Metabolomic mapping of atypical antipsychotic effects in schizophrenia

Altered lipidomics biosignatures in schizophrenia: A systematic review

Multiomics approaches have significantly aided the identification of molecular signatures in complex neuropsychiatric disorders. Lipidomics, one of the newest additions in the -omics family, sheds light on lipid profiles and is an emerging methodological tool to study schizophrenia pathobiology, as lipid dysregulation has been repeatedly observed in schizophrenia. In this review, we performed a detailed literature search for lipidomics studies in schizophrenia. Following elaborate inclusion/exclusion criteria, we focused on human studies in schizophrenia and schizophrenia-related diagnoses in brain and blood specimens, including serum plasma, platelets and red blood cells. Eighteen studies fulfilled our inclusion criteria, of which five were conducted in the brain, 12 in peripheral material and one in both. Here, we first provide background on lipidomics and the main lipid categories addressed, review in detail the included literature and look for common lipidomics patterns in brain and the periphery that emerge from these studies. Furthermore, we highlight current limitations in schizophrenia lipidomics research and underline the need for following up on lipidomics results with complementary molecular approaches.

The identification of novel schizophrenia-related metabolites using untargeted lipidomics

Human lipidome still remains largely unexplored among Chinese schizophrenia patients. We aimed to identify novel lipid molecules associated with schizophrenia and cognition among schizophrenia patients. The current study included 96 male schizophrenia patients and 96 gender-matched healthy controls. Untargeted lipidomics profiling was conducted among all participants. Logistic regression models were used to assess metabolite associations with schizophrenia. We further assessed the incremental predictive value of identified metabolites beyond conventional risk factors on schizophrenia status. In addition, identified metabolites were tested for association with cognitive function among schizophrenia patients using linear regression models. A total of 34 metabolites were associated with schizophrenia. Addition of these identified metabolites to age, body mass index, smoking, and education significantly increased the risk reclassification of schizophrenia. Among the schizophrenia-related metabolites, 10 were further associated with cognition in schizophrenia patients, including four metabolites associated with immediate memory, two metabolites associated with delayed memory, three metabolites associated with visuospatial, four metabolites associated with language, one metabolite associated with attention, and two metabolites associated with the total score. Our findings provide novel insights into the biological mechanisms of schizophrenia, suggesting that lipid metabolites may serve as potential diagnostic or therapeutic targets of schizophrenia.

Anthranilic Acid, a GPR109A Agonist, and Schizophrenia

Introduction

Limited clinical efficiency of current medications warrants search for new antipsychotic agents. Deorphanized G-protein coupled receptor (GPR)109A has not attracted much of attention of schizophrenia researchers. We analyzed literature and our data on endogenous agonists of GPR109A, beta-hydroxybutyrate (BHB), anthranilic (AA), butyric (BA), and nicotinic (NA) acids, in individuals with schizophrenia.

Data

Sex specific differences: plasma AA levels were 27% higher in female than in male patients and correlated with PANSS before 6 weeks of antipsychotics treatment (r = .625, P < .019, Spearman's test). There was no sex specific differences of plasma AA levels after treatment. AA plasma levels inversely correlated (-.58, P < .005) with PANSS scores in responders to treatment (at least, 50% improvement) but not in nonresponders. Preclinical studies suggested antipsychotic effect of BHB and BA. Clinical studies observed antipsychotic effect of NA; benzoate sodium, an AA precursor; and interventions associated with BHB upregulation (eg, fasting and ketogenic diets).

Discussion

Upregulation of GPR109A, an anti-inflammatory and neuroprotective receptor, inhibits cytosolic phospholipase A2 (cPLA2), an enzyme that breakdown myelin, lipid-based insulating axonal sheath that protects and promotes nerve conduction. Brain cPLA2 is upregulated in individuals with schizophrenia and subjects at high-risk for development of psychosis. Lower myelin content is associated with cognitive decline in individuals with schizophrenia. Therefore, GPR109A might exert antipsychotic effect via suppression of cPLA2, and, consequently, preservation of myelin integrity. Future research might explore antipsychotic effects of (1) human pegylated kynureninase, an enzyme that catalyzes formation of AA from kynurenine (Kyn); (2) inhibitors of Kyn conversion into kynurenic acid, for example, KYN5356, to patients with already impaired Kyn conversion into 3-hydroxykynurenine; (3) synthetic GPR 109A agonists, for example, MK-1903 and SCH900271 and GSK256073, that underwent clinical trials as anti-dyslipidemia agents. GPR109A expression, that might be a new endophenotype of schizophrenia, especially associated with cognitive impairment, needs thorough assessment.

Lipids in Psychiatric Disorders: Functional and Potential Diagnostic Role as Blood Biomarkers

Lipids are a crucial component of the human brain, serving important structural and functional roles. They are involved in cell function, myelination of neuronal projections, neurotransmission, neural plasticity, energy metabolism, and neuroinflammation. Despite their significance, the role of lipids in the development of mental disorders has not been well understood. This review focused on the potential use of lipids as blood biomarkers for common mental illnesses, such as major depressive disorder, anxiety disorders, bipolar disorder, and schizophrenia. This review also discussed the impact of commonly used psychiatric medications, such as neuroleptics and antidepressants, on lipid metabolism. The obtained data suggested that lipid biomarkers could be useful for diagnosing psychiatric diseases, but further research is needed to better understand the associations between blood lipids and mental disorders and to identify specific biomarker combinations for each disease.

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.

Lipid-correlated alterations in the transcriptome are enriched in several specific pathways in the postmortem prefrontal cortex of Japanese patients with schizophrenia

AIMS

Schizophrenia is a chronic relapsing psychiatric disorder that is characterized by many symptoms and has a high heritability. There were studies showing that the phospholipid abnormalities in subjects with schizophrenia (Front Biosci, S3, 2011, 153; Schizophr Bull, 48, 2022, 1125; Sci Rep, 7, 2017, 6; Anal Bioanal Chem, 400, 2011, 1933). Disturbances in prefrontal cortex phospholipid and fatty acid composition have been reported in subjects with schizophrenia (Sci Rep, 7, 2017, 6; Anal Bioanal Chem, 400, 2011, 1933; Schizophr Res, 215, 2020, 493; J Psychiatr Res, 47, 2013, 636; Int J Mol Sci, 22, 2021). For exploring the signaling pathways contributing to the lipid changes in previous study (Sci Rep, 7, 2017, 6), we performed two types of transcriptome analyses in subjects with schizophrenia: an unbiased transcriptome analysis solely based on RNA-seq data and a correlation analysis between levels of gene expression and lipids.

METHODS

RNA-Seq analysis was performed in the postmortem prefrontal cortex from 10 subjects with schizophrenia and 5 controls. Correlation analysis between the transcriptome and lipidome from 9 subjects, which are the same samples in the previous lipidomics study (Sci Rep, 7, 2017, 6).

RESULTS

Extraction of differentially expressed genes (DEGs) and further sequence and functional group analysis revealed changes in gene expression levels in phosphoinositide 3-kinase (PI3K)-Akt signaling and the complement system. In addition, a correlation analysis clarified alterations in ether lipid metabolism pathway, which is not found as DEGs in transcriptome analysis alone.

CONCLUSIONS

This study provided results of the integrated analysis of the schizophrenia-associated transcriptome and lipidome within the PFC and revealed that lipid-correlated alterations in the transcriptome are enriched in specific pathways including ether lipid metabolism pathway.

