Global economic burden of schizophrenia: a systematic review

Neuroleptic malignant syndrome and serotonin syndrome: a comparative bibliometric analysis

OBJECTIVE

This study aimed to analyze and map scientific literature on Neuroleptic Malignant Syndrome (NMS) and Serotonin Syndrome (SS) from prestigious, internationally indexed journals. The objective was to identify key topics, impactful articles, prominent journals, research output, growth patterns, hotspots, and leading countries in the field, providing valuable insights for scholars, medical students, and international funding agencies.

METHODS

A systematic search strategy was implemented in the PubMed MeSH database using specific keywords for NMS and SS. The search was conducted in the Scopus database, renowned for its extensive coverage of scholarly publications. Inclusion criteria comprised articles published from 1950 to December 31st, 2022, restricted to journal research and review articles written in English. Data were analyzed using Microsoft Excel for descriptive analysis, and VOSviewer was employed for bibliometric mapping.

RESULTS

The search yielded 1150 articles on NMS and 587 on SS, with the majority being case reports. Growth patterns revealed a surge in NMS research between 1981 and 1991, while SS research increased notably between 1993 and 1997. Active countries and journals differed between NMS and SS, with psychiatry journals predominating for NMS and pharmacology/toxicology journals for SS. Authorship analysis indicated higher multi-authored articles for NMS. Top impactful articles focused on review articles and pathogenic mechanisms. Research hotspots included antipsychotics and catatonia for NMS, while SS highlighted drug interactions and specific medications like linezolid and tramadol.

CONCLUSIONS

NMS and SS represent rare but life-threatening conditions, requiring detailed clinical and scientific understanding. Differential diagnosis and management necessitate caution in prescribing medications affecting central serotonin or dopamine systems, with awareness of potential drug interactions. International diagnostic tools and genetic screening tests may aid in safe diagnosis and prevention. Reporting rare cases and utilizing bibliometric analysis enhance knowledge dissemination and research exploration in the field of rare drug-induced medical conditions.

Targeting metacognitive change mechanisms in acute inpatients with psychotic symptoms: feasibility and acceptability of a modularized group intervention

Emerging evidence suggests the usefulness of psychological interventions targeting metacognitive change mechanisms in patients experiencing psychosis. Although many of these patients are treated in acute psychiatric contexts, only few studies have adapted such interventions for acute inpatient settings. The present study aimed to assess the feasibility, acceptability, and preliminary clinical outcomes of a novel modularized group intervention focusing on different aspects of metacognitive change mechanisms. In particular, the intervention aims to reduce patients' acute symptoms by enhancing cognitive insight and to relieve distress via cognitive defusion (i.e. coping). A sample of 37 participants with acute psychosis received up to nine sessions of the intervention. Baseline and post-intervention assessments were conducted for general psychopathology, psychotic symptoms, global functioning, and symptom distress. Measures of change mechanisms were assessed before and after the respective treatment module. Participants' experiences were explored in feedback questionnaires and interviews. Recruitment, retention, and attendance rate met the pre-set feasibility benchmark of 80%. The intervention was well received by participants, who emphasised the group's clear structure, positive atmosphere, and helpful contents. Response rates were high and linear mixed models revealed significant medium-to-large time effects on all clinical outcomes. As expected, increase in hypothesised change mechanisms cognitive insight and decrease in cognitive fusion was found. However, the uncontrolled design limits interpreting clinical effects. The study provides evidence that an intervention based on a metacognitive model is feasible and acceptable for acute inpatients with psychosis. Positive results on clinical outcomes and change mechanisms warrant further exploration in a randomized controlled trial.

On the Road to Individualizing Pharmacotherapy for Adolescents and Adults with Schizophrenia - Results from an Expert Consensus Following the Delphi Method

Introduction

Schizophrenia is a severe mental illness that usually begins in late adolescence or early adulthood. Current pharmacological treatments, while acceptably effective for many patients, are rarely clinically tailored or individualized. The lack of sufficient etiopathological knowledge of the disease, together with overall comparable effect sizes for efficacy between available antipsychotics and the absence of clinically actionable biomarkers, has hindered the advance of individualized medicine in the treatment of schizophrenia. Nevertheless, some degree of stratification based on clinical markers could guide treatment choices and help clinicians move toward individualized psychiatry. To this end, a panel of experts met to formally discuss the current approach to individualized treatment in schizophrenia and to define how treatment individualization could help improve clinical outcomes.

Methods

A task force of seven experts iteratively developed, evaluated, and refined questionnaire items, which were then evaluated using the Delphi method. Descriptive statistics were used to summarize and rank expert responses. Expert discussion, informed by the results of a scoping review on personalizing the pharmacologic treatment of adults and adolescents with schizophrenia, ultimately generated recommendations to guide individualized pharmacologic treatment in this population.

Results

There was substantial agreement among the expert group members, resulting in the following recommendations: 1) individualization of treatment requires consideration of the patient's diagnosis, clinical presentation, comorbidities, previous treatment response, drug tolerability, adherence patterns, and social factors; 2) patient preferences should be considered in a shared decision-making approach; 3) identified barriers to personalized care that need to be overcome include the lack of actionable biomarkers and mechanistic similarities between available treatments, but digital tools should be increasingly used to enhance individualized treatment.

Conclusion

Individualized care can help provide effective, tailored treatments based on an individual's clinical characteristics, disease trajectory, family and social environment, and goals and preferences.

Effectiveness of a needs-tailored nurse-led recovery program for community-dwelling people with schizophrenia: a cluster-randomized controlled trial

BACKGROUND

Meeting people's needs is positively correlated with their recovery. However, recovery services rarely include nurse-led programs tailored to the needs of these people. This study aimed to evaluate the effectiveness of a new needs-tailored recovery program by using a cluster-randomized controlled trial design.

METHODS

We conducted a parallel randomized controlled trial in two community psychiatric departments, employing nurse-level clustering for intervention delivery and selecting participants through convenience sampling. The participants were people diagnosed with schizophrenia that were receiving homecare services. The experimental group (n = 82) received needs-tailored recovery program for six months. The control group (n = 82) received traditional homecare. Data were collected at baseline, post-intervention, and the three-month follow-up (the study ran from February to December 2021). The outcomes were recovery, needs, hope, empowerment, psychotic symptoms, and medication adherence. We used repeated measures ANOVA tests to examine the effect of the group × time interaction.

RESULTS

The participants in the experimental group demonstrated statistically significant improvements in recovery, hope, and medication adherence compared to the control group, both immediately post-intervention and at the three-month follow-up. Moreover, they exhibited statistically significant reductions in needs compared to the control group at the three-month follow-up (p < .05). While the interaction effect for psychotic symptoms was not significant, the time effect was significant (p < .05). No significant interaction or time effect was observed for empowerment.

CONCLUSION

The findings increase our understanding of recovery-oriented care that prioritizes therapeutic alliance, integrated needs assessment, individual goals, hope, and empowerment.

TRIAL REGISTRATION

The Clinicaltrials.gov identifier NCT05304780 retrospectively registered on 03/31/2022.

Development of family resource indicators for people with schizophrenic disorder in community by modified Delphi method in Beijing, China

INTRODUCTION

Most people with schizophrenia in China are supported by their family members in community. The patient's family is confronted with severe care burden and pressure, which directly affects the caregiver's own health and social life, and indirectly affects the patient's rehabilitation. Adequate family resources can reduce the burden and pressure on families. But there is an absence of systematic family resource indicators for people with schizophrenic disorder in China.

OBJECTIVES

This study aimed to develop a set of family resource indicators for people with schizophrenic disorder in China.

DESIGN

Preliminary family resource indicators were generated and refined by literature review and an expert consultation meeting. Two rounds of email-based Delphi survey were carried out to identify family resource indicators.

SETTING

Two rounds of email-based Delphi survey were performed from July to September 2021 in Beijing, China.

PARTICIPANTS

There were 15 mental health doctors from community health service centres and four psychiatrists from tertiary hospitals, and two primary care researchers from universities in the first and second rounds Delphi survey.

RESULTS

All the 21 experts participated in both rounds of Delphi survey. A total of 46 indicators achieved consensus for inclusion in the final set of indicators after two rounds of Delphi survey. The final set of indicators was grouped into 10 domains: financial support (three indicators), psychological and spiritual support (eight indicators), medical treatment (three indicators), information and education (three indicators), structural support (two indicators), external family resources included social resources (five indicators), cultural resources (two indicators), economic resources (seven indicators), environmental resources (four indicators) and medical resources (nine indicators).

CONCLUSIONS

A set of 46 family resource indicators for people with schizophrenic disorder in community was identified by an iterative Delphi process in Beijing, China. However, the indicators still need to be validated by testing in further studies.

Australian trial of behavioural activation for people with schizophrenia experiencing negative symptoms: a feasibility randomised controlled trial protocol

INTRODUCTION

Negative symptoms are frequently experienced by people with schizophrenia. People with negative symptoms often have impaired social functioning and reduced quality of life. There is some evidence that cognitive-behavioural therapy results in a modest reduction in negative symptoms. Behavioural activation may be an effective alternative treatment for negative symptoms.The study aims to examine the feasibility and acceptability of implementing a behavioural activation trial delivered in three community mental health services in South Australia to support adult consumers experiencing negative symptoms of schizophrenia.

METHOD AND ANALYSIS

This randomised controlled study will recruit a total of 60 consumers aged 18 years or above with mild-moderate negative symptoms of schizophrenia. The consumers will be randomly allocated to receive behavioural activation plus usual mental healthcare or usual mental healthcare alone. The intervention group will receive twelve 30 min sessions of behavioural activation, which will be delivered twice weekly over 6 weeks. In addition, we aim to recruit nine mental health workers from the three rural mental health services who will complete a 10-week online training programme in behavioural activation. Changes in negative symptoms of schizophrenia and depressive symptoms will be assessed at three time points: (a) at baseline, at 6 weeks and 3 month follow-ups. Changes in health-related quality of life (Short Form F36; secondary outcome) will be assessed at two time points: (a) at baseline and (b) immediately at postintervention after 6 weeks. At the end of the trial, interviews will be conducted with purposively selected mental health workers and consumers. Descriptive statistics and thematic analysis will be used to assess feasibility and acceptability.

ETHICS AND DISSEMINATION

The findings from our feasibility study will inform the design of a fully powered randomised controlled trial to test the effectiveness of behavioural activation as a treatment for negative symptoms in schizophrenia. The study protocol was approved by the Central Adelaide Local Health Network Human Research Ethics Committee. The findings from this study will be disseminated through peer-reviewed scientific journals and conferences.

TRIAL REGISTRATION NUMBER

ACTRN12623000348651p.

