Multi-omics analyses of serum metabolome, gut microbiome and brain function reveal dysregulated microbiota-gut-brain axis in bipolar depression.

The intricate processes of microbiota-gut-brain communication in modulating human cognition and emotion, especially in the context of mood disorders, have remained elusive. Here we performed faecal metagenomic, serum metabolomics and neuroimaging studies on a cohort of 109 unmedicated patients with depressed bipolar disorder (BD) patients and 40 healthy controls (HCs) to characterise the microbial-gut-brain axis in BD. Across over 12,000 measured metabolic features, we observed a large discrepancy (73.54%) in the serum metabolome between BD patients and HCs, spotting differentially abundant microbial-derived neuroactive metabolites including multiple B-vitamins, kynurenic acid, gamma-aminobutyric acid and short-chain fatty acids. These metabolites could be linked to the abundance of gut microbiota presented with corresponding biosynthetic potentials, including Akkermansia muciniphila, Citrobacter spp. (Citrobacter freundii and Citrobacter werkmanii), Phascolarctobacterium spp., Yersinia spp. (Yersinia frederiksenii and Yersinia aleksiciae), Enterobacter spp. (Enterobacter cloacae and Enterobacter kobei) and Flavobacterium spp. Based on functional neuroimaging, BD-related neuroactive microbes and metabolites were discovered as potential markers associated with BD-typical features of functional connectivity of brain networks, hinting at aberrant cognitive function, emotion regulation, and interoception. Our study combines gut microbiota and neuroactive metabolites with brain functional connectivity, thereby revealing potential signalling pathways from the microbiota to the gut and the brain, which may have a role in the pathophysiology of BD.

The gut microbiota promotes the pathogenesis of schizophrenia via multiple pathways.

Schizophrenia is a severe mental disorder with unknown etiology. Many mechanisms, including dysregulation of neurotransmitters, immune disturbance, and abnormal neurodevelopment, are proposed for the pathogenesis of schizophrenia. The significance of communication between intestinal flora and the central nervous system through the gut-brain axis is increasingly being recognized. The intestinal microbiota plays an important role in regulating neurotransmission, immune homeostasis, and brain development. We hypothesize that an imbalance in intestinal flora causes immune activation and dysfunction in the gut-brain axis, contributing to schizophrenia. In this review, we examine recent studies that explore the intestinal flora and immune-mediated neurodevelopment of schizophrenia. We conclude that an imbalance in intestinal flora may reduce protectants and increase neurotoxin and inflammatory mediators, causing neuronal and synaptic damage, which induces schizophrenia.

[Analysis of the changes of serum high mobility group protein B1 and cytokines in first-episode schizophrenia patients].

OBJECTIVE: To measure serum levels of high mobility group protein B-1 (HMGB1), interleukin-1ß (IL-1ß), interleukin-6 (IL-6) and tumor necrosis factor-α ( TNF-α) before and after antipsychotic treatment, and further study the role of HMGB1 in schizophrenics. METHODS: Thirty first-episode schizophrenics who were never treated with neuroleptics from First Affiliated Hospital of Zhengzhou University and thirty healthy subjects were enrolled. Serum levels of cytokines such as HMGB1, IL-1ß, IL-6 and TNF-α were examined with enzyme linked immunosorbent assay (ELISA) before and after antipsychotic treatment. RESULTS: The serum levels of HMGB1, IL-10, IL-6 and TNF-α in schizophrenics [(80 zophµ8/L, (51 zo, 441 zo, 591 zopng/L] were significantly higher than those in the healthy subjects [(54 gni) µ4/L, (25 gni, 17 gn, 41 gni) ng/L] (P < 0.05). After treating the schizophrenics with the neuroleptic risperidone for 6 months, the serum levels of HMGB1, IL-1ß, TNF-α and IL-6 were decreased. The serum levels of HMGB1 were positively correlated to IL-1ß, IL-6, TNF-α and Negative Symptoms (r = 0.377, r = 0.426, r = 0.454, r = 0.558, P < 0.05). CONCLUSIONS: Schizophrenics show activation of the cytokine system and immune disturbance. HMGB1 may play a proinflammatory role in schizophrenia and the decrease of HMGB1 after neuroleptic risperidone treatment may be a marker of mental symptoms remission.

