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BACKGROUND: Individuals with Schizophrenia Spectrum Disorders (SSD) often suffer from obesity and do limited Physical Activity (PA). PA has many beneficial effects on a variety of somatic and mental variables and it should be strengthened among people with mental disorders. The relationship between Body Mass Index (BMI), Waist Circumference (WC), and PA in this population is poorly understood, with a lack of precise PA assessment. This study investigates the association between BMI, WC, weight, and PA in individuals with SSD and controls using accelerometers. METHODS: One hundred twenty-six patients with SSD (residents and outpatients) and 110 sex- and age-matched controls were enrolled. Clinical, sociodemographic, and quality-of-life data were collected. PA was measured with a tri-axial ActiGraph GT9X and quantified by Vector Magnitude (VM). Relationships between PA and BMI, WC, and weight changes were analysed using linear regression models. RESULTS: Patients were more likely to be unmarried, unemployed, and less educated compared to controls (p < 0.001). Residents had more medical comorbidities (p = 0.001), while outpatients had higher BMI, weight, and WC (p < 0.001). Residents reported more severe psychopathology, lower functioning, and greater use of psychopharmacological medications (p < 0.001). Higher PA levels were not significantly associated with lower BMI, WC, or weight. Although not statistically significant, increased PA showed a trend towards lower obesity risk. CONCLUSIONS: Sociodemographic, medical, and clinical characteristics of individuals with SSD define vulnerability factors that can inform tailored interventions to improve PA.

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Objective: Social interactions and experiences are increasingly occurring online, including for young adults with psychosis. Healthy social interactions and experiences are widely recognized as a critical component of social recovery, yet research thus far has focused predominantly on offline interactions with limited understanding of these interactions online. We developed the Social Media and Internet sociaL Engagement (SMILE) questionnaire to assess the type, frequency, and nature of online social interactions and experiences among young adults with early psychosis to better assess online social activity and ultimately support personalized interventions. Methods: Participants (N = 49) completed the SMILE questionnaire which asked about online platforms used, frequency of use, and if positive and negative experiences were more likely to happen online or offline. Participants completed additional self-report measures of victimization, positive psychotic symptoms, social functioning, and demographics. Exploratory factor analysis and correlations between identified factors and clinical measures of interest were completed. Results: Exploratory factor analysis revealed three factors: positive engagement, victimization, and internalizing experiences. Most participants (6%-37%) experienced positive engagement offline. Victimization occurred equally online and offline (8%-27% and 4%-24%, respectively). Most participants (37%-51%) endorsed internalizing experiences as occurring equally offline and online, but approximately a third of participants reported internalizing experiences more frequently offline (20%-35%). Victimization was moderately (r = 0.34) correlated with overall online social experiences, suggesting more online time may increase the likelihood of victimization. Age was inversely related to the frequency of overall online social experiences. Conclusion: Young adults with early psychosis experience positive and negative social experiences online and offline. New scales and measures to comprehensively assess the nature and function of online social interactions and experiences are needed.

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BACKGROUND: Schizophrenia Spectrum Disorders (SSDs), which are characterized by social cognitive deficits, have been associated with dysconnectivity in "unimodal" (e.g., visual, auditory) and "multimodal" (e.g., default-mode and frontoparietal) cortical networks. However, little is known regarding how such dysconnectivity relates to social and non-social cognition, and how such brain-behavioral relationships associate with clinical outcomes of SSDs. METHODS: We analyzed cognitive (non-social and social) measures and resting-state functional magnetic resonance imaging data from the 'Social Processes Initiative in Neurobiology of the Schizophrenia(s) (SPINS)' study (247 stable participants with SSDs and 172 healthy controls, ages 18-55). We extracted gradients from parcellated connectomes and examined the association between the first 3 gradients and the cognitive measures using partial least squares correlation (PLSC). We then correlated the PLSC dimensions with functioning and symptoms in the SSDs group. RESULTS: The SSDs group showed significantly lower differentiation on all three gradients. The first PLSC dimension explained 68.53% (p<.001) of the covariance and showed a significant difference between SSDs and Controls (bootstrap p<.05). PLSC showed that all cognitive measures were associated with gradient scores of unimodal and multimodal networks (Gradient 1), auditory, sensorimotor, and visual networks (Gradient 2), and perceptual networks and striatum (Gradient 3), which were less differentiated in SSDs. Furthermore, the first dimension was positively correlated with negative symptoms and functioning in the SSDs group. CONCLUSIONS: These results suggest a potential role of lower differentiation of brain networks in cognitive and functional impairments in SSDs.

