Metabolomic analysis of biochemical changes in the plasma and urine of first-episode neuroleptic-naïve schizophrenia patients after treatment with risperidone

A preliminary metabolomics study of the database for biological samples of schizophrenia among Chinese ethnic minorities

BACKGROUND

Schizophrenia (SCZ) is a profound mental disorder with a multifactorial etiology, including genetics, environmental factors, and demographic influences such as ethnicity and geography. Among these, the studies of SCZ also shows racial and regional differences.

METHODS

We first established a database of biological samples for SCZ in China's ethnic minorities, followed by a serum metabolomic analysis of SCZ patients from various ethnic groups within the same region using the LC-HRMS platform.

RESULTS

Analysis identified 47 metabolites associated with SCZ, with 46 showing significant differences between Miao and Han SCZ patients. These metabolites, primarily fatty acids, amino acids, benzene, and derivatives, are involved in fatty acid metabolism pathways. Notably, L-Carnitine, L-Cystine, Aspartylphenylalanine, and Methionine sulfoxide demonstrated greater diagnostic efficacy in Miao SCZ patients compared to Han SCZ patients.

CONCLUSION

Preliminary findings suggest that there are differences in metabolic levels among SCZ patients of different ethnicities in the same region, offering insights for developing objective diagnostic or therapeutic monitoring strategies that incorporate ethnic considerations of SCZ.

Exploration of urine metabolic biomarkers for new-onset, untreated pediatric epilepsy: A gas and liquid chromatography mass spectrometry-based metabolomics study

OBJECTIVE

The discovery of objective indicators for recent epileptic seizures will help confirm the diagnosis of epilepsy and evaluate therapeutic effects. Past studies had shortcomings such as the inclusion of patients under treatment and those with various etiologies that could confound the analysis results significantly. We aimed to minimize such confounding effects and to explore the small molecule biomarkers associated with the recent occurrence of epileptic seizures using urine metabolomics.

METHODS

This is a multicenter prospective study. Subjects included pediatric patients aged 2 to 12 years old with new-onset, untreated epilepsy, who had had the last seizure within 1 month before urine collection. Controls included healthy children aged 2 to 12 years old. Those with underlying or chronic diseases, acute illnesses, or recent administration of medications or supplements were excluded. Targeted metabolome analysis of spot urine samples was conducted using gas chromatography (GC)- and liquid chromatography (LC)-tandem mass spectrometry (MS/MS).

RESULTS

We enrolled 17 patients and 21 controls. Among 172 metabolites measured by GC/MS/MS and 41 metabolites measured by LC/MS/MS, only taurine was consistently reduced in the epilepsy group. This finding was subsequently confirmed by the absolute quantification of amino acids. No other metabolites were consistently altered between the two groups.

CONCLUSIONS

Urine metabolome analysis, which covers a larger number of metabolites than conventional biochemistry analyses, found no consistently altered small molecule metabolites except for reduced taurine in epilepsy patients compared to healthy controls. Further studies with larger samples, subjects with different ages, expanded target metabolites, and the investigation of plasma samples are required.

Mendelian randomization study of the relationship between blood and urine biomarkers and schizophrenia in the UK Biobank cohort

BACKGROUND

The identification of suitable biomarkers is of crucial clinical importance for the early diagnosis of treatment-resistant schizophrenia (TRS). This study aims to comprehensively analyze the association between TRS and blood and urine biomarkers.

METHODS

Candidate TRS-related single nucleotide polymorphisms (SNPs) were obtained from a recent genome-wide association study. The UK Biobank cohort, comprising 376,807 subjects with blood and urine biomarker testing data, was used to calculate the polygenic risk score (PRS) for TRS. Pearson correlation analyses were performed to evaluate the correlation between TRS PRS and each of the biomarkers, using calculated TRS PRS as the instrumental variables. Bidirectional two-sample Mendelian randomization (MR) was used to assess potential causal associations between candidate biomarkers with TRS.

RESULTS

Here we identify a significant association between TRS PRS and phosphate (r = 0.007, P = 1.96 × 10-4). Sex subgroup analyses identify seven and three candidate biomarkers associated with TRS PRS in male and female participants, respectively. For example, total protein and phosphate for males, creatinine and phosphate for females. Bidirectional two-sample MR analyses indicate that TRS is negatively associated with cholesterol (estimate = -0.363, P  = 0.008). Conversely, TRS is positively associated with total protein (estimate = 0.137, P  = 0.027), mean corpuscular volume (estimate = 0.032, P  = 2.25 × 10-5), and mean corpuscular hemoglobin (estimate = 0.018, P  = 0.007).

CONCLUSIONS

Our findings provide insights into the roles of blood and urine biomarkers in the early detection and treatment of TRS.

Potential for New Therapeutic Approaches by Targeting Lactate and pH Mediated Epigenetic Dysregulation in Major Mental Diseases

Multiple lines of evidence have shown that lactate-mediated pH alterations in the brains of patients with neuropsychiatric diseases such as schizophrenia (SCZ), Alzheimer's disease (AD) and autism may be attributed to mitochondrial dysfunction and changes in energy metabolism. While neuronal activity is associated with reduction in brain pH, astrocytes are responsible for rebalancing the pH to maintain the equilibrium. As lactate level is the main determinant of brain pH, neuronal activities are impacted by pH changes due to the binding of protons (H+) to various types of proteins, altering their structure and function in the neuronal and non-neuronal cells of the brain. Lactate and pH could affect diverse types of epigenetic modifications, including histone lactylation, which is linked to histone acetylation and DNA methylation. In this review, we discuss the importance of pH homeostasis in normal brain function, the role of lactate as an essential epigenetic regulatory molecule and its contributions to brain pH abnormalities in neuropsychiatric diseases, and shed light on lactate-based and pH-modulating therapies in neuropsychiatric diseases by targeting epigenetic modifications. In conclusion, we attempt to highlight the potentials and challenges of translating lactate-pH-modulating therapies to clinics for the treatment of neuropsychiatric diseases.

Lactate levels in the brain and blood of schizophrenia patients: A systematic review and meta-analysis

BACKGROUND

The pathophysiological mechanisms of schizophrenia are still unclear. Converging evidence suggests that energy metabolism abnormalities are involved in schizophrenia, and support its role in the pathophysiology of this disease. Lactate plays an important role in energy metabolism. Many studies have reported changes in the levels of lactate in the brain and serum of schizophrenia patients; however, the results from these studies are not consistent. To overcome this limitation, the goal of the present meta-analysis is to analyze the changes in lactate levels in the brain and blood of schizophrenia patients.

METHODS

For this systematic review and meta-analysis, we performed a thorough search of relevant literature in the English language, using the MEDLINE, Cochrane, and Embase databases.

RESULTS

In the present meta-analysis, 20 studies were scrutinized, including 13 studies on brain lactate levels, which involved 322 schizophrenia patients and 324 healthy individuals as controls. 7 studies on blood lactate levels, involving 234 schizophrenia patients and 238 healthy individuals, were also included. Brain lactate levels were elevated in schizophrenia patients, both in vivo and in post-mortem studies. Nevertheless, blood lactate levels in schizophrenia patients have revealed no statistically significant difference, as compared with control individuals.

CONCLUSIONS

In comparison with healthy individuals, schizophrenia patients had higher lactate levels in the brain, rather than in the blood. These findings suggest independent regulatory mechanisms of lactate levels in the brain and peripheral tissues. Abnormal lactate metabolism in the brain may be an important pathological mechanism in schizophrenia.

Metabolomics, Lipidomics, and Antipsychotics: A Systematic Review

Antipsychotics are an important pharmacotherapy option for the treatment of many mental illnesses. Unfortunately, selecting antipsychotics is often a trial-and-error process due to a lack of understanding as to which medications an individual patient will find most effective and best tolerated. Metabolomics, or the study of small molecules in a biosample, is an increasingly used omics platform that has the potential to identify biomarkers for medication efficacy and toxicity. This systematic review was conducted to identify metabolites and metabolomic pathways associated with antipsychotic use in humans. Ultimately, 42 studies were identified for inclusion in this review, with all but three studies being performed in blood sources such as plasma or serum. A total of 14 metabolite classes and 12 lipid classes were assessed across studies. Although the studies were highly heterogeneous in approach and mixed in their findings, increases in phosphatidylcholines, decreases in carboxylic acids, and decreases in acylcarnitines were most consistently noted as perturbed in patients exposed to antipsychotics. Furthermore, for the targeted metabolomic and lipidomic studies, seven metabolites and three lipid species had findings that were replicated. The most consistent finding for targeted studies was an identification of a decrease in aspartate with antipsychotic treatment. Studies varied in depth of detail provided for their study participants and in study design. For example, in some cases, there was a lack of detail on specific antipsychotics used or concomitant medications, and the depth of detail on sample handling and analysis varied widely. The conclusions here demonstrate that there is a large foundation of metabolomic work with antipsychotics that requires more complete reporting so that an objective synthesis such as a meta-analysis can take place. This will then allow for validation and clinical application of the most robust findings to move the field forward. Future studies should be carefully controlled to take advantage of the sensitivity of metabolomics while limiting potential confounders that may result from participant heterogeneity and varied analysis approaches.