Intestinal mycobiota dysbiosis associated inflammation activation in chronic schizophrenia.

The microbiome-gut-brain axis is related to schizophrenia (SCZ). The role of intestinal mycobiota in SCZ has been under investigated. We present a half-year follow-up study involving 109 chronic SCZ patients and 77 healthy controls. Intestinal mycobiota was tested by internal transcribed spacer (ITS). Untargeted liquid chromatography-mass spectrometry (LC-MS) was used to measure fecal metabolites. Symptom severity was assessed using the Positive and Negative Syndrome Scale. Enterotype analysis showed that Candida-type patients exhibited severer positive symptoms and depression factors than Saccharomyces-type patients. Candida and its top species and operational taxonomic units (OTUs) were positively correlated with depression factors (all p=0.001). Fecal metabolites analysis showed that upregulated metabolites were associated with chronic inflammation (NF-κB pathway and T helper cell differentiation), downregulated metabolites were associated with glutamate metabolism, serotonergic and dopaminergic synapse. Procrustes analysis revealed significant correlation between intestinal mycobiota and fecal metabolites (M2=0.937, p<0.001). Metabolic module analysis showed that the top module, MEturquoise (associated with Th1 and Th2 cell differentiation), was negatively correlated with SCZ (r=-0.783, p<0.0001), positively correlated with Candida, Aspergillus, Trichosporon and Talaromyces (decreased in SCZ) and negatively correlated with Saccharomyces (increased in SCZ). We also found impairments of intestinal barrier in SCZ, characterized by increased in blood D-lactate (mucosa impairment marker) and decreased in blood mucin 2 (mucosal barrier protective protein). Serum levels of TNF-α was increased and showed stable high levels during treatment. This study suggests that mycobiota dysbiosis-related chronic inflammation and an impaired intestinal mucosal barrier are associated with chronic SCZ.

Identifying frequency-dependent imaging genetic associations via hypergraph-structured multi-task sparse canonical correlation analysis.

Identifying complex associations between genetic variations and imaging phenotypes is a challenging task in the research of brain imaging genetics. The previous study has proved that neuronal oscillations within distinct frequency bands are derived from frequency-dependent genetic modulation. Thus it is meaningful to explore frequency-dependent imaging genetic associations, which may give important insights into the pathogenesis of brain disorders. In this work, the hypergraph-structured multi-task sparse canonical correlation analysis (HS-MTSCCA) was developed to explore the associations between multi-frequency imaging phenotypes and single-nucleotide polymorphisms (SNPs). Specifically, we first created a hypergraph for the imaging phenotypes of each frequency and the SNPs, respectively. Then, a new hypergraph-structured constraint was proposed to learn high-order relationships among features in each hypergraph, which can introduce biologically meaningful information into the model. The frequency-shared and frequency-specific imaging phenotypes and SNPs could be identified using the multi-task learning framework. We also proposed a useful strategy to tackle this algorithm and then demonstrated its convergence. The proposed method was evaluated on four simulation datasets and a real schizophrenia dataset. The experimental results on synthetic data showed that HS-MTSCCA outperforms the other competing methods according to canonical correlation coefficients, canonical weights, and cosine similarity. And the results on real data showed that HS-MTSCCA could obtain superior canonical coefficients and canonical weights. Furthermore, the identified frequency-shared and frequency-specific biomarkers could provide more interesting and meaningful information, demonstrating that HS-MTSCCA is a powerful method for brain imaging genetics.

Psychosocial and psychological interventions for schizophrenia relapse prevention: A bibliometric analysis.