Transfer learning and self-distillation for automated detection of schizophrenia using single-channel EEG and scalogram images

Schizophrenia (SZ) has been acknowledged as a highly intricate mental disorder for a long time. In fact, individuals with SZ experience a blurred line between fantasy and reality, leading to a lack of awareness about their condition, which can pose significant challenges during the treatment process. Due to the importance of the issue, timely diagnosis of this illness can not only assist patients and their families in managing the condition but also enable early intervention, which may help prevent its advancement. EEG is a widely utilized technique for investigating mental disorders like SZ due to its non-invasive nature, affordability, and wide accessibility. In this study, our main goal is to develop an optimized system that can achieve automatic diagnosis of SZ with minimal input information. To optimize the system, we adopted a strategy of using single-channel EEG signals and integrated knowledge distillation and transfer learning techniques into the model. This approach was designed to improve the performance and efficiency of our proposed method for SZ diagnosis. Additionally, to leverage the pre-trained models effectively, we converted the EEG signals into images using Continuous Wavelet Transform (CWT). This transformation allowed us to harness the capabilities of pre-trained models in the image domain, enabling automatic SZ detection with enhanced efficiency. To achieve a more robust estimate of the model's performance, we employed fivefold cross-validation. The accuracy achieved from the 5-s records of the EEG signal, along with the combination of self-distillation and VGG16 for the P4 channel, is 97.81. This indicates a high level of accuracy in diagnosing SZ using the proposed method.

Schizophrenia and schizoaffective disorder: Length of stay and associated factors

Background

Patients with schizophrenia and schizoaffective disorder often require longer admissions.

Aim

To explore length of stay (LOS) and associated factors of patients with schizophrenia and schizoaffective disorder, admitted to a public sector specialised psychiatric hospital, over a 4-year period.

Setting

The study was conducted at Tara Hospital in Johannesburg.

Methods

A retrospective record review of 367 adult schizophrenia and schizoaffective disorder patients admitted between 01 January 2015 and 31 December 2018. Average LOS was calculated and the proportion of short-stay (< 30 days), medium-stay (31-90 days) and long-stay (> 90 days) admissions determined. Sociodemographic, clinical and admission outcome data were collected and analysed from a randomly selected subset of patients in each LOS category.

Results

Mean LOS was 128 days (median 87, interquartile range [IQR] 49-164, range 0-755 days). A significantly greater proportion had long-stay admissions (p < 0.001). Male gender (p = 0.018), being unmarried (p = 0.006), treatment resistant (p < 0.001) and on clozapine (p = 0.009) were factors found to have a significant association with long-stay admissions. Rates of unemployment (> 80%), comorbid substance use disorders (> 40%), medical illnesses (> 40%), antipsychotic polypharmacy (> 40%) and readmissions (> 80%) were high. Most (> 80%) were discharged.

Conclusion

Long-stay admissions were frequently required for patients with schizophrenia and schizoaffective disorder admitted to Tara Hospital.

Contribution

This study highlights factors associated with long-stay admissions in patients with schizophrenia and schizoaffective disorder. More research is needed into whether increased access to community-based services, such as residential and daycare facilities, outpatient substance rehabilitation programmes and dual diagnosis clinics, could translate into shorter admissions, less frequent relapses and improved outcomes in this population.

Pharmacokinetics and safety of a new generic lurasidone: a phase I bioequivalence study in healthy Chinese subjects

Latuda® is a novel antipsychotic drug for schizophrenia and bipolar depression. A bioequivalence trial was performed to investigate the bioequivalence of Latuda® and its generic drug lurasidone. Two independent trials were carried out, each involving 28 subjects. In the fasting trial, subjects were randomly assigned to two groups (1:1 ratio), receiving either 40 mg of generic lurasidone or Latuda®. After a 7-day washout period, subjects entered the second period with a crossover administration of 40 mg of generic lurasidone or Latuda®. The postprandial study design was similar to that of the fasting study. In the fasting study, the pharmacokinetic (PK) parameter values of generic lurasidone and Latuda® were as follows: the Cmax was 28.84 ± 19.34 ng/ml and 28.22 ± 21.19 ng/ml, respectively; the AUC0-t was 121.39 ± 58.47 h*ng/ml and 118.35 ± 52.24 h*ng/ml, respectively; and the AUC0-∞ was 129.63 ± 63.26 h*ng/ml and 126.59 ± 57.99 h*ng/ml, respectively. The primary pharmacokinetic parameter, Cmax, was assessed for equivalence using reference-scaled average bioequivalence (RSABE), while other parameters (AUC0-t, AUC0-∞) were evaluated using average bioequivalence (ABE). The results indicate that both Cmax and AUC meet the equivalence criteria. In the postprandial study, the PK values of generic lurasidone and Latuda® were as follows: the Cmax was 74.89 ± 32.06 ng/ml and 83.51 ± 33.52 ng/ml, respectively; the AUC0-t was 274.77 ± 103.05 h*ng/ml and 289.26 ± 95.25 h*ng/ml, respectively; and the AUC0-∞ was 302.44 ± 121.60 h*ng/ml and 316.32 ± 109.04 h*ng/ml, respectively. The primary pharmacokinetic parameters (Cmax, AUC0-t, AUC0-∞) were assessed for equivalence using ABE, and both met the equivalence criteria. In the study, lurasidone and Latuda® both exhibited acceptable safety and tolerability. The results displayed that lurasidone and Latuda® were bioequivalent and safe in healthy Chinese participants. Clinical Trial Registry: This trial is registered at chinadrugtrials.org.cn (no.: CTR20191717, date: 2019.08.29).

Comparing the medication costs of treating patients with schizophrenia who use cannabis with those who do not

Background

Cannabis use is more prevalent among people with schizophrenia than in the general population. This usage detrimentally impacts disease prognosis, contributing to escalated admissions, heightened severity of psychotic symptoms, and reduced medication response. The recent decriminalisation of cannabis in South Africa may lead to an upsurge in usage, consequently intensifying the strain on mental healthcare services.

Aim

This study aimed to compare the medication costs of patients with schizophrenia depending on cannabis use.

Setting

Weskoppies Hospital, Pretoria, South Africa, 2018-2019.

Methods

Data pertaining to medication expenses during the 2018-2019 period were acquired from the hospital pharmacy. Data were collected from 114 patient records to form two equal cohorts: one exposed to cannabis and the other non-exposed, as indicated by urine drug screens or admission of cannabis use. Medications prescribed from admission to time of being ready for discharge were recorded and corresponding costs were calculated.

Results

Patients who were exposed to cannabis had higher medication costs (R 516.47) than patients who were non-exposed (R 328.69) (p = 0.0519), over the whole admission period.

Conclusion

Cannabis exposure escalates the financial burden of treating schizophrenia at Weskoppies Hospital. This might be attributed to failure of cost-effective, first-line medications prompting the prescription of costlier, second-line alternatives or higher prescribed dosages.

Contribution

This study contributes to findings that it is more expensive to treat patients with schizophrenia who have relapsed, if they are using cannabis. This finding has future cost implications when budgeting for pharmacotherapeutic treatment.

Longitudinal inference of multiscale markers in psychosis: from hippocampal centrality to functional outcome

Multiscale neuroscience conceptualizes mental illness as arising from aberrant interactions across and within multiple biopsychosocial scales. We leverage this framework to propose a multiscale disease progression model of psychosis, in which hippocampal-cortical dysconnectivity precedes impairments in episodic memory and social cognition, which lead to more severe negative symptoms and lower functional outcome. As psychosis represents a heterogeneous collection of biological and behavioral alterations that evolve over time, we further predict this disease progression for a subtype of the patient sample, with other patients showing normal-range performance on all variables. We sampled data from two cross-sectional datasets of first- and multi-episode psychosis, resulting in a sample of 163 patients and 119 non-clinical controls. To address our proposed disease progression model and evaluate potential heterogeneity, we applied a machine-learning algorithm, SuStaIn, to the patient data. SuStaIn uniquely integrates clustering and disease progression modeling and identified three patient subtypes. Subtype 0 showed normal-range performance on all variables. In comparison, Subtype 1 showed lower episodic memory, social cognition, functional outcome, and higher negative symptoms, while Subtype 2 showed lower hippocampal-cortical connectivity and episodic memory. Subtype 1 deteriorated from episodic memory to social cognition, negative symptoms, functional outcome to bilateral hippocampal-cortical dysconnectivity, while Subtype 2 deteriorated from bilateral hippocampal-cortical dysconnectivity to episodic memory and social cognition, functional outcome to negative symptoms. This first application of SuStaIn in a multiscale psychiatric model provides distinct disease trajectories of hippocampal-cortical connectivity, which might underlie the heterogeneous behavioral manifestations of psychosis.

Diverse elements comprising studies of peer support complicate evidence synthesis

BACKGROUND

Innovative approaches to care, such as peer support, are needed to address the substantial and frequently unmet needs of people with serious mental illnesses such as schizophrenia. Although peer support services continue to expand in mental healthcare, findings of effectiveness from systematic reviews are mixed. However, the studies evaluated in these reviews consisted of diverse elements which the review methods neglected to consider.

AIMS

This review aims to demonstrate the substantial diversity in intervention components and measured outcomes among studies of peer support and lay the groundwork for more focused reviews of individual intervention components.

METHODS

As part of a realist review of the literature, here we synthesize evidence in a way that examines the substantial diversity in intervention components and measured outcomes comprising studies of peer support.

RESULTS

Seven categories of outcomes were represented, including recovery, symptoms and functioning, and care utilization. Importantly, seven distinct intervention components were represented in 26 studies: "being there," assistance in self-management, linkage to clinical care and community resources, social and emotional support, ongoing support, explicit utilization of shared lived experience or peer support values, and systems advocacy. Reflecting diversity in approaches, no study reported all intervention components, and no component was found among all studies.

IMPLICATIONS

Peer support services constitute a category of intervention approaches far too varied to evaluate as a single entity. Results suggest intervention components deserving more focused research, including assistance in self-management, "being there," and explicit utilization of shared lived experience or peer support values.

PRISMA/PROSPERO

As this article reports results from a realist review of the literature, we did not follow the PRISMA guidance which is suitable for systematic reviews. We did follow the Realist and Meta-narrative Evidence Syntheses: Evolving Standards (RAMESES) guidelines.This review was not registered on PROSPERO as it is not a systematic review.

