Amino Acid and Acylcarnitine Levels in Chronic Patients with Schizophrenia: A Preliminary Study

Discovery of biological markers for schizophrenia based on metabolomics: a systematic review

Introduction and methods

To discover biomarkers for schizophrenia (SCZ) at the metabolomics level, we registered this systematic review (CRD42024572133 (https://www.crd.york.ac.uk/PROSPERO/home)) including 56 qualified articles, and we identified the characteristics of metabolites, metabolite combinations, and metabolic pathways associated with SCZ.

Results

Our findings showed that decreased arachidonic acid, arginine, and aspartate levels, and the increased levels of glucose 6-phosphate and glycylglycine were associated with the onset of SCZ. Metabolites such as carnitine and methionine sulfoxide not only helped to identify SCZ in Miao patients, but also were different between Miao patients and Han patients. The decrease in benzoic acid and betaine and the increase in creatine were the notable metabolic characteristics of first-episode schizophrenia (FESCZ). The metabolite combination formed by metabolites such as methylamine, dimethylamine and other metabolites had the best diagnostic effect. Arginine and proline metabolism and arginine biosynthesis had a clear advantage in identifying SCZ and acute SCZ. Butanoate metabolism played an important role in identifying SCZ, toxoplasma infection and SCZ comorbidity. Biosynthesis of unsaturated fatty acids was also significantly enriched in the diagnosis and treatment of SCZ.

Discussion

This study summarizes the current progress in clinical metabolomic research related to SCZ, deepens understanding of the pathogenesis of SCZ, and lays a foundation for subsequent research on SCZ-related metabolites.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/home, identifier CRD42024572133.

Disturbance of neurotransmitter metabolites in peripheral blood of schizophrenia patients treated with olanzapine: a preliminary targeted metabolomic study

BACKGROUND

The aim of this research was to characterize changes in peripheral blood neurotransmitter metabolites in olanzapine-treated schizophrenia (SCZ) and to identify potential biomarkers for SCZ. Concurrently, the relationship between these differential neurotransmitters and cognitive function is explored.

METHODS

We recruited 40 SCZ treated with single-agent olanzapine and 40 healthy controls (HC). Cognitive function and psychopathology were assessed using the MCCB and PANSS, respectively. Neurotransmitter levels were determined by targeted metabolomics approach using liquid chromatography-mass spectrometry (LC/MS).

RESULTS

SCZ showed cognitive impairment in all domains of the MCCB compared to HC. Interestingly, a 4-neurotransmitter panel consisting of 3-Methoxytyramine hydrochloride (3-MT), 3,4-Dihydroxyphenylacetate (DOPAC), arginine, and r-aminobutyric acid (GABA) illustrated the highest determinative score between SCZ and HC. Arginine was positively correlated with PANSS general psychopathology scores. 3-MT independently predicted the verbal learning scores only in SCZ, whereas GABA independently predicted the social cognition scores only. Furthermore, GABA independently predicted the working memory scores only in HC.

CONCLUSIONS

The collective assessment of these four neurotransmitters (3-MT, DOPAC, arginine, and GABA) holds considerable promise as potential biomarkers for SCZ. Moreover, 3-MT and GABA may enhance our understanding of cognitive dysfunction in SCZ, particularly in areas of verbal learning and social cognitive dysfunction.

Serum metabolic profile evidence for relationship between schizophrenia and depression: An untargeted metabolomics

Given the genetic and clinical overlap observed between schizophrenia and depression, the present study was to identify the similarities and differences in serum metabolic profiles between patients with schizophrenia and depression. Global metabolomics research methods based on UHPLC-QTOF-MS/MS were performed. A total of 113 and 118 differential metabolites were screened and identified in depression and schizophrenia groups, respectively, as compared to health control; among those, 94 differential metabolites were shared by both. Pathway analysis indicated arginine and proline metabolism, alanine, aspartate, and glutamate metabolism were two significant metabolic pathways both in depression and schizophrenia groups as compared with health control groups, respectively. Similarly, 77 differential metabolites were identified between depression and schizophrenia groups, in which, serum N-acetylglutamine and isovalerylglycine levels showed significant differences between patients with depression and schizophrenia with p values less than 0.001 and without significant outliers. Sphingolipid metabolism was identified as a significant metabolic pathway distinguishing between depression and schizophrenia groups based on pathway analysis. Conclusively, common alterations in arginine and proline metabolism, alanine, aspartate, and glutamate metabolism were observed in patients with schizophrenia and depression; whereas differences in serum N-acetylglutamine and isovalerylglycine levels as well as sphingolipid metabolism were discovered between the two categories of patients.

