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Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia
Published on: December 2, 2015
Biomarkers for drug development in early psychosis: Current issues and promising directions
Donald C Goff1, Klaus Romero2, Jeffrey Paul3
1New York University, New York City, NY, USA.
Abstract:
A major goal of current research in schizophrenia is to understand the biology underlying onset and early progression and to develop interventions that modify these processes. Biomarkers can play a critical role in identifying disease state, factors contributing to underlying progression, as well as predicting and monitoring response to treatment. Once biomarker-based therapeutics are established, biomarkers can guide treatment selection. It is increasingly clear that a wide range of potential biomarkers should be examined in schizophrenia, given the large number of genetic and environmental factors that have been identified as risk factors. New models for analysis of biomarkers are needed that represent the central nervous system as a highly complex, dynamic, and interactive system. Many tools are available with which to study relevant brain chemistry, but most are indirect measures and represent only a small fraction of the potential etiologic factors contributing to the molecular, structural and functional components of schizophrenia. This review represents the work of the International Society for CNS Clinical Trials and Methodology (ISCTM) Biomarkers Working Group. It discusses advantages and disadvantages of different categories of biomarkers and provides a summary of evidence that biomarkers representing inflammation, oxidative stress, endocannabinoids, glucocorticoid, and biogenic amines systems are dysregulated and potentially interactive in early phase schizophrenia. As has been recently demonstrated in several neurodevelopmental and neurodegenerative disorders, a multi-modal, longitudinal strategy involving a diverse array of biomarkers and new approaches to statistical modeling are needed to improve early interventions based on the fuller understanding.
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