Structure-Based Design of Novel G-Protein-Coupled Receptor TAAR1 Agonists as Potential Antipsychotic Drug Candidates

The existing available antipsychotics have failed to manage the cognitive impairment of schizophrenia and induced a number of seriously undesirable effects. Trace amine-associated receptor 1 (TAAR1) has emerged as an ideal target for the design of antischizophrenia drugs, with the ability to mediate multiple psychological functions by sensing endogenous amine-containing metabolites without the side effects of catalepsy. In this work, a series of novel TAAR1 agonists were designed based on the structural analysis of the TAAR1 activation pocket. Among them, 6e displayed a potent TAAR1-Gs/Gq dual-pathway activation property, being different from that of the clinical drug candidate SEP-363856 with only TAAR1-Gs pathway activation. In rodent models, 6e significantly alleviated MK-801-induced schizophrenia-like cognitive phenotypes without inducing catalepsy. Furthermore, 6e·HCl exhibited favorable pharmacokinetic (T1/2 = 2.31 h, F = 39%) and safety properties. All these demonstrated that 6e·HCl may be used as a novel drug candidate for schizophrenia treatment.

Exercise or mind-body exercises for psychiatry symptoms and quality of life in schizophrenia spectrum and other psychotic disorders: an overview of systematic reviews with meta-analysis

PURPOSE

This overview of systematic reviews with meta-analysis aimed to summarize the effects of exercise, regular physical activity, and mind-body exercises on negative symptoms, depression symptoms, and quality of life in schizophrenia spectrum and other psychotic disorders.

MATERIAL AND METHODS

The CINAHL, Embase, PubMed, SPORTDiscus, and the Cochrane Library databases were searched up to November 10, 2023. AMSTAR 2 was used and the overlap between reviews was calculated.

RESULTS

Eighteen reviews were included. No reviews meta-analyzed regular physical activity. Aerobic exercise may be more effective than yoga, treatment-as-usual, or multiple controls for reducing negative symptoms. Tai chi may be more effective than multiple controls for decreasing negative symptoms. Aerobic exercise or multimodal exercise programs may be more effective than multiple controls for reducing depression symptoms. Yoga may be more effective than waitlist for decreasing depression symptoms. Aerobic exercise may be more effective than multiple controls for improving quality of life. Yoga may be more effective than treatment-as-usual for improving quality of life. The rest of the meta-analyses found no differences between groups or combined different types of interventions in their meta-analyses.

CONCLUSIONS

Despite these results, important methodological concerns were detected that precluded us from making sound clinical recommendations.

PROTOCOL REGISTRATION

https://doi.org/10.17605/OSF.IO/7V5QZ.

Real-world predictors of relapse in patients with schizophrenia and schizoaffective disorder in a large health system

Schizophrenia is often characterized by recurring relapses, which are associated with a substantial clinical and economic burden. Early identification of individuals at the highest risk for relapse in real-world treatment settings could help improve outcomes and reduce healthcare costs. Prior work has identified a few consistent predictors of relapse in schizophrenia, however, studies to date have been limited to insurance claims data or small patient populations. Thus, this study used a large sample of health systems electronic health record (EHR) data to analyze relationships between patient-level factors and relapse and model a set of factors that can be used to identify the increased prevalence of relapse, a severe and preventable reality of schizophrenia. This retrospective, observational cohort study utilized EHR data extracted from the largest Midwestern U.S. non-profit healthcare system to identify predictors of relapse. The study included patients with a diagnosis of schizophrenia (ICD-10 F20) or schizoaffective disorder (ICD-10 F25) who were treated within the system between October 15, 2016, and December 31, 2021, and received care for at least 12 months. A relapse episode was defined as an emergency room or inpatient encounter with a pre-determined behavioral health-related ICD code. Patients' baseline characteristics, comorbidities and healthcare utilization were described. Modified log-Poisson regression (i.e. log Poisson regression with a robust variance estimation) analyses were utilized to estimate the prevalence of relapse across patient characteristics, comorbidities and healthcare utilization and to ultimately identify an adjusted model predicting relapse. Among the 8119 unique patients included in the study, 2478 (30.52%) experienced relapse and 5641 (69.48%) experienced no relapse. Patients were primarily male (54.72%), White Non-Hispanic or Latino (54.23%), with Medicare insurance (51.40%), and had baseline diagnoses of substance use (19.24%), overweight/obesity/weight gain (13.06%), extrapyramidal symptoms (48.00%), lipid metabolism disorder (30.66%), hypertension (26.85%), and diabetes (19.08%). Many differences in patient characteristics, baseline comorbidities, and utilization were revealed between patients who relapsed and patients who did not relapse. Through model building, the final adjusted model with all significant predictors of relapse included the following variables: insurance, age, race/ethnicity, substance use diagnosis, extrapyramidal symptoms, number of emergency room encounters, behavioral health inpatient encounters, prior relapses episodes, and long-acting injectable prescriptions written. Prevention of relapse is a priority in schizophrenia care. Challenges related to historical health record data have limited the knowledge of real-world predictors of relapse. This study offers a set of variables that could conceivably be used to construct algorithms or models to proactively monitor demographic, comorbidity, medication, and healthcare utilization parameters which place patients at risk for relapse and to modify approaches to care to avoid future relapse.

Estimating the direct effects of the genetic liabilities to bipolar disorder, schizophrenia, and behavioral traits on suicide attempt using a multivariable Mendelian randomization approach

Bipolar disorder (BD) and schizophrenia (SZ) are associated with higher odds of suicide attempt (SA). In this study, we aimed to explore the effect of BD and SZ genetic liabilities on SA, also considering the contribution of behavioral traits, socioeconomic factors, and substance use disorders. Leveraging large-scale genome-wide association data from the Psychiatric Genomics Consortium (PGC) and the UK Biobank (UKB), we conducted a two-sample Mendelian randomization (MR) analysis to evaluate the putative causal effect of BD (41,917 cases, 371,549 controls) and SZ (53,386 cases, 77,258 controls) on SA (26,590 cases, 492,022 controls). Then, we assessed the putative causal effect of BD and SZ on behavioral traits, socioeconomic factors, and substance use disorders. Considering the associations identified, we evaluated the direct causal effect of behavioral traits, socioeconomic factors, and substance use disorders on SA using a multivariable MR approach. The genetic liabilities to BD and SZ were associated with higher odds of SA (BD odds ratio (OR) = 1.24, p = 3.88 × 10-12; SZ OR = 1.09, p = 2.44 × 10-20). However, while the effect of mental distress (OR = 1.17, p = 1.02 × 10-4) and risk-taking (OR = 1.52, p = 0.028) on SA was independent of SZ genetic liability, the BD-SA relationship appeared to account for the effect of these risk factors. Similarly, the association with loneliness on SA was null after accounting for the effect of SZ genetic liability. These findings highlight the complex interplay between genetic risk of psychiatric disorders and behavioral traits in the context of SA, suggesting the need for a comprehensive mental health assessment for high-risk individuals.

Comparative estimation of the effects of antihypertensive medications on schizophrenia occurrence: a multinational observational cohort study

BACKGROUND

The association between antihypertensive medication and schizophrenia has received increasing attention; however, evidence of the impact of antihypertensive medication on subsequent schizophrenia based on large-scale observational studies is limited. We aimed to compare the schizophrenia risk in large claims-based US and Korea cohort of patients with hypertension using angiotensin-converting enzyme (ACE) inhibitors versus those using angiotensin receptor blockers (ARBs) or thiazide diuretics.

METHODS

Adults aged 18 years who were newly diagnosed with hypertension and received ACE inhibitors, ARBs, or thiazide diuretics as first-line antihypertensive medications were included. The study population was sub-grouped based on age (> 45 years). The comparison groups were matched using a large-scale propensity score (PS)-matching algorithm. The primary endpoint was incidence of schizophrenia.

RESULTS

5,907,522; 2,923,423; and 1,971,549 patients used ACE inhibitors, ARBs, and thiazide diuretics, respectively. After PS matching, the risk of schizophrenia was not significantly different among the groups (ACE inhibitor vs. ARB: summary hazard ratio [HR] 1.15 [95% confidence interval, CI, 0.99-1.33]; ACE inhibitor vs. thiazide diuretics: summary HR 0.91 [95% CI, 0.78-1.07]). In the older subgroup, there was no significant difference between ACE inhibitors and thiazide diuretics (summary HR, 0.91 [95% CI, 0.71-1.16]). The risk for schizophrenia was significantly higher in the ACE inhibitor group than in the ARB group (summary HR, 1.23 [95% CI, 1.05-1.43]).

CONCLUSIONS

The risk of schizophrenia was not significantly different between the ACE inhibitor vs. ARB and ACE inhibitor vs. thiazide diuretic groups. Further investigations are needed to determine the risk of schizophrenia associated with antihypertensive drugs, especially in people aged > 45 years.

Effect of immersive virtual reality-based cognitive remediation in patients with mood or psychosis spectrum disorders: study protocol for a randomized, controlled, double-blinded trial

BACKGROUND

Cognitive impairments are prevalent across mood disorders and psychosis spectrum disorders, but there is a lack of real-life-like cognitive training programmes. Fully immersive virtual reality has the potential to ensure motivating and engaging cognitive training directly relevant to patients' daily lives. We will examine the effect of a 4-week, intensive virtual reality-based cognitive remediation programme involving daily life challenges on cognition and daily life functioning in patients with mood disorders or psychosis spectrum disorders and explore the neuronal underpinnings of potential treatment efficacy.

METHODS

The trial has a randomized, controlled, double-blinded, parallel-group design. We will include 66 symptomatically stable outpatients with mood disorders or psychosis spectrum disorders aged 18-55 years with objective and subjective cognitive impairment. Assessments encompassing a virtual reality test of daily life cognitive skills, neuropsychological testing, measures of daily life functioning, symptom ratings, questionnaires on subjective cognitive complaints, and quality of life are carried out at baseline, after the end of 4 weeks of treatment and at a 3-month follow-up after treatment completion. Functional magnetic resonance imaging scans are performed at baseline and at the end of treatment. The primary outcome is a broad cognitive composite score comprising five subtasks on a novel ecologically valid virtual reality test of daily life cognitive functions. Two complete data sets for 54 patients will provide a power of 80% to detect a clinically relevant between-group difference in the primary outcome. Behavioural data will be analysed using linear mixed models in SPSS, while MRI data will be analysed with the FMRIB Expert Analysis Tool (FEAT). Treatment-related changes in neural activity from baseline to end of treatment will be investigated for the dorsal prefrontal cortex and hippocampus as the regions of interest.

DISCUSSION

The results will provide insight into whether virtual reality-based cognitive remediation has beneficial effects on cognition and functioning in symptomatically stable patients with mood disorders or psychosis spectrum disorders, which can aid future treatment development.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06038955. Registered on September 15, 2023.

Healthcare professionals' knowledge, confidence and attitudes in relation to psychosis care: A systematic review

BACKGROUND

Psychosis is a mental disorder that, despite its low prevalence, causes high disease and economic burden. Inadequate knowledge, lack of confidence and stigmatising attitudes of healthcare professionals (HCPs) may lead to suboptimal care.