Identification of Plasma Biomarkers in Drug-Naïve Schizophrenia Using Targeted Metabolomics

OBJECTIVE

Schizophrenia (SCZ) is a severe psychiatric disorder with unknown etiology and lacking specific biomarkers. Herein, we aimed to explore plasma biomarkers relevant to SCZ using targeted metabolomics.

METHODS

Sixty drug-naïve SCZ patients and 36 healthy controls were recruited. Psychotic symptoms were assessed using the Positive and Negative Syndrome Scale. We analyzed the levels of 271 metabolites in plasma samples from all subjects using targeted metabolomics, and identified metabolites that differed significantly between the two groups. Then we evaluated the diagnostic power of the metabolites based on receiver operating characteristic curves, and explored metabolites associated with the psychotic symptoms in SCZ patients.

RESULTS

Twenty-six metabolites showed significant differences between SCZ patients and healthy controls. Among them, 12 metabolites were phosphatidylcholines and cortisol, ceramide (d18:1/22:0), acetylcarnitine, and γ-aminobutyric acid, which could significantly distinguish SCZ from healthy controls with the area under the curve (AUC) above 0.7. Further, a panel consisting of the above 4 metabolites had an excellent performance with an AUC of 0.867. In SCZ patients, phosphatidylcholines were positively related with positive symptoms, and cholic acid was positively associated with negative symptoms.

CONCLUSION

Our study provides insights into the metabolite alterations associated with SCZ and potential biomarkers for its diagnosis and symptom severity assessment.

Serum Metabolic Profile in Schizophrenia Patients With Antipsychotic-Induced Constipation and Its relationship With Gut Microbiome

BACKGROUND AND HYPOTHESIS

Antipsychotics (APs), the cornerstone of schizophrenia treatment, confer a relatively high risk of constipation. However, the mechanisms underpinning AP-induced constipation are poorly understood. Thus, we hypothesized that (1) schizophrenia patients with AP-induced constipation have distinct metabolic patterns; (2) there is more than one mechanism at play in producing this adverse drug effect; and (3) AP-associated changes in the gut microbiome are related to the altered metabolic profiles.

STUDY DESIGN

Eighty-eight schizophrenia patients, including 44 with constipation (C) and 44 matched patients without constipation (NC), were enrolled in this study. Constipation was diagnosed by Rome IV criteria for constipation and colonic transit time using radiopaque markers (ROMs) while severity was evaluated with the Bristol Stool Form Scale (BSS) and Constipation Assessment Scale (CAS). Fasting blood samples were drawn from all participants and were subjected to non-targeted liquid chromatography-mass spectrometry (LC-MS) metabolomic analysis.

STUDY RESULTS

Eleven metabolites were significantly altered in AP-induced constipation which primarily disturbed sphingolipid metabolism, choline metabolism, and sphingolipid signaling pathway (P value < .05, FDR < 0.05). In the C group, changes in the gut bacteria showed a certain degree of correlation with 2 of the significantly altered serum metabolites and were associated with alterations in choline metabolism.

CONCLUSIONS

Our findings indicated that there were disturbances in distinct metabolic pathways that were associated with AP-induced constipation. In addition, this study presents evidence of a link between alterations in the gut microbiome and host metabolism which provides additional mechanistic insights on AP-induced constipation.

Metabolomic signatures associated with weight gain and psychosis spectrum diagnoses: A pilot study

Psychosis spectrum disorders (PSDs), as well as other severe mental illnesses where psychotic features may be present, like bipolar disorder, are associated with intrinsic metabolic abnormalities. Antipsychotics (APs), the cornerstone of treatment for PSDs, incur additional metabolic adversities including weight gain. Currently, major gaps exist in understanding psychosis illness biomarkers, as well as risk factors and mechanisms for AP-induced weight gain. Metabolomic profiles may identify biomarkers and provide insight into the mechanistic underpinnings of PSDs and antipsychotic-induced weight gain. In this 12-week prospective naturalistic study, we compared serum metabolomic profiles of 25 cases within approximately 1 week of starting an AP to 6 healthy controls at baseline to examine biomarkers of intrinsic metabolic dysfunction in PSDs. In 17 of the case participants with baseline and week 12 samples, we then examined changes in metabolomic profiles over 12 weeks of AP treatment to identify metabolites that may associate with AP-induced weight gain. In the cohort with pre-post data (n = 17), we also compared baseline metabolomes of participants who gained ≥5% baseline body weight to those who gained <5% to identify potential biomarkers of antipsychotic-induced weight gain. Minimally AP-exposed cases were distinguished from controls by six fatty acids when compared at baseline, namely reduced levels of palmitoleic acid, lauric acid, and heneicosylic acid, as well as elevated levels of behenic acid, arachidonic acid, and myristoleic acid (FDR < 0.05). Baseline levels of the fatty acid adrenic acid was increased in 11 individuals who experienced a clinically significant body weight gain (≥5%) following 12 weeks of AP exposure as compared to those who did not (FDR = 0.0408). Fatty acids may represent illness biomarkers of PSDs and early predictors of AP-induced weight gain. The findings may hold important clinical implications for early identification of individuals who could benefit from prevention strategies to reduce future cardiometabolic risk, and may lead to novel, targeted treatments to counteract metabolic dysfunction in PSDs.

Neurodevelopmental trajectories, polygenic risk, and lipometabolism in vulnerability and resilience to schizophrenia

BACKGROUND

Schizophrenia (SZ) arises from a complex interplay involving genetic and molecular factors. Early intervention of SZ hinges upon understanding its vulnerability and resiliency factors in study of SZ and genetic high risk for SZ (GHR).

METHODS

Herein, using integrative and multimodal strategies, we first performed a longitudinal study of neural function as measured by amplitude of low frequency function (ALFF) in 21 SZ, 26 GHR, and 39 healthy controls to characterize neurodevelopmental trajectories of SZ and GHR. Then, we examined the relationship between polygenic risk score for SZ (SZ-PRS), lipid metabolism, and ALFF in 78 SZ, and 75 GHR in cross-sectional design to understand its genetic and molecular substrates.

RESULTS

Across time, SZ and GHR diverge in ALFF alterations of the left medial orbital frontal cortex (MOF). At baseline, both SZ and GHR had increased left MOF ALFF compared to HC (P < 0.05). At follow-up, increased ALFF persisted in SZ, yet normalized in GHR. Further, membrane genes and lipid species for cell membranes predicted left MOF ALFF in SZ; whereas in GHR, fatty acids best predicted and were negatively correlated (r = -0.302, P < 0.05) with left MOF.

CONCLUSIONS

Our findings implicate divergence in ALFF alteration in left MOF between SZ and GHR with disease progression, reflecting vulnerability and resiliency to SZ. They also indicate different influences of membrane genes and lipid metabolism on left MOF ALFF in SZ and GHR, which have important implications for understanding mechanisms underlying vulnerability and resiliency in SZ and contribute to translational efforts for early intervention.

Metabolic biomarkers of risperidone-induced weight gain in drug-naïve patients with schizophrenia

Background

Risperidone is a commonly prescribed antipsychotic drug with a potential side effect of weight gain. However, the pathophysiological mechanism is still poorly understood. Here, we sought to identify potential biomarkers of risperidone-induced weight gain by using a targeted metabolomics approach.

Methods

We enrolled 30 subjects who received risperidone monotherapy for 8  weeks from a prospective longitudinal cohort study for drug-naïve schizophrenia patients. Plasma metabolites were measured by targeted metabolomics Biocrates MxP® Quant 500 Kit at baseline and 8-week follow-up.

