Metabolomic profiling of schizophrenia patients at risk for metabolic syndrome

Differences in metabolic biomarkers in people with schizophrenia who are of Mexican descent compared to non-Hispanic whites

Metabolic dysfunction is highly prevalent and contributes to premature mortality among people with schizophrenia (PwS), especially in Hispanic/Latino/a/x/e PwS, compared to non-Hispanic White (NHW) PwS. This study evaluated the relative contributions of Mexican descent and schizophrenia diagnosis to metabolic biomarker levels. This cross-sectional study included 115 PwS and 102 non-psychiatric comparison (NC) participants - English-speakers aged 26-66 years, 27% Mexican descent, and 52% women across both groups. Assessments included evaluations of BMI, psychopathology, and fasting metabolic biomarkers. We used ANOVA analyses to compare metabolic outcomes between diagnostic and ethnic subgroups, linear regression models to examine associations between Mexican descent and metabolic outcomes, and Spearman's correlations to examine relationships between metabolic outcomes and illness-related variables in PwS. Mexican PwS had higher hemoglobin A1c levels, insulin resistance, and body mass index than NHW PwS. Mexican descent was associated with higher hemoglobin A1c levels, insulin resistance, body mass index, and leptin levels, controlling for age, sex, depression, education, and smoking. Among Mexican PwS, worse negative symptoms were associated with greater insulin resistance. These findings support the possibility of ethnicity-based differences in metabolic dysregulation, though further investigation is warranted to create targeted health interventions for Hispanic PwS.

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.

Risk Assessment of Psychotropic Drugs on Mitochondrial Function Using In Vitro Assays

Mitochondria are potential targets responsible for some drug- and xenobiotic-induced organ toxicities. However, molecular mechanisms of drug-induced mitochondrial toxicities are mostly unknown. Here, multiple in vitro assays were used to investigate the effects of 22 psychotropic drugs on mitochondrial function. The acute extracellular flux assay identified inhibitors of the electron transport chain (ETC), i.e., aripiprazole, phenytoin, and fluoxetine, an uncoupler (reserpine), substrate inhibitors (quetiapine, carbamazepine, buspirone, and tianeptine), and cytotoxic compounds (chlorpromazine and valproic acid) in HepG2 cells. Using permeabilized HepG2 cells revealed minimum effective concentrations of 66.3, 6730, 44.5, and 72.1 µM for the inhibition of complex-I-linked respiration for quetiapine, valproic acid, buspirone, and fluoxetine, respectively. Assessing complex-II-linked respiration in isolated rat liver mitochondria revealed haloperidol is an ETC inhibitor, chlorpromazine is an uncoupler in basal respiration and an ETC inhibitor under uncoupled respiration (IC50 = 135 µM), while olanzapine causes a mild dissipation of the membrane potential at 50 µM. This research elucidates some mechanisms of drug toxicity and provides some insight into their safety profile for clinical drug decisions.

Insulin resistance in Alzheimer's disease: The genetics and metabolomics links

Alzheimer's disease (AD) is a neurodegenerative disease with significant socioeconomic burden worldwide. Although genetics and environmental factors play a role, AD is highly associated with insulin resistance (IR) disorders such as metabolic syndrome (MS), obesity, and type two diabetes mellitus (T2DM). These findings highlight a shared pathogenesis. The use of metabolomics as a downstream systems' biology (omics) approach can help to identify these shared metabolic traits and assist in the early identification of at-risk groups and potentially guide therapy. Targeting the shared AD-IR metabolic trait with lifestyle interventions and pharmacological treatments may offer promising AD therapeutic approach. In this narrative review, we reviewed the literature on the AD-IR pathogenic link, the shared genetics and metabolomics biomarkers between AD and IR disorders, as well as the lifestyle interventions and pharmacological treatments which target this pathogenic link.

Dynamic Changes in Plasma Metabolic Profiles Reveal a Potential Metabolite Panel for Interpretation of Fatal Intoxication by Chlorpromazine or Olanzapine in Mice

Diagnosing the cause of fatal intoxication by antipsychotic agents is an important task in forensic practice. In the 2020 Annual Report of the American Association of Poison Control Centers, among 40 deaths caused by antipsychotics, 21 cases were diagnosed as "probably responsible", thereby indicating that more objective diagnostic tools are needed. We used liquid chromatography-mass spectrometry-based integrated metabolomics analysis to measure changes in metabolic profiles in the plasma of mice that died from fatal intoxication due to chlorpromazine (CPZ) or olanzapine (OLA). These results were used to construct a stable discriminative classification model (DCM) comprising L-acetylcarnitine, succinic acid, and propionylcarnitine between fatal intoxication caused by CPZ/OLA and cervical dislocation (control). Performance evaluation of the classification model in mice that suffered fatal intoxication showed relative specificity for different pharmacodynamic drugs and relative sensitivity in different life states (normal, intoxication, fatal intoxication). A stable level of L-acetylcarnitine and variable levels of succinic acid and propionylcarnitine between fatal-intoxication and intoxication groups revealed procedural perturbations in metabolic pathways related to fatal intoxication by CPZ/OLA. Additional stability studies revealed that decomposition of succinic acid in fatal-intoxication samples (especially in the OLA group) could weaken the prediction performance of the binary-classification model; however, levels of these three potential metabolites measured within 6 days in fresh samples kept at 4 °C revealed a good performance of our model. Our findings suggest that metabolomics analysis can be used to explore metabolic alterations during fatal intoxication due to use of antipsychotic agents and provide evidence for the cause of death.

The tryptophan catabolite or kynurenine pathway in schizophrenia: meta-analysis reveals dissociations between central, serum, and plasma compartments

The tryptophan catabolite (TRYCAT) pathway is implicated in the pathophysiology of schizophrenia (SCZ) since the rate-limiting enzyme indoleamine-dioxygenase (IDO) may be induced by inflammatory and oxidative stress mediators. This systematic review searched PubMed, Web of Science, and Google Scholar for papers published from inception until August 2021 and meta-analyzed the association between SCZ and TRYCATs in the central nervous system (CNS) and peripheral blood. We included 61 studies comprising 2813 patients and 2948 healthy controls. In the CNS we found a significant (p < 0.001) increase in the kynurenine/tryptophan (KYN/TRP) (standardized mean difference, SMD = 0.769, 95% confidence interval, CI: 0.456; 1.082) and kynurenic acid (KA)/KYN + TRP (SMD = 0.697, CI: 0.478-0.917) ratios, KA (SMD = 0.646, CI: 0.422; 0.909) and KYN (SMD = 1.238; CI: 0.590; 1.886), while the 3OH-kynurenine (3HK) + KYN-3-monooxygenase (KMO)/KYN ratio was significantly reduced (SMD = -1.089, CI: -1.682; -0.496). There were significant differences between KYN/TRP, (KYN + KA)/TRP, (3HK + KMO)/KYN, KA, and KYN levels among the CNS and peripheral blood, and among serum and plasma KYN. The only useful peripheral marker of CNS TRYCATs findings was the increased KYN/TRP ratio in serum (SMD = 0.211, CI: 0.056; 0.366, p = 0.007), but not in plasma. There was no significant increase in a neurotoxic composite score based on KYN, 3HK, and picolinic, xanthurenic, and quinolinic acid. SCZ is accompanied by increased IDO activity in the CNS and serum, and reduced KMO activity and a shift towards KA production in the CNS. This CNS TRYCATs profile indicates neuroprotective, negative immunoregulatory and anti-inflammatory effects. Peripheral blood levels of TRYCATs are dissociated from CNS findings except for a modest increase in serum IDO activity.