A fast and accurate colorimetric assay for quantifying hippuric acid in human urine

Hippuric acid is an abundant metabolite in human urine. Urinary hippuric acid levels change with toxic exposure to aromatic compounds, consumption of fruits and vegetables, cancers, chronic kidney disease, schizophrenia and Crohn's disease. While urinary hippuric acid can be detected and quantified via mass spectrometry or nuclear magnetic resonance spectroscopy, a colorimetric assay would be preferable for a low-cost, point-of care clinical assay. Two colorimetric methods, that use p-dimethylaminobenzaldehyde (DMAB) or benzenesulfonyl chloride (PhSO2Cl), respectively, have been previously developed to detect hippuric acid but these assays have many limitations. We replaced PhSO2Cl with p-toluenesulfonyl chloride (p-TsCl), to create a simpler, faster and more accurate method that works with human urine. This modified colorimetric assay detects from 60 μM to 1000 μM hippuric acid in urine in 2 min. We also corrected for the effects of interfering compounds present in urine such that the assay works across many urine backgrounds. We validated this improved assay on multiple hippurate-spiked urine samples, observing an excellent correlation (R2 > 0.94) between observed and known hippurate concentrations. These data suggest that this colorimetric assay is accurate and should greatly facilitate the measurement of hippuric acid in urine to detect a variety of human conditions.

Clinical improvement in schizophrenia during antipsychotic treatment in relation to changes in glucose parameters: A systematic review

Antipsychotics (APs) are the cornerstone of treatment for schizophrenia (SCZ) spectrum disorders. Previous research suggests that there may be a positive association between AP-induced weight gain and/or dyslipidemia and improvement in psychiatric symptoms, often referred to as a "metabolic threshold". To determine whether a similar relationship exists for glucose parameters, we conducted a systematic search in six databases from inception to June 2022 for all longitudinal studies that directly examined the relationship between changes in glucose-related outcomes and changes in psychopathology among patients with SCZ treated with APs. We identified 10 relevant studies and one additional study that considered cognition. In most cases, we found that increased levels of fasting glucose and insulin following treatment were associated with clinical improvement. These findings contribute to existing literature that could suggest a common mechanism between AP action and metabolic side effects and support a need for additional work aimed at exploring the validity of a glucose-psychopathology relation in SCZ.

Statistical methods and resources for biomarker discovery using metabolomics

Metabolomics is a dynamic tool for elucidating biochemical changes in human health and disease. Metabolic profiles provide a close insight into physiological states and are highly volatile to genetic and environmental perturbations. Variation in metabolic profiles can inform mechanisms of pathology, providing potential biomarkers for diagnosis and assessment of the risk of contracting a disease. With the advancement of high-throughput technologies, large-scale metabolomics data sources have become abundant. As such, careful statistical analysis of intricate metabolomics data is essential for deriving relevant and robust results that can be deployed in real-life clinical settings. Multiple tools have been developed for both data analysis and interpretations. In this review, we survey statistical approaches and corresponding statistical tools that are available for discovery of biomarkers using metabolomics.

Urinary 1H NMR Metabolomic Analysis of Prenatal Maternal Stress Due to a Natural Disaster Reveals Metabolic Risk Factors for Non-Communicable Diseases: The QF2011 Queensland Flood Study

Prenatal stress alters fetal programming, potentially predisposing the ensuing offspring to long-term adverse health outcomes. To gain insight into environmental influences on fetal development, this QF2011 study evaluated the urinary metabolomes of 4-year-old children (n = 89) who were exposed to the 2011 Queensland flood in utero. Proton nuclear magnetic resonance spectroscopy was used to analyze urinary metabolic fingerprints based on maternal levels of objective hardship and subjective distress resulting from the natural disaster. In both males and females, differences were observed between high and low levels of maternal objective hardship and maternal subjective distress groups. Greater prenatal stress exposure was associated with alterations in metabolites associated with protein synthesis, energy metabolism, and carbohydrate metabolism. These alterations suggest profound changes in oxidative and antioxidative pathways that may indicate a higher risk for chronic non-communicable diseases such obesity, insulin resistance, and diabetes, as well as mental illnesses, including depression and schizophrenia. Thus, prenatal stress-associated metabolic biomarkers may provide early predictors of lifetime health trajectories, and potentially serve as prognostic markers for therapeutic strategies in mitigating adverse health outcomes.

Effects of Softening Dry Food with Water on Stress Response, Intestinal Microbiome, and Metabolic Profile in Beagle Dogs

Softening dry food with water is believed to be more beneficial to the intestinal health and nutrients absorption of dogs by some owners, but there appears to be little scientific basis for this belief. Thus, this study aimed to compare feeding dry food (DF) and water-softened dry food (SDF) on stress response, intestinal microbiome, and metabolic profile in dogs. Twenty healthy 5-month-old beagle dogs were selected and divided into two groups according to their gender and body weight using a completely randomized block design. Both groups were fed the same basal diet, with one group fed DF and the other fed SDF. The trial lasted for 21 days. The apparent total tract digestibility (ATTD) of nutrients, inflammatory cytokines, stress hormones, heat shock protein-70 (HSP-70), fecal microbiota, short-chain fatty acids (SCFAs), branch-chain fatty acids (BCFAs), and metabolomics were measured. Results showed that there was no significant difference in body weight, ATTD, and SCFAs between the DF and SDF groups (p > 0.05), whereas feeding with SDF caused a significant increase in serum cortisol level (p < 0.05) and tended to have higher interleukin-2 (p = 0.062) and HSP-70 (p = 0.097) levels. Fecal 16S rRNA gene sequencing found that the SDF group had higher alpha diversity indices (p < 0.05). Furthermore, the SDF group had higher levels of Streptococcus, Enterococcus, and Escherichia_Shigella, and lower levels of Faecalibacterium (p < 0.05). Serum and fecal metabolomics further showed that feeding with SDF significantly influenced the purine metabolism, riboflavin metabolism, and arginine and proline metabolism (p < 0.05). Overall, feeding with SDF caused higher cortisol level and generated effects of higher intestinal microbial diversity in dogs, but it caused an increase in some pathogenic bacteria, which may result in intestinal microbiome disturbance and metabolic disorder in dogs. In conclusion, feeding with SDF did not provide digestive benefits but caused some stress and posed a potential threat to the intestinal health of dogs. Thus, SDF is not recommended in the feeding of dogs.

1H-NMR-Based Metabolomics in Autism Spectrum Disorder and Pediatric Acute-Onset Neuropsychiatric Syndrome

We recently described a unique plasma metabolite profile in subjects with pediatric acute-onset neuropsychiatric syndrome (PANS), suggesting pathogenic models involving specific patterns of neurotransmission, neuroinflammation, and oxidative stress. Here, we extend the analysis to a group of patients with autism spectrum disorder (ASD), as a consensus has recently emerged around its immune-mediated pathophysiology with a widespread involvement of brain networks. This observational case-control study enrolled patients referred for PANS and ASD from June 2019 to May 2020, as well as neurotypical age and gender-matched control subjects. Thirty-four PANS outpatients, fifteen ASD outpatients, and twenty-five neurotypical subjects underwent physical and neuropsychiatric evaluations, alongside serum metabolomic analysis with 1H-NMR. In supervised models, the metabolomic profile of ASD was significantly different from controls (p = 0.0001), with skewed concentrations of asparagine, aspartate, betaine, glycine, lactate, glucose, and pyruvate. Metabolomic separation was also observed between PANS and ASD subjects (p = 0.02), with differences in the concentrations of arginine, aspartate, betaine, choline, creatine phosphate, glycine, pyruvate, and tryptophan. We confirmed a unique serum metabolomic profile of PANS compared with both ASD and neurotypical subjects, distinguishing PANS as a pathophysiological entity per se. Tryptophan and glycine appear as neuroinflammatory fingerprints of PANS and ASD, respectively. In particular, a reduction in glycine would primarily affect NMDA-R excitatory tone, overall impairing downstream glutamatergic, dopaminergic, and GABAergic transmissions. Nonetheless, we found metabolomic similarities between PANS and ASD that suggest a putative role of N-methyl-D-aspartate receptor (NMDA-R) dysfunction in both disorders. Metabolomics-based approaches could contribute to the identification of novel ASD and PANS biomarkers.