Results

After 8  weeks of risperidone treatment, the levels of 48 differential metabolites were upregulated, including lysophosphatidylcholines (2), phosphatidylcholines (PC) (8), cholesteryl esters (CE) (3), and triglycerides (35), while 6 differential metabolites namely PC aa C38:6, methionine (Met), α-aminobutyric acid (AABA), TrpBetaine, CE (22:6), and Taurocholic acid (TCA) were downregulated. Interestingly, the reduction of PC aa C38:6, AABA and CE (22:6) was linearly related with increased BMI. Further multiple regression analysis showed that the changes of PC aa C38:6 and AABA were independent contributors of increased BMI. In addition, baseline levels of PC aa C36:5, CE (20:5) and AABA had positive relationships with the change of BMI.

Conclusion

Our findings indicate phosphatidylcholines and amino acids may serve as biomarkers for risperidone-induced weight gain.

Potential Plasma Metabolic Biomarkers of Tourette Syndrome Discovery Based on Integrated Nontargeted and Targeted Metabolomics Screening Plasma Metabolic Biomarkers of TS

Objective

Tourette syndrome (TS) is a chronic neuropsychiatric disorder characterized by abnormal movements, phonations, and tics, but an accurate TS diagnosis remains challenging and indeed depends on its description of clinical symptoms. Our study was conducted to discover and verify some metabolite biomarkers based on nontargeted and targeted metabolomics.

Methods

We conducted untargeted ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) for preliminary screening of potential biomarkers on 30 TS patients and 10 healthy controls and then performed validation experiments based on targeted ultrahigh-performance liquid chromatography triple quadrupole-MS (UHPLC/MS/MS) on 35 TS patients and 14 healthy controls.

Results

1775 differentially expressed metabolites were identified by partial least squares discriminant analysis (PLS-DA), fold-change analysis, T-test, and hierarchical clustering analysis (adjusted p value <0.05 and |logFC| > 1). TS plasma samples were found to be differentiated from healthy samples in our approach. Furthermore, aspartate and asparagine metabolism pathways were considered to be a significant enrichment pathway in TS progression based on metabolite pathway enrichment analysis. For the 8 metabolites involved in this pathway that we detected, we then performed validation experiments based on targeted UHPLC/MS/MS. The t-test, Mann-Whitney U test, and receiver operating characteristic (ROC) curve analysis were used to determine potential biomarkers. Ultimately, L-arginine and L-pipecolic acid were validated as significantly differentiated metabolites (p < 0.05), with an AUC of 70.0% and 80.3%, respectively.

Conclusion

L-pipecolic acid was defined as a potential biomarker for TS diagnosis by the combined application of nontargeted and targeted metabolomic analysis.

Plasma linoelaidyl carnitine levels positively correlated with symptom improvement in olanzapine-treated first-episode drug-naïve schizophrenia

INTRODUCTION

Olanzapine (OLA) is one of the most commonly used second-generation antipsychotics for the treatment of schizophrenia. However, the heterogeneity of therapeutic response to OLA among schizophrenia patients deserves further exploration. The role of carnitine in the clinical response to OLA monotherapy remains unclear.

OBJECTIVES

The current study was designed to investigate whether carnitine and its derivatives are linked to the response to OLA treatment. Drug-naïve first-episode patients with schizophrenia were recruited and treated with OLA for 4 weeks. Psychiatric symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS) in pre and post treatment.

RESULTS

After treatment, we found a significant decrease in 2-Octenoylcarnitine levels and a significant increase in linoelaidyl carnitine, 11Z-Octadecenylcarnitine and 9-Decenoylcarnitine levels. Furthermore, baseline linoelaidyl carnitine levels were correlated with the reduction of PANSS positive symptom subscore. Linear regression and logistic regression analyses found that the baseline linoelaidyl carnitine level was a predictive marker for the therapeutic response to OLA monotherapy for 4 weeks.

CONCLUSION

Our pilot study suggests that linoelaidyl carnitine levels at baseline may have a predictive role for the improvement of positive symptoms after OLA monotherapy in the patients with schizophrenia.

Identification of cerebrospinal fluid and serum metabolomic biomarkers in first episode psychosis patients

Psychotic disorders are currently diagnosed by examining the patient's mental state and medical history. Identifying reliable diagnostic, monitoring, predictive, or prognostic biomarkers would be useful in clinical settings and help to understand the pathophysiology of schizophrenia. Here, we performed an untargeted metabolomics analysis using ultra-high pressure liquid chromatography coupled with time-of-flight mass spectroscopy on cerebrospinal fluid (CSF) and serum samples of 25 patients at their first-episode psychosis (FEP) manifestation (baseline) and after 18 months (follow-up). CSF and serum samples of 21 healthy control (HC) subjects were also analyzed. By comparing FEP and HC groups at baseline, we found eight CSF and 32 serum psychosis-associated metabolites with non-redundant identifications. Most remarkable was the finding of increased CSF serotonin (5-HT) levels. Most metabolites identified at baseline did not differ between groups at 18-month follow-up with significant improvement of positive symptoms and cognitive functions. Comparing FEP patients at baseline and 18-month follow-up, we identified 20 CSF metabolites and 90 serum metabolites that changed at follow-up. We further utilized Ingenuity Pathway Analysis (IPA) and identified candidate signaling pathways involved in psychosis pathogenesis and progression. In an extended cohort, we validated that CSF 5-HT levels were higher in FEP patients than in HC at baseline by reversed-phase high-pressure liquid chromatography. To conclude, these findings provide insights into the pathophysiology of psychosis and identify potential psychosis-associated biomarkers.

Metabolomics mapping changed after olanzapine therapy in drug-naive schizophrenia patients—the significant impact of gene polymorphisms

Oxidative stress may contribute to the development of schizophrenia and antipsychotics used in schizophrenia treatment may also cause oxidative stress. Gene polymorphisms on antioxidant and repair enzymes are responsible for individual variations and may change the efficacy of olanzapine treatment among schizophrenia patients. In our study, we assessed oxidative stress-related metabolite changes due to genetic polymorphisms on first diagnosed-schizophrenia patients treated with olanzapine. Blood samples (n = 30 patients) were taken before treatment (T1), after 10 ± 1 days (T2), and after 3 ± 1 months (T3). T1 served as control for T2 and T3, since it is advantageous to perform on same patient to evaluate the impact of olanzapine only. GSTs (GSTM1, GSTT1, and GSTP1) and OGG1 gene polymorphisms were analyzed by polymerase chain reaction. Changes in metabolites were detected with metabolomics profiling by gas chromatography–mass spectrometry according to each genotype before and after treatment. Multivariate analysis showed that metabolomics profiles differed after olanzapine treatment regardless gene polymorphisms. Tryptophan could be a biomarker in response to olanzapine treatment since its levels were increased after treatment. GSTM1 gene polymorphism caused significant changes in some metabolites after treatment. Urea, palmitic acid, and caprylic acid levels increased and alanine levels decreased in patients with GSTM1 null genotypes after olanzapine. In future, targeted metabolomics with these prominent metabolites and assessing gene expressions of GSTs will be beneficial to understand the mechanism of action.

