Omics-Based Biomarkers: Application of Metabolomics in Neuropsychiatric Disorders

Omics-Based Biomarkers: Application of Metabolomics in Neuropsychiatric Disorders

Author Sethi, Sumit Autor UNIFESP Google Scholar
Brietzke, Elisa Autor UNIFESP Google Scholar
Abstract One of the major concerns of modern society is to identify putative biomarkers that serve as a valuable early diagnostic tool to identify a subset of patients with increased risk to develop neuropsychiatric disorders. Biomarker identification in neuropsychiatric disorders is proposed to offer a number of important benefits to patient well-being, including prediction of forthcoming disease, diagnostic precision, and a level of disease description that would guide treatment choice. Nowadays, the metabolomics approach has unlocked new possibilities in diagnostics of devastating disorders like neuropsychiatric disorders. Metabolomics-based technologies have the potential to map early biochemical changes in disease and hence provide an opportunity to develop predictive biomarkers that can be used as indicators of pathological abnormalities prior to development of clinical symptoms of neuropsychiatric disorders. This review highlights different -omics strategies for biomarker discovery in neuropsychiatric disorders. We also highlight initial outcomes from metabolomics studies in psychiatric disorders such as schizophrenia, bipolar disorder, and addictive disorders. This review will also present issues and challenges regarding the implementation of the metabolomics approach as a routine diagnostic tool in the clinical laboratory in context with neuropsychiatric disorders.
Keywords biomarkers
bipolar disorder
drug addiction
xmlui.dri2xhtml.METS-1.0.item-coverage Oxford
Language English
Sponsor Nacional de Desenvolvimento Cientifico e Technologico (CNPq, Brasilia, Brazil)
Date 2016
Published in International Journal Of Neuropsychopharmacology. Oxford, v. 19, n. 3, p. -, 2016.
ISSN 1461-1457 (Sherpa/Romeo, impact factor)
Publisher Oxford Univ Press
Extent -
Access rights Open access Open Access
Type Article
Web of Science ID WOS:000377108200004

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