AIM

To review the literature exploring HCPs' knowledge, confidence and attitudes in relation to psychosis care.

METHOD

A systematic search was undertaken across three databases (MEDLINE, Embase, PsycINFO) using a search strategy encompassing the concepts: 'healthcare professionals', 'knowledge, attitude, and confidence in care' and 'psychotic illnesses and symptoms' to identify relevant records published from 1st January 2002 to 18th March 2022. Results were screened against predetermined inclusion and exclusion criteria by title and abstract, followed by full text. Data were extracted into tables and synthesised narratively.

RESULTS

Initially, 7,397 studies were identified. Following two-stage screening, 24 studies were eligible for inclusion. Of these studies, 16 explored attitudes, four explored knowledge and attitudes, one explored knowledge, one explored confidence, one explored attitudes and confidence in care and one explored all three constructs. Most HCPs in the included studies demonstrated stigmatising attitudes towards people with psychosis. Furthermore, certain HCPs, including nurses and general practitioners, demonstrated low levels of knowledge, while psychiatrists, occupational therapists, psychologists and nurses had low levels of confidence in caring for people with psychosis. Conversely, positive attitudes were also observed in some HCPs resulting from having acquaintances with lived experience of psychosis. The need for additional education and training to improve HCPs' knowledge and confidence in relation to caring for people living with psychosis was identified.

CONCLUSIONS

Most attitudes identified were negative and stemmed from stigma, while some were positive due to HCPs' compassion and familiarity with psychosis. The level of knowledge and confidence identified were mostly suboptimal, and so further research is required to develop and evaluate tailored interventions to address this gap.

Overlap in synaptic neurological condition susceptibility pathways and the neural pannexin 1 interactome revealed by bioinformatics analyses

Many neurological conditions exhibit synaptic impairments, suggesting mechanistic convergence. Additionally, the pannexin 1 (PANX1) channel and signaling scaffold is linked to several of these neurological conditions and is an emerging regulator of synaptic development and plasticity; however, its synaptic pathogenic contributions are relatively unexplored. To this end, we explored connections between synaptic neurodevelopmental disorder and neurodegenerative disease susceptibility genes discovered by genome-wide association studies (GWASs), and the neural PANX1 interactome (483 proteins) identified from mouse Neuro2a (N2a) cells. To identify shared susceptibility genes, we compared synaptic suggestive GWAS candidate genes amongst autism spectrum disorders, schizophrenia, Parkinson's disease, and Alzheimer's disease. To further probe PANX1 signaling pathways at the synapse, we used bioinformatics tools to identify PANX1 interactome signaling pathways and protein-protein interaction clusters. To shed light on synaptic disease mechanisms potentially linking PANX1 and these four neurological conditions, we performed additional cross-analyses between gene ontologies enriched for the PANX1 synaptic and disease-susceptibility gene sets. Finally, to explore the regional specificity of synaptic PANX1-neurological condition connections, we identified brain region-specific elevations of synaptic PANX1 interactome and GWAS candidate gene set transcripts. Our results confirm considerable overlap in risk genes for autism spectrum disorders and schizophrenia and identify potential commonalities in genetic susceptibility for neurodevelopmental disorders and neurodegenerative diseases. Our findings also pinpointed novel putative PANX1 links to synaptic disease-associated pathways, such as regulation of vesicular trafficking and proteostasis, warranting further validation.

Assisting schizophrenia diagnosis using clinical electroencephalography and interpretable graph neural networks: a real-world and cross-site study

Schizophrenia (SCZ) is a chronic and serious mental disorder with a high mortality rate. At present, there is a lack of objective, cost-effective and widely disseminated diagnosis tools to address this mental health crisis globally. Clinical electroencephalogram (EEG) is a noninvasive technique to measure brain activity with high temporal resolution, and accumulating evidence demonstrates that clinical EEG is capable of capturing abnormal SCZ neuropathology. Although EEG-based automated diagnostic tools have obtained impressive performance on individual datasets, the transportability of potential EEG biomarkers in cross-site real-world application is still an open question. To address the challenges of small sample sizes and population heterogeneity, we develop an advanced interpretable deep learning model using multimodal clinical EEG features and demographic information as inputs to graph neural networks, and further propose different transfer learning strategies to adapt to different clinical scenarios. Taking the disease discrimination of health control (HC) and SCZ with 1030 participants as a use case, our model is trained on a small clinical dataset (N = 188, Chinese) and enhanced using a large-scale public dataset (N = 508, American) of adult participants. Cross-site validation from an independent dataset of adult participants (N = 157, Chinese) produced stable performance, with AUCs of 0.793-0.852 and accuracies of 0.786-0.858 for different SCZ prevalence, respectively. In addition, cross-site validation from another dataset of adolescent boys (N = 84, Russian) yielded an AUC of 0.702 and an accuracy of 0.690. Moreover, feature visualization further revealed that the ranking of feature importance varied significantly among different datasets, and that EEG theta and alpha band power appeared to be the most significant and translational biomarkers of SCZ pathology. Overall, our promising results demonstrate the feasibility of SCZ discrimination using EEG biomarkers in multiple clinical settings.

Conceptualizing a less paranoid schizophrenia

Schizophrenia stands as one of the most studied and storied disorders in the history of clinical psychology; however, it remains a nexus of conflicting and competing conceptualizations. Patients endure great stigma, poor treatment outcomes, and condemnatory prognosis. Current conceptualizations suffer from unstable categorical borders, heterogeneity in presentation, outcome and etiology, and holes in etiological models. Taken in aggregate, research and clinical experience indicate that the class of psychopathologies oriented toward schizophrenia are best understood as spectra of phenomenological, cognitive, and behavioral modalities. These apparently taxonomic expressions are rooted in normal human personality traits as described in both psychodynamic and Five Factor personality models, and more accurately represent explicable distress reactions to biopsychosocial stress and trauma. Current categorical approaches are internally hampered by axiomatic bias and systemic inertia rooted in the foundational history of psychological inquiry; however, when such axioms are schematically decentralized, convergent cross-disciplinary evidence outlines a more robust explanatory construct. By reconceptualizing these disorders under a dimensional and cybernetic model, the aforementioned issues of instability and inaccuracy may be resolved, while simultaneously opening avenues for both early detection and intervention, as well as for more targeted and effective treatment approaches.

In vitro cytogenotoxic evaluation of aripiprazole on human peripheral lymphocytes and computational molecular docking analysis

Two different drug groups, typical (classic) and atypical (new), are used in the treatment of schizophrenia. Aripiprazole, an atypical antipsychotic chemical, is the active ingredient of the drug Abilify. This study was conducted to determine the possible genotoxic effect of aripiprazole. For this purpose, four different doses of aripiprazole (5; 10; 20, and 40 µg/mL) were examined with Chromosome Abnormality (CA), Sister Chromatid Exchange (SCE), Micronucleus (MN) tests. Based on these tests, Proliferation Index (PI), Percent Abnormal Cells (AC), Mitotic Index (MI), Micronuclear Binuclear Cell (MNBN), and Nuclear Division Index (NDI) levels were determined in human peripheral lymphocytes treated for 24 and 48 hours. Also, to determine possible binding sites of Aripiprazole on B-DNA molecular docking analysis was performed using AutoDock 4.0 (B-DNA dodecamer, PDB code: 1BNA). Aripiprazole binds to B-DNA with a very significant free binding energy (-11.88 Kcal/mol). According to our study, aripiprazole did not significantly change SCE, CA, AC percentage, MN frequencies when compared with control. According to these results, aripiprazole does not have a genotoxic effect. At the same time, no significant change was observed in the PI, MI, and NDI frequencies when compared with the control. In line with these results, it was observed that the use of aripiprazole in the treatment of schizophrenia did not pose any acute genotoxic and cytotoxic risk.

Expanding Early Psychosis Care across a Large and Diverse State: Implementation Lessons Learned from Administrative Data and Clinical Team Leads in Texas

The U.S. is facing an unprecedented youth mental health crisis. Translating the findings from mental health intervention trials into large scale, accessible community-based services poses substantial challenges. Examination of state actions as a result of research-informed federal policy to improve youth access to quality mental healthcare is necessary. This mixed-methods study examines the implementation of evidence-informed multidisciplinary coordinated specialty care (CSC) for first-episode psychosis (FEP) services across Texas. The study explores CSC service model components, site location and participant characteristics, and implementation barriers. This cross-sectional study analyzes State of Texas public mental health administrative data from 2015 to 2020, including CSC site (n = 23) characteristics and CSC participant (n = 1682) demographics. Texas CSC site contracts were compared to OnTrackNY, a leading CSC model in the U.S. for CSC service element comparison. In-depth interviews with CSC Team Leads (n = 22) were analyzed to further understand CSC service elements and implementation barriers using qualitative content analysis. CSC was implemented across three waves in 2015, 2017, and 2019-serving 1682 participants and families. CSC sites were located in adult mental health programs; approximately one third of CSC participants were under 18 years. CSC implementation challenges reported by Team Leads included: staff role clarification, collaboration and turnover, community outreach and referrals, child and adult service billing issues, and adolescent and family engagement. Study findings have implications for large state-wide evidence-based practice implementation in transition-to-adulthood community mental health.

Ulotaront: review of preliminary evidence for the efficacy and safety of a TAAR1 agonist in schizophrenia

Ulotaront is a trace amine-associated receptor 1 (TAAR1) agonist in Phase 3 clinical development for the treatment of schizophrenia. Ulotaront was discovered through a unique, target-agnostic approach optimized to identify drug candidates lacking D2 and 5-HT2A receptor antagonism, while demonstrating an antipsychotic-like phenotypic profile in vivo. The mechanism of action (MOA) of ulotaront is thought to be mediated by agonism at TAAR1 and serotonin 5-HT1A receptors. Ulotaront has completed two Phase 2 trials (4-week acute study and 26-week open-label extension) which led to Breakthrough Therapy Designation from the US Food and Drug Administration for the treatment of schizophrenia. In the double-blind, placebo-controlled, acute study, ulotaront was associated with significant (p < 0.001) improvement in Positive and Negative Syndrome Scale (PANSS) total score (effect size [ES]: 0.45), with improvements vs. placebo also observed across secondary endpoints. Post-hoc analyses of the acute trial revealed additional evidence to support the effect of ulotaront on negative symptoms. In the 4-week study, ulotaront was well-tolerated, with an incidence of adverse events (AEs) numerically lower compared to placebo (45.8% vs. 50.4%; with a number needed to harm [NNH] for individual ulotaront AEs all > 40). The open-label extension demonstrated further improvement across schizophrenia symptoms and confirmed the tolerability of ulotaront, with a 6-month completion rate of 67%. Based on current data, ulotaront shows potential to be a first-in-class TAAR1 agonist for the treatment of schizophrenia with a safety and efficacy profile distinct from current antipsychotics.