Various psychosocial and psychological interventions have been developed to reduce schizophrenia relapse prevention. A better understanding of these active interventions is important for clinical practice and for meaningful allocation of resources. However, no bibliometric analysis of this area has been conducted. Studies were retrieved from the Web of Science Core Collection database. The publication outputs and cooperation of institutions were visualized with Origin 2021. Global cooperation was visualized using ArcGIS Pro3.0. VOSviewer was used to generate visualizations of network of authors and keywords. The number of annual publications generally showed a fluctuating upward trend over the past 20 years. Germany published the most relevant articles (361, 26.76%). The Technical University of Munich was the most productive institution (70, 9.86%). Leucht Stefan published the most articles (46, 6.48%) and had the highest number of citations (4,375 citations). Schizophrenia Research published the most studies (39, 5.49%). Keywords were roughly classified into three clusters: cognitive behavioral therapy (CBT), family interventions and family psychoeducation and other factors related to interventions. The findings provided the current status of research on psychosocial and psychological interventions for schizophrenia relapse prevention from a bibliometric perspective. Recent research has mainly focused on CBT, family interventions and family psychoeducation.

Gut microbial diversity moderates polygenic risk of schizophrenia.

Background: Schizophrenia (SCZ) is a heritable disorder with a polygenic architecture, and the gut microbiota seems to be involved in its development and outcome. In this study, we investigate the interplay between genetic risk and gut microbial markers. Methods: We included 159 first-episode, drug-naïve SCZ patients and 86 healthy controls. The microbial composition of feces was characterized using the 16S rRNA sequencing platform, and five microbial α-diversity indices were estimated [Shannon, Simpson, Chao1, the Abundance-based Eoverage Estimator (ACE), and a phylogenetic diversity-based estimate (PD)]. Polygenic risk scores (PRS) for SCZ were constructed using data from large-scale genome-wide association studies. Effects of microbial α-diversity, microbial abundance, and PRS on SCZ were evaluated via generalized linear models. Results: We confirmed that PRS was associated with SCZ (OR = 2.08, p = 1.22×10-5) and that scores on the Shannon (OR = 0.29, p = 1.15×10-8) and Simpson (OR = 0.29, p = 1.25×10-8) indices were inversely associated with SCZ risk. We found significant interactions (p < 0.05) between PRS and α-diversity indices (Shannon, Simpson, and PD), with the effects of PRS being larger in those exhibiting higher diversity compared to those with lower diversity. Moreover, the PRS effects were larger in individuals with a high abundance of the genera Romboutsia, Streptococcus, and Anaerostipes than in those with low abundance (p < 0.05). All three of these genera showed protective effects against SCZ. Conclusion: The current findings suggest an interplay between the gut microbiota and polygenic risk of SCZ that warrants replication in independent samples. Experimental studies are needed to determine the underpinning mechanisms.

Multiomics Analyses Reveal Microbiome-Gut-Brain Crosstalk Centered on Aberrant Gamma-Aminobutyric Acid and Tryptophan Metabolism in Drug-Naïve Patients with First-Episode Schizophrenia.

BACKGROUND AND HYPOTHESIS: Schizophrenia (SCZ) is associated with complex crosstalk between the gut microbiota and host metabolism, but the underlying mechanism remains elusive. Investigating the aberrant neurotransmitter processes reflected by alterations identified using multiomics analysis is valuable to fully explain the pathogenesis of SCZ. STUDY DESIGN: We conducted an integrative analysis of multiomics data, including the serum metabolome, fecal metagenome, single nucleotide polymorphism data, and neuroimaging data obtained from a cohort of 127 drug-naïve, first-episode SCZ patients and 92 healthy controls to characterize the microbiome-gut-brain axis in SCZ patients. We used pathway-based polygenic risk score (PRS) analyses to determine the biological pathways contributing to genetic risk and mediation effect analyses to determine the important neuroimaging features. Additionally, a random forest model was generated for effective SCZ diagnosis. STUDY RESULTS: We found that the altered metabolome and dysregulated microbiome were associated with neuroactive metabolites, including gamma-aminobutyric acid (GABA), tryptophan, and short-chain fatty acids. Further structural and functional magnetic resonance imaging analyses highlighted that gray matter volume and functional connectivity disturbances mediate the relationships between Ruminococcus_torgues and Collinsella_aerofaciens and symptom severity and the relationships between species Lactobacillus_ruminis and differential metabolites l-2,4-diaminobutyric acid and N-acetylserotonin and cognitive function. Moreover, analyses of the Polygenic Risk Score (PRS) support that alterations in GABA and tryptophan neurotransmitter pathways are associated with SCZ risk, and GABA might be a more dominant contributor. CONCLUSIONS: This study provides new insights into systematic relationships among genes, metabolism, and the gut microbiota that affect brain functional connectivity, thereby affecting SCZ pathogenesis.