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Objective: The incidence of neuroleptic malignant syndrome (NMS), a rare, potentially fatal adverse effect of antipsychotics, among children and youth is unknown. This cohort study estimated NMS incidence in antipsychotic users age 5-24 years and described its variation according to patient and antipsychotic characteristics. Methods: We used national Medicaid data (2004-2013) to identify patients beginning antipsychotic treatment and calculated the incidence of NMS during antipsychotic current use. Adjusted hazard ratios (HRs) assessed the independent contribution of patient and antipsychotic characteristics to NMS risk. Results: The 1,032,084 patients had 131 NMS cases during 1,472,558 person-years of antipsychotic current use, or 8.9 per 100,000 person-years. The following five factors independently predicted increased incidence: age 18-24 years (HR [95% CI] = 2.45 [1.65-3.63]), schizophrenia spectrum and other psychotic disorders (HR = 5.86 [3.16-10.88]), neurodevelopmental disorders (HR = 7.11 [4.02-12.56]), antipsychotic dose >200mg chlorpromazine-equivalents (HR = 1.71 [1.15-2.54]), and first-generation antipsychotics (HR = 4.32 [2.74-6.82]). NMS incidence per 100,000 person-years increased from 1.8 (1.1-3.0) for those with none of these factors to 198.1 (132.8-295.6) for those with 4 or 5 factors. Findings were essentially unchanged in sensitivity analyses that restricted the study data to second-generation antipsychotics, children age 5-17 years, and the 5 most recent calendar years. Conclusion: In children and youth treated with antipsychotics, five factors independently identified patients with increased NMS incidence: age 18-24 years, schizophrenia spectrum and other psychotic disorders, neurodevelopmental disorders, first-generation drugs, and antipsychotic doses greater than 200 mg chlorpromazine-equivalents. Patients with 4 or 5 of these factors had more than 100 times the incidence of those with none. These findings could improve early identification of children and youth with elevated NMS risk, potentially leading to earlier detection and improved outcomes.

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With the growing availability of medical data and the enhanced performance of computers, new opportunities for data analysis in research are emerging. One of these modern approaches is machine learning (ML), an advanced form of statistics broadly defined as the application of complex algorithms. ML provides innovative methods for detecting patterns in complex datasets. This enables the identification of correlations or the prediction of specific events. These capabilities are especially valuable for multifactorial phenomena, such as those found in mental health and forensic psychiatry. ML also allows for the quantification of the quality of the emerging statistical model. The present study aims to examine various sociodemographic variables in order to detect differences in a sample of 370 offender patients and 370 non-offender patients, all with schizophrenia spectrum disorders, through discriminative model building using ML. In total, 48 variables were tested. Out of seven algorithms, gradient boosting emerged as the most suitable for the dataset. The discriminative model finally included three variables (regarding country of birth, residence status, and educational status) and yielded an area under the curve (AUC) of 0.65, meaning that the statistical discrimination of offender and non-offender patients based purely on the sociodemographic variables is rather poor.

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BACKGROUND AND OBJECTIVE: The accurate diagnosis of schizophrenia spectrum disorder plays an important role in improving patient outcomes, enabling timely interventions, and optimizing treatment plans. Functional connectivity analysis, utilizing functional magnetic resonance imaging data, has been demonstrated to offer invaluable biomarkers conducive to clinical diagnosis. However, previous studies mainly focus on traditional machine learning methods or hand-crafted neural networks, which may not fully capture the spatial topological relationship between brain regions. METHODS: This paper proposes an evolutionary algorithm (EA) based graph neural architecture search (GNAS) method. EA-GNAS has the ability to search for high-performance graph neural networks for schizophrenia spectrum disorder prediction. Moreover, we adopt GNNExplainer to investigate the explainability of the acquired architectures, ensuring that the model's predictions are both accurate and comprehensible. RESULTS: The results suggest that the graph neural network model, derived using genetic algorithm search, outperforms under five-fold cross-validation, achieving a fitness of 0.1850. Relative to conventional machine learning and other deep learning approaches, the proposed method yields superior accuracy, F1 score, and AUC values of 0.8246, 0.8438, and 0.8258, respectively. CONCLUSION: Based on a multi-site dataset from schizophrenia spectrum disorder patients, the findings reveal an enhancement over prior methods, advancing our comprehension of brain function and potentially offering a biomarker for diagnosing schizophrenia spectrum disorder.