Diminished treatment response in relapsed versus first-episode schizophrenia as revealed by a panel of blood-based biomarkers: A combined cross-sectional and longitudinal study

There is a paucity of biomarkers for the prediction of treatment response in schizophrenia. In this study, we aimed to investigate whether diminished antipsychotic treatment response in relapsed versus first-episode schizophrenia can be revealed and predicted by a panel of blood-based biomarkers. A cross-sectional cohort consisting of 655 schizophrenia patients at different episodes and 606 healthy controls, and a longitudinal cohort including 52 first-episode antipsychotic-naïve schizophrenia patients treated with the same antipsychotic drugs during the 5-year follow-up of their first three episodes were enrolled. Plasma biomarker changes and symptom improvement were compared between the drug-free phase of psychosis onset and after 4 weeks of atypical antipsychotic drug (AAPD) treatment. In response to treatment, the extent of changes in the biomarkers of bioenergetic, purinergic, phospholipid and neurosteroid metabolisms dwindled down as number of episode and illness duration increased in relapsed schizophrenia. The changes of creatine, inosine, progesterone, allopregnanolone, cortisol and PE(16:0/22:6) were significantly correlated with the improvement of symptomatology. Inosine and progesterone at baseline were shown to be strong predictive biomarkers of treatment response. The results suggest that AAPD treatment response is diminished in the context of relapse, and our findings open new avenues for understanding the pathophysiology of treatment-resistance schizophrenia.

Pesticides Exposure-Induced Changes in Brain Metabolome: Implications in the Pathogenesis of Neurodegenerative Disorders

Pesticides have been used in agriculture, public health programs, and pharmaceuticals for many decades. Though pesticides primarily target pests by affecting their nervous system and causing other lethal effects, these chemical entities also exert toxic effects in inadvertently exposed humans through inhalation or ingestion. Mounting pieces of evidence from cellular, animal, and clinical studies indicate that pesticide-exposed models display metabolite alterations of pathways involved in neurodegenerative diseases. Hence, identifying common key metabolites/metabolic pathways between pesticide-induced metabolic reprogramming and neurodegenerative diseases is necessary to understand the etiology of pesticides in the rise of neurodegenerative disorders. The present review provides an overview of specific metabolic pathways, including tryptophan metabolism, glutathione metabolism, dopamine metabolism, energy metabolism, mitochondrial dysfunction, fatty acids, and lipid metabolism that are specifically altered in response to pesticides. Furthermore, we discuss how these metabolite alterations are linked to the pathogenesis of neurodegenerative diseases and to identify novel biomarkers for targeted therapeutic approaches.

Effect of Probiotic Supplements on Oxidative Stress Biomarkers in First-Episode Bipolar Disorder Patients: A Randomized, Placebo-Controlled Trial

Background: Currently no study has examined the effects of probiotic administration on the symptoms of anxiety, depression, and mania, as well as their correlations with the biomarkers of oxidative stress in patients with bipolar disorder (BPD). The aim of this study is to determine the effects of probiotic supplementation on plasma oxidative stress-related biomarkers and different domains of clinical symptom in patients suffering from BPD.

Methods: Eighty first-episode drug-naive patients with BPD were recruited. The subjects were randomized to receive psychotropic drugs supplementing with either probiotic or placebo and scheduled to evaluate with follow-ups for clinical symptom improvements and changes in the oxidative stress biomarkers. The Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, and Young Mania Rating Scale were used to assess the clinical symptomatology. The panel of plasma oxidative stress biomarkers were determined by ultra-performance liquid chromatography–mass spectrometry (UPLC–MS/MS) at baseline and for 3 months of follow-up, i.e., at post-treatment month 1, 2, and 3.

Results: After 3 months of intervention, decreased levels of plasma lysophosphatidylcholines (LPCs) were found in both placebo and probiotic groups. However, six other oxidative stress biomarkers (i.e., creatine, inosine, hypoxanthine, choline, uric acid, allantoic acid) increased in BPD patients after the two types of therapies. In addition, a positive correlation between changes of LPC (18:0) and YMRS scale was found in BPD patients and this association only existed in the probiotic group. Additionally, the mania symptom greatly alleviated (pretreatment–posttreatment, odds ratio = 0.09, 95%CI = 0.01, 0.64, p= 0.016) in patients who received probiotic supplements as compared with the placebo group.

Conclusion: The changes in plasma biomarkers of oxidative stress in patients with BPD have a potential to be trait-like markers, and serve as prognostic indexes for bipolar patients. Daily intakes of probiotics have advantageous effects on BPD patients with certain clinical symptoms, especially manic symptoms. The treatment may be a promising adjunctive therapeutic strategy for BPD patients in manic episode.

Plasma lipid alterations in young adults with psychotic experiences: A study from the Avon Longitudinal Study of Parents and Children cohort

BACKGROUND

Psychotic experiences (PEs) are associated with an increased risk of future psychotic and non-psychotic mental disorders. The identification of biomarkers of PEs may provide insights regarding the underlying pathophysiology.

METHODS

The current study applied targeted lipidomic approaches to compare plasma lipid profiles in participants from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort who did (n = 206) or did not (n = 206) have PEs when aged approximately 24 years.

RESULTS

In total, 202 lipids including 8 lipid classes were measured by using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS). Eight lipid clusters were generated. Thirteen individual lipids were nominally significantly higher in the PEs group compared to the control group. After correction for multiple comparisons, 9 lipids comprising 3 lysophosphatidylcholines (LPCs), 2 phosphatidylcholines (PCs) and 4 triacylglycerols (TGs) remained significant. In addition, PEs cases had increased levels of TGs and LPCs with a low double bond count.

CONCLUSIONS

These findings indicate plasma lipidomic abnormalities in individuals experiencing PEs. The lipidomic profile measures could aid our understanding of the underlying pathophysiological mechanisms.

Prediction of Low-Dose Aspirin-Induced Gastric Toxicity Using Nuclear Magnetic Resonance Spectroscopy-Based Pharmacometabolomics in Rats

BACKGROUND

Low-dose aspirin (LDA) is the backbone for secondary prevention of coronary artery disease, although limited by gastric toxicity. This study aimed to identify novel metabolites that could predict LDA-induced gastric toxicity using pharmacometabolomics.

METHODS

Pre-dosed urine samples were collected from male Sprague-Dawley rats. The rats were treated with either LDA (10 mg/kg) or 1% methylcellulose (10 mL/kg) per oral for 28 days. The rats' stomachs were examined for gastric toxicity using a stereomicroscope. The urine samples were analyzed using a proton nuclear magnetic resonance spectroscopy. Metabolites were systematically identified by exploring established databases and multivariate analyses to determine the spectral pattern of metabolites related to LDA-induced gastric toxicity.

RESULTS

Treatment with LDA resulted in gastric toxicity in 20/32 rats (62.5%). The orthogonal projections to latent structures discriminant analysis (OPLS-DA) model displayed a goodness-of-fit (R2Y) value of 0.947, suggesting near-perfect reproducibility and a goodness-of-prediction (Q2Y) of -0.185 with perfect sensitivity, specificity and accuracy (100%). Furthermore, the area under the receiver operating characteristic (AUROC) displayed was 1. The final OPLS-DA model had an R2Y value of 0.726 and Q2Y of 0.142 with sensitivity (100%), specificity (95.0%) and accuracy (96.9%). Citrate, hippurate, methylamine, trimethylamine N-oxide and alpha-keto-glutarate were identified as the possible metabolites implicated in the LDA-induced gastric toxicity.

CONCLUSION

The study identified metabolic signatures that correlated with the development of a low-dose Aspirin-induced gastric toxicity in rats. This pharmacometabolomic approach could further be validated to predict LDA-induced gastric toxicity in patients with coronary artery disease.

Multi-Omics Analysis Reveals Aberrant Gut-Metabolome-Immune Network in Schizophrenia

Schizophrenia (SCZ) is associated with several immune dysfunctions, including elevated levels of pro-inflammatory cytokines. Microorganisms and their metabolites have been found to regulate the immune system, and that intestinal microbiota is significantly disturbed in schizophrenic patients. To systematically investigate aberrant gut-metabolome-immune network in schizophrenia, we performed an integrative analysis of intestinal microbiota, serum metabolome, and serum inflammatory cytokines in 63 SCZ patients and 57 healthy controls using a multi-omics strategy. Eighteen differentially abundant metabolite clusters were altered in patients displayed higher cytokine levels, with a significant increase in pro-inflammatory metabolites and a significant decrease in anti-inflammatory metabolites (such as oleic acid and linolenic acid). The bacterial co-abundance groups in the gut displayed more numerous and stronger correlations with circulating metabolites than with cytokines. By integrating these data, we identified that certain bacteria might affect inflammatory cytokines by modulating host metabolites, such as amino acids and fatty acids. A random forest model was constructed based on omics data, and seven serum metabolites significantly associated with cytokines and α-diversity of intestinal microbiota were able to accurately distinguish the cases from the controls with an area under the receiver operating characteristic curve of 0.99. Our results indicated aberrant gut-metabolome-immune network in SCZ and gut microbiota may influence immune responses by regulating host metabolic processes. These findings suggest a mechanism by which microbial-derived metabolites regulated inflammatory cytokines and insights into the diagnosis and treatment of mental disorders from the microbial-immune system in the future.