Reduced erythrocyte membrane polyunsaturated fatty acid levels indicate diminished treatment response in patients with multi- versus first-episode schizophrenia

Antipsychotic effects seem to decrease in relapsed schizophrenia patients and the underlying mechanisms remain to be elucidated. Based on the essential role of polyunsaturated fatty acids in brain function and the treatment of schizophrenia, we hypothesize that disordered fatty acid metabolism may contribute to treatment resistance in multi-episode patients. We analyzed the erythrocyte membrane fatty acids in 327 schizophrenia patients under various episodes (numbers of patients: first-episode drug naïve 89; 2–3 episodes 110; 4–6 episodes 80; over 6 episodes 48) and 159 age- and gender-matched healthy controls. Membrane fatty acid levels and PANSS scales were assessed at baseline of antipsychotic-free period and one-month of follow-up after treatment. Totally, both saturated and unsaturated fatty acids were reduced at baseline when compared to healthy controls. Subgroup analyses among different episodes indicated that in response to atypical antipsychotic treatment, the membrane fatty acids were only increased in patients within 3 episodes, and this therapeutic effects on omega-3 index were merely present in the first episode. Results of fatty acid ratios suggested that dysregulations of enzymes such as D6 desaturase, D5 desaturase, and elongases for polyunsaturated fatty acids in patients with multi-episode schizophrenia could account for the differences. Additionally, certain fatty acid level/ratio changes were positively correlated with symptom improvement. The alterations of C22:5n3 and omega-3 index, gender, and the number of episodes were significant risk factors correlated with treatment responsiveness. Using targeted metabolomic approach, we revealed the potential mechanisms underlying abnormal fatty acid metabolism responsible for reduced treatment response in patients with multi-episode schizophrenia.

Profiling the Skeletal Muscle Proteome in Patients on Atypical Antipsychotics and Mood Stabilizers

Atypical antipsychotics (AAP) are used in the treatment of severe mental illness. They are associated with several metabolic side effects including insulin resistance. The skeletal muscle is the primary tissue responsible for insulin-stimulated glucose uptake. Dysfunction of protein regulation within the skeletal muscle following treatment with AAPs may play a role in the associated metabolic side effects. The objective of this study was to measure protein abundance in the skeletal muscle of patients on long-term AAP or mood stabilizer treatment. Cross-sectional muscle biopsies were obtained from patients with bipolar disorder and global protein abundance was measured using stable isotope labeling by amino acid (SILAC) combined with high-performance liquid chromatography-electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). Sixteen patients completed muscle biopsies and were included in the proteomic analyses. A total of 40 proteins were significantly different between the AAP group and the mood stabilizer group. In-silico pathway analysis identified significant enrichment in several pathways including glucose metabolism, cell cycle, apoptosis, and folate metabolism. Proteome abundance changes also differed based on protein biological processes and function. In summary, significant differences in proteomic profiles were identified in the skeletal muscle between patients on AAPs and mood stabilizers. Future work is needed to validate these findings in prospectively sampled populations.

Small phenolic and indolic gut-dependent molecules in the primate central nervous system: levels vs. bioactivity

INTRODUCTION

A rapidly growing body of data documents associations between disease of the brain and small molecules generated by gut-microbiota (GMB). While such metabolites can affect brain function through a variety of mechanisms, the most direct action would be on the central nervous system (CNS) itself.

OBJECTIVE

Identify indolic and phenolic GMB-dependent small molecules that reach bioactive concentrations in primate CNS.

METHODS

We conducted a PubMed search for metabolomic studies of the primate CNS [brain tissue or cerebrospinal fluid (CSF)] and then selected for phenolic or indolic metabolites that (i) had been quantified, (ii) were GMB-dependent. For each chemical we then conducted a search for studies of bioactivity conducted in vitro in human cells of any kind or in CNS cells from the mouse or rat.

RESULTS

36 metabolites of interests were identified in primate CNS through targeted metabolomics. Quantification was available for 31/36 and in vitro bioactivity for 23/36. The reported CNS range for 8 metabolites 2-(3-hydroxyphenyl)acetic acid, 2-(4-hydroxyphenyl)acetic acid, 3-(3-hydroxyphenyl)propanoic acid, (E)-3-(3,4-dihydroxyphenyl)prop-2-enoic acid [caffeic acid], 3-hydroxybenzoic acid, 4-hydroxybenzoic acid, 2-acetamido-3-(1H-indol-3-yl)propanoic acid [N-acetyltryptophan], 1H-indol-3-yl hydrogen sulfate [indoxyl-3-sulfate] overlapped with a bioactive concentration. However, the number and quality of relevant studies of CNS neurochemistry as well as of bioactivity were highly limited. Structural isomers, multiple metabolites and potential confounders were inadequately considered.

CONCLUSION

The potential direct bioactivity of GMB-derived indolic and phenolic molecules on primate CNS remains largely unknown. The field requires additional strategies to identify and prioritize screening of the most promising small molecules that enter the CNS.

Current State of Fluid Lipid Biomarkers for Personalized Diagnostics and Therapeutics in Schizophrenia Spectrum Disorders and Related Psychoses: A Narrative Review

Schizophrenia spectrum disorders (SSD) are traditionally diagnosed and categorized through clinical assessment, owing to their complex heterogeneity and an insufficient understanding of their underlying pathology. However, disease progression and accurate clinical diagnosis become problematic when differentiating shared aspects amongst mental health conditions. Hence, there is a need for widely accessible biomarkers to identify and track the neurobiological and pathophysiological development of mental health conditions, including SSD. High-throughput omics applications involving the use of liquid chromatography-mass spectrometry (LC-MS) are driving a surge in biological data generation, providing systems-level insight into physiological and pathogenic conditions. Lipidomics is an emerging subset of metabolomics, largely underexplored amongst the omics systems. Lipid profiles in the brain are highly enriched with well-established functions, including maintenance, support, and signal transduction of neuronal signaling pathways, making them a prospective and exciting source of biological material for neuropsychiatric research. Importantly, changes in the lipid composition of the brain appear to extend into the periphery, as there is evidence that circulating lipid alterations correlate with alterations of psychiatric condition(s). The relative accessibility of fluid lipids offers a unique source to acquire a lipidomic "footprint" of molecular changes, which may support reliable diagnostics even at early disease stages, prediction of treatment response and monitoring of treatment success (theranostics). Here, we summarize the latest fluid lipidomics discoveries in SSD-related research, examining the latest strategies to integrate information into multi-systems overviews that generate new perspectives of SSD-related psychosis identification, development, and treatment.

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.

UPLC-MS-Based Serum Metabolic Profiling Reveals Potential Biomarkers for Predicting Propofol Responsiveness in Females

Although previous studies have shown that certain factors interfere with the sensitivity of propofol, the mechanisms for interindividual variability in response to propofol remain unclear. This study aimed to screen the metabolites to predict patients' sensitivity to propofol and to identify metabolic pathways to explore possible mechanisms associated with propofol resistance. Sera from 40 female patients undergoing elective hysteroscopic surgery in a prospective cohort propofol study were obtained before the administration of propofol. The patients' responsiveness to propofol was differentiated based on propofol effect-site concentration. Serum samples from two sets, a discovery set (n = 24) and an independent validation set (n = 16), were analyzed using ultraperformance liquid chromatography coupled with mass spectrometry based untargeted metabolomics. In the discovery set, 494 differential metabolites were screened out, and then 391 potential candidate biomarkers with the area under receiver operating characteristic curve >0.80 were selected. Pathway analysis showed that the pathway of glycerophospholipid metabolism was the most influential pathway. In the independent validation set, six potential biomarkers enabled the discrimination of poor responders from good and intermediate responders, which might be applied to predict propofol sensitivity. The mass spectrometry data are available via MetaboLights (http://www.ebi.ac.uk/metabolights/login) with the identifier MTBLS2311.

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.