Blood and Urinary Biomarkers of Antipsychotic-Induced Metabolic Syndrome

Metabolic syndrome (MetS) is a clustering of at least three of the following five medical conditions: abdominal obesity, high blood pressure, high blood sugar, high serum triglycerides, and low serum high-density lipoprotein (HDL). Antipsychotic (AP)-induced MetS (AIMetS) is the most common adverse drug reaction (ADR) of psychiatric pharmacotherapy. Herein, we review the results of studies of blood (serum and plasma) and urinary biomarkers as predictors of AIMetS in patients with schizophrenia (Sch). We reviewed 1440 studies examining 38 blood and 19 urinary metabolic biomarkers, including urinary indicators involved in the development of AIMetS. Among the results, only positive associations were revealed. However, at present, it should be recognized that there is no consensus on the role of any particular urinary biomarker of AIMetS. Evaluation of urinary biomarkers of the development of MetS and AIMetS, as one of the most common concomitant pathological conditions in the treatment of patients with psychiatric disorders, may provide a key to the development of strategies for personalized prevention and treatment of the condition, which is considered a complication of AP therapy for Sch in clinical practice.

Untargeted metabolic analysis in dried blood spots reveals metabolic signature in 22q11.2 deletion syndrome

The 22q11.2 deletion syndrome (22q11.2DS) is characterized by a well-defined microdeletion and is associated with increased risk of neurodevelopmental phenotypes including autism spectrum disorders (ASD) and intellectual impairment. The typically deleted region in 22q11.2DS contains multiple genes with the potential of altering metabolism. Deficits in metabolic processes during early brain development may help explain the increased prevalence of neurodevelopmental phenotypes seen in 22q11.2DS. However, relatively little is known about the metabolic impact of the 22q11.2 deletion, while such insight may lead to increased understanding of the etiology. We performed untargeted metabolic analysis in a large sample of dried blood spots derived from 49 22q11.2DS patients and 87 controls, to identify a metabolic signature for 22q11.2DS. We also examined trait-specific metabolomic patterns within 22q11.2DS patients, focusing on intelligence (intelligence quotient, IQ) and ASD. We used the Boruta algorithm to select metabolites distinguishing patients from controls, patients with ASD from patients without, and patients with an IQ score in the lowest range from patients with an IQ score in the highest range. The relevance of the selected metabolites was visualized with principal component score plots, after which random forest analysis and logistic regression were used to measure predictive performance of the selected metabolites. Analysis yielded a distinct metabolic signature for 22q11.2DS as compared to controls, and trait-specific (IQ and ASD) metabolomic patterns within 22q11.2DS patients. The metabolic characteristics of 22q11.2DS provide insights in biological mechanisms underlying the neurodevelopmental phenotype and may ultimately aid in identifying novel therapeutic targets for patients with developmental disorders.

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.

Plasma Lysophosphatidylcholine and Lysophosphatidylethanolamine Levels Were Associated With the Therapeutic Response to Olanzapine in Female Antipsychotics-naïve First-episode Patients With Schizophrenia

Background: Accumulating studies have shown that the pathophysiology of schizophrenia may be associated with aberrant lysophospolipid metabolism in the early stage of brain development. Recent evidence demonstrates that antipsychotic medication can regulate the phospholipase activity. However, it remains unclear whether lysophospolipid is associated with the therapeutic response to antipsychotic medication in schizophrenia. This study aimed to investigate the influence of olanzapine monotherapy on lysophosphatidylcholine (LPC) and lysophosphatidylethanolamine (LPE) and the association between symptom improvement and changes of LPC and LPE levels during treatment in antipsychotic-naïve first-episode (ANFE) patients.

Materials and Methods: The psychotic symptoms were evaluated by the Positive and Negative Syndrome Scale (PANSS). 25 ANFE patients were treated with olanzapine for 1 mo. The levels of LPC and LPE were determined and psychotic symptoms were assessed at baseline and at 1-mo follow-up.

Results: Relative to baseline, the psychotic symptoms were significantly reduced after olanzapine treatment, except for negative symptoms. Moreover, the levels of most LPC and LPE increased after treatment. Interestingly, increased LPC(18:3) and LPC(20:2) levels were positively associated with the reduction rates of PANSS positive subscore. In addition, baseline levels of LPE(20:5), LPE(18:3) and LPE(22:5) were predictors for the reduction of positive symptoms.

Conclusion: Our study reveals that the levels of lysophospolipid are associated with the improvement of positive symptoms, indicating that LPC may be a potential therapeutic target for olanzapine in schizophrenia. Moreover, baseline LPE levels were predictive biomarkers for the therapeutic response to olanzapine in the early stage of treatment in ANFE patients.

Metabolomic connections between schizophrenia, antipsychotic drugs and metabolic syndrome: A variety of players

BACKGROUND

Diagnosis of schizophrenia lacks of reliable medical diagnostic tests and robust biomarkers applied to clinical practice. Schizophrenic patients undergoing treatment with antipsychotics suffer a reduced life expectancy due to metabolic disarrangements that co-exist with their mental illness and predispose them to develop metabolic syndrome, also exacerbated by medication. Metabolomics is an emerging and potent technology able to accelerate this biomedical research. <P> Aim: This review focus on a detailed vision of the molecular mechanisms involved both in schizophrenia and antipsychotic-induced metabolic syndrome, based on innovative metabolites that consistently change in nascent metabolic syndrome, drug-naïve, first episode psychosis and/or schizophrenic patients compared to healthy subjects. <P> Main lines: Supported by metabolomic approaches, although not exclusively, noteworthy variations are reported mainly through serum samples of patients and controls in several scenes: 1) alterations in fatty acids, inflammatory response indicators, amino acids and biogenic amines, biometals and gut microbiota metabolites (schizophrenia); 2) alterations in metabolites involved in carbohydrate and gut microbiota metabolism, inflammation and oxidative stress (metabolic syndrome), some of them shared with the schizophrenia scene; 3) alterations of cytokines secreted by adipose tissue, phosphatidylcholines, acylcarnitines, Sirtuin 1, orexin-A and changes in microbiota composition (antipsychotic-induced metabolic syndrome). <P> Conclusion: Novel insights into the pathogenesis of schizophrenia and metabolic side-effects associated to its antipsychotic treatment, represent an urgent request for scientifics and clinicians. Leptin, carnitines, adiponectin, insulin or interleukin-6 represent some examples of candidate biomarkers. Cutting-edge technologies like metabolomics have the power of strengthen research for achieving preventive, diagnostic and therapeutical solutions for schizophrenia.

Evaluation of Metabolic Profiles of Patients with Anorexia Nervosa at Inpatient Admission, Short- and Long-Term Weight Regain-Descriptive and Pattern Analysis

Acute anorexia nervosa (AN) constitutes an extreme physiological state. We aimed to detect state related metabolic alterations during inpatient admission and upon short- and long-term weight regain. In addition, we tested the hypothesis that metabolite concentrations adapt to those of healthy controls (HC) after long-term weight regain. Thirty-five female adolescents with AN and 25 female HC were recruited. Based on a targeted approach 187 metabolite concentrations were detected at inpatient admission (T₀), after short-term weight recovery (T₁; half of target-weight) and close to target weight (T₂). Pattern hunter and time course analysis were performed. The highest number of significant differences in metabolite concentrations (N = 32) were observed between HC and T₁. According to the detected main pattern, metabolite concentrations at T₂ became more similar to those of HC. The course of single metabolite concentrations (e.g., glutamic acid) revealed different metabolic subtypes within the study sample. Patients with AN after short-term weight regain are in a greater “metabolic imbalance” than at starvation. After long-term weight regain, patients reach a metabolite profile similar to HC. Our results might be confounded by different metabolic subtypes of patients with AN.