Microporous carbon in the selective electro-oxidation of molecular biomarkers: uric acid, ascorbic acid, and dopamine

Herein, we demonstrate the superior electrocatalytic activities of microporous carbon in the oxidation of three molecular biomarkers, ascorbic acid (AA), dopamine (DA), and uric acid (UA), which are co-present in biological fluids.

Serum metabolic signatures of schizophrenia patients complicated with hepatitis B virus infection: A 1H NMR-based metabolomics study

INTRODUCTION

Schizophrenia (SZ) is a severe chronic mental disorder with increased risk of hepatitis B virus (HBV) infection, which is incurable currently and induces various negative emotions and psychological pressures in patients to exacerbate mental disorders. To facilitate the therapeutic design for SZ patients complicated with HBV infection (SZ + HBV), it is helpful to first elucidate the metabolic perturbations in SZ + HBV patients.

METHODS

In this study, metabolic profiles of the serum samples from four groups of participants comprising healthy controls (HC, n = 72), HBV infection (n = 52), SZ patients (n = 37), and SZ + HBV (n = 41) patients were investigated using a high-resolution ¹H NMR-based metabolomics approach.

RESULTS AND DISCUSSION

Distinguishable metabolic profiles were found in the four groups. In comparison with HC, HBV infection induced increased levels of citrate and succinate to perturbate the tricarboxylic acid cycle and succinate-related pathways. Similar to SZ cases, SZ + HBV patients exhibited decreased glucose but increased citrate, pyruvate, and lactate, suggesting the occurrence of disturbance in glucose metabolism. Moreover, in comparison with HC, several serum amino acid levels in SZ + HBV patients were significantly altered. Our findings suggest that Warburg effect, energy metabolism disorders, neurotransmitter metabolism abnormalities, mitochondrial dysfunction and several disturbed pathways in relation to tyrosine and choline appear to play specific and central roles in the pathophysiology of SZ + HBV. Apart from replicating metabolic alterations induced by SZ and HBV separately (e.g., in energy metabolism and Warburg effect), the specific metabolic abnormalities in the SZ + HBV group (e.g., several tyrosine- and choline-related pathways) highlighted the existence of a synergistic action between SZ and HBV pathologies. Current study revealed the metabolic alterations specific to the interaction between SZ and HBV pathologies, and may open important perspectives for designing precise therapies for SZ + HBV patients beyond the simple combination of two individual treatments.

Searching for biomarkers in schizophrenia and psychosis: Case-control study using capillary electrophoresis and liquid chromatography time-of-flight mass spectrometry and systematic review for biofluid metabolites

Metabolomics has been attracting attention in recent years as an objective method for diagnosing schizophrenia. In this study, we analyzed 378 metabolites in the serum of schizophrenia patients using capillary electrophoresis‐ and liquid chromatography‐time‐of‐flight mass spectrometry. Using multivariate analysis with the orthogonal partial least squares method, we observed significantly higher levels of alanine, glutamate, lactic acid, ornithine, and serine and significantly lower levels of urea, in patients with chronic schizophrenia compared to healthy controls. Additionally, levels of fatty acids (15:0), (17:0), and (19:1), cis‐11‐eicosenoic acid, and thyroxine were significantly higher in patients with acute psychosis than in those in remission. Moreover, we conducted a systematic review of comprehensive metabolomics studies on schizophrenia over the last 20 years and observed consistent trends of increase in some metabolites such as glutamate and glucose, and decrease in citrate in schizophrenia patients across several studies. Hence, we provide substantial evidence for metabolic biomarkers in schizophrenia patients through our metabolomics study.

In this study, we analyzed 378 metabolites in the serum of schizophrenia patients using CE and LC‐TOFMS. With a systematic review, here we provide substantial evidence for metabolic biomarkers in schizophrenia patients through our metabolomics study.

Targeted metabolomics analysis of serum amino acid profiles in patients with Moyamoya disease

Amino acids are one of the main metabolites in the body, and provide energy for the body and brain. The purpose of this study is to provide a profile of amino acid changes in the serum of patients with Moyamoya disease (MMD) and identify potential disease biomarkers. In this paper, we quantitatively determined the serum amino acid metabolic profiles of 43 MMD patients and 42 healthy controls (HCs). T test, multivariate statistical analysis, and receiver operating characteristic (ROC) curve analysis were used to identify candidate markers. Thirty-nine amino acids were quantified, and 12 amino acid levels differed significantly between the MMD patients and HCs. Moreover, based on ROC curve analysis, four amino acid (L-methionine, L-glutamic acid, β-alanine and o-phosphoserine) biomarkers showed high sensitivity and specificity (AUC > 0.90), and showed the best sensitivity and specificity in MetaboAnalyst 5.0 using binary logistic regression analysis. We have provided serum amino acid metabolic profiles of MMD patients, and identified four potential biomarkers which may both provide clinicians with an objective diagnostic method for early detection of MMD and further our understanding of MMD pathogenesis.

Profiling Tryptophan Catabolites of Human Gut Microbiota and Acute-Phase Protein Levels in Neonatal Dried Blood Specimens

National screening programs use dried blood specimens to detect metabolic disorders or aberrant protein functions that are not clinically evident in the neonatal period. Similarly, gut microbiota metabolites and immunological acute-phase proteins may reveal latent immune aberrations. Microbial metabolites interact with xenobiotic receptors (i.e., aryl hydrocarbon and pregnane-X) to maintain gastrointestinal tissue health, supported by acute-phase proteins, functioning as sensors of microbial immunomodulation and homeostasis. The delivery (vaginal or cesarean section) shapes the microbial colonization, which substantially modulates both the immune system’s response and mucosal homeostasis. This study profiled microbial metabolites of the kynurenine and tryptophan pathway and acute-phase proteins in 134 neonatal dried blood specimens. We newly established neonatal blood levels of microbial xenobiotic receptors ligands (i.e., indole-3-aldehyde, indole-3-butyric acid, and indole-3-acetamide) on the second day of life. Furthermore, we observed diverse microbial metabolic profiles in neonates born vaginally and via cesarean section, potentially due to microbial immunomodulatory influence. In summary, these findings suggest the supportive role of human gut microbiota in developing and maintaining immune system homeostasis.

Metabolomic alteration induced by psychotropic drugs: Short-term metabolite profile as a predictor of weight gain evolution

Psychotropic drugs can induce strong metabolic adverse effects, potentially increasing morbidity and/or mortality of patients. Metabolomic profiling, by studying the levels of numerous metabolic intermediates and products in the blood, allows a more detailed examination of metabolism dysfunctions. We aimed to identify blood metabolomic markers associated with weight gain in psychiatric patients. Sixty-two patients starting a treatment known to induce weight gain were recruited. Two hundred and six selected metabolites implicated in various pathways were analyzed in plasma, at baseline and after 1 month of treatment. Additionally, 15 metabolites of the kynurenine pathway were quantified. This latter analysis was repeated in a confirmatory cohort of 24 patients. Among the 206 metabolites, a plasma metabolomic fingerprint after 1 month of treatment embedded 19 compounds from different chemical classes (amino acids, acylcarnitines, carboxylic acids, catecholamines, nucleosides, pyridine, and tetrapyrrole) potentially involved in metabolic disruption and inflammation processes. The predictive potential of such early metabolite changes on 3 months of weight evolution was then explored using a linear mixed-effects model. Of these 19 metabolites, short-term modifications of kynurenine, hexanoylcarnitine, and biliverdin, as well as kynurenine/tryptophan ratio at 1 month, were associated with 3 months weight evolution. Alterations of the kynurenine pathway were confirmed by quantification, in both exploratory and confirmatory cohorts. Our metabolomic study suggests a specific metabolic dysregulation after 1 month of treatment with psychotropic drugs known to induce weight gain. The identified metabolomic signature could contribute in the future to the prediction of weight gain in patients treated with psychotropic drugs.