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OBJECTIVE: Antipsychotic effectiveness in preventing relapse declines around menopausal age in women with schizophrenia or schizoaffective disorder (SSD). It is not known whether systemic menopausal hormone therapy (MHT) can help to prevent psychosis relapse. METHODS: A within-subject study design was used to study the effectiveness of MHT in preventing relapse in a Finnish nationwide cohort of women with SSD between 40 and 62 years of age who used MHT during follow-up (1994-2017). Hazard ratios adjusted for age and psychotropic drug use were calculated for psychosis relapse as main outcome and any psychiatric hospitalization as secondary outcome. RESULTS: The study population comprised 3,488 women using MHT. Use of MHT was associated with a 16% lower relapse risk (adjusted hazard ratio [aHR]=0.84, 95% CI=0.78-0.90) when compared to non-use. Stratified by age, MHT was associated with decreased relapse risks when used between ages 40-49 (aHR=0.86, 95% CI=0.78-0.95) and ages 50-55 (aHR=0.74, 95% CI=0.66-0.83), but not between ages 56-62 (aHR=1.11, 95% CI=0.91-1.37). Similar effectiveness was found for estrogen alone or combined with fixed or sequential progestogens (aHRs between 0.79 and 0.86), transdermal and oral formulations (aHRs 0.75-0.87), and for most specific formulations (aHRs 0.75-0.85), except tibolone (aHR=1.04, 95% CI=0.75-1.44) and formulations with dydrogesterone (aHR=1.05, 95% CI=0.85-1.30). Similar results were observed with any psychiatric hospitalization as outcome measure. CONCLUSIONS: The findings underscore the potential value of MHT in preventing psychosis relapse among women with SSD of menopausal age. These findings translate clinical evidence on the neuroprotective effects of estrogens to real-world settings, encompassing a group of women for whom current antipsychotic treatment options may be insufficient.

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OBJECTIVE: Amphetamine prescribing has increased in the United States in recent years. Previous research identified an increased risk of incident psychosis with prescription amphetamines. The purpose of this study was to examine the impact of dose levels of prescription amphetamines on the risk of this rare but serious adverse outcome. METHODS: A case-control study using electronic health records was conducted to compare the odds of incident psychosis or mania with past-month exposure to prescription amphetamines. Case subjects were patients ages 16-35 hospitalized at McLean Hospital for incident psychosis or mania between 2005 and 2019. Control subjects were patients with an initial psychiatric hospitalization for other reasons, most commonly depression and/or anxiety. Amphetamine doses were converted to dextroamphetamine equivalents and divided into terciles. Secondary analyses evaluated the odds of psychosis or mania with methylphenidate use. RESULTS: Among 1,374 case subjects and 2,748 control subjects, the odds of psychosis and mania were increased for individuals with past-month prescription amphetamine use compared with no use (adjusted odds ratio=2.68, 95% CI=1.90-3.77). A dose-response relationship was observed; high doses of amphetamines (>30 mg dextroamphetamine equivalents) were associated with 5.28-fold increased odds of psychosis or mania. Past-month methylphenidate use was not associated with increased odds of psychosis or mania compared with no use (adjusted odds ratio=0.91, 95% CI=0.54-1.55). CONCLUSIONS: Although use of hospitalized control subjects excludes individuals with less severe disease, leading to selection bias, the study results suggest that caution should be exercised when prescribing high doses of amphetamines, with regular screening for symptoms of psychosis or mania.