An exploratory study of metabolomics in endogenous and cannabis-use-associated psychotic-like experiences in adolescence

In adolescence, psychotic-like experiences (PLE) may indicate potential prodromal symptoms preceding the onset of psychosis. Metabolomic studies have shown promise in providing valuable insights into predicting psychosis with enhanced precision compared to conventional clinical features. This study investigated metabolomic alterations associated with PLE in 76 depressed adolescents aged 14-20 years. Serum concentrations of 92 metabolites were analyzed with liquid chromatography-mass spectrometry. PLE were assessed using the Youth Experiences and Health (YEAH) questionnaire. The associations between PLE symptom dimensions (delusions, paranoia, hallucinations, negative symptoms, thought disorder, and dissociation) and metabolite concentrations were analyzed in linear regression models adjusted for different covariates. The symptom dimensions consistently correlated with the metabolome in different models, except those adjusted for cannabis use. Specifically, the hallucination dimension was associated with 13 metabolites (acetoacetic acid, allantoin, asparagine, decanoylcarnitine, D-glucuronic acid, guanidinoacetic acid, hexanoylcarnitine, homogentisic acid, leucine, NAD+, octanoylcarnitine, trimethylamine-N-oxide, and valine) in the various linear models. However, when adjusting for cannabis use, eight metabolites were associated with hallucinations (adenine, AMP, cAMP, chenodeoxycholic acid, cholic acid, L-kynurenine, neopterin, and D-ribose-5-phosphate). The results suggest diverse mechanisms underlying PLE in adolescence; hallucinatory experiences may be linked to inflammatory functions, while cannabis use may engage an alternative metabolic pathway related to increased energy demand and ketogenesis in inducing PLE. The limited sample of individuals with depression restricts the generalizability of these findings. Future research should explore whether various experiences and related metabolomic changes jointly predict the onset of psychoses and related disorders.

The amino acid metabolism pathway of peripheral T lymphocytes and ketamine-induced schizophrenia-like phenotype

BACKGROUND

The intricate interplay between peripheral adaptive immune cells and the central nervous system (CNS) has garnered increasing recognition. Given that alterations in cell quantities often translate into modifications in metabolite profiles and that these metabolic changes can potentially traverse the bloodstream and enter the CNS, thereby modulating the progression of mental illnesses, we sought to explore the metabolic profiles of peripheral immune cells in a ketamine-treated mouse model of schizophrenia.

METHODS

We used flow cytometry to scrutinize the alterations in peripheral adaptive immune cells in a ketamine-induced schizophrenia mouse model. Subsequently, we implemented an untargeted metabolomic approach with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) to detect the metabolite profiles of peripheral abnormal lymphocytes and identify differential metabolites present in plasma. We then employed targeted metabolomics using UPLC-MS/MS to quantify the common differential metabolites detected in mouse plasma.

RESULTS

Flow cytometry analysis detected a notable increase in the count of peripheral CD3+ T cells in a ketamine-induced schizophrenia mouse model. Subsequent untargeted metabolomics analysis revealed that the amino acid metabolism pathway underwent substantial alterations. A detailed quantification of 22 amino acid profiles in the peripheral plasma indicated significant elevation in the levels of glycine, alanine, asparagine, and aspartic acid.

LIMITATIONS

Our ongoing research has yet to conclusively identify the precise amino acid metabolism pathway that serves as the pivotal factor in the manifestation of the schizophrenia-like phenotype induced by ketamine.

CONCLUSION

The peripheral amino acid metabolism pathway is involved in the ketamine-induced schizophrenia-like phenotype. The metabolic profile of peripheral immune cells could provide accurate biomarkers for the diagnosis and treatment of psychiatric diseases.

A systematic review and meta-analysis of nitric oxide-associated arginine metabolites in schizophrenia

There is increasing interest in the pathophysiological role of arginine metabolism in schizophrenia, particularly in relation to the modulation of the endogenous messenger nitric oxide (NO). The assessment of specific arginine metabolites that, unlike NO, are stable can provide useful insights into NO regulatory enzymes such as isoform 1 of dimethylarginine dimethylaminohydrolase (DDAH1) and arginase. We investigated the role of arginine metabolomics in schizophrenia by conducting a systematic review and meta-analysis of the circulating concentrations of arginine metabolites associated with DDAH1, arginase, and NO synthesis [arginine, citrulline, asymmetric dimethylarginine (ADMA), symmetric dimethylarginine (SDMA), dimethylamine, and ornithine] in this patient group. We searched PubMed, Scopus, and Web of Science from inception to the 31st of May 2023 for studies investigating arginine metabolites in patients with schizophrenia and healthy controls. The JBI Critical Appraisal Checklist for analytical studies and GRADE were used to assess the risk of bias and the certainty of evidence, respectively (PROSPERO registration number: CRD42023433000). Twenty-one studies were identified for analysis. There were no significant between-group differences in arginine, citrulline, and SDMA. By contrast, patients with schizophrenia had significantly higher ADMA (DDAH1 substrate, standard mean difference, SMD = 1.23, 95% CI 0.86-1.61, p < 0.001; moderate certainty of evidence), dimethylamine (DDAH1 product, SMD = 0.47, 95% CI 0.24-0.70, p < 0.001; very low certainty of evidence), and ornithine concentrations (arginase product, SMD = 0.32, 95% CI 0.16-0.49, p < 0.001; low certainty of evidence). In subgroup analysis, the pooled SMD for ornithine was significantly different in studies of untreated, but not treated, patients. Our study suggests that DDAH1 and arginase are dysregulated in schizophrenia. Further studies are warranted to investigate the expression/activity of these enzymes in the brain of patients with schizophrenia and the effects of targeted treatments.