Endophytic Bacterial Communities of Ginkgo biloba Leaves During Leaf Developmental Period

Plant-specialized secondary metabolites have ecological functions in mediating interactions between plants and their entophytes. In this study, high-throughput gene sequencing was used to analyze the composition and abundance of bacteria from Ginkgo leaves at five different sampling times. The results indicated that the bacterial community structure varied during leaf developmental stage. Bacterial diversity was observed to be the highest at T2 stage and the lowest at T1 stage. Proteobacteria, Firmicutes, Actinobacteria, Chloroflexi, Cyanobacteria, and Bacteroidetes were found as the dominant phyla. The major genera also showed consistency across sampling times, but there was a significant variation in their abundance, such as Bacillus, Lysinibacillus, and Staphylococcus. Significant correlations were observed between endophytic bacteria and flavonoids. Especially, Staphylococcus showed a significant positive correlation with quercetin, and changes in the abundance of Staphylococcus also showed a strong correlation with flavonoid content. In order to determine the effect of flavonoids on endophytic bacteria of Ginkgo leaves, an extracorporeal culture of related strains (a strain of Staphylococcus and a strain of Deinococcus) was performed, and it was found that the effect of flavonoids on them remained consistent. The predicted result of Tax4Fun2 revealed that flavonoids might lead to a lower abundance of endophytic microorganisms, which further proved the correlation between bacterial communities and flavonoids. This study provided the first insight into the bacterial community composition during the development of Ginkgo leaves and the correlation between the endophytic bacteria and flavonoids.

Metabolomics-based understanding of the olanzapine-induced weight gain in female first-episode drug-naïve patients with schizophrenia

Previous studies have demonstrated that patients with schizophrenia (SZ) have greater rate of metabolic disorder as compared with the control population, which likely be the consequence of use of atypical antipsychotics. Olanzapine is a widely used antipsychotic, which increases the weight of SZ patients. However, the underlying mechanism remains poorly understood. Here we report the metabolomics-based understanding of the weight gain induced by olanzapine. 57 first-episode drug-naïve patients (FEDN) were recruited, of whom 27 patients completed a 4-week clinical trial. We then profiled the metabolomes of their plasma with the LC-MS-based nontargeted metabolomics approach at the baseline and after olanzapine monotherapy for 4 weeks. We observed that the plasma of the olanzapine-treated patient had significantly higher lysophosphatidylcholine (LysoPC), lysophosphatidylethanolamine (LysoPE) and lower carnitine as compared with that of the baseline plasma samples. Moreover, regression analyses indicated that the change of LysoPC(14:0) level was an independent contributor to the olanzapine-induced weight gain. Our study suggests that the metabolomics-based approach may facilitate the identification of biomarkers associated with the metabolic disorder causing by antipsychotic in schizophrenia patients.

A system biology approach based on metabolic biomarkers and protein-protein interactions for identifying pathways underlying schizophrenia and bipolar disorder

Mental disorders (MDs), including schizophrenia (SCZ) and bipolar disorder (BD), have attracted special attention from scientists due to their high prevalence and significantly debilitating clinical features. The diagnosis of MDs is still essentially based on clinical interviews, and intensive efforts to introduce biochemical based diagnostic methods have faced several difficulties for implementation in clinics, due to the complexity and still limited knowledge in MDs. In this context, aiming for improving the knowledge in etiology and pathophysiology, many authors have reported several alterations in metabolites in MDs and other brain diseases. After potentially fishing all metabolite biomarkers reported up to now for SCZ and BD, we investigated here the proteins related to these metabolites in order to construct a protein-protein interaction (PPI) network associated with these diseases. We determined the statistically significant clusters in this PPI network and, based on these clusters, we identified 28 significant pathways for SCZ and BDs that essentially compose three groups representing three major systems, namely stress response, energy and neuron systems. By characterizing new pathways with potential to innovate the diagnosis and treatment of psychiatric diseases, the present data may also contribute to the proposal of new intervention for the treatment of still unmet aspects in MDs.

A potential biomarker for treatment stratification in psychosis: evaluation of an [18F] FDOPA PET imaging approach

[¹⁸F]FDOPA PET imaging has shown dopaminergic function indexed as K_i^cer differs between antipsychotic treatment responders and non-responders. However, the theragnostic potential of this biomarker to identify non-responders has yet to be evaluated. In view of this, we aimed to evaluate this as a theragnostic test using linear and non-linear machine-learning (i.e., Bernoulli, support vector, random forest and Gaussian processes) analyses and to develop and evaluate a simplified approach, standardised uptake value ratio (SUVRc). Both [¹⁸F]FDOPA PET approaches had good test-rest reproducibility across striatal regions (K_i^cer ICC: 0.68-0.94, SUVRc ICC: 0.76-0.91). Both our linear and non-linear classification models showed good predictive power to distinguish responders from non-responders (receiver operating curve area under the curve for region-of-interest approach: K_i^cer = 0.80, SUVRc = 0.79; for voxel-wise approach using a linear support vector machine: 0.88) and similar sensitivity for identifying treatment non-responders with 100% specificity (K_i^cer: ~50%, SUVRc: 40-60%). Although the findings were replicated in two independent datasets, given the total sample size (n = 84) and single setting, they warrant testing in other samples and settings. Preliminary economic analysis of [¹⁸F]FDOPA PET to fast-track treatment-resistant patients with schizophrenia to clozapine indicated a potential healthcare cost saving of ~£3400 (equivalent to $4232 USD) per patient. These findings indicate [¹⁸F]FDOPA PET dopamine imaging has potential as biomarker to guide treatment choice.

Design of Multi-Shelled Hollow Cr2 O3 Spheres for Metabolic Fingerprinting

Schizophrenia (SZ) detection enables effective treatment to improve the clinical outcome, but objective and reliable SZ diagnostics are still limited. An ideal diagnosis of SZ suited for robust clinical screening must address detection throughput, low invasiveness, and diagnosis accuracy. Herein, we built a multi-shelled hollow Cr₂ O₃ spheres (MHCSs) assisted laser desorption/ionization mass spectrometry (LDI MS) platform for the direct metabolic profiling of biofluids towards SZ diagnostics. The MHCSs displayed strong light absorption for enhanced ionization and microscale surface roughness with stability for the effective LDI of metabolites. We profiled urine and serum metabolites (≈1 μL) with the enhanced LDI efficacy in seconds. We discriminated SZ patients (SZs) from healthy controls (HCs) with the highest area under the curve (AUC) value of 1.000 for the blind test. We identified four compounds with optimal diagnostic power as a simplified metabolite panel for SZ and demonstrated the metabolite quantification for clinic use. Our approach accelerates the growth of new platforms toward a precision diagnosis in the near future.

UPLC-Q-TOF/MS based fecal metabolomics reveals the potential anti-diabetic effect of Xiexin Decoction on T2DM rats

Xiexin Decoction (XXD), a traditional Chinese medicine prescription composed of Rhei rhizome (RR), Scutellaria radix (SR) and Coptidis rhizome (CR), has been used to cure diabetes in clinical practices for thousands of years, but its mechanism is not clear. Our previous study indicated that XXD could significantly ameliorate the symptom of type 2 diabetes mellitus (T2DM) rats by shifting the composition of gut microbiota. However, the effect of XXD on the metabolic activity of gut microbiota is not clarified. In this study, the underlying mechanism of XXD on the amelioration of T2DM was explored by fecal metabolic profiling analysis based on ultra performance liquid chromatography coupled with quadrupole time-of-fight mass spectrometry (UPLC-Q-TOF/MS). The disordered metabolic profiles in T2DM rats were notably improved by XXD. Ten potential biomarkers, which were mainly involved in arachidonic acid metabolism, amino acid metabolism, bile acid metabolism, glycolysis and gluconeogenesis, were identified. Furthermore, these metabolites were closely related to SCFAs-producing and anti-inflammatory gut microflora. After XXD intervention, these biomarkers restored to the normal level at some extent. This study not only revealed potential biomarkers and related pathways in T2DM rats affected by XXD, but also provided a novel insight to uncover how traditional herb medicines worked from fecal metabolomics.