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OBJECTIVE: The authors used longitudinal biobank data with up to 25 years of follow-up on over 2,600 clozapine users to derive reliable estimates of the real-world burden of clozapine adverse drug events (ADEs). METHODS: A total of 2,659 participants in the FinnGen biobank project had a schizophrenia diagnosis and clozapine purchases with longitudinal electronic health record follow-up for up to 25 years after clozapine initiation. Diseases and health-related events enriched during clozapine use were identified, adjusting for disease severity. The incidence and recurrence of ADEs over years of clozapine use, their effect on clozapine discontinuation and deaths, and their pharmacogenetics were studied. RESULTS: Median follow-up time after clozapine initiation was 12.7 years. Across 2,157 diseases and health-related events, 27 were enriched during clozapine use, falling into five disease categories: gastrointestinal hypomotility, seizures, pneumonia, other acute respiratory tract infections, and tachycardia, along with a heterogeneous group including neutropenia and type 2 diabetes, among others. Cumulative incidence estimates for ileus (severe gastrointestinal hypomotility) and pneumonia were 5.3% and 29.5%, respectively, 20 years after clozapine initiation. Both events were significantly associated with increased mortality among clozapine users (ileus: odds ratio=4.5; pneumonia: odds ratio=2.8). Decreased genotype-predicted CYP2C19 and CYP1A2 activities were associated with higher pneumonia risk. CONCLUSIONS: Clozapine-induced ileus and pneumonia were notably more frequent than has previously been reported and were associated with increased mortality. Two CYP genes influenced pneumonia risk. Pneumonia and ileus call for improved utilization of available preventive measures.

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BACKGROUND: Autism and schizophrenia spectrum disorders (SSDs) both feature atypical social cognition. Despite evidence for comparable group-level performance in lower-level emotion processing and higher-level mentalizing, limited research has examined the neural basis of social cognition across these conditions. Our goal was to compare the neural correlates of social cognition in autism, SSDs, and typically developing controls (TDCs). METHODS: Data came from two harmonized studies in individuals diagnosed with autism or SSDs and TDCs (aged 16-35 years), including behavioral social cognitive metrics and two functional magnetic resonance imaging (fMRI) tasks: a social mirroring Imitate/Observe (ImObs) task and the Empathic Accuracy (EA) task. Group-level comparisons, and transdiagnostic analyses incorporating social cognitive performance, were run using FSL's PALM for each task, covarying for age and sex (1000 permutations, thresholded at p < 0.05 FWE-corrected). Exploratory region of interest (ROI)-based analyses were also conducted. RESULTS: ImObs and EA analyses included 164 and 174 participants, respectively (autism N = 56/59, SSD N = 50/56, TDC N = 58/59). EA and both lower- and higher-level social cognition scores differed across groups. While canonical social cognitive networks were activated, no significant whole-brain or ROI-based group-level differences in neural correlates for either task were detected. Transdiagnostically, neural activity during the EA task, but not the ImObs task, was associated with lower- and higher-level social cognitive performance. LIMITATIONS: Despite attempting to match our groups on age, sex, and race, significant group differences remained. Power to detect regional brain differences is also influenced by sample size and multiple comparisons in whole-brain analyses. Our findings may not generalize to autism and SSD individuals with co-occurring intellectual disabilities. CONCLUSIONS: The lack of whole-brain and ROI-based group-level differences identified and the dimensional EA brain-behavior relationship observed across our sample suggest that the EA task may be well-suited to target engagement in novel intervention testing. Our results also emphasize the potential utility of cross-condition approaches to better understand social cognition across autism and SSDs.