[Schizophrenia and cardiometabolic disorders]

The aim of this review is to analyze the basic biological mechanisms of comorbidity of schizophrenia and metabolic, cardiovascular diseases, which are not directly associated with external risk factors. The study of the general pathophysiological mechanisms of schizophrenia and metabolic disorders can provide a significant basis not only for the fundamentally novel therapeutic, preventive and diagnostic measures, but also for a better understanding of the etiopathogenesis of these diseases. It seems likely that schizophrenia represents a heterogeneous group with a varying genetic basis for both mental symptoms and neuroendocrine, inflammatory processes that form concomitant somatic disorders. Thus, the new integrated approaches to the study of this problem with the latest methods of genetic and molecular research are relevant.

The Antipsychotic Risperidone Alters Dihydroceramide and Ceramide Composition and Plasma Membrane Function in Leukocytes In Vitro and In Vivo

Atypical or second-generation antipsychotics are used in the treatment of psychosis and behavioral problems in older persons with dementia. However, these pharmaceutical drugs are associated with an increased risk of stroke in such patients. In this study, we evaluated the effects of risperidone treatment on phospholipid and sphingolipid composition and lipid raft function in peripheral blood mononuclear cells (PBMCs) of older patients (mean age >88 years). The results showed that the levels of dihydroceramides, very-long-chain ceramides, and lysophosphatidylcholines decreased in PBMCs of the risperidone-treated group compared with untreated controls. These findings were confirmed by in vitro assays using human THP-1 monocytes. The reduction in the levels of very-long-chain ceramides and dihydroceramides could be due to the decrease in the expression of fatty acid elongase 3, as observed in THP-1 monocytes. Moreover, risperidone disrupted lipid raft domains in the plasma membrane of PBMCs. These results indicated that risperidone alters phospholipid and sphingolipid composition and lipid raft domains in PBMCs of older patients, potentially affecting multiple signaling pathways associated with these membrane domains.

Characterising phospholipids and free fatty acids in patients with schizophrenia: A case-control study

OBJECTIVES

Previous studies have indicated that schizophrenia (SCZ) is linked to abnormal phospholipid and fatty acid metabolism. However, comprehensive analysis of phospholipids and free fatty acids (FFAs) for SCZ is very limited. Herein, we sought to compare serum levels of phospholipids and FFAs between patients with SCZ and healthy controls (HCs).

METHODS

One hundred and nineteen SCZ patients and 109 HCs were enrolled in the study. The levels of 177 phospholipids and FFAs were measured in serum samples using a targeted liquid chromatography-mass spectrometry (LC-MS)-based platform.

RESULTS

One hundred and ten metabolites, including 16 FFAs, 25 phosphatidylcholines, 23 lysophosphatidylcholines, 11 phosphatidylcholine plasmalogens, 7 phosphatidylethanolamines, 9 lysophosphatidylethanolamines, 6 phosphatidylethanolamine plasmalogens, and 13 sphingomyelins, were observed to be significantly altered in SCZ patients compared to HCs. These disturbances may represent underlying pathophysiology, including but not limited to altered activity of phospholipases and acyltransferases, increased oxidative stress, dysfunctional oligodendrocyte glycosynapses, and elevated lipid mobilisation and β-oxidation.

CONCLUSIONS

Our findings suggest that complex lipid profile abnormalities are associated with SCZ. This study may contribute to investigating the role of phospholipid and FFA alterations in the pathoetiology of SCZ.

Effects of Psychostimulants and Antipsychotics on Serum Lipids in an Animal Model for Schizophrenia

Schizophrenia (SCZ) treatment is essentially limited to the use of typical or atypical antipsychotic drugs, which suppress the main symptoms of this mental disorder. Metabolic syndrome is often reported in patients with SCZ under long-term drug treatment, but little is known about the alteration of lipid metabolism induced by antipsychotic use. In this study, we evaluated the blood serum lipids of a validated animal model for SCZ (Spontaneously Hypertensive Rat, SHR), and a normal control rat strain (Normotensive Wistar Rat, NWR), after long-term treatment (30 days) with typical haloperidol (HAL) or atypical clozapine (CLZ) antipsychotics. Moreover, psychostimulants, amphetamine (AMPH) or lisdexamfetamine (LSDX), were administered to NWR animals aiming to mimic the human first episode of psychosis, and the effects on serum lipids were also evaluated. Discrepancies in lipids between SHR and NWR animals, which included increased total lipids and decreased phospholipids in SHR compared with NWR, were similar to the differences previously reported for SCZ patients relative to healthy controls. Administration of psychostimulants in NWR decreased omega-3, which was also decreased in the first episode of psychosis of SCZ. Moreover, choline glycerophospholipids allowed us to distinguish the effects of CLZ in SHR. Thus, changes in the lipid metabolism in SHR seem to be reversed by the long-term treatment with the atypical antipsychotic CLZ, which was under the same condition described to reverse the SCZ-like endophenotypes of this validated animal model for SCZ. These data open new insights for understanding the potential influence of the treatment with typical or atypical antipsychotics on circulating lipids. This may represent an outcome effect from metabolic pathways that regulate lipids synthesis and breakdown, which may be reflecting a cell lipids dysfunction in SCZ.

Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations

The study of metabolomics and disease has enabled the discovery of new risk factors, diagnostic markers, and drug targets. For neurological and psychiatric phenotypes, the cerebrospinal fluid (CSF) is of particular importance. However, the CSF metabolome is difficult to study on a large scale due to the relative complexity of the procedure needed to collect the fluid. Here, we present a metabolome-wide association study (MWAS), which uses genetic and metabolomic data to impute metabolites into large samples with genome-wide association summary statistics. We conduct a metabolome-wide, genome-wide association analysis with 338 CSF metabolites, identifying 16 genotype-metabolite associations (metabolite quantitative trait loci, or mQTLs). We then build prediction models for all available CSF metabolites and test for associations with 27 neurological and psychiatric phenotypes, identifying 19 significant CSF metabolite-phenotype associations. Our results demonstrate the feasibility of MWAS to study omic data in scarce sample types.

Identification of biomarkers to diagnose diseases and find adverse drug reactions by metabolomics

Metabolomics has been widely used for investigating the biological functions of disease expression and has the potential to discover biomarkers in circulating biofluids or tissue extracts that reflect in phenotypic changes. Metabolic profiling has advantages because of the use of unbiased techniques, including multivariate analysis, and has been applied in pharmacological studies to predict therapeutic and adverse reactions of drugs, which is called pharmacometabolomics (PMx). Nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based metabolomics has contributed to the discovery of recent disease biomarkers; however, the optimal strategy for the study purpose must be selected from many established protocols, methodologies and analytical platforms. Additionally, information on molecular localization in tissue is essential for further functional analyses related to therapeutic and adverse effects of drugs in the process of drug development. MS imaging (MSI) is a promising technology that can visualize molecules on tissue surfaces without labeling and thus provide localized information. This review summarizes recent uses of MS-based global and wide-targeted metabolomics technologies and the advantages of the MSI approach for PMx and highlights the PMx technique for the biomarker discovery of adverse drug effects.