New insight in the cross-talk between microglia and schizophrenia: From the perspective of neurodevelopment.

Characterized by psychotic symptoms, negative symptoms and cognitive deficits, schizophrenia had a catastrophic effect on patients and their families. Multifaceted reliable evidence indicated that schizophrenia is a neurodevelopmental disorder. Microglia, the immune cells in central nervous system, related to many neurodevelopmental diseases. Microglia could affect neuronal survival, neuronal death and synaptic plasticity during neurodevelopment. Anomalous microglia during neurodevelopment may be associated with schizophrenia. Therefore, a hypothesis proposes that the abnormal function of microglia leads to the occurrence of schizophrenia. Nowadays, accumulating experiments between microglia and schizophrenia could afford unparalleled probability to assess this hypothesis. Herein, this review summarizes the latest supporting evidence in order to shed light on the mystery of microglia in schizophrenia.

Establishment of an assistive diagnostic model for schizophrenia with oxidative stress biomarkers.

Objective: In this study, alterations in oxidative stress-related indicators were evaluated in drug-naïve, first-episode schizophrenia (SCZ) patients, and the effectiveness of blood serum glucose, superoxide dismutase (SOD), bilirubin in the objective assistive diagnosis of schizophrenia was explored. Materials and methods: We recruited 148 drug-naïve, first-episode SCZ patients and 97 healthy controls (HCs). Blood biochemical indexes including blood glucose, SOD, bilirubin and homocysteine (HCY) in participants were measured, the indexes were compared between patients with SCZ and HCs. The assistive diagnostic model for SCZ was established on the basis of the differential indexes. Results: In SCZ patients, the blood serum levels of glucose, total (TBIL), indirect bilirubin (IBIL) and homocysteine (HCY) were significantly higher than those in HCs (p < 0.05), and the serum levels of SOD were significantly lower than those in HCs (p < 0.05). There was a negative correlation between SOD with the general symptom scores and total scores of PANSS. After risperidone treatment, the levels of uric acid (UA) and SOD tended to increase in patients with SCZ (p = 0.02, 0.19), and the serum levels of TBIL and HCY tended to decrease in patients with SCZ (p = 0.78, 0.16). The diagnostic model based on blood glucose, IBIL and SOD was internally cross-validated, and the accuracy was 77%, with an area under the curve (AUC) of 0.83. Conclusion: Our study demonstrated an oxidative state imbalance in drug-naïve, first-episode SCZ patients, which might be associated with the pathogenesis of the disease. Our study proved that glucose, IBIL and SOD may be potential biological markers of schizophrenia, and the model based on these markers can assist the early objective and accurate diagnosis of schizophrenia.

Multi-loss Disentangled Generative-Discriminative Learning for Multimodal Representation in Schizophrenia.

Schizophrenia (SCZ) is a multifactorial mental illness, thus it will be beneficial for exploring this disease using multimodal data, including functional magnetic resonance imaging (fMRI), genes, and the gut microbiome. Previous studies reported combining multimodal data can offer complementary information for better depicting the abnormalities of SCZ. However, the existing multimodal-based methods have multiple limitations. First, most approaches cannot fully use the relationships among different modalities for the downstream tasks. Second, representing multimodal data by the modality-common and modality-specific components can improve the performance of multimodal analysis but often be ignored. Third, most methods conduct the model for classification or regression, thus a unified model is needed for finishing these tasks simultaneously. To this end, a multi-loss disentangled generative-discriminative learning (MDGDL) model was developed to tackle these issues. Specifically, using disentangled learning method, the genes and gut microbial biomarkers were represented and separated into two modality-specific vectors and one modality-common vector. Then, a generative-discriminative framework was introduced to uncover the relationships between fMRI features and these three latent vectors, further producing the attentive vectors, which can help fMRI features for the downstream tasks. To validate the performance of MDGDL, an SCZ classification task and a cognitive score regression task were conducted. Results showed the MDGDL achieved superior performance and identified the most important multimodal biomarkers for the SCZ. Our proposed model could be a supplementary approach for multimodal data analysis. Based on this method, we could analyze the SCZ by combining multimodal data, and further obtain some interesting findings.