Mass Spectrometry Imaging of Two Neocortical Areas Reveals the Histological Selectivity of Schizophrenia-Associated Lipid Alterations

BACKGROUND

Schizophrenia is a psychiatric disorder known to affect brain structure and functionality. Structural changes in the brain at the level of gross anatomical structures have been fairly well studied, while microstructural changes, especially those associated with changes in the molecular composition of the brain, are still being investigated. Of special interest are lipids and metabolites, for which some previous studies have shown association with schizophrenia.

AIM

To utilize a spatially resolved analysis of the brain lipidome composition to investigate the degree and nature of schizophrenia-associated lipidome alterations in the gray and white matter structures of two neocortical regions - the dorsolateral prefrontal cortex (Brodmann area 9, BA9) and the posterior part of the superior temporal gyrus (Brodmann area 22, posterior part, BA22p), as well compare the distribution of the changes between the two regions and tissue types.

METHODS

We employed Matrix-Assisted Laser Desorption/Ionization Mass Spectrometric Imaging (MALDI-MSI), supplemented by a statistical analysis, to examine the lipid composition of brain sections. A total of 24 neocortical sections from schizophrenia patients (n=2) and a healthy control group (n=2), representing the two aforementioned neocortical areas, were studied, yielding data for 131 lipid compounds measured across more than a million MALDI-MSI pixels.

RESULTS

Our findings revealed an uneven distribution of schizophrenia-related lipid alterations across the two neocortical regions. The BA22p showed double the differences in its subcortical white matter structures compared to BA9, while less bias was detected in the gray matter layers. While the schizophrenia-associated lipid differences generally showed good agreement between brain regions at the lipid class level for both gray and white matter, there were consistently more discrepancies for white matter structures.

CONCLUSION

Our study found a consistent yet differential association of schizophrenia with the brain lipidome composition of distinct neocortical areas, particularly subcortical white matter. These findings highlight the need for broader brain coverage in future schizophrenia research and underscore the potential of spatially resolved molecular analysis methods in identifying structure-specific effects.

Peripheral Lipid Signatures, Metabolic Dysfunction, and Pathophysiology in Schizophrenia Spectrum Disorders

Metabolic dysfunction is commonly observed in schizophrenia spectrum disorders (SSDs). The causes of metabolic comorbidity in SSDs are complex and include intrinsic or biological factors linked to the disorder, which are compounded by antipsychotic (AP) medications. The exact mechanisms underlying SSD pathophysiology and AP-induced metabolic dysfunction are unknown, but dysregulated lipid metabolism may play a role. Lipidomics, which detects lipid metabolites in a biological sample, represents an analytical tool to examine lipid metabolism. This systematic review aims to determine peripheral lipid signatures that are dysregulated among individuals with SSDs (1) with minimal exposure to APs and (2) during AP treatment. To accomplish this goal, we searched MEDLINE, Embase, and PsychINFO databases in February 2024 to identify all full-text articles written in English where the authors conducted lipidomics in SSDs. Lipid signatures reported to significantly differ in SSDs compared to controls or in relation to AP treatment and the direction of dysregulation were extracted as outcomes. We identified 46 studies that met our inclusion criteria. Most of the lipid metabolites that significantly differed in minimally AP-treated patients vs. controls comprised glycerophospholipids, which were mostly downregulated. In the AP-treated group vs. controls, the significantly different metabolites were primarily fatty acyls, which were dysregulated in conflicting directions between studies. In the pre-to-post AP-treated patients, the most impacted metabolites were glycerophospholipids and fatty acyls, which were found to be primarily upregulated and conflicting, respectively. These lipid metabolites may contribute to SSD pathophysiology and metabolic dysfunction through various mechanisms, including the modulation of inflammation, cellular membrane permeability, and metabolic signaling pathways.

