Literature DB >> 28040324

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

Ljubica Tasic1, João G M Pontes2, Michelle S Carvalho3, Guilherme Cruz2, Carolines Dal Mas3, Sumit Sethi4, Mariana Pedrini4, Lucas B Rizzo4, Maiara Zeni-Graiff4, Elson Asevedo4, Acioly L T Lacerda5, Rodrigo A Bressan5, Ronei Jesus Poppi6, Elisa Brietzke4, Mirian A F Hayashi7.   

Abstract

Using 1H NMR-based metabolomics in association to chemometrics analysis, we analyzed here the metabolic differences between schizophrenia patients (SCZ) compared to healthy controls (HCs). HCs and SCZ patients underwent clinical interview using the Structured Clinical Interview for DSM Disorders (SCID). SCZ patients were further assessed by Positive and Negative Syndrome Scale (PANSS), Calgary Depression Scale, Global Assessment of Functioning Scale (GAF), and Clinical Global Impressions Scale (CGI). Using the principal component analysis (PCA) and supervised partial least-squares discriminate analysis (PLS-DA) in obtained NMR data, a clear group separation between HCs and SCZ patients was achieved. Interestingly, all metabolite compounds identified as exclusively present in the SCZ group, except for the gamma-aminobutyric acid (GABA), were never previously associated with mental disorders. Although the initial perception of an absence of obvious biological link among the different key molecules exclusively observed in each group, and no identification of any specific pathway yet, the present work represents an important contribution for the identification of potential biomarkers to inform diagnosis, as it was possible to completely separate the affected SCZ patients from HCs, with no outliers or exceptions. In addition, the data presented here reinforced the role of the modulation of glycolysis pathway and the loss of GABA interneuron/hyperglutamate hypothesis in SCZ.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Biomarkers; Lipidomics; Metabolomics; NMR; Psychosis; Schizophrenia; Serum

Mesh:

Substances:

Year:  2016        PMID: 28040324     DOI: 10.1016/j.schres.2016.12.024

Source DB:  PubMed          Journal:  Schizophr Res        ISSN: 0920-9964            Impact factor:   4.939


  7 in total

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Authors:  Banny Silva Barbosa Correia; João Victor Nani; Raniery Waladares Ricardo; Danijela Stanisic; Tássia Brena Barroso Carneiro Costa; Mirian A F Hayashi; Ljubica Tasic
Journal:  Biomedicines       Date:  2021-02-26

4.  The Potential Regulatory Network of Glutamate Metabolic Pathway Disturbance in Chinese Han Withdrawal Methamphetamine Abusers.

Authors:  Sufang Peng; Hang Su; Tianzhen Chen; Xiaotong Li; Jiang Du; Haifeng Jiang; Min Zhao
Journal:  Front Genet       Date:  2021-03-23       Impact factor: 4.599

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Journal:  Metabolites       Date:  2022-07-29

6.  Plasma metabolomics of schizophrenia with cognitive impairment: A pilot study.

Authors:  Yihe Jiang; Xiujia Sun; Miaowen Hu; Lei Zhang; Nan Zhao; Yifeng Shen; Shunying Yu; Jingjing Huang; Huafang Li; Wenjuan Yu
Journal:  Front Psychiatry       Date:  2022-09-28       Impact factor: 5.435

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

Authors:  Md Altaf-Ul-Amin; Kazuhisa Hirose; João V Nani; Lucas C Porta; Ljubica Tasic; Shaikh Farhad Hossain; Ming Huang; Naoaki Ono; Mirian A F Hayashi; Shigehiko Kanaya
Journal:  Sci Rep       Date:  2021-07-14       Impact factor: 4.379

  7 in total

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