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Pharmacotherapy of schizophrenia: toward a metabolomic-based approach

Published online by Cambridge University Press:  05 June 2018

Haythum O. Tayeb
Affiliation:
Department of Medicine, Division of Neurology, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
Hussam A. Murad*
Affiliation:
Department of Pharmacology, Faculty of Medicine, Rabigh, King Abdulaziz University, Jeddah, Saudi Arabia Department of Pharmacology, Faculty of Medicine, Ain Shams University, Cairo, Egypt
Misbahuddin M. Rafeeq
Affiliation:
Department of Pharmacology, Faculty of Medicine, Rabigh, King Abdulaziz University, Jeddah, Saudi Arabia
Frank I. Tarazi
Affiliation:
Department of Psychiatry and Neuroscience Program, Harvard Medical School and McLean Hospital, Boston, Massachusetts, USA
*
*Address for correspondence: Dr. Hussam A. Murad, Department of Pharmacology, Faculty of Medicine, Rabigh, King Abdulaziz University, Jeddah, Saudi Arabia. (Email: [email protected])

Abstract

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.

Type
Review
Copyright
© Cambridge University Press 2018 

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