Oxidative stress impairs cognitive function by affecting hippocampal fimbria volume in drug-naïve, first-episode schizophrenia.

Objective: The aim of the present study was to explore influencing factors of cognitive impairments and their interrelationships in drug-naïve, first-episode schizophrenia (SCZ). Methods: Patients with drug naïve, first episode SCZ and healthy controls (HCs) were enrolled. Cognitive function was assessed by the MATRICS Consensus Cognitive Battery (MCCB). Serum levels of oxidative stress indices, including folate, superoxide dismutase (SOD), uric acid (UA) and homocysteine (Hcy), were determined after an overnight fast. Hippocampal subfield volumes were measured using FreeSurfer. Mediation models were conducted using the SPSS PROCESS v3.4 macro. A false discovery rate (FDR) correction was applied for multiple comparisons. Results: Sixty-seven patients with SCZ and 65 HCs were enrolled in our study. The patient group had significantly lower serum levels of folate and SOD and higher serum levels of HCY compared with the HCs (all p < 0.05). The patient group had a significantly smaller volume of the whole hippocampus than the HC group (p < 0.05). We also found significant volume differences between the two groups in the following subfields: CA1, molecular layer, GC-ML-DG and fimbria (all p < 0.05, uncorrected). The partial correlation analysis controlling for age and sex showed that the fimbria volume in the patient group was significantly positively associated with NAB scores (r = 0.382, pFDR = 0.024); serum levels of SOD in the patient group showed a significantly positive correlation with fimbria volume (r = 0.360, pFDR = 0.036). Mediation analyses controlling for age and sex showed that the serum levels of SOD in patients with SCZ had significant indirect effects on the NAB scores which were mediated by the fimbria volume [indirect effect = 0.0565, 95% CI from the bootstrap test excluding zero (0.0066 to 0.0891)]. Conclusion: Oxidative stress, a reduction in hippocampal subfield volumes and cognitive impairments occur in early SCZ. Oxidative stress impairs cognitive function by affecting hippocampal subfield volumes.

Exploring Brain Structural and Functional Biomarkers in Schizophrenia via Brain-Network-Constrained Multi-View SCCA.

Recent studies have proved that dynamic regional measures extracted from the resting-state functional magnetic resonance imaging, such as the dynamic fractional amplitude of low-frequency fluctuation (d-fALFF), could provide a great insight into brain dynamic characteristics of the schizophrenia. However, the unimodal feature is limited for delineating the complex patterns of brain deficits. Thus, functional and structural imaging data are usually analyzed together for uncovering the neural mechanism of schizophrenia. Investigation of neural function-structure coupling enables to find the potential biomarkers and further helps to understand the biological basis of schizophrenia. Here, a brain-network-constrained multi-view sparse canonical correlation analysis (BN-MSCCA) was proposed to explore the intrinsic associations between brain structure and dynamic brain function. Specifically, the d-fALFF was first acquired based on the sliding window method, whereas the gray matter map was computed based on voxel-based morphometry analysis. Then, the region-of-interest (ROI)-based features were extracted and further selected by performing the multi-view sparse canonical correlation analysis jointly with the diagnosis information. Moreover, the brain-network-based structural constraint was introduced to prompt the detected biomarkers more interpretable. The experiments were conducted on 191 patients with schizophrenia and 191 matched healthy controls. Results showed that the BN-MSCCA could identify the critical ROIs with more sparse canonical weight patterns, which are corresponding to the specific brain networks. These are biologically meaningful findings and could be treated as the potential biomarkers. The proposed method also obtained a higher canonical correlation coefficient for the testing data, which is more consistent with the results on training data, demonstrating its promising capability for the association identification. To demonstrate the effectiveness of the potential clinical applications, the detected biomarkers were further analyzed on a schizophrenia-control classification task and a correlation analysis task. The experimental results showed that our method had a superior performance with a 5-8% increment in accuracy and 6-10% improvement in area under the curve. Furthermore, two of the top-ranked biomarkers were significantly negatively correlated with the positive symptom score of Positive and Negative Syndrome Scale (PANSS). Overall, the proposed method could find the association between brain structure and dynamic brain function, and also help to identify the biological meaningful biomarkers of schizophrenia. The findings enable our further understanding of this disease.

