Schizophrenia (SCH) is a devastating mental disease that affects the human population worldwide with an incidence of about 1%. Most individuals with this illness benefit from long-term pharmacotherapy, however, the therapeutic effects of antipsychotic treatment are inconsistent, incomplete, and often countered by significant side-effects associated with long-term physical morbidity (e.g., tardive dyskinesia, obesity, hyperglycemia, hyperlipidemia. Metabolomics is a powerful new technology that provides a snap shot of biochemical pathways at a particular point in time. It has been earmarked as an important area to develop under the NIH roadmap initiative. We plan to use this platform to map biochemical signatures in unmedicated schizophrenic patients prior to and 4 weeks post treatment with the antipsychotic drug aripiprazole and compare that to lipid perturbations induced by risperidone. These drugs have inherently different risk for metabolic adverse effects and patients respond to them differently. Metabolic signatures for the drugs capture significant biochemical information that could explain part of the basis for varied drug response within individuals and will highlight pathways implicated in drug action and in disease pathogenesis possibly enabling new drug design strategies.In addition, we will compare patients to healthy controls at baseline in regard lipid profiles, to assess whether lipid profiles differ between unmedicated schizophrenia patients and healthy controls.
