Schizophrenia (Heidelberg, Germany)最新文献

Experiential negative symptoms (ENS) of schizophrenia, such as asociality, anhedonia, and avolition, are associated with poor outcomes, yet no FDA-approved pharmacotherapies currently exist specifically to target these symptoms. With the increasing use of smartphones, evidence-based digital interventions delivered by prescription digital therapeutics (DTx) may present an opportunity to address the unmet therapeutic need for ENS of schizophrenia. CT‑155/BI 3972080 (CT-155) is being developed as a smartphone-based prescription DTx for the treatment of ENS. A multicenter, 7-week, single-arm, open-label, exploratory study (NCT05486312) evaluated the engagement, adherence, potential effectiveness, acceptability, user experience, and safety of an abbreviated version of CT-155 (CT‑155 beta). Engagement and adherence with CT-155 beta were measured passively throughout the study using the study app. Change in ENS severity was assessed using the clinically administered clinical assessment interview for negative symptoms, motivation, and pleasure subscale (CAINS-MAP). Acceptability and user experience were assessed using the validated Mobile App Rating Scale (MARS) along with an episodic user experience survey, respectively. Fifty participants with a clinically confirmed schizophrenia diagnosis were enrolled; 80% were male, 58% were Black or African American, and the median (range) age was 53.5 (23-64) years. At baseline, participants' mean (SD) CAINS-MAP total score was 20.5 (8.3). Most participants (n = 43; 86%) completed the 7-week study. Participants readily engaged with CT-155 beta. Kaplan-Meier retention analysis showed that 84% of participants (N = 42/50) engaged with CT-155 beta (i.e., last app open) until the end of the study period. Daily app check-ins were completed on a median (IQR) of 43.0 (19-47) days of the 49 possible days (88%). The median (IQR) duration of engagement was 11.6 (8.1-16.1) min per session. Additionally, adherence with CT-155 was high, with participants completing a median of 18 (IQR 13-20) of the 21 therapeutic lessons available. After 7 weeks of CT-155 beta usage, the mean change in within-subject CAINS-MAP score was 3.6 points from baseline (95% CI 1.3, 5.8; p = 0.0026; baseline: 20.4 (8.6) Week 7: 16.8 (7.7)). Most participants (91%; n = 39/43) rated CT-155 beta functionality using MARS assessment as acceptable or higher, with an overall mean MARS functionality subscale score of 4.2 points out of 5 points, with 5 corresponding to "excellent" at Week 7. The end of study participant feedback survey showed that 95% (n = 42/44) of participants would recommend using CT-155 beta. No app-related adverse events nor severe adverse events leading to discontinuation of the study were reported. Overall, the study demonstrated the feasibility of CT-155 beta in participants with ENS of schizophrenia. Results from this feasibility study show the potential of evidence-based DTx approaches to address ENS of schizophrenia.

It has been proposed that dysfunctions in emotional multisensory integration (MSI) could contribute to the development of psychosis. To further substantiate this proposition, we investigated whether impaired MSI of emotional cues can be observed in people with high psychosis proneness without a diagnosis of psychosis and whether it is associated with aberrant perception and psychotic experiences. Adults scoring high vs. low on the positive subscale of the Community Assessment of Psychic Experiences (score ≥9 or <9, respectively; n = 36 each) categorized the perceived emotion and rated the intensity of unimodal, bimodal emotionally congruent and bimodal emotionally incongruent dynamic face-voice stimuli. In different blocks, participants were asked to attend to one modality and to ignore the other modality input. Additionally, participants completed self-report questionnaires on anomalous perceptual experiences, hallucinations and paranoia. Participants with high and low psychosis proneness did not differ in emotion categorization performance as indicated by similar inverse efficiency (IE) scores (i.e., mean reaction time divided by accuracy) in all conditions, nor did they differ in intensity ratings in any condition. Correlation analyses did not reveal significant associations between crossmodal (in)congruency effects and self-reported anomalous perceptual experiences, hallucinations or paranoia. Our findings, thus, do not provide support for the assumption that MSI of emotional cues is linked to altered perception or subclinical psychotic symptoms, nor for the notion that MSI of emotional cues is already altered at a very early stage in the developmental trajectory of psychosis.