Inflammation and JNK's Role in Niacin-GPR109A Diminished Flushed Effect in Microglial and Neuronal Cells With Relevance to Schizophrenia

Schizophrenia is a neuropsychiatric illness with no single definitive aetiology, making its treatment difficult. Antipsychotics are not fully effective because they treat psychosis rather than the cognitive or negative symptoms. Antipsychotics fail to alleviate symptoms when patients enter the chronic stage of illness. Topical application of niacin showed diminished skin flush in the majority of patients with schizophrenia compared to the general population who showed flushing. The niacin skin flush test is useful for identifying patients with schizophrenia at their ultra-high-risk stage, and understanding this pathology may introduce an effective treatment. This review aims to understand the pathology behind the diminished skin flush response, while linking it back to neurons and microglia. First, it suggests that there are altered proteins in the GPR109A-COX-prostaglandin pathway, inflammatory imbalance, and kinase signalling pathway, c-Jun N-terminal kinase (JNK), which are associated with diminished flush. Second, genes from the GPR109A-COX-prostaglandin pathway were matched against the 128-loci genome wide association study (GWAS) for schizophrenia using GeneCards, suggesting that G-coupled receptor-109A (GPR109A) may have a genetic mutation, resulting in diminished flush. This review also suggests that there may be increased pro-inflammatory mediators in the GPR109A-COX-prostaglandin pathway, which contributes to the diminished flush pathology. Increased levels of pro-inflammatory markers may induce microglial-activated neuronal death. Lastly, this review explores the role of JNK on pro-inflammatory mediators, proteins in the GPR109A-COX-prostaglandin pathway, microglial activation, and neuronal death. Inhibiting JNK may reverse the changes observed in the diminished flush response, which might make it a good therapeutic target.

Associations of C-Reactive Protein, Free Triiodothyronine, Thyroid Stimulating Hormone and Creatinine Levels with Agitation in Patients with Schizophrenia: A Comparative Cross-Sectional Study

PURPOSE

Agitation is prevalent among inpatients with schizophrenia. The aim of this study was to investigate whether biochemical parameters are associated with agitation in schizophrenia.

PATIENTS AND METHODS

Agitation was evaluated by the Positive and Negative Syndrome Scale-Excited Component questionnaire (PANSS-EC). Fasting serum levels of C-reactive protein (CRP), free triiodothyronine (FT3), free thyroxine (FT4), thyroid-stimulating hormone (TSH), uric acid (UA), creatinine, glucose and lipids were measured.

RESULTS

The analysis included 154 inpatients with schizophrenia (71 with agitation, 83 without agitation) and 75 healthy control subjects. Patients with schizophrenia and agitation had higher serum levels of CRP, FT3, FT4 and UA as well as lower levels of serum TSH and creatinine than patients without agitation (all P < 0.05). Multivariate logistic regression analysis indicated that serum CRP (odds ratio [OR] = 1.470, P = 0.001), FT3 (OR = 13.026, P < 0.001), TSH (OR = 0.758, P = 0.033) and creatinine (OR = 0.965, P = 0.004) were significantly associated with agitation in schizophrenia. CRP, FT3, TSH and creatinine achieved an area under the ROC curve of 0.626, 0.728, 0.620 and 0.663 respectively in discriminating schizophrenia with or without agitation.

CONCLUSION

Increased serum CRP and FT3 levels and decreased serum TSH and creatinine levels are independent risk factors for agitation in hospitalized patients with schizophrenia. Inflammation, thyroid hormones and renal function may be involved in the pathogenesis of agitation in schizophrenia.

Lipidomics of the brain, retina, and biofluids: from the biological landscape to potential clinical application in schizophrenia

Schizophrenia is a serious neuropsychiatric disorder, yet a clear pathophysiology has not been identified. To date, neither the objective biomarkers for diagnosis nor specific medications for the treatment of schizophrenia are clinically satisfactory. It is well accepted that lipids are essential to maintain the normal structure and function of neurons in the brain and that abnormalities in neuronal lipids are associated with abnormal neurodevelopment in schizophrenia. However, lipids and lipid-like molecules have been largely unexplored in contrast to proteins and their genes in schizophrenia. Compared with the gene- and protein-centric approaches, lipidomics is a recently emerged and rapidly evolving research field with particular importance for the study of neuropsychiatric disorders such as schizophrenia, in which even subtle aberrant alterations in the lipid composition and concentration of the neurons may disrupt brain functioning. In this review, we aimed to highlight the lipidomics of the brain, retina, and biofluids in both human and animal studies, discuss aberrant lipid alterations in correlation with schizophrenia, and propose future directions from the biological landscape towards potential clinical applications in schizophrenia. Recent studies are in support of the concept that aberrations in some lipid species [e.g. phospholipids, polyunsaturated fatty acids (PUFAs)] lead to structural alterations and, in turn, impairments in the biological function of membrane-bound proteins, the disruption of cell signaling molecule accessibility, and the dysfunction of neurotransmitter systems. In addition, abnormal lipidome alterations in biofluids are linked to schizophrenia, and thus they hold promise in the discovery of biomarkers for the diagnosis of schizophrenia.

Metabolomics approach revealed robust changes in amino acid and biogenic amine signatures in patients with schizophrenia in the early course of the disease

The primary objective of this study was to evaluate how schizophrenia (SCH) spectrum disorders and applied antipsychotic (AP) treatment affect serum level of amino acids (AAs) and biogenic amines (BAs) in the early course of the disorder. We measured 21 different AAs and 10 BAs in a sample of antipsychotic (AP)-naïve first-episode psychosis (FEP) patients (n = 52) at baseline, after 0.6-year as well as after 5.1-year treatment compared to control subjects (CSs, n = 37). Serum levels of metabolites were determined with AbsoluteIDQ p180 kit using flow injection analysis tandem mass spectrometry and liquid chromatography technique. Elevated level of taurine and reduced level of proline and alpha-aminoadipic acid (alpha-AAA) were established as metabolites with significant change in AP-naïve FEP patients compared to CSs. The following 0.6-year treatment restored these alterations. However, further continuous 5.1-year AP treatment changed the metabolic profile substantially. Significantly elevated levels of asparagine, glutamine, methionine, ornithine and taurine, alongside with decreased levels of aspartate, glutamate and alpha-AAA were observed in the patient group compared to CSs. These biomolecule profile alterations provide further insights into the pathophysiology of SCH spectrum disorders and broaden our understanding of the impact of AP treatment in the early stages of the disease.

Metabolic variation in Cistus monspeliensis L. ecotypes correlated to their plant-fungal interactions

The effect of environmental factors on the chemical composition of plants eventually resulting in plant growth regulation is an age-old issue in plant biology. Nowadays, the acceleration in changes in environmental conditions (e.g. global warming) can act as an incentive to investigate their correlation with metabolic changes. In this study, Cistus monspeliensis plants grown on the island of Sardinia (Italy) were used to explore the geographical-mediated metabolic variation and its repercussion on plant-fungus interactions. Samples of different ecotypes of C. monspeliensis were collected and chemically profiled by ¹H NMR and HPTLC-based metabolomics and the relationship between the variations of biological activity was examined by multivariate data analysis. The ecotypes, collected from different geographical zones and altitudes, exhibited clearly distinguishable chemical profiles, particularly in their terpene and phenolic contents. In particular, multivariate data analysis revealed several diterpenes of the labdane and clerodane series among the terpenes and methoxyflavonoids to be responsible for the differentiation. The antifungal activity of the plants was used to explore the correlation between chemical variation and biological activity. Results showed that there was a strong correlation between the metabolic profiles and the antifungal activity, revealing terpenes and methoxylated flavonoids as the main involved metabolites. This demonstrated that environmental factors can influence the chemical variation of plant ecotypes, resulting in the generation of chemotypes that are potentially adapted to their niche conditions including the plant-fungal interactions.

Influence of Geographical Location on the Metabolic Production of Giant Barrel Sponges (Xestospongia spp.) Revealed by Metabolomics Tools

Despite their high therapeutic potential, only a limited number of approved drugs originate from marine natural products. A possible reason for this is their broad metabolic variability related to the environment, which can cause reproducibility issues. Consequently, a further understanding of environmental factors influencing the production of metabolites is required. Giant barrel sponges, Xestospongia spp., are a source of many new compounds and are found in a broad geographical range. In this study, the relationship between the metabolome and the geographical location of sponges within the genus Xestospongia spp. was investigated. One hundred and thirty-nine specimens of giant barrel sponges (Xestospongia spp.) collected in four locations, Martinique, Curaçao, Taiwan, and Tanzania, were studied using a multiplatform metabolomics methodology (nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry). A clear grouping of the collected samples according to their location was shown. Metabolomics analysis revealed that sterols and various fatty acids, including polyoxygenated and brominated derivatives, were related to the differences in locations. To explore the relationship between observed metabolic changes and their bioactivity, antibacterial activity was assessed against Escherichia coli and Staphylococcus aureus. The activity was found to correlate with brominated fatty acids. These were isolated and identified as (9E,17E)-18-bromooctadeca-9,17-dien-5,7,15-triynoic acid (1), xestospongic acid (2), (7E,13E,15Z)-14,16-dibromohexadeca-7,13,15-trien-5-ynoic acid (3), and two previously unreported compounds.