Advances in Mass Spectrometry-Based Blood Metabolomics Profiling for Non-Cancer Diseases: A Comprehensive Review

Blood metabolomics profiling using mass spectrometry has emerged as a powerful approach for investigating non-cancer diseases and understanding their underlying metabolic alterations. Blood, as a readily accessible physiological fluid, contains a diverse repertoire of metabolites derived from various physiological systems. Mass spectrometry offers a universal and precise analytical platform for the comprehensive analysis of blood metabolites, encompassing proteins, lipids, peptides, glycans, and immunoglobulins. In this comprehensive review, we present an overview of the research landscape in mass spectrometry-based blood metabolomics profiling. While the field of metabolomics research is primarily focused on cancer, this review specifically highlights studies related to non-cancer diseases, aiming to bring attention to valuable research that often remains overshadowed. Employing natural language processing methods, we processed 507 articles to provide insights into the application of metabolomic studies for specific diseases and physiological systems. The review encompasses a wide range of non-cancer diseases, with emphasis on cardiovascular disease, reproductive disease, diabetes, inflammation, and immunodeficiency states. By analyzing blood samples, researchers gain valuable insights into the metabolic perturbations associated with these diseases, potentially leading to the identification of novel biomarkers and the development of personalized therapeutic approaches. Furthermore, we provide a comprehensive overview of various mass spectrometry approaches utilized in blood metabolomics research, including GC-MS, LC-MS, and others discussing their advantages and limitations. To enhance the scope, we propose including recent review articles supporting the applicability of GC×GC-MS for metabolomics-based studies. This addition will contribute to a more exhaustive understanding of the available analytical techniques. The Integration of mass spectrometry-based blood profiling into clinical practice holds promise for improving disease diagnosis, treatment monitoring, and patient outcomes. By unraveling the complex metabolic alterations associated with non-cancer diseases, researchers and healthcare professionals can pave the way for precision medicine and personalized therapeutic interventions. Continuous advancements in mass spectrometry technology and data analysis methods will further enhance the potential of blood metabolomics profiling in non-cancer diseases, facilitating its translation from the laboratory to routine clinical application.

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.

Levels of Acylcarnitines and Branched-Chain Amino Acids in Antipsychotic-Treated Patients with Paranoid Schizophrenia with Metabolic Syndrome

Several studies have shown that patients with schizophrenia are at high risk for metabolic syndrome (MetS) and bioenergetic dysfunction. Because acylcarnitines are involved in bioenergetic pathways and reflect the functioning of mitochondria, we hypothesized that these compounds are biomarkers of MetS in schizophrenia. The aim of this work was to quantify acylcarnitines and branched-chain amino acids in patients with schizophrenia comorbid with MetS. The study included 112 patients with paranoid schizophrenia treated with antipsychotics. Among them, 39 subjects met criteria of MetS. Concentrations of 30 acylcarnitines and three amino acids in dry serum spots were measured by liquid chromatography coupled with tandem mass spectrometry. MetS patients were found to have higher levels of valeryl carnitine (C5), leucine/isoleucine, and alanine as compared with patients without MetS, indicating possible participation of these compounds in the pathogenesis of metabolic disorders in schizophrenia. In patients with paranoid schizophrenia with or without MetS, lower levels of carnitines C10, C10:1, C12, and C18 were recorded as compared with the healthy individuals (n = 70), implying deterioration of energy metabolism. We believe that this finding can be explained by effects of antipsychotic medication on an enzyme called carnitine-palmitoyl transferase I.

NMR Metabolomics in Serum Fingerprinting of Schizophrenia Patients in a Serbian Cohort

Schizophrenia is a widespread mental disorder that leads to significant functional impairments and premature death. The state of the art indicates gaps in the understanding and diagnosis of this disease, but also the need for personalized and precise approaches to patients through customized medical treatment and reliable monitoring of treatment response. In order to fulfill existing gaps, the establishment of a universal set of disorder biomarkers is a necessary step. Metabolomic investigations of serum samples of Serbian patients with schizophrenia (51) and healthy controls (39), based on NMR analyses associated with chemometrics, led to the identification of 26 metabolites/biomarkers for this disorder. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models with prediction accuracies of 0.9718 and higher were accomplished during chemometric analysis. The established biomarker set includes aspartate/aspartic acid, lysine, 2-hydroxybutyric acid, and acylglycerols, which are identified for the first time in schizophrenia serum samples by NMR experiments. The other 22 identified metabolites in the Serbian samples are in accordance with the previously established NMR-based serum biomarker sets of Brazilian and/or Chinese patient samples. Thirteen metabolites (lactate/lactic acid, threonine, leucine, isoleucine, valine, glutamine, asparagine, alanine, gamma-aminobutyric acid, choline, glucose, glycine and tyrosine) that are common for three different ethnic and geographic origins (Serbia, Brazil and China) could be a good start point for the setup of a universal NMR serum biomarker set for schizophrenia.

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.