Plasma amino acids profile in first-episode psychosis, unaffected siblings and community-based controls

Investigations of plasma amino acids in early psychosis and their unaffected siblings are rare. We measured plasma amino acids involved in the co-activation of dopaminergic, GABAergic, glutamatergic, and serotoninergic neurotransmitters in first-episode psychosis (FEP) patients (n = 166), unaffected siblings (n = 76), and community-based controls (n = 166) included in a cross-sectional study. Plasma levels of glutamic acid (GLU), glutamine, glycine, proline (PRO), tryptophan (TRP), tyrosine, serine and GABA were quantified by gas-chromatography-mass spectrometry. We used the generalized linear model adjusted by sex, age, and body mass index for group comparison and paired t-test for FEP-Sibling pairs. FEP had reduced GABA plasma levels compared to siblings and controls (p < 0.05 for both). Siblings had lower GLU, Glx and PRO (p < 0.05 for all) but increased TRP compared to patients and controls (p < 0.05 for both). FEP patients with longer duration of pharmacological treatment and medicated only with antipsychotics had increased GLU compared to FEP with shorter periods, or with those treated with a combination of medications (p < 0.05 for both). Finally, FEP patients treated only with antipsychotics presented higher Glx compared to those with mixed medications (p = 0.026). Our study suggests that FEP have low a GABA plasma profile. Unaffected siblings may be a possible risk group for metabolic abnormalities.

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.

Big data in severe mental illness: the role of electronic monitoring tools and metabolomics

There is an increasing interest in the development of effective early detection and intervention strategies in severe mental illness (SMI). Ideally, these efforts should lead to the delineation of accurate staging models of SMI enabling personalized interventions. It is plausible that big data approaches will be instrumental in describing the developmental trajectories of SMI by facilitating the incorporation of data from multiple sources, including those pertaining to the biological make-up of affected subjects. In this review, we first aimed to offer a perspective on how big data are helping the delineation of personalized approaches in SMI, and, second, to offer a quantitative synthesis of big data approaches in metabolomics of SMI. We finally described future directions of this research area.

Metabolomic profiles associated with a mouse model of antipsychotic-induced food intake and weight gain

Antipsychotic drugs (AP) are used to treat a multitude of psychiatric conditions including schizophrenia and bipolar disorder. However, APs also have metabolic side effects including increased food intake and body weight, but the underlying mechanisms remain unknown. We previously reported that minocycline (MINO) co-treatment abrogates olanzapine (OLZ)-induced hyperphagia and weight gain in mice. Using this model, we investigated the changes in the pharmacometabolome in the plasma and hypothalamus associated with OLZ-induced hyperphagia and weight gain. Female C57BL/6 mice were divided into groups and fed either i) control, CON (45% fat diet) ii) CON + MINO, iii) OLZ (45% fat diet with OLZ), iv) OLZ + MINO. We identified one hypothalamic metabolite indoxylsulfuric acid and 389 plasma metabolites (including 19 known metabolites) that were specifically associated with AP-induced hyperphagia and weight gain in mice. We found that plasma citrulline, tricosenoic acid, docosadienoic acid and palmitoleic acid were increased while serine, asparagine and arachidonic acid and its derivatives were decreased in response to OLZ. These changes were specifically blocked by co-treatment with MINO. These pharmacometabolomic profiles associated with AP-induced hyperphagia and weight gain provide candidate biomarkers and mechanistic insights related to the metabolic side effects of these widely used drugs.

Links between central CB1-receptor availability and peripheral endocannabinoids in patients with first episode psychosis

There is an established, link between psychosis and metabolic abnormalities, such as altered glucose metabolism and dyslipidemia, which often precede the initiation of antipsychotic treatment. It is known that obesity-associated metabolic disorders are promoted by activation of specific cannabinoid targets (endocannabinoid system (ECS)). Our recent data suggest that there is a change in the circulating lipidome at the onset of first episode psychosis (FEP). With the aim of characterizing the involvement of the central and peripheral ECSs, and their mutual associations; here, we performed a combined neuroimaging and metabolomic study in patients with FEP and healthy controls (HC). Regional brain cannabinoid receptor type 1 (CB1R) availability was quantified in two, independent samples of patients with FEP (n = 20 and n = 8) and HC (n = 20 and n = 10), by applying three-dimensional positron emission tomography, using two radiotracers, [¹¹C]MePPEP and [¹⁸F]FMPEP-d2. Ten endogenous cannabinoids or related metabolites were quantified in serum, drawn from these individuals during the same imaging session. Circulating levels of arachidonic acid and oleoylethanolamide (OEA) were reduced in FEP individuals, but not in those who were predominantly medication free. In HC, there was an inverse association between levels of circulating arachidonoyl glycerol, anandamide, OEA, and palmitoyl ethanolamide, and CB1R availability in the posterior cingulate cortex. This phenomenon was, however, not observed in FEP patients. Our data thus provide evidence of cross talk, and dysregulation between peripheral endocannabinoids and central CB1R availability in FEP.

Changes in the blood plasma lipidome associated with effective or poor response to atypical antipsychotic treatments in schizophrenia patients

Atypical antipsychotics are widely used to manage schizophrenia symptoms. However, these drugs can induce deleterious side effects, such as MetS, which are associated with an increased cardiovascular risk to patients. Lipids play a central role in this context, and changes in lipid metabolism have been implicated in schizophrenia's pathobiology. Furthermore, recent evidence suggests that lipidome changes may be related to antipsychotic treatment response. The aim of this study was to evaluate the lipidome changes in blood plasma samples of schizophrenia patients before and after 6 weeks of treatment with either risperidone, olanzapine, or quetiapine. Liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis showed changes in the levels of ceramides (Cer), glycerophosphatidic acids (PA), glycerophosphocholines (PC), phosphatidylethanolamines (PE), phosphatidylinositols (PI), glycerophosphoglycerols (PG), and phosphatidylserines (PS) for all treatments. However, the treatment with risperidone also affected diacylglycerides (DG), ceramide 1-phosphates (CerP), triglycerides (TG), sphingomyelins (SM), and ceramide phosphoinositols (PI-Cer). Moreover, specific lipid profiles were observed that could be used to distinguish poor and good responders to the different antipsychotics. As such, further work in this area may lead to lipid-based biomarkers that could be used to improve the clinical management of schizophrenia patients.

Metabolic profiling for water-soluble metabolites in patients with schizophrenia and healthy controls in a Chinese population: A case-control study

Objectives: Objective measures integrated with clinical symptoms may improve early prevention and detection of schizophrenia. Herein we aim to evaluate potential water-soluble metabolic biomarkers in schizophrenia.Methods: We recruited adults with schizophrenia (n = 113) who had not received pharmacological treatment for at least 1 month prior to enrollment and 111 age- and sex-matched healthy subjects from Weifang, Shandong province, China. All serum samples were analysed using liquid chromatography-tandem mass spectrometry coupled with a hydrophilic interaction liquid chromatography column.Results: Eleven metabolites, namely carnitines (oleoylcarnitine, l-palmitoylcarnitine, 9-decenoylcarnitine and 2-trans,4-cis-decadienoylcarnitine), polar lipids (lysophosphatidylcholine (LPC)(P-16:0), LPC (16:0), LPC (15:0) and LPC(14:0)), amino acids (taurine and l-arginine), and organic acid (2,5-dichloro-4-oxohex-2-enedioate), separated the patients and healthy controls. Compared with healthy controls, taurine, l-palmitoylcarnitine and oleoylcarnitine levels were higher, whereas the remaining eight metabolites were lower in patients with schizophrenia. A combination of four metabolites, i.e., oleoylcarnitine, 9-decenoylcarnitine, LPC (15:0) and LPC (14:0), provided the most robust between-group separation.Conclusions: This study appears to distinguish between groups of patients and controls, which should be considered as a contribution to putative potential biomarkers. The water-soluble metabolites were determined to be significantly different between the groups in the current study, and were primarily related to cellular bioenergetics, notably oxidative stress.