Estimating the direct effects of the genetic liabilities to bipolar disorder, schizophrenia, and behavioral traits on suicide attempt using a multivariable Mendelian randomization approach

Bipolar disorder (BD) and schizophrenia (SZ) are associated with higher odds of suicide attempt (SA). In this study, we aimed to explore the effect of BD and SZ genetic liabilities on SA, also considering the contribution of behavioral traits, socioeconomic factors, and substance use disorders. Leveraging large-scale genome-wide association data from the Psychiatric Genomics Consortium (PGC) and the UK Biobank (UKB), we conducted a two-sample Mendelian randomization (MR) analysis to evaluate the putative causal effect of BD (41,917 cases, 371,549 controls) and SZ (53,386 cases, 77,258 controls) on SA (26,590 cases, 492,022 controls). Then, we assessed the putative causal effect of BD and SZ on behavioral traits, socioeconomic factors, and substance use disorders. Considering the associations identified, we evaluated the direct causal effect of behavioral traits, socioeconomic factors, and substance use disorders on SA using a multivariable MR approach. The genetic liabilities to BD and SZ were associated with higher odds of SA (BD odds ratio (OR)=1.24, p=3.88×10-12; SZ OR=1.09, p=2.44×10-20). However, while the effect of mental distress (OR=1.17, p=1.02×10-4) and risk-taking (OR=1.52, p=0.028) on SA was independent of SZ genetic liability, the BD-SA relationship appeared to account for the effect of these risk factors. Similarly, the association with loneliness on SA was null after accounting for the effect of SZ genetic liability. These findings highlight the complex interplay between genetic risk of psychiatric disorders and behavioral traits in the context of SA, suggesting the need for a comprehensive mental health assessment for high-risk individuals.

Efficacy of immersive extended reality (XR) interventions on different symptom domains of schizophrenia spectrum disorders. A systematic review

Introduction

Extended reality (XR) is an umbrella term for virtual reality (VR) and augmented reality (AR), both novel vectors for therapeutic intervention modalities. In VR, head-mounted devices (HMD) allow interaction with three-dimensional virtual environments and simulated avatars, while AR overlaps virtual, simulated objects to observe physical reality. Treatment through immersive VR has been studied in psychiatry, including patients suffering from schizophrenia spectrum disorders, while there has not been much attention to AR technologies in psychiatry. Our systematic review aimed to examine the currently available literature regarding the treatment efficacy of immersive VR or AR technologies on different symptom domains of schizophrenia spectrum disorders, screen for potential adverse effects, and gather data on the technological and human resource requirements of such interventions to help guide future research.

Methods

We conducted a systematic literature review with database searches carried out between 9/2021 and 8/2022 through PubMed, Scopus, EBSCOhost Academic Search Premier, and Web of Science.

Results

We identified 2,157 records, 214 were assessed further for eligibility and 12 met inclusion criteria. All included articles studied immersive VR and none used AR technology. Included studies were heterogenous in nature, including AVATAR therapy (3) and CBT-based (5) VR interventions, as well as cognitive (2), social (1), and relaxation (1) training through VR. The comparison groups were either passive controls (waitlist and treatment as usual), therapeutic interventions (CBT and Integrated psychological treatment), passive VR environments, or traditional, comparable, non-virtual treatment modalities (social roleplay and progressive muscle relaxation training). Pooled together, the included studies on VR show positive treatment effects in all major symptom domains of schizophrenia spectrum disorders with hardly any adverse effects related to the intervention modalities.

Conclusions

In this review, we have showcased how different symptom domains can be targeted through VR interventions, highlighting VR as a potential new vector for a diverse range of psychosocial therapeutic modalities that allow for completely new possibilities in the treatment of schizophrenia spectrum disorders. VR technology still requires more research and validation. Our review also shows that there are currently no studies examining AR technology in the treatment of schizophrenia spectrum disorders, indicating a distinctive research gap.

Excitatory and inhibitory imbalances in the trisynaptic pathway in the hippocampus in schizophrenia: a postmortem ultrastructural study

BACKGROUND

A preponderance of evidence suggests that the hippocampus is a key region of dysfunction in schizophrenia. Neuroimaging and other studies indicate a relationship between hippocampal dysfunction and the degree of psychosis. Clinical data indicate hyperactivity in the hippocampus that precedes the onset of psychosis, and is correlated with symptom severity. In this study, we sought to identify circuitry at the electron microscopic level that could contribute to region-specific imbalances in excitation and inhibition in the hippocampus in schizophrenia. We used postmortem tissue from the anterior hippocampus from patients with schizophrenia and matched controls. Using stereological techniques, we counted and measured synapses, postsynaptic densities (PSDs), and evaluated size, number and optical density of mitochondria and parvalbumin-containing interneurons in key nodes of the trisynaptic pathway. Compared to controls, the schizophrenia group had decreased numbers of inhibitory synapses in CA3 and increased numbers of excitatory synapses in CA1; together, this indicates deficits in inhibition and an increase in excitation. The thickness of the PSD was larger in excitatory synapses in CA1, suggesting greater synaptic strength. In the schizophrenia group, there were fewer mitochondria in the dentate gyrus and a decrease in the optical density, a measure of functional integrity, in CA1. The number and optical density of parvalbumin interneurons were lower in CA3. The results suggest region-specific increases in excitatory circuitry, decreases in inhibitory neurotransmission and fewer or damaged mitochondria. These results are consistent with the hyperactivity observed in the hippocampus in schizophrenia in previous studies.

Prediction of treatment response to antipsychotic drugs for precision medicine approach to schizophrenia: randomized trials and multiomics analysis

BACKGROUND

Choosing the appropriate antipsychotic drug (APD) treatment for patients with schizophrenia (SCZ) can be challenging, as the treatment response to APD is highly variable and difficult to predict due to the lack of effective biomarkers. Previous studies have indicated the association between treatment response and genetic and epigenetic factors, but no effective biomarkers have been identified. Hence, further research is imperative to enhance precision medicine in SCZ treatment.

METHODS

Participants with SCZ were recruited from two randomized trials. The discovery cohort was recruited from the CAPOC trial (n = 2307) involved 6 weeks of treatment and equally randomized the participants to the Olanzapine, Risperidone, Quetiapine, Aripiprazole, Ziprasidone, and Haloperidol/Perphenazine (subsequently equally assigned to one or the other) groups. The external validation cohort was recruited from the CAPEC trial (n = 1379), which involved 8 weeks of treatment and equally randomized the participants to the Olanzapine, Risperidone, and Aripiprazole groups. Additionally, healthy controls (n = 275) from the local community were utilized as a genetic/epigenetic reference. The genetic and epigenetic (DNA methylation) risks of SCZ were assessed using the polygenic risk score (PRS) and polymethylation score, respectively. The study also examined the genetic-epigenetic interactions with treatment response through differential methylation analysis, methylation quantitative trait loci, colocalization, and promoter-anchored chromatin interaction. Machine learning was used to develop a prediction model for treatment response, which was evaluated for accuracy and clinical benefit using the area under curve (AUC) for classification, R² for regression, and decision curve analysis.

RESULTS

Six risk genes for SCZ (LINC01795, DDHD2, SBNO1, KCNG2, SEMA7A, and RUFY1) involved in cortical morphology were identified as having a genetic-epigenetic interaction associated with treatment response. The developed and externally validated prediction model, which incorporated clinical information, PRS, genetic risk score (GRS), and proxy methylation level (proxyDNAm), demonstrated positive benefits for a wide range of patients receiving different APDs, regardless of sex [discovery cohort: AUC = 0.874 (95% CI 0.867-0.881), R² = 0.478; external validation cohort: AUC = 0.851 (95% CI 0.841-0.861), R² = 0.507].

CONCLUSIONS

This study presents a promising precision medicine approach to evaluate treatment response, which has the potential to aid clinicians in making informed decisions about APD treatment for patients with SCZ. Trial registration Chinese Clinical Trial Registry ( https://www.chictr.org.cn/ ), 18. Aug 2009 retrospectively registered: CAPOC-ChiCTR-RNC-09000521 ( https://www.chictr.org.cn/showproj.aspx?proj=9014 ), CAPEC-ChiCTR-RNC-09000522 ( https://www.chictr.org.cn/showproj.aspx?proj=9013 ).

Association Between Clozapine Plasma Concentrations and Treatment Response: A Systematic Review, Meta-analysis and Individual Participant Data Meta-analysis

BACKGROUND AND OBJECTIVES

Although therapeutic drug monitoring of clozapine is recommended, its optimisation is often adjusted only on the basis of dosage. The aim of this study was to assess the link between clozapine plasma concentrations and clinical response by a meta-analysis of published studies and by an individual participant data meta-analysis.

METHODS

We conducted a computerised search of bibliographic databases (EMBASE, PubMed, Clinical Trials, and Web of Science) to identify studies that assessed the relationship between clozapine serum or plasma concentrations and clinical efficacy. Using pooled data, we investigated the association between improvement of clinical outcome and clozapine or norclozapine plasma concentrations, the sum of clozapine and norclozapine plasma concentrations, and the coefficient of variation of clozapine plasma concentrations. Using available individual data, we assessed the relationship between clozapine plasma concentrations and clinical response (changes in the Brief Psychiatric Rating Scale score) and identified a threshold level for a favourable clinical response.

RESULTS

Fifteen studies satisfied inclusion criteria. Our meta-analysis showed that responders had clozapine plasma concentrations that were, on average, 117 ng/mL higher than non-responders. The patients with plasma clozapine concentrations above the thresholds identified in each study had a higher likelihood of responding (odds ratio = 2.94, p < 0.001). Norclozapine plasma concentrations were not associated with a clinical response. The meta-analysis of individual data supported this result and confirmed the link between clozapine concentrations and a change in the Brief Psychiatric Rating Scale score and/or the probability of clinical response. Finally, with the analysis of the coefficient of variation of clozapine plasma concentrations, we found that a greater inter-individual fluctuation in plasma concentrations was associated with a loss of clinical response.

CONCLUSIONS

Our work confirmed that, in contrast to clozapine doses, clozapine plasma concentrations were related to a favourable clinical response, with a mean difference between responders and non-responders of 117 ng/mL. A threshold for a treatment response of 407 ng/mL was determined, with a high discriminatory capacity, and a sensitivity and specificity of 71% and 89.1%, respectively.

Decreased plasma neuropeptides in first-episode schizophrenia, bipolar disorder, major depressive disorder: associations with clinical symptoms and cognitive function

Background

There is an urgent need to identify differentiating and disease-monitoring biomarkers of schizophrenia, bipolar disorders (BD), and major depressive disorders (MDD) to improve treatment and management.