Blood-based kynurenine pathway alterations in schizophrenia spectrum disorders: A meta-analysis

INTRODUCTION

The kynurenine pathway (KP) has been proposed as indirect link between systemic immune responses and clinical symptom development in schizophrenia spectrum disorders (SSD). Empirical evidence for such immune-related KP shifts in SSD has however resulted in divergent findings.

METHODS

We conducted a systematic literature search in PubMed. Thirty papers (total number of patients n = 1506; controls: n = 1432) reported on peripheral concentrations of KP metabolites in SSD patients versus controls. Six KP metabolites were included in a meta-analysis, with secondary analysis of covariate and subgroup effects of patients' symptomatic state, age and duration of illness.

RESULTS

Tryptophan (SMD: -0.30; p = .003) and Xanthurenic Acid (SMD: -0.80; p < .001) were significantly decreased in SSD compared to controls, while Quinolinic Acid (SMD: -0.40; p = .08) and Kynurenic Acid (SMD: -0.39; p = .04) were only significantly decreased in patients with acute or highly symptomatic illness. Finally, in relatively older patient cohorts Kynurenine (SMD: -0.31; p = .02) and Kynurenic Acid (SMD: -0.40; p = .002) were found to be decreased.

CONCLUSION

A partial downregulation of the KP is observed in SSD patients, in particular during acute symptomatic states and in older age, effects that were independent from each other. In contrast, younger and stable or remitted patients display limited to no KP metabolite abnormalities. The current meta-analysis illustrates the dynamic nature of KP abnormalities. It should be noted that all included studies investigated peripheral KP metabolites, which do not necessarily reflect central KP metabolite abnormalities in schizophrenic patients.

Metabolomic Biomarkers in Anxiety Disorders

Anxiety disorders range among the most prevalent psychiatric disorders and belong to the leading disorders in the study of the total global burden of disease. Anxiety disorders are complex conditions, with not fully understood etiological mechanisms. Numerous factors, including psychological, genetic, biological, and chemical factors, are thought to be involved in their etiology. Although the diagnosis of anxiety disorders is constantly evolving, diagnostic manuals rely on symptom lists, not on objective biomarkers and treatment effects are small to moderate. The underlying biological factors that drive anxiety disorders may be better suited to serve as biomarkers for guiding personalized medicine, as they are objective and can be measured externally. Therefore, the incorporation of novel biomarkers into current clinical methods might help to generate a classification system for anxiety disorders that can be linked to the underlying dysfunctional pathways. The study of metabolites (metabolomics) in a large-scale manner shows potential for disease diagnosis, for stratification of patients in a heterogeneous patient population, for monitoring therapeutic efficacy and disease progression, and for defining therapeutic targets. All of these are important properties for anxiety disorders, which is a multifactorial condition not involving a single-gene mutation. This review summarizes recent investigations on metabolomics studies in anxiety disorders.

Association Between SIRT1, Cytokines, and Metabolic Syndrome in Schizophrenia Patients With Olanzapine or Clozapine Monotherapy

Objective: Previous studies consistently showed the interaction between Sirtuin 1 (SIRT1) and immune inflammation is significantly related to metabolic abnormalities, but their role in the pathogenesis of metabolic syndrome caused by second-generation antipsychotics (SGAs) in schizophrenia patients largely remains unknown. Hence, the present study aimed to fill this gap. Methods: A total of 54 schizophrenia patients with olanzapine or clozapine monotherapy [metabolic syndrome (MetS)/non-MetS patients, 27/27] and 67 healthy subjects were recruited in the present study. The Positive and Negative Syndrome Scale was used, and the plasma levels of SIRT1, interleukin 6 (IL-6), IL-8, IL-10, and tumor necrosis factor α (TNF-α) were measured. Results: The results showed that schizophrenia patients treated with olanzapine or clozapine (both MetS and non-MetS groups) had significantly higher plasma levels of IL-6, IL-10, and TNF-α compared to normal controls (all P < 0.05). Moreover, the MetS patients exhibited markedly lower plasma levels of SIRT1 and higher plasma levels of IL-6 than non-MetS patients and normal controls (all P < 0.05). However, there were no significant differences in IL-8 levels between groups. Our correlation analysis showed that SIRT1 was significantly correlated with diastolic blood pressure, triglyceride, and high-density lipoprotein cholesterol in schizophrenia patients. The stepwise logistic regression analysis further identified the IL-6 × SIRT1 (β = -0.463, t = 10.040, P = 0.002) as the influencing factor for the MetS in the patients. Conclusion: Our preliminary findings suggest that SIRT1 interacted with inflammatory cytokines associated with MetS in schizophrenia patients treated with SGA monotherapy.

Excess hydrogen sulfide and polysulfides production underlies a schizophrenia pathophysiology

Mice with the C3H background show greater behavioral propensity for schizophrenia, including lower prepulse inhibition (PPI), than C57BL/6 (B6) mice. To characterize as-yet-unknown pathophysiologies of schizophrenia, we undertook proteomics analysis of the brain in these strains, and detected elevated levels of Mpst, a hydrogen sulfide (H₂ S)/polysulfide-producing enzyme, and greater sulfide deposition in C3H than B6 mice. Mpst-deficient mice exhibited improved PPI with reduced storage sulfide levels, while Mpst-transgenic (Tg) mice showed deteriorated PPI, suggesting that "sulfide stress" may be linked to PPI impairment. Analysis of human samples demonstrated that the H₂ S/polysulfides production system is upregulated in schizophrenia. Mechanistically, the Mpst-Tg brain revealed dampened energy metabolism, while maternal immune activation model mice showed upregulation of genes for H₂ S/polysulfides production along with typical antioxidative genes, partly via epigenetic modifications. These results suggest that inflammatory/oxidative insults in early brain development result in upregulated H₂ S/polysulfides production as an antioxidative response, which in turn cause deficits in bioenergetic processes. Collectively, this study presents a novel aspect of the neurodevelopmental theory for schizophrenia, unraveling a role of excess H₂ S/polysulfides production.

Advances and challenges in development of precision psychiatry through clinical metabolomics on mood and psychotic disorders

Metabolomics is defined as the study of the global metabolite profile in a system under a given set of conditions. The objective of this review is to comprehensively assess the literature on metabolomics in mood disorders and schizophrenia and provide data for mental health researchers about the challenges and potentials of metabolomics. The majority of studies in metabolomics in Psychiatry uses peripheral blood or urine. The most widely used analytical techniques in metabolomics research are nuclear magnetic resonance (NMR) and mass spectrometry (MS). They are multiparametric and provide extensive structural and conformational information on multiple chemical classes. NMR is useful in untargeted analysis, which focuses on biosignatures or 'metabolic fingerprints' of illnesses. MS targeted metabolomics approach focuses on the identification and quantification of selected metabolites known to be involved in a particular metabolic pathway. The available studies of metabolomics in Schizophrenia, Bipolar Disorder and Major Depressive Disorder suggest a potential in investigating metabolic pathways involved in these diseases' pathophysiology and response to treatment, as well as its potential in biomarkers identification.