The effect of serum lipids and short-chain fatty acids on cognitive functioning in drug-naïve, first episode schizophrenia patients.

OBJECTIVE: Many studies have reported the important role of serum levels of short-chain fatty acids (SCFAs) in lipid metabolism and cognitive dysfunction. This study investigated the role of plasma lipids and SCFAs on cognitive functioning in drug- naïve first episode schizophrenia. METHODS: This study recruited 44 schizophrenia inpatients and 35 healthy controls. Plasma lipid metabolism was characterized using standard enzymatic methods and an automated analyzer. Serum levels of SCFAs were measured by Gas chromatography mass spectrometry (GC-MS). Cognitive performance was evaluated by the MATRICS Consensus Cognitive Battery (MCCB). RESULTS: The patient group showed significantly higher serum levels of total SCFAs, acetic acid, acetic acid/ propionic acid ratio, and poorer cognitive scores compared with the control group (p's < 0.05). Within the patient group, the lipid levels were positively associated with acetic acid/ propionic acid ratio (p's < 0.05). Furthermore, multiple regression analysis revealed that the interactions of LDL level × acetic acid/ propionic acid ratio was a significant predictor of the MCCB working memory, and processing speed subscale scores within the patient group. CONCLUSIONS: Cognitive dysfunction and abnormal serum levels of SCFAs occur in the early phase of schizophrenia. Lipid metabolism and serum levels of SCFAs might be, both independently or interactively, associated with cognitive dysfunction in schizophrenia.

Gut mycobiota dysbiosis in drug-naïve, first-episode schizophrenia.

Bacterial dysbiosis has been demonstrated in patients with schizophrenia (SCH). The aim of the present study was to investigate alterations in mycobiota composition and fungi-bacteria correlation network in drug-naïve, first episode SCH. We recruited 205 SCH patients and 125 healthy controls (HCs), whose gut bacterial and fungal compositions were characterized by 16S and 18S ribosomal RNA gene amplicon sequencing, respectively. Fungal-bacterial relative correlation network analysis was performed using the Spearman's test and distance correlation. We also computed relative networks connectedness, which represents the ratio of significant interactions (edges) and taxa (nodes) in the network. SCH patients showed lower fungal α-diversity compared with that of HCs. Furthermore, we identified 29 differential fungal markers at multiple taxonomies between SCH patients and HCs. SCH patients also showed a significantly lower fungi-to-bacteria α-diversity ratio compared with that of HCs (p = 1.81 × 10-8). In risk prediction models, we observed that combining bacterial and fungal markers achieved higher accuracy than that of bacterial markers alone (AUC = 0.847 vs AUC = 0.739; p = 0.043). Fungal-bacterial correlation network was denser in HCs than in SCH patients and was characterized by a high number of neighbors (p < 0.05). In addition, an increased abundance of Purpureocillium was associated with more severe psychiatric symptoms and poorer cognitive function in SCH patients (p < 0.05). Our study demonstrated a disrupted and weakened fungi-bacteria network in SCH patients, which might be associated with their clinical manifestations. Future research on fungal-bacterial correlation network is warranted to advance our understanding about the role of mycobiota in the etiology of SCH and to explore novel intervention approaches.

Metagenomic analysis reveals gut bacterial signatures for diagnosis and treatment outcome prediction in bipolar depression.