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BACKGROUND: Schizophrenia spectrum disorders are characterized by cognitive decline, which is evident even in the prodromal phase. Aging is a complex gradual procedure that affects, among other organs, the central nervous system, resulting in age-related cognitive decline. OBJECTIVE: The objective of this study is to assess the cognitive function of patients diagnosed with psychotic disorders, in comparison with healthy controls, along the age spectrum. METHODS: Sixty patients diagnosed with schizophrenia spectrum disorders in remission, 20-59 years old, and 60 healthy controls, matched by age and educational level, from the region of Thessaly in Central Greece, were evaluated, with respect to their cognitive performance, using the Greek version of the Montreal Cognitive Assessment (MoCA). Correlations between age and MoCA total and cognitive domains' scores, as well as statistical analysis of variance (ANOVA) and t-test among age groups, were performed using Statistical Product and Service Solutions (SPSS, version 23; IBM SPSS Statistics for Windows, Armonk, NY). RESULTS: The MoCA score was negatively correlated with age, both in the patients' group (p<0.001) and in the control group (p=0.001). A significant statistical difference in mean MoCA scores between patients and healthy controls was observed, not only in the total sample (p<0.001) but also in all age groups (20-29: p=0.006, 40-49: p=0.024, 50-59: p<0.001), except for age group 30-39 (30-39: p=0.356). Statistically significant differences were also found between patients and healthy controls in the total sample, regarding specific cognitive domains, in the visuospatial and executive function domain (p=0.01), attention domain (p<0.001), language domain (p<0.001), and orientation domain (p<0.005). Interestingly, different deterioration patterns in cognitive domains were observed in each age group. Specifically, in the age group 20-29, statistically significant differences were found between patients and healthy controls in the language domain (p<0.014) and orientation domain (p<0.041). No difference was found in the age group 30-39, while statistically significant differences were found between patients and healthy controls in the age group 40-49 in the attention domain (p<0.001) and language domain (p<0.001). Finally, in the age group 50-59, such differences were found in the visuospatial and executive function domain (p=0.041), attention domain (p=0.006), and language domain (p=0.001). Statistically significant cognitive decline occurs in a shorter period in the patients' group, suggesting an accelerated cognitive decline in psychotic patients after middle age. CONCLUSIONS: Age-related cognitive decline in psychotic patients occurs at an accelerated rate in relation to the control sample, with age-specific cognitive domain decline patterns, due to the cumulative effect of aging and psychosis on cognition. Further, larger, multicenter research should focus on establishing these results and designing relevant procognitive interventions.

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We implemented a pilot study to investigate symptoms and functional outcomes of Asian Americans treated in urban community mental health centers for a diagnosis of schizophrenia spectrum disorder. Furthermore, we investigated whether these outcomes differed between East and Southeast Asians. We collected quantitative data from 75 participants recruited using a nonprobability sampling strategy from six urban community mental health centers. We used the Positive and Negative Syndrome Scale (Kay et al. in Schizophrenia Bulletin 13(2):261-276, 1987) and the Strauss and Carpenter Outcome Scale (Strauss and Carpenter in Archives of General Psychiatry 27(6):739-746, 1972) to measure their symptoms and functional outcomes. To compare the outcomes between East and Southeast Asians, we used a multivariable logistic regression model, which adjusted for the estimated effects of age, sex assigned at birth, and age at onset of illness for each outcome examined. The data shows that the treatment outcomes for this group are poor. Only a small number of participants experienced symptomatic remission (30.67%), role restoration (34.67%), and clinical recovery (21.33%). The majority of those who did not experience clinical recovery had difficulties sustaining symptomatic remission and restoring role functioning (54.67%). However, more participants achieved social restoration (68.00%). The results did not vary by national origin groups and sex assigned at birth. However, the participant's age, the age at which the illness began, or both determined whether the treatment outcomes were favorable. Findings underscore the need for interventions that improve symptom control to increase the likelihood of other favorable outcomes.

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OBJECTIVE: Stigma toward schizophrenia spectrum disorders is pervasive and negatively influences service access and delivery. Cognitive impairment associated with schizophrenia (CIAS) is common, but its association with stigma is unknown. In this study, the authors examined whether individuals with CIAS receiving cognitive remediation treatment report experiencing CIAS-related stigma and sought to establish associations between CIAS-related stigma and recovery-relevant outcomes. METHODS: Data from 48 individuals with schizophrenia spectrum diagnoses were drawn from a larger study evaluating cognitive remediation. Participants completed measures of CIAS-related stigma, internalized mental illness stigma, self-perceived cognitive impairment, cognitive performance, and interviewer-rated quality of life. RESULTS: CIAS-related stigma was commonly reported and significantly positively associated with internalized stigma and self-perceived cognitive impairment. CIAS-related stigma was also significantly negatively associated with motivation to engage in goal-directed behavior and daily activities. CONCLUSIONS: CIAS-related stigma exists and warrants additional exploration with regard to implications for psychiatric service delivery.

