The quest for psychiatric disorder biomarkers: from protein expression to isoforms to pathways |
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| Launch in standalone player | |
| Air date: | Wednesday, November 18, 2009, 10:00:00 AM Time displayed is Eastern Time, Washington DC Local |
| Category: | Proteomics |
| Description: | Proteomics Interest Group Special Seminar
Biomarkers, which are measures of biological parameters of disease that also can predict which new molecular entities will be effective and safe in treating patients, are experiencing a great deal of attention in today’s life sciences. For both types of investigation, drug response and disease susceptibility, biomarkers are needed in order to move the area of psychiatric disorders into the rest of medicine. Ultimately, it is hoped that biomarkers will assist in stratifying patient groups with similar clinical features for a personalized medicine approach and at the same time help in the identification of neural circuitries that are responsible for disease etiology. This will enable the complementation of the presently applied DSM-IV and ICD-10 criteria with specific sets of biomarkers and result in a more precise nosological framework for psychiatric disorders. Good animal models representing distinct features of a psychiatric disorder phenotype are one way to come up with specific biomarkers. Here a good representation of the relevant psychiatric disease mechanisms in an animal disease model is critical in order to enable subsequent pre-clinical to clinical study translation. The identified biomarker candidates can also provide important information on pathways that are relevant for psychiatric disorder pathophysiology. We have implemented a comprehensive and sensitive platform that is based on metabolic labeling of mouse models with stable isotopes and subsequent mass spectrometry-based quantitation. Proteomic and metabolomic analyses are implicating pathways relevant for disease pathobiology. |
| Author: | Chris Turck, Max Planck Institute |
| Runtime: | 60 minutes |
| CIT File ID: | 15444 |
| CIT Live ID: | 8218 |
| Permanent link: | http://videocast.nih.gov/launch.asp?15444 |