BACKGROUND: We aimed to characterize gut microbial alterations in depressed patients with bipolar disorder (BD) following quetiapine monotherapy and explored its potential for disease diagnosis and outcome prediction. METHODS: Fecal samples were obtained from 60 healthy individuals and 62 patients in acute depressive episodes. All patients received one-month quetiapine treatment after enrollment. The structure of gut microbiota was measured with metagenomic sequencing, and its correlation with clinical profiles and brain function as indicated by resting-state functional magnetic resonance imaging was analyzed. Random forest models based on bacterial species were constructed to distinguish patients from controls, and responders from non-responders, respectively. RESULTS: BD patients displayed specific alterations in gut microbial diversity and composition. Quetiapine treatment increased the diversity of microbial communities and changed the composition. The abundance of Clostridium bartlettii was negatively associated with age, baseline depression severity, while positively associated with spontaneous neural oscillation in the hippocampus. Tree-based classification models for (1) patients and controls and (2) responders and non-responders showed an area under the curve of 0.733 and 0.800, respectively. CONCLUSION: Our findings add new evidence to the existing literature regarding gut dysbiosis in BD and reveal the potential of microbe-based biomarkers for disease diagnosis and treatment outcome prediction.

The Role of Butyric Acid in Treatment Response in Drug-Naïve First Episode Schizophrenia.

Background: Butyric acid, a major short-chain fatty acid (SCFA), has an important role in the microbiota-gut-brain axis and brain function. This study investigated the role of butyric acid in treatment response in drug-naïve first episode schizophrenia. Methods: The study recruited 56 Chinese Han schizophrenia inpatients with normal body weight and 35 healthy controls. Serum levels of butyric acid were measured using Gas Chromatography-Mass Spectrometer (GC-MS) analysis at baseline (for all participants) and 24 weeks after risperidone treatment (for patients). Clinical symptoms were measured using the Positive and Negative Syndrome Scale (PANSS) for patients at both time points. Results: At baseline, there was no significant difference in serum levels of butyric acid between patients and healthy controls (p = 0.206). However, there was a significant increase in serum levels of butyric acid in schizophrenia patients after 24-week risperidone treatment (p = 0.030). The PANSS total and subscale scores were decreased significantly after 24-week risperidone treatment (p's < 0.001). There were positive associations between baseline serum levels of butyric acid and the reduction ratio of the PANSS total and subscale scores after controlling for age, sex, education, and duration of illness (p's < 0.05). Further, there was a positive association between the increase in serum levels of butyric acid and the reduction of the PANSS positive symptoms subscale scores (r = 0.38, p = 0.019) after controlling for potential confounding factors. Conclusions: Increased serum levels of butyric acid might be associated with a favorable treatment response in drug-naïve, first episode schizophrenia. The clinical implications of our findings were discussed.

Gut microbial biomarkers for the treatment response in first-episode, drug-naïve schizophrenia: a 24-week follow-up study.

Preclinical studies have shown that the gut microbiota can play a role in schizophrenia (SCH) pathogenesis via the gut-brain axis. However, its role in the antipsychotic treatment response is unclear. Here, we present a 24-week follow-up study to identify gut microbial biomarkers for SCH diagnosis and treatment response, using a sample of 107 first-episode, drug-naïve SCH patients, and 107 healthy controls (HCs). We collected biological samples at baseline (all participants) and follow-up time points after risperidone treatment (SCH patients). Treatment response was assessed using the Positive and Negative Symptoms Scale total (PANSS-T) score. False discovery rate was used to correct for multiple testing. We found that SCH patients showed lower α-diversity (the Shannon and Simpson's indices) compared to HCs at baseline (p = 1.21 × 10-9, 1.23 × 10-8, respectively). We also found a significant difference in ß-diversity between SCH patients and HCs (p = 0.001). At baseline, using microbes that showed different abundance between patients and controls as predictors, a prediction model can distinguish patients from HCs with an area under the curve (AUC) of 0.867. In SCH patients, after 24 weeks of risperidone treatment, we observed an increase of α-diversity toward the basal level of HCs. At the genus level, we observed decreased abundance of Lachnoclostridium (p = 0.019) and increased abundance Romboutsia (p = 0.067). Moreover, the treatment response in SCH patients was significantly associated with the basal levels of Lachnoclostridium and Romboutsia (p = 0.005 and 0.006, respectively). Our results suggest that SCH patients may present characteristic microbiota, and certain microbiota biomarkers may predict treatment response in this patient population.