The relationship between serum adiponectin levels, cardiometabolic indices and metabolic syndrome in schizophrenia

BACKGROUND

Adiponectin is a hormone secreted by adipose tissues that is thought to influence lipid and glucose metabolism, and the development of metabolic derangements, including metabolic syndrome (MetS), in schizophrenia. We aim to determine the serum adiponectin levels in Chinese patients with schizophrenia, and explore the relationship between adiponectin levels and metabolic parameters, including MetS and its components. We hypothesized that serum adiponectin levels are similar in schizophrenia patients and controls, but decreased amongst patients on atypical antipsychotics.

METHODS

81 patients and 81 controls were recruited. Anthropometric parameters and fasted blood samples for metabolic measurements were obtained. Serum adiponectin levels were measured using Bioplex assays.

RESULTS

There was no difference in median adiponectin levels between schizophrenia patients and controls. Those taking typical antipsychotics alone had lower median adiponectin levels than those on mixed typical and atypical antipsychotics. Serum adiponectin level, controlled for age, gender and body mass index, was positively correlated with high-density lipoprotein cholesterol, and negatively correlated with diastolic blood pressure, total cholesterol, low-density lipoprotein cholesterol, and triglyceride levels in schizophrenia patients. Patients with MetS had lower median adiponectin levels than those without MetS, and serum adiponectin levels decreased as the number of MetS components increased. After adjusting for variables thought to influence MetS, our logistic regression model did not reveal any significant association between adiponectin levels and MetS in schizophrenia patients.

CONCLUSION

Our findings highlight the need for more studies focusing on serum adiponectin level and its relationship with MetS in schizophrenia, particularly in those taking typical antipsychotics.

X-Aptamer Technology Identifies C4A and ApoB in Blood as Potential Markers for Schizophrenia

The field of proteomics is rapidly gaining territory as a promising alternative to genomic approaches in the efforts to unravel the complex molecular mechanisms underlying schizophrenia and other psychiatric disorders. X-aptamer tech-nology has emerged as a novel proteomic approach for high-sensitivity analyses, and we hypothesized that this technology would identify unique molecular signatures in plasma samples from schizophrenia patients (n = 60) compared to controls (n = 20). Using a combinatorial library of X-aptamer beads, we developed a two-color flow cytometer-based approach to identify specific X-aptamers that bound with high specificity to each target group. Based on this, we synthesized two unique X-aptamer sequences, and specific proteins pulled down from the patient and control groups by these X-aptamers were identified by mass spectrometry. We identified two protein biomarkers, complement component C4A and ApoB, upregulated in plasma samples from schizophrenia patients. ELISA validation suggested that the observed differences in C4 levels in patients are likely due to the presence of the illness itself, while ApoB may be a marker of antipsychotic-induced alterations. These studies highlight the utility of the X-aptamer technology in the identification of biomarkers for schizophrenia that will advance our understanding of the pathophysiological mechanisms of this disorder.

Hyperprolactinemia and insulin resistance in drug naive patients with early onset first episode psychosis

BACKGROUND

Hyperprolactinemia and glucose and lipid metabolism abnormalities are often found in patients with schizophrenia and are generally considered secondary to the use of antipsychotic drugs. More recent studies have shown these same neuroendocrine and metabolic abnormalities in antipsychotic naïve patients with first episode psychosis (FEP), rising the hypothesis that schizophrenia itself may be related to an abnormal regulation of prolactin secretion and to impaired glucose tolerance. The aim of this study was to compare prolactin levels, glycometabolism parameters and lipid profile between a sample of 31 drug-naive adolescents in the acute phase of FEP and a control group of 23 subjects at clinical high risk (CHR) of developing psychosis.

METHODS

The assessment involved anthropometric data (weight, height, BMI index, pubertal stage) and blood tests (levels of glucose, glycated hemoglobin, serum insulin, triglycerides, total and fractionated cholesterol, prolactin). Insulin resistance (IR) was calculated through the homeostatic model of assessment (HOMA-IR), assuming a cut-off point of 3.16 for adolescent population. FEP patients and CHR controls were compared by using Student's t-distribution (t-test) for parametric data. P < 0.05 was considered significant.

RESULTS

Significant higher level of prolactin was found in FEP group than in CHR group (mean = 28.93 ± 27.16 vs 14.29 ± 7.86, P = 0.009), suggesting a condition of hyperprolactinemia (HPRL). Patients with FEP were more insulin resistant compared to patients at CHR, as assessed by HOMA-IR (mean = 3.07 ± 1.76 vs 2.11 ± 1.11, P = 0.043). Differences of fasting glucose (FEP = 4.82 ± 0.71, CHR = 4.35 ± 0.62, P = 0.016) and HbA1c (FEP = 25.86 ± 13.31, CHR = 33.00 ± 2.95, P = 0.013), were not clinically significant as the mean values were within normal range for both groups. No significant differences were found for lipid profile. A BMI value within the range of normal weight was found for both groups, with no significant differences.

CONCLUSION

We suggested that HPRL, increase in HOMA-IR, and psychotic symptoms may be considered different manifestations of the acute onset of schizophrenia spectrum psychosis, with a common neurobiological vulnerability emerging since adolescence. The influence of age and gender on clinical manifestations of psychotic onset should be considered for early prevention and treatment of both schizophrenia spectrum psychosis and neuroendocrine-metabolic dysfunctions.

13C-phenylalanine breath test and serum biopterin in schizophrenia, bipolar disorder and major depressive disorder

Phenylalanine is required for the synthesis of the neurotransmitters dopamine, noradrenaline, and adrenaline. The rate-limiting step for phenylalanine metabolism is catalyzed by phenylalanine hydroxylase (PAH) and its cofactor tetrahydrobiopterin. We aimed to detect altered phenylalanine metabolism in major psychiatric disorders using the l-[1-13C]phenylalanine breath test (13C-PBT) and serum biopterin levels. We also investigated association of PAH mutations with schizophrenia and phenylalanine metabolism. 13C-phenylalanine (100 mg) was orally administered, and the breath 13CO2/12CO2 ratio was monitored for 120 min in four groups: 103 patients with schizophrenia (DSM-IV), 39 with bipolar disorder, 116 with major depressive disorder (MDD), and 241 healthy controls. Serum biopterin levels were measured by high performance liquid chromatography. Mutation screening of PAH exons was performed by direct sequencing in 46 schizophrenia patients. Association analysis was performed using six tag single nucleotide polymorphisms and the PAH Arg53His mutation by TaqMan assays in 616 schizophrenia patients and 1194 healthy controls. Analyses of covariance controlling for age, sex, and body weight showed that the index for the amount of exhaled 13CO2 was significantly lower in the schizophrenia group than in the other three groups (all p < 0.05). Biopterin levels in schizophrenia and MDD were significantly lower than those in controls. Biopterin levels correlated with 13C-PBT indices in controls. PAH polymorphisms were not associated with schizophrenia or 13C-PBT indices. 13C-PBT revealed reduced phenylalanine metabolism in schizophrenia, though we obtained no evidence of involvement of PAH polymorphism. Serum biopterin levels were lower in schizophrenia and MDD, warranting further investigation.

