Optimizing and Individualizing the Pharmacological Treatment of First-Episode Schizophrenic Patients: Study Protocol for a Multicenter Clinical Trial

Subgroups of cognitive impairments in schizophrenia characterized by executive function and their morphological features: a latent profile analysis study

BACKGROUND

The heterogeneity of cognitive impairments in schizophrenia has been widely observed. However, reliable cognitive boundaries to differentiate the subgroups remain elusive. The key challenge for cognitive subtyping is applying an integrated and standardized cognitive assessment and understanding the subgroup-specific neurobiological mechanisms. The present study endeavors to explore cognitive subgroups and identify their morphological features.

METHODS

A total of 920 schizophrenia patients and 169 healthy controls were recruited. MATRICS Consensus Cognitive Battery was applied to assess cognitive performance and recognize cognitive subgroups through latent profile and latent transition analysis. Cortical thickness and gray matter volume were employed for the morphological features across subgroups.

RESULTS

Four reproducible cognitive subgroups were identified, including multidomain-intact, executive-preserved, executive-deteriorated, and multidomain-deteriorated subgroup. After 12 weeks of follow-up, the cognitive characteristics of three out of the four subgroups kept stability, except for multidomain-deteriorated subgroup in which 48.8% of patients with improved cognition transited into the executive-deteriorated subgroup. Across subgroups, significant gradient features of brain structure were exhibited in fronto-temporal regions, hippocampus, and insula. Compared to healthy controls, multidomain-intact subgroup showed the most intact cognition and morphology, and multidomain-deteriorated subgroup with youngest age showed morphological decline in extensive regions. The remaining two subgroups showed intermediate cognitive performance, but could be distinguished by executive function and morphological differences in posterior cingulate cortex.

CONCLUSIONS

Our study provides novel insights into the heterogeneity of cognitive impairments in schizophrenia and the morphological features from cross-sectional and longitudinal levels, which could advance our understanding of complex cognition-morphology relationships and guide personalized interventions.

The role of isothiocyanate-rich plants and supplements in neuropsychiatric disorders: a review and update

Neuroinflammation in response to environmental stressors is an important common pathway in a number of neurological and psychiatric disorders. Responses to immune-mediated stress can lead to epigenetic changes and the development of neuropsychiatric disorders. Isothiocyanates (ITC) have shown promise in combating oxidative stress and inflammation in the nervous system as well as organ systems. While sulforaphane from broccoli is the most widely studied ITC for biomedical applications, ITC and their precursor glucosinolates are found in many species of cruciferous and other vegetables including moringa. In this review, we examine both clinical and pre-clinical studies of ITC on the amelioration of neuropsychiatric disorders (neurodevelopmental, neurodegenerative, and other) from 2018 to the present, including documentation of protocols for several ongoing clinical studies. During this time, there have been 16 clinical studies (9 randomized controlled trials), most of which reported on the effect of sulforaphane on autism spectrum disorder and schizophrenia. We also review over 80 preclinical studies examining ITC treatment of brain-related dysfunctions and disorders. The evidence to date reveals ITC have great potential for treating these conditions with minimal toxicity. The authors call for well-designed clinical trials to further the translation of these potent phytochemicals into therapeutic practice.

