered. A gradual, hyperbolic approach to tapering has been proposed to reduce the adverse effects of withdrawal and relapse on stopping-approximated, for example, by reductions of 5-10% of the most recent dose every month. Patients should be supported to make decisions about long-term antipsychotic treatment based on weighing up the pros and cons of antipsychotic effects, in the light of the evidence base and the individual's priorities. Given that increasing duration of treatment is likely to increase the risk of withdrawal on stopping, long-term antipsychotic treatment should be minimized where possible.

Fundamental to coherence in discourse is referential structure - identifying entities through noun phrases (NPs, e.g. a man; that large cat) and tracking them in discourse. But coherence is also mediated by conceptual-semantic structure, as tracked through semantic similarity relations between words, and by predictability ("perplexity"). Alterations in speech coherence have long been noted in schizophrenia spectrum disorders (SSD) along all three of these dimensions. These are likely connected, but have largely been studied in isolation. This study targeted them together, in Turkish-speaking people with a first episode of psychosis (FEP, n = 53), youths at ultra-high risk (UHR, n = 64) of SSD, people with a family history of psychosis (FHP, N = 39), and 34 neurotypical controls (NC). In FEP, we confirmed a pattern previously attested in chronic SSD, of fewer definite NPs (e.g., this bald man), more "bare" NPs-i.e., lacking functional elements such as this/a -, and an unexpected random distribution of indefinite NPs; moreover, referential anomalies (unclarities of reference) were more prevalent in all groups relative to NC. FEP and UHR also showed higher word-to-word semantic similarity, and FEP larger image-to-text bimodal semantic distance, mirroring a pattern previously attested in English. NP-related variables related to both semantic similarity and perplexity, with crucially different correlational patterns seen for definite vs. indefinite NPs. Together, these results substantiate crosslinguistic evidence of a referential disturbance in early psychosis, partially extending to the extended schizophrenia phenotype, while additionally supporting that referential structure is closely integrated with conceptual semantics and the probabilistic structure of speech.