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This publication presents an analysis of the psychological concepts, involved in the construction of clinical models of schizophrenia; in particular - the new clinical-biological paradigm of schizophrenia (reflecting the data of own psychometric studies). Based on the analysis, 3 modes of interaction between clinical and psychological constructs in the construction of models of schizophrenia were identified. The conceptualization of clinical models was carried out from the perspective of the contribution of psychological and psychometric constructs - allowing to expand theoretical ideas about the dynamics of views on the clinical construct of schizophrenia.

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Schizophrenia is recognized as one of the most severe psychiatric disorders, with its pathogenesis likely involving genetic, epigenetic, developmental, and environmental factors. Members of the Methyl-CpG Binding Domain (MBD) Family play a crucial role in the regulation of genomic DNA methylation, and studies have implicated the association between MBD family and neurodevelopmental disorders. Copy number variations (CNVs) are a significant genetic basis for human genomic variation, also playing a critical role in the genetic processes of schizophrenia. Therefore, we aimed to evaluate the susceptibility of MBD family CNVs to schizophrenia by exploring and validating them in two separate populations using CNVplex™ and qPCR methods, and to explore the relationship between MBD family CNVs and clinical phenotypes in the overall population using chi-square tests and Fisher's exact tests. Results suggest that an increase in MBD1 gene copy number and a deficiency in MBD2 gene copy number may be associated with the risk of schizophrenia. The deficiency in MBD2 gene copy number may increase the risk of delusion of reference and delusion of persecutory in the overall sample, as well as in males. This research provides preliminary evidence supporting the association between MBD family CNVs and schizophrenia, highlighting the potential role of the MBD family in the pathogenesis of schizophrenia.

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Background and hypothesis: Assigning a psychiatric diagnosis in real-world situations is often difficult, given that the clinical presentation does not usually conform to the list of condensed, simplified behavioral descriptors of mainstream operational taxonomies (MOT) (eg, ICD-11 and DSM-5). The goal of this study was to benchmark diagnostic accuracy and reliability on a central and severe spectrum of psychopathology (ie, the schizophrenia spectrum disorders [SSDs]), adopting a pragmatic approach as close as possible to real-world clinical settings. Study Design: We examined the diagnostic performance of 30 international psychiatrists experts in SSD. The clinicians were asked to make their clinical best diagnostic estimate for two written clinical vignettes excerpted from real-world SSD cases. Study Results: In the first vignette, 22 out of the 30 clinicians (73.5%) indicated a SSD as their main diagnostic hypothesis. In the second vignette, 12 clinicians (40%) chose SSD as their main diagnostic hypothesis. Only 10 of the 30 clinicians (33%) correctly identified both vignettes as cases of SSD. The level of interrater diagnostic agreement (Fleiss' Kappa) was low but statistically significant (KFleiss = 0.08, P = .01). Conclusions: The results suggest that, even in a sample of influential international psychiatrists, the diagnostic accuracy and reliability on SSD presentations is poor and substantially inferior to those obtained in reliability studies using structured or semi-structured interviews. The widespread adoption of MOT systems in the last decades may have inadvertently eroded the ability of clinicians to detect a typical pattern of psychiatric illnesses.

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Schizophrenia spectrum disorders (SSD) are debilitating, with auditory verbal hallucinations (AVHs) being a core characteristic. While gray matter volume (GMV) reductions are commonly replicated in SSD populations, the neural basis of AVHs remains unclear. Using previously published data, this study comprises two main analyses, one of GMV dissimilarities between SSD and healthy controls (HC), and one of GMV differences specifically associated with AVHs. Structural brain images from 71 adults with (n = 46) and without (n = 25) SSD were employed. Group differences in GMVs of the cortex, anterior cingulate (ACC), superior temporal gyrus (STG), hippocampi, and thalami were assessed. Additionally, volumes of left Heschl's gyrus (HG) in a subgroup experiencing AVHs (AVH+, n = 23) were compared with those of patients who did not (AVH-, n = 23). SSD patients displayed reduced GMVs of the cortex, ACC, STG, hippocampi, and thalami compared to HC. AVH+ had significantly reduced left HG volume when compared to AVH-. Finally, a right-lateralized ventral prefrontal cluster was found to be uniquely associated with AVH severity. This study corroborates previous findings of GMV reductions in SSD cohorts. Chiefly, our secondary analysis suggests that AVHs are associated with language areas and their contralateral homologues.