Sulforaphane and ophthalmic diseases

Sulforaphane (SFN) is an organosulfur compound categorized as an isothiocyanate (ITC), primarily extracted from cruciferous vegetables like broccoli and cabbage. The molecular formula of sulforaphane (SFN) is C6H11NOS2. SFN is generated by the hydrolysis of glucoraphanin (GRP) through the enzyme myrosinase, showing notable properties including anti-diabetic, anti-inflammatory, antimicrobial, anti-angiogenic, and anticancer attributes. Ongoing clinical trials are investigating its potential in diseases such as cancer, neurodegenerative diseases, diabetes-related complications, chronic kidney disease, cardiovascular disease, and liver diseases. Several animal carcinogenesis models and cell culture models have shown it to be a very effective chemopreventive agent, and the protective effects of SFN in ophthalmic diseases have been linked to multiple mechanisms. In murine models of diabetic retinopathy and age-related macular degeneration, SFN delays retinal photoreceptor cell degeneration through the Nrf2 antioxidative pathway, NF-κB pathway, AMPK pathway, and Txnip/mTOR pathway. In rabbit models of keratoconus and cataract, SFN has been shown to protect corneal and lens epithelial cells from oxidative stress injury by activating the Keap1-Nrf2-ARE pathway and the Nrf-2/HO-1 antioxidant pathway. Oral delivery or intraperitoneal injection at varying concentrations are the primary strategies for SFN intake in current preclinical studies. Challenges remain in the application of SFN in eye disorders due to its weak solubility in water and limited bioavailability because of the presence of blood-ocular barrier systems. This review comprehensively outlines recent research on SFN, elucidates its mechanisms of action, and discusses potential therapeutic benefits for eye disorders such as age-related macular degeneration (AMD), diabetic retinopathy (DR), cataracts, and other ophthalmic diseases, while also indicating directions for future clinical research to achieve efficient SFN treatment for ophthalmic diseases.

Orlistat for the treatment of antipsychotic-induced weight gain: an eight-week multicenter, randomized, placebo-controlled, double-blind trial

BACKGROUND

Weight gain and metabolic disorders are commonly induced by antipsychotics. Orlistat is a lipase inhibitor used for weight control. The effect of orlistat on weight gain and metabolic disturbances in people (especially women) treated with antipsychotics has not been sufficiently studied. This study aimed to investigate the efficacy of orlistat in mitigating antipsychotic-induced weight gain and abnormal glycolipid metabolism.

METHODS

Patients with schizophrenia or bipolar disorder with a weight gain ≥ 7% after taking antipsychotics were recruited. Participants were randomly allocated to two groups: one received eight weeks of orlistat (360 mg/day) and the other received a placebo. Anthropometric and fasting serum biochemical parameters were measured at baseline, week 4 and week 8.

RESULTS

Sixty individuals (orlistat:placebo = 32:28) participated in the study. After controlling for the study center, the eight-week changes in body mass index (BMI), cholesterol (CHOL), high-density lipoprotein cholesterol (HDL-CH) and low-density lipoprotein cholesterol (LDL-CH) were significantly different between the groups. According to the mixed linear models, CHOL and LDL-CH were significantly lower in the orlistat group than in the control group at week 8. The week 0-to-8 slopes of BMI, CHOL and LDL-CH were also significantly lower in the orlistat group.

CONCLUSIONS

These findings suggested that orlistat is an effective intervention for attenuating weight gain and serum lipid disturbances in antipsychotic-treated patients.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03451734.

Exploring the latent cognitive structure in schizophrenia: implications for antipsychotic treatment responses

BACKGROUND

Individuals diagnosed with schizophrenia present diverse degrees and types of cognitive impairment, leading to variations in responses to antipsychotic treatments. Understanding the underlying cognitive structures is crucial for assessing this heterogeneity. Utilizing latent profile analysis (LPA) enables the delineation of latent categories of cognitive function. Integrating this approach with a dimensional perspective allows for the exploration of the relationship between cognitive function and treatment response.

METHODS

This study examined 647 patients from two distinct cohorts. Utilizing LPA within the discovery cohort (n = 333) and the replication cohort (n = 314), latent subtypes were identified categorically. The stability of cognitive structures was evaluated employing Latent Transition Analysis (LTA). The relationship between cognitive function and treatment response were investigated by comparing Positive and Negative Syndrome Scale (PANSS) reduction rates across diverse cognitive subtypes. Furthermore, dimensional insights were gained through correlation analyses between cognitive tests and PANSS reduction rates.

RESULTS

In terms of categorical, individuals diagnosed with schizophrenia can be categorized into three distinct subtypes: those 'without cognitive deficit', those 'with mild-moderate cognitive 'eficit', and those 'with moderate-severe cognitive deficit'. There are significant differences in PANSS reduction rates among patients belonging to these subtypes following antipsychotic treatment (p < 0.05). Furthermore, from a dimensional perspective, processing speed at baseline is positively correlated with PANSS score reduction rates at week 8/week 10 (p < 0.01).

