Format

Send to

Choose Destination
Schizophr Res. 2017 Jul;185:182-189. doi: 10.1016/j.schres.2016.12.024. Epub 2016 Dec 29.

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

Author information

1
Department of Organic Chemistry, Institute of Chemistry, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil. Electronic address: ljubica@iqm.unicamp.br.
2
Department of Organic Chemistry, Institute of Chemistry, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil.
3
Integrated Laboratory of Clinical Neurosciences (LiNC) and Schizophrenia Program (PROESQ), Department of Psychiatry, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil; Department of Pharmacology, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil.
4
Department of Psychiatry, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil.
5
Integrated Laboratory of Clinical Neurosciences (LiNC) and Schizophrenia Program (PROESQ), Department of Psychiatry, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil.
6
Department of Analytical Chemistry, Institute of Chemistry, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil.
7
Integrated Laboratory of Clinical Neurosciences (LiNC) and Schizophrenia Program (PROESQ), Department of Psychiatry, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil; Department of Pharmacology, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil. Electronic address: mhayashi@unifesp.br.

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.

KEYWORDS:

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

PMID:
28040324
DOI:
10.1016/j.schres.2016.12.024
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center