Second generation antipsychotic-induced mitochondrial alterations: Implications for increased risk of metabolic syndrome in patients with schizophrenia

Metabolic syndrome (MetS) is seen more frequently in persons with schizophrenia than in the general population, and these metabolic abnormalities are further aggravated by second generation antipsychotic (SGA) drugs. Although the underlying mechanisms responsible for the increased prevalence of MetS among patients under SGA treatment are not well understood, alterations in mitochondria function have been implicated. We performed a comprehensive evaluation of the role of mitochondrial dysfunction in the pathophysiology of drug-induced MetS in schizophrenia. We found a downregulation in genes encoding subunits of the electron transport chain complexes (ETC), enzyme activity, and mitochondrial dynamics in peripheral blood cells from patients at high-risk for MetS. Additionally, we evaluated several markers of energy metabolism in lymphoblastoid cell lines from patients with schizophrenia and controls following exposure to antipsychotics. We found that the high-risk drugs clozapine and olanzapine induced a general down-regulation of genes involved in the ETC, as well as decreased activities of the corresponding enzymes, ATP levels and a significant decrease in all the functional parameters of mitochondrial oxygen consumption in cells from patients and controls. We also observed that the medium-risk SGA quetiapine decreased oxygen consumption and respiratory control ratio in controls and patients. Additionally, clozapine and olanzapine induced a downregulation of Drp1 and Mfn2 both in terms of mRNA and protein levels. Together, these data suggest that an intrinsic defect in multiple components of oxidative metabolism may contribute to the increased prevalence of MetS in patients under treatment with SGAs known to cause risk for MetS.

Platform for systems medicine research and diagnostic applications in psychotic disorders-The METSY project

Psychotic disorders are associated with metabolic abnormalities including alterations in glucose and lipid metabolism. A major challenge in the treatment of psychosis is to identify patients with vulnerable metabolic profiles who may be at risk of developing cardiometabolic co-morbidities. It is established that both central and peripheral metabolic organs use lipids to control energy balance and regulate peripheral insulin sensitivity. The endocannabinoid system, implicated in the regulation of glucose and lipid metabolism, has been shown to be dysregulated in psychosis. It is currently unclear how these endocannabinoid abnormalities relate to metabolic changes in psychosis. Here we review recent research in the field of metabolic co-morbidities in psychotic disorders as well as the methods to study them and potential links to the endocannabinoid system. We also describe the bioinformatics platforms developed in the EU project METSY for the investigations of the biological etiology in patients at risk of psychosis and in first episode psychosis patients. The METSY project was established with the aim to identify and evaluate multi-modal peripheral and neuroimaging markers that may be able to predict the onset and prognosis of psychiatric and metabolic symptoms in patients at risk of developing psychosis and first episode psychosis patients. Given the intrinsic complexity and widespread role of lipid metabolism, a systems biology approach which combines molecular, structural and functional neuroimaging methods with detailed metabolic characterisation and multi-variate network analysis is essential in order to identify how lipid dysregulation may contribute to psychotic disorders. A decision support system, integrating clinical, neuropsychological and neuroimaging data, was also developed in order to aid clinical decision making in psychosis. Knowledge of common and specific mechanisms may aid the etiopathogenic understanding of psychotic and metabolic disorders, facilitate early disease detection, aid treatment selection and elucidate new targets for pharmacological treatments.

Ziprasidone, a second-generation antipsychotic drug, triggers a macrophage inflammatory response in vitro

Antipsychotic drugs are used to treat schizophrenia and other psychiatric disorders. However, most of these drugs present side effects causing obesity and other serious metabolic alterations that correlate with grade of chronic inflammation. In contrast, ziprasidone's (ZIP) metabolic side effects are attenuated relative to those of other antipsychotic drugs, but some reports suggest that this drug could cause allergic, hypersensitive reactions in susceptible patients. At present, the mechanism of ZIP's effect on peripheral inflammatory metabolism is not well characterized. We conducted an in vitro study to evaluate the effect of ZIP on a macrophage cell line (RAW 264.1). Our results showed that in non-activated macrophage cells, ZIP exposure initiated macrophage spreading; increased cellular proliferation, as evaluated by MTT and flow cytometry assays; and presented higher levels of oxidant molecules involved in the inflammatory response (nitric oxide, superoxide, reactive oxygen species), and proinflammatory cytokines (IL-1, IL-6, TNFα, INFγ). Levels of IL-10, an anti-inflammatory cytokine were lower in ZIP-exposed cells. These effects were less potent than those caused by the positive control for inflammation induction (phytohemagglutinin), and more intense than the effects of lithium (LI), which was used as an anti-inflammatory molecule. ZIP also modulated cytokine gene expression. Taken together, these data suggest that ZIP can produce a peripheral inflammatory response, and this response may explain the allergen-inflammatory response observed in some patients treated with this antipsychotic drug.

Association among serum cortisol, dehydroepiandrosterone-sulfate levels and psychiatric symptoms in men with chronic schizophrenia

PURPOSE

The purpose of this study was to examine possible associations of serum levels of cortisol and dehydroepiandrosterone-sulfate (DHEA-S) with psychiatric symptoms in men with chronic schizophrenia.

METHODS

This retrospective study involved 162 men with schizophrenia and 138 age-matched healthy controls, for whom data were collected on demographic characteristics, age at disease onset, disease duration, positive and negative syndrome scale (PANSS) scores, and history of atypical antipsychotic treatment. Serum levels of cortisol and DHEA-S were calculated, as well as the ratios of the two levels. Possible correlations were explored between these levels and psychiatric symptoms before and after antipsychotic treatment.

RESULTS

Serum levels of cortisol and DHEA-S levels as well as the ratios of cortisol to DHEA-S levels were higher in patients than in controls (p < 0.01). Among patients, serum levels of cortisol and DHEA-S were significantly lower after treatment than before (p < 0.01), although the ratios of cortisol to DHEA-S levels remained similar. Serum levels of cortisol, DHEA-S and the ratios of the two levels were positively correlated with the negative symptoms score on the PANSS.

CONCLUSIONS

The pathophysiology of schizophrenia may involve in the spread levels of cortisol and DHEA-S. These levels may serve as biomarkers for diagnosing schizophrenia and monitoring treatment efficacy.

Metabolomics and lipidomics analyses by 1H nuclear magnetic resonance of schizophrenia patient serum reveal potential peripheral biomarkers for diagnosis

Using ¹H NMR-based metabolomics in association to chemometrics analysis, we analyzed here the metabolic differences between schizophrenia patients (SCZ) compared to healthy controls (HCs). HCs and SCZ patients underwent clinical interview using the Structured Clinical Interview for DSM Disorders (SCID). SCZ patients were further assessed by Positive and Negative Syndrome Scale (PANSS), Calgary Depression Scale, Global Assessment of Functioning Scale (GAF), and Clinical Global Impressions Scale (CGI). Using the principal component analysis (PCA) and supervised partial least-squares discriminate analysis (PLS-DA) in obtained NMR data, a clear group separation between HCs and SCZ patients was achieved. Interestingly, all metabolite compounds identified as exclusively present in the SCZ group, except for the gamma-aminobutyric acid (GABA), were never previously associated with mental disorders. Although the initial perception of an absence of obvious biological link among the different key molecules exclusively observed in each group, and no identification of any specific pathway yet, the present work represents an important contribution for the identification of potential biomarkers to inform diagnosis, as it was possible to completely separate the affected SCZ patients from HCs, with no outliers or exceptions. In addition, the data presented here reinforced the role of the modulation of glycolysis pathway and the loss of GABA interneuron/hyperglutamate hypothesis in SCZ.