Individuals with schizophrenia face significantly higher mortality rates than the general population, with a typical reduction in life expectancy of 15-20 years. This study investigated 10-year all-cause mortality and its clinical correlates in a Romanian cohort of patients with schizophrenia, using real-world clinical and hospital and forensic records. A total of 635 individuals hospitalized between 2010 and 2013 were followed for 10 years. Mortality rates, causes of death, and risk factors were assessed using Cox regression models and standardized mortality ratios (SMRs). During the follow-up, 123 patients (19.37%) died, corresponding to a mortality rate of 21.3 per 1000 person-years. The SMR was 1.58 compared to the Romanian general population. Non-violent causes predominated, with cardiovascular disease (27.64%) and infections (17.07%) being the most frequent. Violent deaths, including suicides and accidents, accounted for 17.07% of all mortality. The mean age at death was 58.97 years, reflecting a 17-year reduction in life expectancy. Age was the strongest independent predictor of mortality (HR = 1.07, p < 0.001). Use of second-generation antipsychotics (HR = 0.37, p < 0.001) and low frequency hospitalization (HR = 0.09, p < 0.001) were significantly associated with reduced all-cause and cause-specific mortality. Schizophrenia is associated with significantly increased premature mortality, primarily due to preventable physical illnesses and violent deaths. Early intervention, sustained treatment adherence, and integrated medical care are essential to improve survival outcomes.

Psychiatric disorders present a significant global health burden with limited effective medications. Observing the widespread comorbidities between diabetes and psychiatric disorders, we explored the potential of repurposing antidiabetic drug targets for psychiatric treatments. We identified 32 target genes of 60 antidiabetics and performed Mendelian randomization analyses using expression and protein quantitative trait loci data from brain tissues alongside summary data for seven psychiatric disorders. Additionally, we conducted colocalization analyses, replication analyses in blood and at the single-cell level, single-cell gene annotation, developmental trajectory analysis, and various functional assessments. We found that elevated GANC expression in the putamen basal ganglia, nucleus accumbens basal ganglia, cortex, and whole blood was associated with a reduced risk of bipolar disorder (OR, 0.532-0.877; P, 4.04 × 10^-5 to 1.45 × 10^-7), implying that antagonism of GANC by the antidiabetic drug miglitol could increase bipolar risk. Conversely, increased ABCC8 expression in the cortex, cerebellum, cerebellar hemisphere, and VIP- and LAMP5-expressing inhibitory neurons was linked to a higher risk of schizophrenia (OR, 1.054-1.119; P, 1.46 × 10^-3 to 4.42 × 10^-5), suggesting that ABCC8 inhibition by sulfonylureas or glinides may lower the risk of schizophrenia. Colocalization analysis further confirmed the above associations. GANC and ABCC8 displayed specific developmental trajectories, and functional analyses revealed that they affected psychiatric risk through pathways related to potassium ion channels, insulin secretion, and glucose metabolism. Our findings highlight GANC and ABCC8 as potential targets, suggesting caution in miglitol use for bipolar disorder and the potential repurposing of sulfonylureas and glinides for schizophrenia.

Perinatal insults (e.g., obstetric complications, substance exposure) are increasing in prevalence and confer risk for psychotic-like experiences in offspring, contributing to a growing public health burden. Perinatal insults often co-occur, creating methodological challenges in understanding their impacts on psychosis-spectrum phenotypes. Data-driven approaches to organizing perinatal insults and testing their longitudinal effects on psychotic-like experiences in youth increases ecological validity and translational utility. Using data from 11,417 youth ages 9-14 across five years of the Adolescent Brain Cognitive Development (ABCD) Study, data-driven dimensions of perinatal insults were derived through exploratory factor analysis of thirty-one perinatal insults. Latent growth modeling tested the effect of perinatal insult dimensions on trajectories (baseline, rate-of-change, year-four severity) of distressing psychotic-like experiences. Six dimensions of perinatal insults were observed (substance exposure, obstetric complications, birth complications, postnatal challenges, parental age, medical needs). Substance exposure (β = 0.42, 95% CI [0.20, 0.63]), obstetric complications (β = 0.34, 95% CI [0.08, 0.61]), and parental age (β = 1.00, 95% CI [0.76, 1.22]) were associated with elevated baseline psychotic-like experiences. Perinatal insult dimensions were not associated with increasing rates-of-change in psychotic-like experiences. Medical needs (β = -0.12, 95% CI [-0.20, -0.05]) and parental age (β = -0.11, 95% CI [-0.18, -0.03]) were associated with steeper declines in psychotic-like experiences. Perinatal insult dimensions remained associated with elevated psychotic-like experiences at year-four. Data-driven dimensions of perinatal insults are associated with stably elevated psychotic-like experience trajectories across early adolescence. Given the role of psychotic-like experiences in later psychopathology and functioning, early identification of at-risk offspring is critical in reducing the public health burden of these exposures.