CONCLUSIONS

Our findings have unveiled the latent subtypes of cognitive function in schizophrenia, illuminating the association between cognitive function and responses to antipsychotic treatment from both categorical and dimensional perspectives.

PCSK9 dysregulates cholesterol homeostasis and triglyceride metabolism in olanzapine-induced hepatic steatosis via both receptor-dependent and receptor-independent pathways

Schizophrenia, affecting approximately 1% of the global population, is often treated with olanzapine. Despite its efficacy, olanzapine's prolonged use has been associated with an increased risk of cardiovascular diseases and nonalcoholic fatty liver disease (NAFLD); however, the underlying mechanism remains unclear. Proprotein convertase subtilisin kexin type 9 (PCSK9) plays a crucial role in lipid metabolism and is involved in NAFLD pathogenesis via an unknown mechanism. This study aims to investigate the role of PCSK9 in olanzapine-induced NAFLD. C57BL/6J mice and HepG2 and AML12 cell lines were treated with varying concentrations of olanzapine to examine the effects of olanzapine on PCSK9 and lipid metabolism. PCSK9 levels were manipulated using recombinant proteins, plasmids, and small interfering RNAs in vitro, and the effects on hepatic lipid accumulation and gene expression related to lipid metabolism were assessed. Olanzapine treatment significantly increased PCSK9 levels in both animal and cell line models, correlating with elevated lipid accumulation. PCSK9 manipulation demonstrated its central role in mediating hepatic steatosis through both receptor-dependent pathways (impacting NPC1L1) and receptor-independent pathways (affecting lipid synthesis, uptake, and cholesterol biosynthesis). Interestingly, upregulation of SREBP-1c, rather than SREBP-2, was identified as a key driver of PCSK9 increase in olanzapine-induced NAFLD. Our findings establish PCSK9 as a pivotal factor in olanzapine-induced NAFLD, influencing both receptor-related and metabolic pathways. This highlights PCSK9 inhibitors as potential therapeutic agents for managing NAFLD in schizophrenia patients treated with olanzapine.

Early non-response as a predictor of later non-response to antipsychotics in schizophrenia: a randomized trial

BACKGROUND

It remains a challenge to predict the long-term response to antipsychotics in patients with schizophrenia who do not respond at an early stage. This study aimed to investigate the optimal predictive cut-off value for early non-response that would better predict later non-response to antipsychotics in patients with schizophrenia.

METHODS

This multicenter, 8-week, open-label, randomized trial was conducted at 19 psychiatric centers throughout China. All enrolled participants were assigned to olanzapine, risperidone, amisulpride, or aripiprazole monotherapy for 8 weeks. The positive and negative syndrome scale (PANSS) was evaluated at baseline, week 2, week 4, and week 8. The main outcome was the prediction of nonresponse. Nonresponse is defined as a < 20% reduction in the total scores of PANSS from baseline to endpoint. Severity ratings of mild, moderate, and severe illness corresponded to baseline PANSS total scores of 58, 75, and 95, respectively.

RESULTS

At week 2, a reduction of < 5% in the PANSS total score showed the highest total accuracy in the severe and mild schizophrenia patients (total accuracy, 75.0% and 80.8%, respectively), and patients who were treated with the risperidone and amisulpride groups (total accuracy, 82.4%, and 78.2%, respectively). A 10% decrease exhibited the best overall accuracy in the moderate schizophrenia patients (total accuracy, 84.0%), olanzapine (total accuracy, 79.2%), and aripiprazole group (total accuracy, 77.4%). At week 4, the best predictive cut-off value was < 20%, regardless of the antipsychotic or severity of illness (total accuracy ranging from 89.8 to 92.1%).

CONCLUSIONS

Symptom reduction at week 2 has acceptable discrimination in predicting later non-response to antipsychotics in schizophrenia, and a more accurate predictive cut-off value should be determined according to the medication regimen and baseline illness severity. The response to treatment during the next 2 weeks after week 2 could be further assessed to determine whether there is a need to change antipsychotic medication during the first four weeks.