Risperidone and Cardiometabolic Risk in Children and Adolescents: Clinical and Instrumental Issues

PURPOSE/BACKGROUND

Although second-generation antipsychotics are used to treat and manage symptoms for several psychiatric disorders, data about their adverse effects in developmental age are limited. The aim of this prospective observational study was to verify the cardiovascular and metabolic risk in a sample of antipsychotic-naive children/adolescent patients starting risperidone therapy.

METHODS

Twenty-two patients, younger than 18 years, were recruited. The assessment included anthropometric data, cardiovascular parameters, blood tests, and ultrasonographic abdominal study.

RESULTS

After an average follow-up period of 7.6 months, statistically significant increases in mean values of waist circumference, body mass index (BMI), BMI percentile, BMI z score, total cholesterol, and prolactin were found. Other cardiometabolic parameters showed an upward trend in time. Subjects in pubertal/postpubertal stage and female patients were more susceptible to developing cardiometabolic changes. Moreover, significant correlations between changes in anthropometric and several metabolic parameters were found. A tendency to change in constitution of the liver parenchyma and distribution of the abdominal fat mass with ultrasonographic abdominal study was also evident.

CONCLUSIONS

In our sample, several metabolic parameters showed a sensitivity to risperidone treatment. Because most of these parameters are age dependent, metabolic syndrome criteria used for adults were inappropriate in children and adolescents. Periodic clinical and instrumental evaluations and guidelines for monitoring of any metabolic, laboratory, and instrumental complications are necessary in the perspective of even long-time second-generation antipsychotics treatment in children and adolescents.

Body and liver fat content and adipokines in schizophrenia: a magnetic resonance imaging and spectroscopy study

RATIONALE

Although antipsychotic treatment often causes weight gain and lipid abnormalities, quantitative analyses of tissue-specific body fat content and its distribution along with adipokines have not been reported for antipsychotic-treated patients.

OBJECTIVES

The purposes of the present study were to quantitatively assess abdominal and liver fat in patients with schizophrenia on antipsychotic treatment and age- and body mass index (BMI)-matched healthy controls and to evaluate their associations with plasma leptin and adiponectin levels.

METHODS

In 13 schizophrenia patients on antipsychotic treatment and 11 age- and BMI-matched controls, we simultaneously quantified visceral and subcutaneous fat content using T1-weighted magnetic resonance imaging and liver fat content by ¹H magnetic resonance spectroscopy. Associations of tissue-specific fat content with plasma levels of leptin and adiponectin were evaluated.

RESULTS

Plasma adiponectin level (μg/mL) was not statistically different between groups (7.02 ± 2.67 vs. 7.59 ± 2.92), whereas plasma leptin level (ng/mL) trended to be higher in patients than in controls (11.82 ± 7.89 vs. 7.93 ± 5.25). The values of liver fat (%), visceral fat (L), and subcutaneous fat (L) were 9.64 ± 8.03 vs. 7.07 ± 7.35, 4.41 ± 1.64 vs. 3.31 ± 1.97, and 8.37 ± 3.34 vs. 7.16 ± 2.99 in patients vs. controls, respectively. Liver fat content was inversely correlated with adiponectin in controls (r =  - 0.87, p < 0.001) but not in patients (r =  - 0.26, p = 0.39). In both groups, visceral fat was inversely associated with adiponectin (controls : r =  - 0.66, p = 0.03; patients : r =  - 0.65, p = 0.02), while subcutaneous fat was positively correlated with leptin (controls : r = 0.90, p < 0.001; patients : r = 0.67, p = 0.01).

CONCLUSIONS

These findings suggest that antipsychotic treatment may disrupt the physiological relationship between liver fat content and adiponectin but does not essentially affect the associations of adiponectin and leptin with visceral and subcutaneous compartments.

Targeted High Performance Liquid Chromatography Tandem Mass Spectrometry-based Metabolomics differentiates metabolic syndrome from obesity

Both obesity and the metabolic syndrome are risk factors for type 2 diabetes and cardiovascular disease. Identification of novel biomarkers are needed to distinguish metabolic syndrome from equally obese individuals in order to direct them to early interventions that reduce their risk of developing further health problems. We utilized mass spectrometry-based targeted metabolic profiling of 221 metabolites to evaluate the associations between metabolite profiles and established metabolic syndrome criteria (i.e. elevated waist circumference, hypertension, elevated fasting glucose, elevated triglycerides, and low high-density lipoprotein cholesterol) in plasma samples from obese men ( n = 29; BMI = 35.5 ± 5.2 kg/m²) and women ( n = 40; 34.9 ± 6.7 kg/m²), of which 26 met the criteria for metabolic syndrome (17 men and 9 women). Compared to obese individuals without metabolic syndrome, univariate statistical analysis and partial least squares discriminant analysis showed that a specific group of metabolites from multiple metabolic pathways (i.e. purine metabolism, valine, leucine and isoleucine degradation, and tryptophan metabolism) were associated with the presence of metabolic syndrome. Receiver operating characteristic curves generated based on the PLS-DA models showed excellent areas under the curve (0.85 and 0.96, for metabolites only model and enhanced metabolites model, respectively), high specificities (0.86 and 0.93), and good sensitivities (0.71 and 0.91). Moreover, principal component analysis revealed that metabolic profiles can be used to further differentiate metabolic syndrome with 3 versus 4-5 metabolic syndrome criteria. Collectively, these findings support targeted metabolomics approaches to distinguish metabolic syndrome from obesity alone, and to stratify metabolic syndrome status based on the number of criteria met. Impact statement We utilized mass spectrometry-based targeted metabolic profiling of 221 metabolites to evaluate the associations between metabolite profiles and established MetS criteria. To our best knowledge, the findings of this study provide the first evidence that metabolic profiles can be used to differentiate participants with MetS from similarly obese individuals who do not meet established criteria of MetS. Furthermore, the study demonstrated that within MetS participants, their unique metabolic profiles correlated to the number of criteria used for MetS determination. Taken together, this metabolic profiling approach can potentially serve as a novel tool for MetS detection and monitoring, and provide useful metabolic information for future interventions targeting obesity and MetS.

Evaluating metabolic response to light exposure in Lactobacillus species via targeted metabolic profiling

This study reported metabolic profiles of three representative strains from Lactobacillus species, and explored their metabolic response to visible light exposure. We utilized strains from three Lactobacillus species, Lactobacillus acidophilus, Lactobacillus fermentum and Lactobacillus delbrueckii as our model bacteria and applied mass spectrometry base targeted metabolomics to specifically investigate 221 metabolites within multiple metabolic pathways. Similar and diverse metabolome from three tested strains were discovered. Furthermore, all three Lactobacillus strains demonstrated different metabolic profiles in comparison between light expose verse control. In all three strains, 12 metabolites were detected to have significant differences (p-value<0.01) in light exposure culture compared to the control samples (culture grown without light exposure). Principal components analysis using these significantly changed metabolites clearly separated the exposure and control groups in all three studied Lactobacillus strains. Additionally, metabolic pathway impact analysis indicated that several commonly impacted pathways can be observed.