Genetic Influence on Efficacy of Pharmacotherapy for Pediatric Attention-Deficit/Hyperactivity Disorder: Overview and Current Status of Research

Multiple stimulant and non-stimulant medications are approved for the treatment of attention-deficit/hyperactivity disorder (ADHD), one of the most prevalent childhood neurodevelopmental disorders. Choosing among the available agents and determining the most effective ADHD medication for a given child can be a time-consuming process due to the high inter-individual variability in treatment efficacy. As a result, there is growing interest in identifying predictors of ADHD medication response in children through the burgeoning field of pharmacogenomics. This article reviews childhood ADHD pharmacogenomics efficacy studies published during the last decade (2009-2019), which have largely focused on pharmacodynamic candidate gene investigations of methylphenidate and atomoxetine response, with a smaller number investigating pharmacokinetic candidate genes and genome-wide approaches. Findings from studies which have advanced the field of ADHD pharmacogenomics through investigation of meta-analytic approaches and gene-gene interactions are also overviewed. Despite recent progress, no one genetic variant or currently available pharmacogenomics test has demonstrated clinical utility in pinpointing the optimal ADHD medication for a given individual patient, highlighting the need for further investigation.

Current Concepts in Pharmacometabolomics, Biomarker Discovery, and Precision Medicine

Pharmacometabolomics (PMx) studies use information contained in metabolic profiles (or metabolome) to inform about how a subject will respond to drug treatment. Genome, gut microbiome, sex, nutrition, age, stress, health status, and other factors can impact the metabolic profile of an individual. Some of these factors are known to influence the individual response to pharmaceutical compounds. An individual’s metabolic profile has been referred to as his or her “metabotype.” As such, metabolomic profiles obtained prior to, during, or after drug treatment could provide insights about drug mechanism of action and variation of response to treatment. Furthermore, there are several types of PMx studies that are used to discover and inform patterns associated with varied drug responses (i.e., responders vs. non-responders; slow or fast metabolizers). The PMx efforts could simultaneously provide information related to an individual’s pharmacokinetic response during clinical trials and be used to predict patient response to drugs making pharmacometabolomic clinical research valuable for precision medicine. PMx biomarkers can also be discovered and validated during FDA clinical trials. Using biomarkers during medical development is described in US Law under the 21st Century Cures Act. Information on how to submit biomarkers to the FDA and their context of use is defined herein.

Metabolomics in pharmacology - a delve into the novel field of pharmacometabolomics

Introduction: Pharmacometabolomics is an emerging science pursuing the application of precision medicine. Combining both genetic and environmental factors, the so-called pharmacometabolomic approach guides patient selection and stratification in clinical trials and optimizes personalized drug dosage, improving efficacy and safety.Areas covered: This review illustrates the progressive introduction of pharmacometabolomics as an innovative solution for enhancing the discovery of novel drugs and improving research and development (R&D) productivity of the pharmaceutical industry. An extended analysis on published pharmacometabolomics studies both in animal models and humans includes results obtained in several areas such as hepatology, gastroenterology, nephrology, neuropsychiatry, oncology, drug addiction, embryonic cells, neonatology, and microbiomics.Expert opinion: a tailored, individualized therapy based on the optimization of pharmacokinetics and pharmacodynamics, the improvement of drug efficacy, and the abolition of drug toxicity and adverse drug reactions is a key issue in precision medicine. Genetics alone has become insufficient for deciphring intra- and inter-individual variations in drug-response, since they originate both from genetic and environmental factors, including human microbiota composition. The association between pharmacogenomics and pharmacometabolomics may be considered the new strategy for an in-deep knowledge on changes and alterations in human and microbial metabolic pathways due to the action of a drug.

A targeted neurotransmitter quantification and nontargeted metabolic profiling method for pharmacometabolomics analysis of olanzapine by using UPLC-HRMS

Neurotransmitters (NTs) are specific endogenous metabolites that act as “messengers” in synaptic transmission and are widely distributed in the central nervous system. Olanzapine (OLZ), a first-line antipsychotic drug, plays a key role in sedation and hypnosis, but, it presents clinical problems with a narrow therapeutic window, large individual differences and serious adverse effects, as well as an unclear mechanism in vivo. Herein, a simultaneous targeted NT quantification and nontargeted metabolomics method was developed and validated for pharmacometabolomics analysis of OLZ by using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UPLC-HRMS). Considering the low physiological concentrations of NTs, a full MS scan and target selective ion monitoring (tSIM) scan were combined for nontargeted metabolomics and targeted NT quantification, respectively. By using this strategy, NTs at a very low physiological concentration can be accurately detected and quantified in biological samples by tSIM scans. Moreover, simultaneously nontargeted profiling was also achieved by the full MS scan. The newly established UPLC-HRMS method was further used for the pharmacometabolomics study of OLZ. Statistical analysis revealed that tryptophan, 5-hydroxytryptophan, 5-hydroxytryptamine, γ-aminobutyric acid etc. were significantly downregulated, while tyrosine was significantly upregulated, which suggested that OLZ could promote the downstream phase II reaction of 5-hydroxytryptamine, inhibit tyrosine hydroxylase activity, and increase the activity of γ-aminobutyric acid transaminase. In conclusion, this method could provide novel insights for revealing the pharmacodynamic effect and mechanism of antipsychotic drugs.

We developed a method that would provide novel insights for revealing the pharmacodynamic effect and mechanism of antipsychotic drugs (olanzapine).

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.

Lipidome alterations in human prefrontal cortex during development, aging, and cognitive disorders

Lipids are essential to brain functions, yet they remain largely unexplored. Here we investigated the lipidome composition of prefrontal cortex gray matter in 396 cognitively healthy individuals with ages spanning 100 years, as well as 67 adult individuals diagnosed with autism (ASD), schizophrenia (SZ), and Down syndrome (DS). Of the 5024 detected lipids, 95% showed significant age-dependent concentration differences clustering into four temporal stages, and resulting in a gradual increase in membrane fluidity in individuals ranging from newborn to nonagenarian. Aging affects 14% of the brain lipidome with late-life changes starting predominantly at 50-55 years of age-a period of general metabolic transition. All three diseases alter the brain lipidome composition, leading-among other things-to a concentration decrease in glycerophospholipid metabolism and endocannabinoid signaling pathways. Lipid concentration decreases in SZ were further linked to genetic variants associated with disease, indicating the relevance of the lipidome changes to disease progression.

Exploring mechanisms of increased cardiovascular disease risk with antipsychotic medications: Risperidone alters the cardiac proteomic signature in mice

Atypical antipsychotic (AA) medications including risperidone (RIS) and olanzapine (OLAN) are FDA approved for the treatment of psychiatric disorders including schizophrenia, bipolar disorder and depression. Clinical side effects of AA medications include obesity, insulin resistance, dyslipidemia, hypertension and increased cardiovascular disease risk. Despite the known pharmacology of these AA medications, the mechanisms contributing to adverse metabolic side-effects are not well understood. To evaluate drug-associated effects on the heart, we assessed changes in the cardiac proteomic signature in mice administered for 4 weeks with clinically relevant exposure of RIS or OLAN. Using proteomic and gene enrichment analysis, we identified differentially expressed (DE) proteins in both RIS- and OLAN-treated mouse hearts (p < 0.05), including proteins comprising mitochondrial respiratory complex I and pathways involved in mitochondrial function and oxidative phosphorylation. A subset of DE proteins identified were further validated by both western blotting and quantitative real-time PCR. Histological evaluation of hearts indicated that AA-associated aberrant cardiac gene expression occurs prior to the onset of gross pathomorphological changes. Additionally, RIS treatment altered cardiac mitochondrial oxygen consumption and whole body energy expenditure. Our study provides insight into the mechanisms underlying increased patient risk for adverse cardiac outcomes with chronic treatment of AA medications.