Insulin Resistance and Oxidative Stress: In Relation to Cognitive Function and Psychopathology in Drug-Naïve, First-Episode Drug-Free Schizophrenia.

Objective: The present study aimed to examine whether insulin resistance and oxidative stress are associated with cognitive impairment in first-episode drug-free schizophrenia (SZ) patients. Methods: Ninety first-episode SZ patients and 70 healthy controls were enrolled. Fasting insulin (FINS) and markers of oxidative stress [oxidized glutathione (GSSG), superoxide dismutase (SOD), nitric oxide (NO) and uric acid (UA) levels] were measured in serum before pharmacological treatment was initiated. Psychiatric symptoms and cognitive function were assessed with the Positive and Negative Syndrome Scale (PANSS) and MATRICS Consensus Cognitive Battery (MCCB), respectively. In addition, the homeostatic model assessment of insulin resistance (HOMA-IR) was also studied. Results: HOMA-IR and serum levels of GSSG and NO were significantly higher in SZ patients than in healthy controls (P < 0.001), while the serum levels of SOD were significantly lower than in healthy controls (P < 0.001). HOMA-IR, GSSG and NO levels were significantly correlated to the total cognitive function scores of the patient group (r = -0.345,-0.369,-0.444, respectively, P < 0.05). But these factors were not co-related to the cognitive functions in the healthy control group. And, levels of SOD, UA were not associated with the total cognitive function scores in both the patient and the healthy control groups. NO was positively correlated with general pathological and the total score in the PANSS, and was negatively correlated with six cognitive domains (r = -0.316 to -0.553, P < 0.05). Conclusions: The levels of insulin resistance and oxidative stress are elevated, and correlated with the severity of cognitive impairment in drug-naïve, first-episode SZ patients. Treatment approaches targeting on reducing insulin resistance and oxidative stress may improve cognitive function in SZ patients.

A synergistic effect between family intervention and rTMS improves cognitive and negative symptoms in schizophrenia: A randomized controlled trial.

OBJECTIVE: The present study explored an efficient new therapy that combined repetitive transcranial magnetic stimulation (rTMS) and family intervention in addition to risperidone to improve schizophrenia. METHODS: A randomized controlled trial (January 2016-September 2017) involving 200 patients, of which 188 patients completed the 12-week study, and 50 controls were conducted in the research. The patients were randomly assigned to 12 weeks of treatment with risperidone alone (risperidone group), rTMS and risperidone (rTMS group), family intervention and risperidone (family intervention group), rTMS and risperidone plus family intervention (combined group). MATRICS Consensus Cognitive Battery (MCCB) and the Positive and Negative Symptoms Scale (PANSS) were used to evaluate treatment efficacy. Repeated measures analysis of variance (RMANOVA) were performed to evaluate different treatment efficacy between four groups after 12 weeks of treatment. RESULTS: (1) There were no significant differences in sex, age, education, cognitive function, or PANSS scores between the four groups at baseline (p's > 0.05). (2) There was a significant decrease in the PANSS scores and an increase in the MCCB scores after 12 weeks of treatment in all groups (time effect p's < 0.001). (3) The improvements in positive symptoms and negative symptoms were more obvious in the combined group than in other groups (p's < 0.05). (4) The combined group showed the superior effect in cognition function after 12 weeks. (5) And, interestingly, a remarkable synergistic effect between rTMS and family intervention therapy was observed. CONCLUSION: There was a synergistic effect between rTMS and the family intervention as an effective combined therapy in improving schizophrenia. This study is registered with Chictr.org, number ChiCTR1900024422 (http://www.chictr.org.cn/edit.aspx?pid=34285&htm=4).