Treatment resistance affects up to one in four individuals with psychosis in the first few years of illness. However, there is limited information about the brain changes associated with treatment resistance, restricting our ability to develop effective prognostic biomarkers or new treatments. Using resting-state functional MRI, we examined striatocortical connectivity in 87 patients who presented a non-affective first-episode of psychosis and 118 healthy controls, with follow-up imaging on more than half of the participants in the next 6 years, totaling 361 images. Crucially, we identified 30 patients who presented treatment-resistant psychosis in this follow-up period. Thus, we examined baseline (at first episode) and longitudinal striatocortical differences within psychosis subgroups (treatment-responsive and treatment-resistant psychosis), and between patients subgroups and healthy controls. Compared to healthy controls, participants with treatment-responsive psychosis presented baseline differences in functional connectivity of ventral striatal systems, without changes over time; whereas patients with treatment-resistant psychosis showed both baseline and longitudinal differences in ventral striatal systems, compared to healthy controls. Treatment-responsive and treatment-resistant psychosis groups differed in longitudinal changes in connectivity between ventral striatal and temporal cortical regions. This is one of the circuits which has been previously related to symptom improvements in patients with first-episode of psychosis. No baseline differences were observed between the two psychosis groups. Overall, treatment-resistant psychosis is characterized by longitudinal changes in striatal systems in early psychosis, which might be used as the basis of future prognostic biomarkers.

Structural and functional brain abnormalities in schizophrenia (SZ) are well-documented, yet the role of the glymphatic system remains largely unexplored. Given emerging evidence linking the microbiome-gut-brain axis to SZ, this study aims to investigate the glymphatic system function in SZ patients using diffusion tensor image analysis along the perivascular space (DTI-ALPS) and to explore its associations with gut microbiota and cognitive performance. Multi-omics data were obtained from a cohort of 87 SZ patients and 70 healthy controls (HCs), including fecal 16S rRNA sequencing, DTI-ALPS index analysis, and cognitive assessments. Correlation and mediation analyses were conducted to explore the relationships among the gut microbiome, DTI-ALPS index, and cognitive performance. Compared to HCs, patients with SZ exhibited significantly lower DTI-ALPS indices in the left, right, and bilateral hemispheres. These indices were positively associated with multiple cognitive domains. In addition, gut microbial dysbiosis was observed in SZ, characterized by a decrease in butyrate-producing bacteria and an increase in pathogenic bacteria. Exploratory analyses further revealed a tripartite link among the key microbial genera, DTI-ALPS indices, and cognitive performance. Notably, the higher abundance of Proteus as well as the lower abundance of Blautia and Faecalibacterium may contribute to poorer cognitive performance, potentially through disruptions in the right DTI-ALPS index. These findings provide novel insights into glymphatic dysfunction in SZ and highlight a potential microbiota-glymphatic-cognition pathway contributing to cognitive impairments.

Faces are essential for effective communication and social interaction. Substantial alterations in face processing are observed in a wide range of mental disorders, in particular, in schizophrenia (SZ). Individuals with SZ experience difficulties to seeing faces in face-pareidolia images that easily elicit face impression in their typically developing (TD) peers. Here, males with SZ and TD controls performed a task with Arcimboldo-like Face-n-Food face-pareidolia images during MEG recording. The outcome reveals that already at early processing stages, the bursts of gamma oscillations differ between SZ and TD individuals in terms of frequency and topography. When contrasting gamma activity for face responses between TD individuals and SZ, the maximum activation for the frequency range of 40-45 Hz originates from the right LOC. In accord with this, in SZ, an advanced analysis of brain connectivity unfolding over time in the low (40-45 Hz) and high (65-70 Hz) gamma ranges reveals alterations in communication between the right LOC and the social brain. In SZ, early engagement of the right LOC is limited to transmitting signals to higher-order regions, whereas in TD, it also serves as a recipient of sophisticated feedback communication from the higher-order areas of the social brain. This study offers novel insights into altered brain communication and the origins of social cognition deficits in SZ that is characterized by a skewed sex ratio with substantial gender differences in disease manifestation.

Schizophrenia is a complex neuropsychiatric disorder, and the abnormalities in brain networks during its early stages remain incompletely understood. Previously, we identified a stable high-intensity functional network, termed the "Frame Network," in healthy individuals and observed its aberrations in schizophrenia patients. This study aimed to utilize this network to explore disconnection abnormalities in early-stage schizophrenia. This study compared drug-naïve first-episode schizophrenia patients (FES, n = 83), ultra-high risk of schizophrenia (UHR, n = 65), and matched healthy controls (HC, n = 67). Frame networks were analyzed across groups, and differences were assessed using networks from healthy people (HP) derived from stable connections in two public datasets. Network-Based Statistics (NBS)-predict identified connections for a disease classification model. FES patients were divided into two subtypes, and connections related to negative symptoms were identified using Connectome-based Predictive Modeling (CPM). UHR and FES patients showed increasing abnormalities in frame connections compared to controls. HP and FES frame networks effectively differentiated groups. Connections crucial for classification were found in the prefrontal motor cortex. Patients divided into two subtypes showed distinct pathological presentations. Frame networks predicted negative symptoms effectively. Variations in regions such as the visual and prefrontal cortex were observed based on symptom severity, indicating diverse underlying connection differences in the clinical heterogeneity of schizophrenia. Our findings indicate that Frame Network abnormalities likely play a significant role in early-stage pathological processes of schizophrenia and show promise as biomarkers for disease classification and symptom prognosis.