Methods

We recruited 54 first-episode schizophrenia (FES) patients, 52 BD patients, 35 MDD patients, and 54 healthy controls from inpatient and outpatient clinics. α-Melanocyte Stimulating Hormone (α-MSH), β-endorphin, neurotensin, orexin-A, oxytocin, and substance P were investigated using quantitative multiplex assay method. Psychotic symptoms were measured using the Brief Psychiatric Rating Scale (BPRS) and Positive and Negative Syndrome Scale (PANSS), manic symptoms using the Young Mania Rating Scale (YMRS), and depressive symptoms using 17 item-Hamilton Depression Rating Scale (HAMD). We additionally measured cognitive function by using a battery of tests given to all participants.

Results

α-MSH, neurotensin, orexin-A, oxytocin, and substance P were decreased in the three patient groups compared with controls. Neurotensin outperformed all biomarkers in differentiating patient groups from controls. There were no significant differences for 6 neuropeptides in their ability to differentiate between the three patient groups. Higher neurotensin was associated with better executive function across the entire sample. Lower oxytocin and higher substance p were associated with more psychotic symptoms in FES and BD groups. β-endorphin was associated with early morning wakening symptom in all three patient groups.

Conclusion

Our research shows decreased circulating neuropeptides have the potential to differentiate severe mental illnesses from controls. These neuropeptides are promising treatment targets for improving clinical symptoms and cognitive function in FES, BD, and MDD.

Efficacy, safety, and tolerability of ulotaront (SEP-363856, a trace amine-associated receptor 1 agonist) for the treatment of schizophrenia and other mental disorders with similar pathophysiology: a systematic review of preclinical and clinical trials

INTRODUCTION

Schizophrenia is a mental illness that can disrupt emotions, perceptions, cognition, and reduce quality of life. The classical approach to treat schizophrenia uses typical and atypical antipsychotics; however, limitations include low efficacy in mitigating negative symptoms and cognitive dysfunctions, and a range of adverse effects. Evidence has accumulated on trace amine-associated receptor 1 (TAAR1) as a novel therapeutic target for treating schizophrenia. This systematic review investigates the available evidence on a TAAR1 agonist, ulotaront, as a treatment for schizophrenia.

METHODS

A systematic search was conducted on PubMed/MEDLINE, and Ovid databases for English-published articles from inception to December 18, 2022. Literature focusing on the association between ulotaront and schizophrenia were evaluated based on an inclusion/exclusion criterion. Selected studies were assessed for risk of bias, using Cochrane Collaboration tool, and summarized in a table to generate discussion topics.

RESULTS

Three clinical, two comparative, and five preclinical studies examining ulotaront's pharmacology, tolerability and safety, and/or efficacy were identified. Results indicate that ulotaront has a differing adverse effects profile from other antipsychotics, may mitigate metabolic-related adverse effects commonly associated with antipsychotics, and may be effective for treating positive and negative symptoms.

CONCLUSIONS

Findings from available literature present ulotaront as a potential and promising alternative treatment method for schizophrenia. Despite this, our results were limited due to lack of clinical trials on ulotaront's long-term efficacy and mechanisms of action. Future research should focus on these limitations to elucidate ulotaront's efficacy and safety for the treatment of schizophrenia and other mental disorders with similar pathophysiology.

Mediating role of coping styles on the relationship between personality types and mental disorders in cardiovascular patients: a cross-sectional study in Iran

BACKGROUND

Many mental problems lead to the occurrence of physical diseases, causing worse consequences of diseases. Despite many studies in the field of personality types and types of mental disorders, this relationship and the mediating role of coping styles in cardiovascular patients are still not well known. Therefore, the present study was conducted to investigate the mediating role of coping styles in the relationship between personality types and mental disorders in cardiovascular patients.

METHOD

The present study is a cross-sectional study that was conducted on 114 cardiovascular patients at the heart center in Bushehr, Iran. The sampling method is simple random sampling. Demographic information form, MCMI-III questionnaire, NEO-FFI questionnaire, and Lazarus and Folkman coping styles questionnaire were used to collect data. Data were analyzed using SPSS 22 and Amos 24 software. Descriptive statistics methods (mean, variance and percentage), Pearson correlation, and structural equation model (SEM) were applied to analyze the data.

RESULTS

The findings showed that the two variables of personality types and problem-oriented explain 15.2% of the variable of mental disorders, of which 10.7% is related to the variable of personality types and 4.5% is related to the intermediate variable of problem-oriented. Among the personality types, the neurotic personality type has the biggest role (0.632) and has a direct and significant effect on mental disorders. Also, the personality types of extroversion (-0.460), agreeableness (-0.312), and responsibility (-0.986) exert inverse and significant effects on mental disorders.

CONCLUSION

The results of the present study showed the frequency of personality disorders and other mental disorders among heart patients. Problem-oriented coping style plays a mediating role between personality types and mental disorders.

Reprioritising global mental health: psychoses in sub-Saharan Africa

Arthur Kleinman's 2009 Lancet commentary described global mental health as a "moral failure of humanity", asserting that priorities should be based not on the epidemiological and utilitarian economic arguments that tend to favour common mental health conditions like mild to moderate depression and anxiety, but rather on the human rights of those in the most vulnerable situations and the suffering that they experience. Yet more than a decade later, people with severe mental health conditions like psychoses are still being left behind. Here, we add to Kleinman's appeal a critical review of the literature on psychoses in sub-Saharan Africa, highlighting contradictions between local evidence and global narratives surrounding the burden of disease, the outcomes of schizophrenia, and the economic costs of mental health conditions. We identify numerous instances where the lack of regionally representative data and other methodological shortcomings undermine the conclusions of international research carried out to inform decision-making. Our findings point to the need not only for more research on psychoses in sub-Saharan Africa, but also for more representation and leadership in the conduct of research and in international priority-setting more broadly-especially by people with lived experience from diverse backgrounds. This paper aims to encourage debate about how this chronically under-resourced field, as part of wider conversations in global mental health, can be reprioritised.

Fusion of pattern-based and statistical features for Schizophrenia detection from EEG signals

Schizophrenia (SZ) is a chronic disorder affecting the functioning of the brain. It can lead to irrational behaviour amongst the patients suffering from this disease. A low-cost diagnostic needs to be developed for SZ so that timely treatment can be provided to the patients. In this work, we propose an accurate and easy-to-implement system to detect SZ using electroencephalogram (EEG) signals. The signal is divided into sub-band components by a Fourier-based technique that can be implemented in real-time using fast Fourier transform. Thereafter, statistical features are computed from these components. Further, look ahead pattern (LAP) is developed as a feature to capture local variations in the EEG signal. The fusion of these two distinct schemes enables a thorough examination of EEG signals. Kruskal-Wallis test is utilized for the selection of significant features. Various machine learning classifiers are employed and the proposed framework achieves 98.62% and 99.24% accuracy in identifying SZ cases, considering two distinct datasets, using boosted trees classifier. This method provides a promising candidate for widespread deployment in efficient real-time systems for SZ detection.

Mental health recovery for people with schizophrenia in Southeast Asia: A systematic review

WHAT IS KNOWN ON THE SUBJECT?: Mental health recovery has become a more prevalent approach to empowering people with schizophrenia (PWS), especially in western countries. However, despite the benefits, there is a lack of evidence regarding its practice in developing countries such as Southeast Asian Countries. The optimal treatment for PWS has not yet been identified, since most mental health care is provided in hospital-based settings in Southeast Asia. Mental health treatment in Southeast Asia is highly influenced by cultural norms, values, and practices. WHAT THE PAPER ADDS TO EXISTING KNOWLEDGE?: The findings highlight the importance of integrating cultural aspects into the treatment of people with schizophrenia. The sample of unique elements in Southeast Asian mental health recovery include using a close neighbour/cadre as social support and using religious activity to increase hope. Lack of government support, high level of employment, and stigma are the biggest barriers in the PWS recovery process. WHAT IS THE IMPLICATION FOR PRACTICE?: There is a research gap regarding the awareness and implementation of mental health recovery in psychiatric programs across the Southeast Asian region which likely impacts the effectiveness of the treatment. The review shows that little research has explored the concept of personal recovery in Southeast Asian Countries.

ABSTRACT

INTRODUCTION: Recovery has become an important approach used by mental health services around the world. Many mental health systems have taken steps to move towards more recovery-oriented practices and service delivery. Therefore, establishing recovery-oriented services in developing countries like those in the Southeast Asian region requires a detailed understanding of the cultural norms, values, and current mental health practices.

AIMS

To investigate the mental health practices that promote recovery, its barrier in Southeast Asia, and to determine if they align with the CHIME recovery model.

METHOD

Electronic databases MEDLINE, EMBASE, CINAHL, PsycINFO and SCOPUS, were searched [PROSPERO] (CRD42021227962). Peer-reviewed English language articles from 2004 to January 2021 were included. Methodological quality was assessed using the CASP checklist, and thematic synthesis of included studies was conducted.

RESULTS

Thirty-one studies met inclusion criteria. Several themes illustrated mental health recovery services and the current obstacles identified in South-east Asian studies. Connection includes peer support and support groups, relationship status, and limited opportunities to become involved in the community. Hope is found in cultural concepts of hope, stimulating recovery through mental health programs, whilst lack of knowledge and education are the main barriers. Ethnicity is linked to a high level of stigma, but ethnicity also builds identity. Meaning and spirituality manifest in religious activities as the catalyst for recovery. Finally, the opposite of Empowerment is seen in the tendency of people with schizophrenia to remain in a passive position. Further barriers to empowerment are unemployment and a lack of social support.

DISCUSSION

In Southeast Asia, the elements of culture, religiosity, and communality are essential to mental health recovery. The obstacles to recovery are relate to human rights, social support, family involvement, and continuity of care.

IMPLICATIONS FOR PRACTICE

This review explores the concept of mental health recovery for people who are experiencing psychosis and living in Southeast Asian countries. The evidence may contribute to the further development of mental health programs in this region.

A 10-Year Observational Study of the Use, Acceptability and Effectiveness of Long-Acting Paliperidone Palmitate: Implications for Clinical Decision Making

BACKGROUND

Long-acting injectable antipsychotics (LAIs) have been shown to improve adherence and prevent relapse in the treatment of schizophrenia and psychotic disorders, though longitudinal data on treatment outcomes are limited.

OBJECTIVES

To establish the long-term acceptability and effectiveness of paliperidone palmitate once monthly (PP1M).