Metabolomic signature of exposure and response to citalopram/escitalopram in depressed outpatients

Metabolomics provides valuable tools for the study of drug effects, unraveling the mechanism of action and variation in response due to treatment. In this study we used electrochemistry-based targeted metabolomics to gain insights into the mechanisms of action of escitalopram/citalopram focusing on a set of 31 metabolites from neurotransmitter-related pathways. Overall, 290 unipolar patients with major depressive disorder were profiled at baseline, after 4 and 8 weeks of drug treatment. The 17-item Hamilton Depression Rating Scale (HRSD17) scores gauged depressive symptom severity. More significant metabolic changes were found after 8 weeks than 4 weeks post baseline. Within the tryptophan pathway, we noted significant reductions in serotonin (5HT) and increases in indoles that are known to be influenced by human gut microbial cometabolism. 5HT, 5-hydroxyindoleacetate (5HIAA), and the ratio of 5HIAA/5HT showed significant correlations to temporal changes in HRSD17 scores. In the tyrosine pathway, changes were observed in the end products of the catecholamines, 3-methoxy-4-hydroxyphenylethyleneglycol and vinylmandelic acid. Furthermore, two phenolic acids, 4-hydroxyphenylacetic acid and 4-hydroxybenzoic acid, produced through noncanconical pathways, were increased with drug exposure. In the purine pathway, significant reductions in hypoxanthine and xanthine levels were observed. Examination of metabolite interactions through differential partial correlation networks revealed changes in guanosine-homogentisic acid and methionine-tyrosine interactions associated with HRSD17. Genetic association studies using the ratios of these interacting pairs of metabolites highlighted two genetic loci harboring genes previously linked to depression, neurotransmission, or neurodegeneration. Overall, exposure to escitalopram/citalopram results in shifts in metabolism through noncanonical pathways, which suggest possible roles for the gut microbiome, oxidative stress, and inflammation-related mechanisms.

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.

Reverting Metabolic Dysfunction in Cortex and Cerebellum of APP/PS1 Mice, a Model for Alzheimer's Disease by Pioglitazone, a Peroxisome Proliferator-Activated Receptor Gamma (PPARγ) Agonist

Identification of molecular mechanisms underlying early-stage Alzheimer's disease (AD) is important for the development of new therapies against and diagnosis of AD. In this study, gas chromatography time-of-flight mass spectrometry (GC-TOF-MS)-based metabolomics approach was employed to investigate the metabolic profiles in plasma and brain tissues harvested from 5-month-old APP/PS1 transgenic mice and their wildtype counterparts. Since different brain regions were expected to have their own distinct metabolic signals, four different brain regions, namely cortex, hippocampus, midbrain and cerebellum tissues, were dissected and had their metabolic profiles studied separately. Biochemical assays were also performed on plasma and brain cortex tissue of transgenic mice and wildtype mice, with a focus on mitochondrial health. Amyloid precursor protein and amyloid-β levels in plasma, brain cortex tissue and mitochondria fractions isolated from brain cortex were measured to assess the amyloid pathology. Our findings include the observation of extensive metabolic alterations in cortex and cerebellum of APP/PS1 mice, but not in their hippocampus, midbrain and plasma. The major pathways affected in cortex and cerebellum of APP/PS1 mice were closely related to impaired energy metabolism and perturbation of amino acid metabolism in these mice. APP/PS1 mice also exhibited higher amyloid-β40 and amyloid-β42 in their cortex, accumulation of mitochondria APP in their cortex, and presented an altered oxidative state in their brain. Treatment with the peroxisome proliferator-activated receptor gamma (PPARγ) agonist pioglitazone (PIO) successfully restored the energy metabolism, lowered amyloid-β levels and afforded the APP/PS1 mice a better antioxidative capacity in their cortex.

Metabolomic analysis of male combat veterans with post traumatic stress disorder

Posttraumatic stress disorder (PTSD) is associated with impaired major domains of psychology and behavior. Individuals with PTSD also have increased co-morbidity with several serious medical conditions, including autoimmune diseases, cardiovascular disease, and diabetes, raising the possibility that systemic pathology associated with PTSD might be identified by metabolomic analysis of blood. We sought to identify metabolites that are altered in male combat veterans with PTSD. In this case-control study, we compared metabolomic profiles from age-matched male combat trauma-exposed veterans from the Iraq and Afghanistan conflicts with PTSD (n = 52) and without PTSD (n = 51) (‘Discovery group’). An additional group of 31 PTSD-positive and 31 PTSD-negative male combat-exposed veterans was used for validation of these findings (‘Test group’). Plasma metabolite profiles were measured in all subjects using ultrahigh performance liquid chromatography/tandem mass spectrometry and gas chromatography/mass spectrometry. We identified key differences between PTSD subjects and controls in pathways related to glycolysis and fatty acid uptake and metabolism in the initial ‘Discovery group’, consistent with mitochondrial alterations or dysfunction, which were also confirmed in the ‘Test group’. Other pathways related to urea cycle and amino acid metabolism were different between PTSD subjects and controls in the ‘Discovery’ but not in the smaller ‘Test’ group. These metabolic differences were not explained by comorbid major depression, body mass index, blood glucose, hemoglobin A1c, smoking, or use of analgesics, antidepressants, statins, or anti-inflammatories. These data show replicable, wide-ranging changes in the metabolic profile of combat-exposed males with PTSD, with a suggestion of mitochondrial alterations or dysfunction, that may contribute to the behavioral and somatic phenotypes associated with this disease.

Serum metabolic profiling using small molecular water-soluble metabolites in individuals with schizophrenia: A longitudinal study using a pre-post-treatment design

AIM

We sought to compare alterations in serum bioenergetic markers within a well-characterized sample of adults with schizophrenia at baseline and after 8 weeks of pharmacological treatment with the hypothesis that treatment would be associated with significant changes in bioenergetic markers given the role of bioenergetic dysfunction in schizophrenia.

METHODS

We recruited adults with schizophrenia (n = 122) who had not received pharmacological treatment for at least 1 month prior to enrollment, including drug-naïve (i.e., first-episode) participants and treatment non-adherent participants. Pre- and post-treatment serum samples were analyzed using liquid chromatography-tandem mass spectrometry.

RESULTS

Metabolites with the greatest change, when comparing pre- and post-treatment levels, were identified revealing 14 water-soluble metabolites of interest. The composition of these metabolites was: amino acids (n = 6), carnitines (n = 4), polar lipids (n = 3), and organic acid (n = 1). All amino acids and lysophosphatidylcholines (LysoPC) were increased, while the four carnitines - oleoylcarnitine, L-palmitoylcarnitine, linoleyl carnitine, and L-acetylcarnitine - were decreased post-treatment. Of these metabolite biomarkers, six - oleoylcarnitine, linoleyl carnitine, L-acetylcarnitine, LysoPC(15:0), D-glutamic acid, and L-arginine - were identified as having most consistently and predictably changed after 8 weeks of treatment.

CONCLUSION

The current study identified several bioenergetic markers that consistently change with pharmacological treatment. These bioenergetic changes may provide further insights into the pathophysiology of schizophrenia along with furthering our understanding of the mechanisms subserving both the effects (e.g., antipsychotic effects) and side-effects (e.g., metabolic syndrome) of antipsychotics.