Sex Differences in Body Mass Index and Obesity in Chinese Patients With Chronic Schizophrenia

Sex differences in schizophrenia have been well recognized. However, sex differences in obesity associated with antipsychotics have received little systematic study. This study was conducted to compare sex difference effects of antipsychotics and related risk factors on obesity and body mass index (BMI) in Chinese patients with schizophrenia. A total of 204 inpatients with chronic schizophrenia (males/females = 140/66) were recruited. Demographic and clinical data were collected, and serum glucose and lipid levels were measured. The Positive and Negative Syndrome Scale (PANSS) was used to assess patients' psychopathology. The prevalence of obesity in female patients (21/66, 31.82%) was approximately 2 times that of male patients (22/140, 15.83%; P < 0.001) and women also had higher BMI than men (25.49 ± 4.42 kg/m versus 23.95 ± 3.67 kg/m; P < 0.005). Regression analyses showed that obesity was associated with type 2 diabetes (P < 0.05) and triglycerides (P < 0.05) in women, and limited to triglyceride in men (P < 0.01). Further correlation analysis showed that BMI was associated with the PANSS negative symptom subscore (P < 0.001) and the PANSS total score (P < 0.01) in men. In addition, women had higher low-density lipoprotein plasma levels than men. Our findings suggest that there are significant sex differences in bodyweight and obesity in chronic medicated patients with schizophrenia, with worse lipid metabolic dysfunction in female patients.

Serum metabolite profile associates with the development of metabolic co-morbidities in first-episode psychosis

Psychotic patients are at high risk for developing obesity, metabolic syndrome and type 2 diabetes. These metabolic co-morbidities are hypothesized to be related to both treatment side effects as well as to metabolic changes occurring during the psychosis. Earlier metabolomics studies have shown that blood metabolite levels are predictive of insulin resistance and type 2 diabetes in the general population as well as sensitive to the effects of antipsychotics. In this study, we aimed to identify the metabolite profiles predicting future weight gain and other metabolic abnormalities in psychotic patients. We applied comprehensive metabolomics to investigate serum metabolite profiles in a prospective study setting in 36 first-episode psychosis patients during the first year of the antipsychotic treatment and 19 controls. While corroborating several earlier findings when comparing cases and controls and the effects of the antipsychotic medication, we also found that prospective weight gain in psychotic patients was associated with increased levels of triacylglycerols with low carbon number and double-bond count at baseline, that is, lipids known to be associated with increased liver fat. Our study suggests that metabolite profiles may be used to identify the psychotic patients most vulnerable to develop metabolic co-morbidities, and may point to a pharmacological approach to counteract the antipsychotic-induced weight gain.

Quality of Life and Hormonal, Biochemical, and Anthropometric Profile Between Olanzapine and Risperidone Users

This cross-sectional study compared quality of life and side effects in 108 users of olanzapine or risperidone suffering schizophrenia and being attended at psychiatric ambulatory services in Rio Grande do Norte, Brazil. Economic, socio-demographic, anthropometric, biochemical, and hormonal variables were compared. The EuroQoL Five-Dimension Scale (EQ-5D) was used to evaluate quality of life, and side effects were assessed using the Udvalg for Kliniske Undersøgelser (UKU) Side Effect Rating Scale and the Simpson-Angus Scale. Data were analysed using the χ(2) test and Student's t test, with a significance level of 5 %.The household incomes of approximately 80 % of patients were <2.0 minimum wages ($678). Anthropometric variables (waist circumference, hip circumference, weight, waist-to-hip ratio) and systolic and diastolic blood pressure were noted among male olanzapine users (all p < 0.05). EQ-5D scores showed that olanzapine use significantly impacted self-help ability (p < 0.001). Risperidone users had a mean quality-adjusted life year value of 1. Mean total Simpson-Angus Scale scores was 0.38 for olanzapine users and 0.11 for risperidone users (p < 0.02). Significant differences in UKU were observed for the following items: asthenia/lassitude/fatigue (higher among olanzapine users, p = 0.02), dystonia (higher among olanzapine users, p = 0.01), tremors (higher among olanzapine users, p = 0.03), gynecomastia (higher among risperidone users, p < 0.02), and ejaculatory dysfunction (higher among risperidone users, p < 0.02). Olanzapine users had impaired quality of life, which can be explained in part by adverse motor, biochemical, and hormonal effects characteristic of metabolic syndrome.

Increased Circulating Levels of Alpha-Ketoglutarate in Morbidly Obese Women with Non-Alcoholic Fatty Liver Disease

Background

Non-alcoholic fatty liver disease (NAFLD) causes a wide spectrum of liver damage, ranging from simple steatosis to cirrhosis. However, simple steatosis (SS) and steatohepatitis (NASH) cannot yet be distinguished by clinical or laboratory features. The aim of this study was to assess the relationship between alpha-ketoglutarate and the degrees of NAFLD in morbidly obese patients.

Materials and Methods

We used a gas chromatography-quadruple time-of-flight-mass spectrometry analysis to quantify alpha-ketoglutarate in serum from normal-weight subjects (n = 30) and morbidly obese women (n = 97) with or without NAFLD.

Results

We found that serum levels of alpha-ketoglutarate were significantly higher in morbidly obese women than in normal-weight women. We showed that circulating levels of alpha-ketoglutarate were lower in lean controls and morbidly obese patients without NAFLD. We also found that alpha-ketoglutarate serum levels were higher in both SS and NASH than in normal liver of morbidly obese patients. However, there was no difference between SS and NASH. Moreover, we observed that circulating levels of alpha-ketoglutarate were associated with glucose metabolism parameters, lipid profile, hepatic enzymes and steatosis degree. In addition, diagnostic performance of alpha-ketoglutarate has been analyzed in NAFLD patients. The AUROC curves from patients with liver steatosis exhibited an acceptable clinical utility. Finally, we showed that the combination of biomarkers (AST, ALT and alpha-ketoglutarate) had the highest accuracy in diagnosing liver steatosis.

Conclusion

These findings suggest that alpha-ketoglutarate can determine the presence of non-alcoholic fatty liver in morbidly obese patients but it is not valid a biomarker for NASH.

Metabolomic Profiling of Post-Mortem Brain Reveals Changes in Amino Acid and Glucose Metabolism in Mental Illness Compared with Controls

Metabolomic profiling was carried out on 53 post-mortem brain samples from subjects diagnosed with schizophrenia, depression, bipolar disorder (SDB), diabetes, and controls. Chromatography on a ZICpHILIC column was used with detection by Orbitrap mass spectrometry. Data extraction was carried out with m/z Mine 2.14 with metabolite searching against an in-house database. There was no clear discrimination between the controls and the SDB samples on the basis of a principal components analysis (PCA) model of 755 identified or putatively identified metabolites. Orthogonal partial least square discriminant analysis (OPLSDA) produced clear separation between 17 of the controls and 19 of the SDB samples (R2CUM 0.976, Q2 0.671, p-value of the cross-validated ANOVA score 0.0024). The most important metabolites producing discrimination were the lipophilic amino acids leucine/isoleucine, proline, methionine, phenylalanine, and tyrosine; the neurotransmitters GABA and NAAG and sugar metabolites sorbitol, gluconic acid, xylitol, ribitol, arabinotol, and erythritol. Eight samples from diabetic brains were analysed, six of which grouped with the SDB samples without compromising the model (R2 CUM 0.850, Q2 CUM 0.534, p-value for cross-validated ANOVA score 0.00087). There appears on the basis of this small sample set to be some commonality between metabolic perturbations resulting from diabetes and from SDB.