METHODS

This independent 10-year mirror image study was carried out in a large urban mental health provider. The study evaluated the retention and hospitalization rates 5 years following initiation of PP1M in a naturalistic patient cohort of all adult patients who were newly initiated on PP1M between 2011 and 2015. Electronic records were used to compare the frequency and length of hospital admissions in the 5 years before and after introduction of PP1M. Switching and discontinuation rates and reasons were also recorded with a separate analysis of patients who continued and discontinued PP1M during the study period.

RESULTS

A total of 167 patients were included in the study (70% with schizophrenia, 30% with other diagnoses). Discontinuation rates were 24%, 15%, 17%, 5% and 8% in years 1-5, respectively; poor tolerability was the most common cause for stopping PP1M. Demographic and clinical factors such as age, sex, diagnosis and care setting did not discriminate between continuers and discontinuers. The group that completed 5 years on PP1M (46%) showed an overall reduction of 72% in the mean number and 68% in the mean length of admissions compared to the 5-year period before initiation, with more than half of the patients requiring no admission at all during this period of time (median = 0). On the contrary, discontinuers demonstrated worse outcomes in overall bed occupancy than continuers. Findings were overall similar across the total cohort and schizophrenia-only group.

CONCLUSIONS

Our study has one of the longest durations of follow up of a naturalistic cohort treated with LAIs confirming sustained improvements for patients who continued treatment for up to 5 years with implicit implications for cost effectiveness. Study findings may facilitate shared decision making in this area, overcoming some of the common barriers for use.

Schizophrenia and cell senescence candidate genes screening, machine learning, diagnostic models, and drug prediction

Background

Schizophrenia (SC) is one of the most common psychiatric diseases. Its potential pathogenic genes and effective treatment methods are still unclear. Cell senescence has been confirmed in mental diseases. A link exists between cellular senescence and immunity, and immune-related problems affect suicide rates in individuals suffering from schizophrenia. Therefore, the aims of this study were to identify candidate genes based on cell senescence that can affect the diagnosis and treatment of schizophrenia.

Methods

Two data sets of schizophrenia were provided by the Gene Expression Omnibus (GEO) database, one was taken as training and the other as a validation group. The genes related to cell senescence were obtained from the CellAge database. DEGs were identified using the Limma package and weighted gene co-expression network analysis (WGCNA). The function enrichment analysis was conducted, followed by machine learning-based identification for least absolute shrinking and selection operators (LASSO) regression. Random Forest were used to identify candidate immune-related central genes and establish artificial neural networks for verification of the candidate genes. The receiver operating characteristic curve (ROC curve) was used for the diagnosis of schizophrenia. Immune cell infiltrates were constructed to study immune cell dysregulation in schizophrenia, and relevant drugs with candidate genes were collected from the DrugBank database.

Results

Thirteen co-expression modules were screened for schizophrenia, of which 124 were the most relevant genes.There were 23 intersected genes of schizophrenia (including DEGs and the cellular senescence-related genes), and through machine learning six candidate genes were finally screened out. The diagnostic value was evaluated using the ROC curve data. Based on these results it was confirmed that these candidate genes have high diagnostic value.Two drugs related to candidate genes, Fostamatinib and Ritodine, were collected from the DrugBanks database.

Conclusion

Six potential candidate genes (SFN, KDM5B, MYLK, IRF3, IRF7, and ID1) had been identified, all of which had diagnostic significance. Fostamatinib might be a drug choice for patients with schizophrenia to develop immune thrombocytopenic purpura (ITP) after treatment, providing effective evidence for the pathogenesis and drug treatment of schizophrenia.

Cross-Platform Detection of Psychiatric Hospitalization via Social Media Data: Comparison Study

BACKGROUND

Previous research has shown the feasibility of using machine learning models trained on social media data from a single platform (eg, Facebook or Twitter) to distinguish individuals either with a diagnosis of mental illness or experiencing an adverse outcome from healthy controls. However, the performance of such models on data from novel social media platforms unseen in the training data (eg, Instagram and TikTok) has not been investigated in previous literature.

OBJECTIVE

Our study examined the feasibility of building machine learning classifiers that can effectively predict an upcoming psychiatric hospitalization given social media data from platforms unseen in the classifiers' training data despite the preliminary evidence on identity fragmentation on the investigated social media platforms.

METHODS

Windowed timeline data of patients with a diagnosis of schizophrenia spectrum disorder before a known hospitalization event and healthy controls were gathered from 3 platforms: Facebook (254/268, 94.8% of participants), Twitter (51/268, 19% of participants), and Instagram (134/268, 50% of participants). We then used a 3 × 3 combinatorial binary classification design to train machine learning classifiers and evaluate their performance on testing data from all available platforms. We further compared results from models in intraplatform experiments (ie, training and testing data belonging to the same platform) to those from models in interplatform experiments (ie, training and testing data belonging to different platforms). Finally, we used Shapley Additive Explanation values to extract the top predictive features to explain and compare the underlying constructs that predict hospitalization on each platform.

RESULTS

We found that models in intraplatform experiments on average achieved an F₁-score of 0.72 (SD 0.07) in predicting a psychiatric hospitalization because of schizophrenia spectrum disorder, which is 68% higher than the average of models in interplatform experiments at an F₁-score of 0.428 (SD 0.11). When investigating the key drivers for divergence in construct validities between models, an analysis of top features for the intraplatform models showed both low predictive feature overlap between the platforms and low pairwise rank correlation (<0.1) between the platforms' top feature rankings. Furthermore, low average cosine similarity of data between platforms within participants in comparison with the same measurement on data within platforms between participants points to evidence of identity fragmentation of participants between platforms.

CONCLUSIONS

We demonstrated that models built on one platform's data to predict critical mental health treatment outcomes such as hospitalization do not generalize to another platform. In our case, this is because different social media platforms consistently reflect different segments of participants' identities. With the changing ecosystem of social media use among different demographic groups and as web-based identities continue to become fragmented across platforms, further research on holistic approaches to harnessing these diverse data sources is required.

Ten-year follow-up of social functioning and behaviour problems in people with schizophrenia and related disorders

BACKGROUND

In recent years, several variables in the course of schizophrenia and related psychotic disorders have been studied. However, an instrumental analysis of the evolution of social functioning and behaviour problems has scarcely been explored.

AIM

To analyse the evolution of social functioning and behaviour problems and find any diagnosis or gender differences.

METHOD

The Social Functioning Scale (SFS) and the Behaviour Problems Inventory (BPI) were administered in Stages I (2003-2007) and II (2014-2017) to 100 close relatives of patients under treatment at a Community Mental Health Unit. A related samples t-test, analysis of variance and multivariate analysis of variance were performed to study the evolution and differences in social functioning and behaviour problems. Then a stepwise multiple linear regression analysis was done to predict the evolution of social functioning.

RESULTS

No deterioration in the evolution of social functioning or behaviour problems was observed, and schizophrenia patient scores were lower. Women scored higher in withdrawal/social engagement, interpersonal behaviour, independence-performance, independence-competence and total social functioning, with no significant differences in behaviour problems. Previous social functioning, underactivity/social withdrawal and education are predictive factors in the evolution of social functioning. Conclusion: The results show the need for implementing psychosocial intervention programs that promote functional recovery and keep problems from becoming chronic.

Delay in psychiatric hospitalization from the diagnosis of first-episode schizophrenia and its association with clinical outcomes and direct medical costs: a nationwide, health insurance data-based study

BACKGROUND

Early intervention is essential for improving the prognosis in patients with first-episode schizophrenia (FES). The Mental Health Act limits involuntary hospitalization in South Korea to cases where an individual exhibits both a mental disorder and a potential for harming themselves or others, which could result in a delay in the required treatment in FES. We investigated the effect of delay in the first psychiatric hospitalization on clinical outcomes in FES.

METHODS

The South Korean Health Insurance Review Agency database (2012-2019) was used. We identified 15,994 patients with FES who had a record of at least one psychiatric hospitalization within 1 year from their diagnosis. A multivariate linear regression model and a generalized linear model with a gamma distribution and log link were used to examine associations between the duration from the diagnosis to the first psychiatric admission and clinical outcomes as well as direct medical costs after 2 and 5 years.

RESULTS

Within both the 2-year and the 5-year period, longer durations from the diagnosis to the first psychiatric admission were associated with an increase in the number of psychiatric hospitalizations (2-y: B = 0.003, p = 0.003, 5-y: B = 0.007, p = 0.001) and an increase in direct medical costs (total: 2-y: B = 0.005, p < 0.001, 5-y: B = 0.004, p = 0.005; inpatient care: 2-y: B = 0.005, p < 0.001, 5-y: B = 0.004, p = 0.017).

CONCLUSIONS

Earlier psychiatric admission from the diagnosis is associated with a decrease in the number of psychiatric admissions as well as in direct medical costs in patients with FES.

Factors associated with high health care spending among patients with schizophrenia

INTRODUCTION

Understanding the reasons for the wide variation in health care spending among patients with schizophrenia may benefit the development of interventions aimed at improving patient outcomes and health care spending efficiency. The aim of our study was to determine factors associated with high health care spending in the patient population.

METHODS

A serial cross-sectional study used the administrative health records of residents of Alberta, Canada between 1 January 2008 and 31 December 2017 and provincial costing methodologies to calculate total health care spending and sector-specific costs. Factors that modified the odds of being a high cost (i.e. 95th percentile or higher) patient with schizophrenia were estimated using generalized estimating equations.

RESULTS

This study captured 242 818 person-years of observations among 38 177 unique patients with schizophrenia. Increased odds of being a high-cost patient were associated with younger age (18-29 years), male sex, unstable housing status and requiring care from multiple medical specialties. The strongest estimated associations between high cost status and comorbidity were for metastatic cancer (OR = 2.26) and cirrhosis (OR = 2.07). In contrast, polypharmacy was associated with a decreased odds of being high cost compared with untreated patients.

CONCLUSION

Factors associated with being a high-cost patient are the result of complex interactions between individual, structural and treatment-related factors. Efforts to improve patient outcomes and address rising health care costs must consider the value of allocating resources towards early detection and support of patients with schizophrenia along with the prevention/management of comorbidity.