Metabolomic Profiling Revealed Potential Biomarkers in Patients With Moyamoya Disease

Metabolomics is increasingly used to observe metabolic patterns and disease-specific metabolic biomarkers. However, serum metabolite analysis of moyamoya disease (MMD) is rarely reported. We investigated serum metabolites in MMD and compared them with those of healthy controls (HCs) using a non-targeted gas chromatography-mass spectrometry (GC-MS) approach to identify metabolic biomarkers associated with MMD. Forty-one patients with MMD diagnosed by cerebral angiography and 58 HCs were recruited for our study. Comparative analyses (univariate, multivariate, correlation, heatmaps, receiver operating characteristi curves) were performed between MMD patients and HCs. Twenty-five discriminating serum metabolic biomarkers between MMD patients and HCs were identified. Compared with HCs, MMD patients had higher levels of phenol, 2-hydroxybutyric acid, L-isoleucine, L-serine, glycerol, pelargonic acid, L-methionine, myristic acid, pyroglutamic acid, palmitic acid, palmitoleic acid, stearic acid, octadecanamide, monoglyceride (MG) (16:0/0:0/0:0), and MG (0:0/18:0/0:0), and lower levels of L-alanine, L-valine, urea, succinic acid, L-phenylalanine, L-threonine, L-tyrosine, edetic acid, and oleamide. These metabolic biomarkers are involved in several pathways and are closely associated with the metabolism of amino acids, lipids, carbohydrates, and carbohydrate translation. A GC-MS-based metabolomics approach could be useful in the clinical diagnosis of MMD. The identified biomarkers may be helpful to develop an objective diagnostic method for MMD and improve our understanding of MMD pathogenesis.

Overview of Brain-to-Gut Axis Exposed to Chronic CNS Bacterial Infection(s) and a Predictive Urinary Metabolic Profile of a Brain Infected by Mycobacterium tuberculosis

A new paradigm in neuroscience has recently emerged - the brain-gut axis (BGA). The contemporary focus in this paradigm has been gut → brain ("bottom-up"), in which the gut-microbiome, and its perturbations, affects one's psychological state-of-mind and behavior, and is pivotal in neurodegenerative disorders. The emerging brain → gut ("top-down") concept, the subject of this review, proposes that dysfunctional brain health can alter the gut-microbiome. Feedback of this alternative bidirectional highway subsequently aggravates the neurological pathology. This paradigm shift, however, focuses upon non-communicable neurological diseases (progressive neuroinflammation). What of infectious diseases, in which pathogenic bacteria penetrate the blood-brain barrier and interact with the brain, and what is this effect on the BGA in bacterial infection(s) that cause chronic neuroinflammation? Persistent immune activity in the CNS due to chronic neuroinflammation can lead to irreversible neurodegeneration and neuronal death. The properties of cerebrospinal fluid (CSF), such as immunological markers, are used to diagnose brain disorders. But what of metabolic markers for such purposes? If a BGA exists, then chronic CNS bacterial infection(s) should theoretically be reflected in the urine. The premise here is that chronic CNS bacterial infection(s) will affect the gut-microbiome and that perturbed metabolism in both the CNS and gut will release metabolites into the blood that are filtered (kidneys) and excreted in the urine. Here we assess the literature on the effects of chronic neuroinflammatory diseases on the gut-microbiome caused by bacterial infection(s) of the CNS, in the context of information attained via metabolomics-based studies of urine. Furthermore, we take a severe chronic neuroinflammatory infectious disease - tuberculous meningitis (TBM), caused by Mycobacterium tuberculosis, and examine three previously validated CSF immunological biomarkers - vascular endothelial growth factor, interferon-gamma and myeloperoxidase - in terms of the expected changes in normal brain metabolism. We then model the downstream metabolic effects expected, predicting pivotal altered metabolic pathways that would be reflected in the urinary profiles of TBM subjects. Our cascading metabolic model should be adjustable to account for other types of CNS bacterial infection(s) associated with chronic neuroinflammation, typically prevalent, and difficult to distinguish from TBM, in the resource-constrained settings of poor communities.

Dysregulation of amino acids and lipids metabolism in schizophrenia with violence

BACKGROUND

Many studies have related biochemical characteristics to violence and have reported schizophrenia could elevated the risk of violent behaviour. However, the metabolic characteristics of schizophrenia patients with violence (V.SC) are unclear.

METHODS

To explore the metabolic characteristics of schizophrenia with violence and to identify potential biomarkers, untargeted metabolomics was performed by using gas chromatography time-of-flight mass spectrometry to analyse the plasma metabolites of fifty-three V.SC and twenty-four schizophrenia patients without violence (NV.SC). Multivariate and univariate analyses were performed to identify differential metabolites and biomarkers. Violence was assessed by the MacArthur Violence Assessment Study method. Psychiatric symptoms were assessed by the Positive and Negative Syndrome Scale.

RESULTS

Multivariate analysis was unable to distinguish V.SC from NV.SC. Glycerolipid metabolism and phenylalanine, tyrosine and tryptophan biosynthesis were the differential metabolic pathways between V.SC and NV.SC. We confirmed ten metabolites and five metabolites as metabolic biomarkers of V.SC by random forest and support vector machine analysis, respectively. The biomarker panel, including the ratio of L-asparagine to L-aspartic acid, vanillylmandelic acid and glutaric acid, yielded an area under the receiver operating characteristic curve of 0.808.

CONCLUSIONS

This study gives a holistic view of the metabolic phenotype of schizophrenia with violence which is characterized by the dysregulation of lipids and amino acids. These results might provide information for the aetiological understanding and management of violence in schizophrenia; however, this is a preliminary metabolomics study about schizophrenia with violence, which needs to be repeated in future studies.

Plasma Metabolite Profiles in First Episode Psychosis: Exploring Symptoms Heterogeneity/Severity in Schizophrenia and Bipolar Disorder Cohorts

INTRODUCTION

The first symptoms of psychosis are frequently shared amongst several neuropsychiatry disorders, which makes the differentiation by clinical diagnosis challenging. Early recognition of symptoms is important in the management of psychosis. Therefore, the implementation of molecular biomarkers will be crucial for transforming the currently used diagnostic and therapeutic approach, improving insights into the underlying biological processes and clinical management.

OBJECTIVES

To define a set of metabolites that supports diagnosis or prognosis of schizophrenia (SCZ) and bipolar disorder (BD) at first onset psychosis.

METHODS

Plasma samples from 55 drug-naïve patients, 28 SCZ and 27 BD, and 42 healthy controls (HC). All participants underwent a seminaturalistic treatment regimen, clinically evaluated on a weekly basis until achieving clinical remission. All clinical or sociodemographic aspects considered for this study were equivalent between the groups at first-onset psychosis time point. The plasma samples were analyzed by untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) using reversed-phase and hydrophilic interaction chromatography. The acquired molecular features were analyzed with MetaboAnalyst.

RESULTS

We identified two patient groups with different metabolite profiles. Both groups are composed of SCZ and BD patients. We found differences between these two groups regarding general symptoms of PANSS score after remission (p = 0.008), and the improvement of general symptoms (delta of the score at remission minus the baseline) (-0.50 vs. -0.33, p = 0.019).

CONCLUSION

Our results suggest that plasma metabolite profiles cluster clinical remission phenotypes based on PANSS general psychopathology scores.

Lycium barbarum L. leaves ameliorate type 2 diabetes in rats by modulating metabolic profiles and gut microbiota composition

The leaf of Lycium barbarum L. (LLB) has been widely used as a tea, vegetable, and herb in China and Southeast Asia for centuries; this is because of the hypoglycemic effect it has, but the mechanism behind this effect is still unclear. In this study, a type 2 diabetic mellitus (T2DM) rat model, induced by a high-fat diet combined with low-dose streptozotocin (STZ) injections, was adopted. The biochemical index was determined and the histopathological and metabolomics analyses of serum and urine and 16S rDNA sequencing of the gut microbiota were performed. We evaluated the hypoglycemic effects and the mechanism of action of the water extract from LLB, which contained neochlorogenic acid, chlorogenic acid, caffeic acid, and rutin (up to 6.06%). The relationships between biochemical indexes, serum and urine metabolites, and gut microbiota were analyzed. The results showed that the LLB extract could noticeably modulate the levels of blood glucose and lipids in diabetic rats as well as repair injuries in livers, kidneys and pancreas. The changes in serum and urine metabolites caused by T2DM were reversed after the administration of LLB; these changes were found to mainly be correlated with the following pathways: nicotinate and nicotinamide metabolism, arachidonic acid metabolism, and purine metabolism. Sequencing of the 16S rDNA from fecal samples showed that the LLB extract could reverse the gut microbiota dysbiosis that T2DM had induced. Therefore, we conclude that T2DM, which altered the metabolic profiles and gut microbiota, could be alleviated effectively using the LLB extract.