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The concept of basic Self-disorders (SD) captures the experiential aspects associated with vulnerability to schizophrenia spectrum disorders (SSD). SD emerge prior to, and constitute the underlying structure for, the emergence of major diagnostic symptoms, including positive psychotic ones. SD are also detectable in populations with familial risk for SSD. This paper proposes a two-stage phenomenological-developmental model, exploring the early deficit in multisensory integration and their impact on the ontogeny of the Minimal Self in the first years of life. It also examines subsequent emergence of schizotaxic vulnerability, which later manifests as typical anomalies of subjectivity, such as basic symptoms and self-disorders.

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OBJECTIVE: Contemporary research suggests reduced telomere length in schizophrenia spectrum disorders (SZ) compared to age-adjusted non-affected individuals. However, the role of telomere maintenance and telomere repair in SZ is poorly understood as well as the involvement of telomere biology in cognitive abnormalities in SZ. METHODS: The study consisted of 758 participants (SZ [n = 357] and healthy controls, HC [n = 401]) collected as part of the Norwegian TOP study. Participants were assessed with standardized neuropsychological tests measuring five cognitive domains. Leucocyte telomere length (TL) was measured via blood and determined by quantitative real-time Polymerase Chain Reaction (qPCR) providing a telomere to single copy ratio (T/S ratio), used to estimate the mean telomere length. Telomerase activity was assessed by the expression levels of the Telomerase Reverse Transcriptase (TERT) and Telomerase RNA Component (TERC) genes. To assess telomere maintenance and telomere repair we calculated the telomerase expression to TL ratio (TERT/TL and TERC/TL respectively). RESULTS: Patients had reduced TERT (F = 5.03, p = 0.03), but not TERC expression (F = 1.04, p = 0.31), and higher TERT/TL (F = 6.68, p = 0.01) and TERC/TL (F = 6.71, p = 0.01), adjusted for age, sex, and ethnicity. No statistically significant association was observed between any of the telomere biology markers and the cognitive domains (p > 0.05). CONCLUSION: Our study shows changes in TERT expression and telomere maintenance and telomere repair in SZ compared HC. However, the role of telomere biology in the mechanism underlying cognitive impairment in psychosis seems limited.

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To assess the effect of Long-acting injectable (LAI) antipsychotics in acutely ill patients, we systematically searched major databases for randomized controlled trials (RCTs) comparing LAIs with other LAIs, oral antipsychotics, or placebo in acutely symptomatic adults with schizophrenia-spectrum disorders. Data were analyzed with a random-effects network meta-analysis. Co-primary outcomes were efficacy (mean change in psychopathology rating scales) and acceptability (all-cause discontinuations) at study endpoint. Of 25 RCTs, 19 studies tested second-generation LAIs (SGA-LAIs) and six first-generation LAIs (FGA-LAIs). Due to a disconnected network, FGA-LAIs were analyzed separately, with poor data quality. The SGA-LAIs network included 8,418 individuals (males=63%, mean age=39.3 years). All SGA-LAIs outperformed placebo in reducing acute symptoms at study endpoint (median follow-up=13 weeks). They were more acceptable than placebo with the only exception of olanzapine, for which no differences with placebo emerged. Additionally, we distinguished between different LAI formulations of the same antipsychotic to explore potential pharmacokinetic differences. Most formulations outperformed placebo in the very short-term (2 weeks or less), regardless of the need for initial oral supplementation. SGA-LAIs are evidence-based treatments in acutely ill individuals with schizophrenia-spectrum disorders. Findings support the use of SGA-LAIs to manage psychopathology and improve adherence right from the acute phases of illness.

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