Insights into the Promising Prospect of G Protein and GPCR-Mediated Signaling in Neuropathophysiology and Its Therapeutic Regulation

G protein-coupled receptors (GPCRs) are intricately involved in the conversion of extracellular feedback to intracellular responses. These specialized receptors possess a crucial role in neurological and psychiatric disorders. Most nonsensory GPCRs are active in almost 90% of complex brain functions. At the time of receptor phosphorylation, a GPCR pathway is essentially activated through a G protein signaling mechanism via a G protein-coupled receptor kinase (GRK). Dopamine, an important neurotransmitter, is primarily involved in the pathophysiology of several CNS disorders; for instance, bipolar disorder, schizophrenia, Parkinson's disease, and ADHD. Since dopamine, acetylcholine, and glutamate are potent neuropharmacological targets, dopamine itself has potential therapeutic effects in several CNS disorders. GPCRs essentially regulate brain functions by modulating downstream signaling pathways. GPR6, GPR52, and GPR8 are termed orphan GPCRs because they colocalize with dopamine D1 and D2 receptors in neurons of the basal ganglia, either alone or with both receptors. Among the orphan GPCRs, the GPR52 is recognized for being an effective psychiatric receptor. Various antipsychotics like aripiprazole and quetiapine mainly target GPCRs to exert their actions. One of the most important parts of signal transduction is the regulation of G protein signaling (RGS). These substances inhibit the activation of the G protein that initiates GPCR signaling. Developing a combination of RGS inhibitors with GPCR agonists may prove to have promising therapeutic potential. Indeed, several recent studies have suggested that GPCRs represent potentially valuable therapeutic targets for various psychiatric disorders. Molecular biology and genetically modified animal model studies recommend that these enriched GPCRs may also act as potential therapeutic psychoreceptors. Neurotransmitter and neuropeptide GPCR malfunction in the frontal cortex and limbic-related regions, including the hippocampus, hypothalamus, and brainstem, is likely responsible for the complex clinical picture that includes cognitive, perceptual, emotional, and motor symptoms. G protein and GPCR-mediated signaling play a critical role in developing new treatment options for mental health issues, and this study is aimed at offering a thorough picture of that involvement. For patients who are resistant to current therapies, the development of new drugs that target GPCR signaling cascades remains an interesting possibility. These discoveries might serve as a fresh foundation for the creation of creative methods for pharmacologically useful modulation of GPCR function.

Cost-utility analysis of lurasidone for the first-line treatment of schizophrenia in China

Objective

To evaluate the cost-effectiveness of lurasidone compared with olanzapine and risperidone in the first-line treatment of patients with schizophrenia from a Chinese healthcare system perspective.

Methods

A Markov model with 6-week cycle was constructed to reflect the disease progression of schizophrenia patients in the acute and maintenance phase. Probabilities of treatment discontinuation and adverse events in the acute phase were derived from the 6-week lurasidone clinical trial and a published network meta-analysis; long-term risks of relapse and discontinuation were estimated based on the 12-month lurasidone clinical trial and other treatment comparison studies. Cost inputs were derived from published literature and Chinese official documents, supplemented by expert opinions when necessary. Utility values were taken from published literature. Costs and quality-adjusted life-years (QALYs) were assessed over 15 years with a discount rate of 5% per year.

Results

Over a 15-year time horizon, lurasidone yielded an improvement of 0.197 QALYs with a cost saving of CN¥12,093 (US$1,753) vs. olanzapine and an improvement of 0.116 QALYs with a cost saving of CN¥6,781 (US$983) vs. risperidone. One-way sensitivity analyses demonstrated robust base-case results since all analyses yielded net monetary benefits >0 at a willingness-to-pay threshold of CN¥72,447.00 (US$10,499.57)/QALY. Probabilistic sensitivity analyses suggested that lurasidone had 99.7, 99.9, and 100% probability of being cost-effective vs. olanzapine and risperidone at the conventional decision thresholds of 1, 2, and 3 times the Chinese per capita gross domestic product [namely CN¥72,447.00 (US$10,499.57)/QALY, CN¥1,44,894.00 (US$20,999.13)/QALY, and CN¥2,17,341.00 (US$31,498.70)/QALY in 2020], respectively.

Conclusion

Treatment with lurasidone was predicted to improve health outcomes and be a dominant strategy for patients with schizophrenia, compared with olanzapine and risperidone, in China.

Evaluating physical urban features in several mental illnesses using electronic health record data

Objectives

Understanding the potential impact of physical characteristics of the urban environment on clinical outcomes on several mental illnesses.

Materials and Methods

Physical features of the urban environment were examined as predictors for affective and non-affective several mental illnesses (SMI), the number and length of psychiatric hospital admissions, and the number of short and long-acting injectable antipsychotic prescriptions. In addition, the urban features with the greatest weight in the predicted model were determined. The data included 28 urban features and 6 clinical variables obtained from 30,210 people with SMI receiving care from the South London and Maudsley NHS Foundation Trust (SLaM) using the Clinical Record Interactive Search (CRIS) tool. Five machine learning regression models were evaluated for the highest prediction accuracy followed by the Self-Organising Map (SOM) to represent the results visually.

Results

The prevalence of SMI, number and duration of psychiatric hospital admission, and antipsychotic prescribing were greater in urban areas. However, machine learning analysis was unable to accurately predict clinical outcomes using urban environmental data.

Discussion

The urban environment is associated with an increased prevalence of SMI. However, urban features alone cannot explain the variation observed in psychotic disorder prevalence or clinical outcomes measured through psychiatric hospitalisation or exposure to antipsychotic treatments.

Conclusion

Urban areas are associated with a greater prevalence of SMI but clinical outcomes are likely to depend on a combination of urban and individual patient-level factors. Future mental healthcare service planning should focus on providing appropriate resources to people with SMI in urban environments.

"Why I stay in community psychiatric rehabilitation": a semi-structured survey in persons with schizophrenia

AIMS

Although community psychiatric rehabilitation plays an important role in returning persons with schizophrenia to the society, many patients in China stay in rehabilitation centers for longer periods of time and subsequently fail to integrate. This study is aimed to explore the underlying causes of this trend and identify possible solutions.

METHODS

This study used a qualitative descriptive design to examine the persons with schizophrenia who stay in rehabilitation centers for longer periods of time. The researchers conducted semi-structured telephone interviews with the patients recruited through purposeful sampling. The audio-recorded interviews were transcribed in transcripts in Chinese. Thematic analysis was performed using Colaizzi's 7-step method.

RESULTS

Most patients believe that they have gained knowledge, improved skills, friendship and social circles through community mental rehabilitation, with the sense of belonging and enriched life strongly attracting them to the rehabilitation centers. They felt that the difficulty of further integration into society is mainly because of social prejudice and rejection. In addition, the activities of community mental rehabilitation meet the needs of social communication, which also hinder patients from further entering the society.

CONCLUSIONS

Persons with schizophrenia with long-term stay in community mental rehabilitation centers meet their friendship, sense of belonging and social needs by participating in rehabilitation activities. Providing special social opportunity for these patients can get them out of the rehabilitation center. Overall, it is possible for patients to gradually return to society in a collective form.

Measuring functional outcomes in schizophrenia in an increasingly digital world

With an unmet clinical need for effective interventions for cognitive and negative symptoms in patients with schizophrenia, measures of functional status (often a co-primary endpoint) remain key clinical trial outcomes. This review aims to give an overview of the different types of functional assessments commonly used in clinical trials and research involving patients with schizophrenia and highlight pertinent challenges surrounding the use of these as reliable, sensitive, and specific assessments in intervention trials. We provide examples of commonly used functional measures and highlight emerging real-time digital assessment tools. Informant- and clinician-rated functional outcome measures and functional capacity assessments are valid, commonly used measures of functional status that try to overcome the need for often overly ambitious and insensitive ‘real world’ milestones. The wide range of scientific and practical challenges associated with these different tools leave room for the development of improved functional outcome measures for use in clinical trials. In particular, many existing measures fail to capture small, but meaningful, functional changes that may occur over the course of typically short intervention trials. Adding passive digital data collection and short active real-time digital assessments whilst patients go about their day offers the opportunity to build a more fine-grained picture of functional improvements that, if thoughtfully developed and carefully applied, could provide the sensitivity needed to accurately evaluate functional status in intervention studies, aiding the development of desperately needed treatments.

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Functional outcome measures are important for evaluating the efficacy of treatments.

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A variety of these are available, each with their own strengths and limitations.

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However, consensus on the optimal functional outcome measure(s) is lacking.

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Digital measures may enhance the assessment of associated functional constructs.

Visual system assessment for predicting a transition to psychosis

The field of psychiatry is far from perfect in predicting which individuals will transition to a psychotic disorder. Here, we argue that visual system assessment can help in this regard. Such assessments have generated medium-to-large group differences with individuals prior to or near the first psychotic episode or have shown little influence of illness duration in larger samples of more chronic patients. For example, self-reported visual perceptual distortions-so-called visual basic symptoms-occur in up to 2/3rds of those with non-affective psychosis and have already longitudinally predicted an impending onset of schizophrenia. Possibly predictive psychophysical markers include enhanced contrast sensitivity, prolonged backward masking, muted collinear facilitation, reduced stereoscopic depth perception, impaired contour and shape integration, and spatially restricted exploratory eye movements. Promising brain-based markers include visual thalamo-cortical hyperconnectivity, decreased occipital gamma band power during visual detection (MEG), and reduced visually evoked occipital P1 amplitudes (EEG). Potentially predictive retinal markers include diminished cone a- and b-wave amplitudes and an attenuated photopic flicker response during electroretinography. The foregoing assessments are often well-described mechanistically, implying that their findings could readily shed light on the underlying pathophysiological changes that precede or accompany a transition to psychosis. The retinal and psychophysical assessments in particular are inexpensive, well-tolerated, easy to administer, and brief, with few inclusion/exclusion criteria. Therefore, across all major levels of analysis-from phenomenology to behavior to brain and retinal functioning-visual system assessment could complement and improve upon existing methods for predicting which individuals go on to develop a psychotic disorder.

NMR Metabolomics in Serum Fingerprinting of Schizophrenia Patients in a Serbian Cohort

Schizophrenia is a widespread mental disorder that leads to significant functional impairments and premature death. The state of the art indicates gaps in the understanding and diagnosis of this disease, but also the need for personalized and precise approaches to patients through customized medical treatment and reliable monitoring of treatment response. In order to fulfill existing gaps, the establishment of a universal set of disorder biomarkers is a necessary step. Metabolomic investigations of serum samples of Serbian patients with schizophrenia (51) and healthy controls (39), based on NMR analyses associated with chemometrics, led to the identification of 26 metabolites/biomarkers for this disorder. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models with prediction accuracies of 0.9718 and higher were accomplished during chemometric analysis. The established biomarker set includes aspartate/aspartic acid, lysine, 2-hydroxybutyric acid, and acylglycerols, which are identified for the first time in schizophrenia serum samples by NMR experiments. The other 22 identified metabolites in the Serbian samples are in accordance with the previously established NMR-based serum biomarker sets of Brazilian and/or Chinese patient samples. Thirteen metabolites (lactate/lactic acid, threonine, leucine, isoleucine, valine, glutamine, asparagine, alanine, gamma-aminobutyric acid, choline, glucose, glycine and tyrosine) that are common for three different ethnic and geographic origins (Serbia, Brazil and China) could be a good start point for the setup of a universal NMR serum biomarker set for schizophrenia.