Omics-Based Biomarkers: Application of Metabolomics in Neuropsychiatric Disorders

One of the major concerns of modern society is to identify putative biomarkers that serve as a valuable early diagnostic tool to identify a subset of patients with increased risk to develop neuropsychiatric disorders. Biomarker identification in neuropsychiatric disorders is proposed to offer a number of important benefits to patient well-being, including prediction of forthcoming disease, diagnostic precision, and a level of disease description that would guide treatment choice. Nowadays, the metabolomics approach has unlocked new possibilities in diagnostics of devastating disorders like neuropsychiatric disorders. Metabolomics-based technologies have the potential to map early biochemical changes in disease and hence provide an opportunity to develop predictive biomarkers that can be used as indicators of pathological abnormalities prior to development of clinical symptoms of neuropsychiatric disorders. This review highlights different -omics strategies for biomarker discovery in neuropsychiatric disorders. We also highlight initial outcomes from metabolomics studies in psychiatric disorders such as schizophrenia, bipolar disorder, and addictive disorders. This review will also present issues and challenges regarding the implementation of the metabolomics approach as a routine diagnostic tool in the clinical laboratory in context with neuropsychiatric disorders.

c-Myc and AMPK Control Cellular Energy Levels by Cooperatively Regulating Mitochondrial Structure and Function

The c-Myc (Myc) oncoprotein and AMP-activated protein kinase (AMPK) regulate glycolysis and oxidative phosphorylation (Oxphos) although often for different purposes. Because Myc over-expression depletes ATP with the resultant activation of AMPK, we explored the potential co-dependency of and cross-talk between these proteins by comparing the consequences of acute Myc induction in ampk+/+ (WT) and ampk-/- (KO) murine embryo fibroblasts (MEFs). KO MEFs showed a higher basal rate of glycolysis than WT MEFs and an appropriate increase in response to activation of a Myc-estrogen receptor (MycER) fusion protein. However, KO MEFs had a diminished ability to increase Oxphos, mitochondrial mass and reactive oxygen species in response to MycER activation. Other differences between WT and KO MEFs, either in the basal state or following MycER induction, included abnormalities in electron transport chain function, levels of TCA cycle-related oxidoreductases and cytoplasmic and mitochondrial redox states. Transcriptional profiling of pathways pertinent to glycolysis, Oxphos and mitochondrial structure and function also uncovered significant differences between WT and KO MEFs and their response to MycER activation. Finally, an unbiased mass-spectrometry (MS)-based survey capable of quantifying ~40% of all mitochondrial proteins, showed about 15% of them to be AMPK- and/or Myc-dependent in their steady state. Significant differences in the activities of the rate-limiting enzymes pyruvate kinase and pyruvate dehydrogenase, which dictate pyruvate and acetyl coenzyme A abundance, were also differentially responsive to Myc and AMPK and could account for some of the differences in basal metabolite levels that were also detected by MS. Thus, Myc and AMPK are highly co-dependent and appear to engage in significant cross-talk across numerous pathways which support metabolic and ATP-generating functions.

Plasma adiponectin levels in schizophrenia and role of second-generation antipsychotics: a meta-analysis

BACKGROUND

People with schizophrenia are more likely than general population to suffer from metabolic abnormalities, with second-generation antipsychotics (SGAs) increasing the risk. Low plasma adiponectin levels may lead to metabolic dysregulations but evidence in people with schizophrenia, especially for the role of SGAs, is still inconclusive.

OBJECTIVE

To compare plasma adiponectin levels between people with schizophrenia and healthy controls, and to estimate the relative effect of schizophrenia and SGAs on adiponectin.

METHODS

We performed a systematic review and meta-analysis of observational studies published up to 13 June 2014 in main electronic databases. Pooled standardized mean differences (SMDs) between index and control groups were generated. Appropriate subanalyses and additional subgroup analyses were carried out.

RESULTS

Data from 2735 individuals, 1013 with and 1722 without schizophrenia, respectively, were analysed. Schizophrenia was not associated with lower adiponectin levels (SMD of -0.28, 95%CI: -0.59, 0.04; p=0.09). However, individuals with schizophrenia taking SGAs had plasma levels significantly lower than controls (p=0.002), which was not the case of drug free/drug naïve subjects (p=0.52). As regards single antipsychotic drugs clozapine (p<0.001) and olanzapine (p=0.04)--but not risperidone (p=0.88)--were associated with adiponectin levels lower than controls.

CONCLUSIONS

People with schizophrenia per se may not have levels of adiponectin lower than controls, though treatment with SGAs is associated with this metabolic abnormality. This bears clinical significance because of hypoadiponectinemia involvement in cardiovascular diseases, even if mechanisms whereby SGAs affect adiponectin remain unexplained. Longitudinal studies evaluating long-term effects of SGAs on adiponectin are needed.

Transcriptome alterations of mitochondrial and coagulation function in schizophrenia by cortical sequencing analysis

Background

Transcriptome sequencing of brain samples provides detailed enrichment analysis of differential expression and genetic interactions for evaluation of mitochondrial and coagulation function of schizophrenia. It is implicated that schizophrenia genetic and protein interactions may give rise to biological dysfunction of energy metabolism and hemostasis. These findings may explain the biological mechanisms responsible for negative and withdraw symptoms of schizophrenia and antipsychotic-induced venous thromboembolism.

We conducted a comparison of schizophrenic candidate genes from literature reviews and constructed the schizophrenia-mediator network (SCZMN) which consists of schizophrenic candidate genes and associated mediator genes by applying differential expression analysis to BA22 RNA-Seq brain data. The network was searched against pathway databases such as PID, Reactome, HumanCyc, and Cell-Map. The candidate complexes were identified by MCL clustering using CORUM for potential pathogenesis of schizophrenia.

Results

Published BA22 RNA-Seq brain data of 9 schizophrenic patients and 9 controls samples were analyzed. The differentially expressed genes in the BA22 brain samples of schizophrenia are proposed as schizophrenia candidate marker genes (SCZCGs). The genetic interactions between mitochondrial genes and many under-expressed SCZCGs indicate the genetic predisposition of mitochondria dysfunction in schizophrenia. The biological functions of SCZCGs, as listed in the Pathway Interaction Database (PID), indicate that these genes have roles in DNA binding transcription factor, signal and cancer-related pathways, coagulation and cell cycle regulation and differentiation pathways.

In the query-query protein-protein interaction (QQPPI) network of SCZCGs, TP53, PRKACA, STAT3 and SP1 were identified as the central "hub" genes. Mitochondrial function was modulated by dopamine inhibition of respiratory complex I activity. The genetic interaction between mitochondria function and schizophrenia may be revealed by DRD2 linked to NDUFS7 through protein-protein interactions of FLNA and ARRB2.

The biological mechanism of signaling pathway of coagulation cascade was illustrated by the PPI network of the SCZCGs and the coagulation-associated genes. The relationship between antipsychotic target genes (DRD2/3 and HTR2A) and coagulation factor genes (F3, F7 and F10) appeared to cascade the following hemostatic process implicating the bottleneck of coagulation genetic network by the bridging of actin-binding protein (FLNA).

Conclusions

It is implicated that the energy metabolism and hemostatic process have important roles in the pathogenesis for schizophrenia. The cross-talk of genetic interaction by these co-expressed genes and reached candidate genes may address the key network in disease pathology. The accuracy of candidate genes evaluated from different quantification tools could be improved by crosstalk analysis of overlapping genes in genetic networks.