Glucose metabolism dysregulation at the onset of mental illness is not limited to first episode psychosis: A systematic review and meta-analysis

AIM

To compare the differences of glucose metabolism outcomes between treatment-naïve, patients with first episode psychosis (FEP) and mood disorders.

METHODS

We conducted a systematic review and meta-analysis of glucose intolerance in treatment-naïve, first episode patients with severe mental illnesses (SMIs).

RESULTS

We identified 31 eligible studies. Compared to healthy controls, FEP group have higher insulin and insulin resistance levels, and both groups have higher glucose tolerance test results. No significant differences were found in glucose metabolism outcomes between FEP and mood disorder groups.

CONCLUSIONS

Our results highlight impaired glucose metabolism at the onset of SMIs, suggesting both patients with psychosis and mood disorders are high-risk groups for diabetes development.

Integrated Lipidomics and Proteomics Point to Early Blood-Based Changes in Childhood Preceding Later Development of Psychotic Experiences: Evidence From the Avon Longitudinal Study of Parents and Children

BACKGROUND

The identification of early biomarkers of psychotic experiences (PEs) is of interest because early diagnosis and treatment of those at risk of future disorder is associated with improved outcomes. The current study investigated early lipidomic and coagulation pathway protein signatures of later PEs in subjects from the Avon Longitudinal Study of Parents and Children cohort.

METHODS

Plasma of 115 children (12 years of age) who were first identified as experiencing PEs at 18 years of age (48 cases and 67 controls) were assessed through integrated and targeted lipidomics and semitargeted proteomics approaches. We assessed the lipids, lysophosphatidylcholines (n = 11) and phosphatidylcholines (n = 61), and the protein members of the coagulation pathway (n = 22) and integrated these data with complement pathway protein data already available on these subjects.

RESULTS

Twelve phosphatidylcholines, four lysophosphatidylcholines, and the coagulation protein plasminogen were altered between the control and PEs groups after correction for multiple comparisons. Lipidomic and proteomic datasets were integrated into a multivariate network displaying a strong relationship between most lipids that were significantly associated with PEs and plasminogen. Finally, an unsupervised clustering approach identified four different clusters, with one of the clusters presenting the highest case-control ratio (p < .01) and associated with a higher concentration of smaller low-density lipoprotein cholesterol particles.

CONCLUSIONS

Our findings indicate that the lipidome and proteome of subjects who report PEs at 18 years of age are already altered at 12 years of age, indicating that metabolic dysregulation may contribute to an early vulnerability to PEs and suggesting crosstalk between these lysophosphatidylcholines, phosphatidylcholines, and coagulation and complement proteins.

Pharmacotherapy of schizophrenia: toward a metabolomic-based approach

Approximately 20%-30% of schizophrenia patients are resistant to current standard pharmacotherapies. Recent schizophrenia research aims to identify specific pathophysiological abnormalities and novel targets in the disease, with the goals of identifying at-risk individuals, facilitating diagnosis, prompting early and personalized interventions, and helping predict response to treatment. Metabolomics involves the systematic study of the profile of biochemical alterations early in the course of a given disorder. Major aspects of the schizophrenia metabolome have been characterized, uncovering potential selective biomarkers for the disease that may change how the disorder is diagnosed, and how patients are stratified and treated. This review focuses on the most common metabolomic fingerprints of the different pathways involved in the pathophysiology of schizophrenia, and the potential development of novel metabolomic-related pharmacotherapies for improved treatment of schizophrenia and other related idiopathic psychotic disorders.

Alterations in body mass index and waist-to-hip ratio in never and minimally treated patients with psychosis: A systematic review and meta-analysis

BACKGROUND

Obesity is up to 4 times higher in patients with schizophrenia than in the general population. However, the link between obesity and schizophrenia in the absence of antipsychotic use is unclear. Therefore, we aimed to examine differences in obesity measures (body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR)) in antipsychotic-naive and minimally treated (up to 2 weeks of lifetime antipsychotic exposure) patients with psychosis compared to healthy controls (HCs).

METHODS

A systematic search was conducted using Ovid Medline®, PsycINFO, and Embase. Standardized mean differences (SMDs) in obesity measures between groups were calculated. Separate sensitivity analyses were performed to examine the effects of age, sex, and ethnicity; antipsychotic exposure; and schizophrenia-related psychosis on SMDs.

RESULTS

A total of 23 studies were included in the meta-analysis (BMI = 23, WC = 9, WHR = 5). BMI was lower (SMD = -0.19, 95% CI = -0.34 to -0.05, P = 0.009) and WHR was elevated (SMD = 0.34, 95% CI = 0.14 to 0.55, P = 0.001) in patients. These differences remained after analyses were restricted to patients matched with HCs for age, sex, and ethnicity; to antipsychotic-naive patients; and to patients with schizophrenia-related diagnoses.

CONCLUSIONS

Differences in BMI and WHR were observed in never and minimally treated patients with psychosis compared to HCs. Future research is warranted to understand these alterations in the context of body fat biomarkers and neuropathology of psychiatric disorders, independent of the effects of antipsychotics.

Enhanced Molecular Appreciation of Psychiatric Disorders Through High-Dimensionality Data Acquisition and Analytics

The initial diagnosis, molecular investigation, treatment, and posttreatment care of major psychiatric disorders (schizophrenia and bipolar depression) are all still significantly hindered by the current inability to define these disorders in an explicit molecular signaling manner. High-dimensionality data analytics, using large datastreams from transcriptomic, proteomic, or metabolomic investigations, will likely advance both the appreciation of the molecular nature of major psychiatric disorders and simultaneously enhance our ability to more efficiently diagnose and treat these debilitating conditions. High-dimensionality data analysis in psychiatric research has been heterogeneous in aims and methods and limited by insufficient sample sizes, poorly defined case definitions, methodological inhomogeneity, and confounding results. All of these issues combine to constrain the conclusions that can be extracted from them. Here, we discuss possibilities for overcoming methodological challenges through the implementation of transcriptomic, proteomic, or metabolomics signatures in psychiatric diagnosis and offer an outlook for future investigations. To fulfill the promise of intelligent high-dimensionality data-based differential diagnosis in mental disease diagnosis and treatment, future research will need large, well-defined cohorts in combination with state-of-the-art technologies.

A prebiotic intervention study in children with autism spectrum disorders (ASDs)

BACKGROUND

Different dietary approaches, such as gluten and casein free diets, or the use of probiotics and prebiotics have been suggested in autistic spectrum disorders in order to reduce gastrointestinal (GI) disturbances. GI symptoms are of particular interest in this population due to prevalence and correlation with the severity of behavioural traits. Nowadays, there is lack of strong evidence about the effect of dietary interventions on these problems, particularly prebiotics. Therefore, we assessed the impact of exclusion diets and a 6-week Bimuno® galactooligosaccharide (B-GOS®) prebiotic intervention in 30 autistic children.

RESULTS

The results showed that children on exclusion diets reported significantly lower scores of abdominal pain and bowel movement, as well as lower abundance of Bifidobacterium spp. and Veillonellaceae family, but higher presence of Faecalibacterium prausnitzii and Bacteroides spp. In addition, significant correlations were found between bacterial populations and faecal amino acids in this group, compared to children following an unrestricted diet. Following B-GOS® intervention, we observed improvements in anti-social behaviour, significant increase of Lachnospiraceae family, and significant changes in faecal and urine metabolites.

CONCLUSIONS

To our knowledge, this is the first study where the effect of exclusion diets and prebiotics has been evaluated in autism, showing potential beneficial effects. A combined dietary approach resulted in significant changes in gut microbiota composition and metabolism suggesting that multiple interventions might be more relevant for the improvement of these aspects as well as psychological traits.

TRIAL REGISTRATION

NCT02720900 ; registered in November 2015.

A systematic review of metabolite biomarkers of schizophrenia

Current diagnosis of schizophrenia relies exclusively on the potentially subjective interpretation of clinical symptoms and social functioning as more objective biological measurement and medical diagnostic tests are not presently available. The use of metabolomics in the discovery of disease biomarkers has grown in recent years. Metabolomic methods could aid in the discovery of diagnostic biomarkers of schizophrenia. This systematic review focuses on biofluid metabolites associated with schizophrenia. A systematic search of Web of Science and Ovid Medline databases was conducted and 63 studies investigating metabolite biomarkers of schizophrenia were included. A review of these studies revealed several potential metabolite signatures of schizophrenia including reduced levels of essential polyunsaturated fatty acids (EPUFAs), vitamin E and creatinine; and elevated levels of lipid peroxidation metabolites and glutamate. Further research is needed to validate these biomarkers and would benefit from large cohort studies and more homogeneous and well-defined subject groups.