TRIAL REGISTRATION

This study was registered on Clinicaltrials.gov (NCT03451734).

Influencing factors of medication adherence in schizophrenic patients: a meta-analysis

Medication adherence of schizophrenic patients is a growing public health problem. We conducted a meta-analysis on the influencing factors of medication compliance in schizophrenic patients. We searched PubMed, Embase, Cochrane Library, and Web Of Science for relevant articles published up to December 22, 2022. Combined odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess influencing factors. Egger's test, funnel plot, the trim and fill method, and meta-regression analysis were used to assess publication bias. A total of 20 articles were included in the analysis. Twenty influencing factors were divided into seven categories: drug factors (OR = 1.96, 95% CI: 1.48-2.59), problem behavior (OR = 1.77, 95% CI: 1.43-2.19), income and quality of life (OR = 1.23, 95% CI: 1.08-1.39), personal characteristics (OR = 1.21, 95% CI: 1.14-1.30), disease factors (OR = 1.14, 95% CI: 1.98-1.21), support level (OR = 0.54, 95% CI: 0.42-0.70), and positive attitude and behavior (OR = 0.52, 95% CI: 0.45-0.62). This meta-analysis found that drug factors, disease factors, problem behavior, low income and quality of life, and factors related to personal characteristics appear to be risk factors for medication adherence in people with schizophrenia. And support level, positive attitude and behavior appear to be protective factors.

Association between olanzapine concentration and metabolic dysfunction in drug-naive and chronic patients: similarities and differences

Second-generation antipsychotics are widely used to treat schizophrenia but their use could induce metabolic dysfunction. To balance efficacy and side effects, various guidelines recommend the use of therapeutic drug monitoring. Given the controversial relationship between olanzapine serum concentration and metabolic dysfunction, its use in clinical practice is still debated. To address this issue, we conducted a prospective cohort study to explore the associations in patients with schizophrenia. Specifically, first-episode drug-naive patients and patients with chronic schizophrenia were recruited. All participants received olanzapine monotherapy for 8 weeks. Anthropometric parameters and metabolic indices were tested at baseline and at week 8, and olanzapine serum concentration was tested at week 4. After 8 weeks of observation, body weight and BMI increased significantly in drug-naive patients. Moreover, triglycerides and LDL increased significantly in both drug-naive and chronic patients. Among chronic patients, those who have never used olanzapine/clozapine before had a significantly higher increase in weight and BMI than those who have previously used olanzapine/clozapine. Furthermore, olanzapine concentration was associated with changes in weight, BMI, and LDL levels in the drug-naive group and glucose, triglyceride and LDL levels in chronic patients who have not used olanzapine/clozapine previously. In conclusion, the metabolic dysfunction induced by olanzapine is more severe and dose-dependent in drug-naive patients but independent in patients with chronic schizophrenia. Future studies with a longer period of observation and a larger sample are warranted.

Schizophrenia and Hospital Admissions for Cardiovascular Events in a Large Population: The APNA Study

(1) Background: Patients with schizophrenia have higher mortality, with cardiovascular diseases being the first cause of mortality. This study aims to estimate the excess risk of hospital admission for cardiovascular events in schizophrenic patients, adjusting for comorbidity and risk factors. (2) Methods: The APNA study is a dynamic prospective cohort of all residents in Navarra, Spain. A total of 505,889 people over 18 years old were followed for five years. The endpoint was hospital admissions for a cardiovascular event. Direct Acyclic Graphs (DAG) and Cox regression were used. (3) Results: Schizophrenic patients had a Hazard Ratio (HR) of 1.414 (95% CI 1.031–1.938) of hospital admission for a cardiovascular event after adjusting for age, sex, hypertension, type 2 diabetes, dyslipidemia, smoking, low income, obesity, antecedents of cardiovascular disease, and smoking. In non-adherent to antipsychotic treatment schizophrenia patients, the HR was 2.232 (95% CI 1.267–3.933). (4) Conclusions: Patients with schizophrenia have a higher risk of hospital admission for cardiovascular events than persons with the same risk factors without schizophrenia. Primary care nursing interventions should monitor these patients and reduce cardiovascular risk factors.