Alzheimer's disease (AD), a neurodegenerative disorder, is the most common cause of dementia in the elderly. With the rapid growth of the aging population, there is an urgent need to develop more effective therapies to prevent and treat AD. Although AD is traditionally diagnosed and monitored by clinical criteria (e.g. cognitive tests, staging instruments), there is a need for validated biomarkers that can compliment clinical measures and that can provide further insights into disease mechanisms. Large studies have been undertaken to validate biomarkers such as brain atrophy measures, hippocampal volumes, glucose metabolic uptake and beta-amyloid ortau protein levels. However, to date, no single biomarker has yet been fully accepted as being sufficiently sensitive and specific for diagnosis or tracking response to therapy. Metabolomics is a powerful new technology platform that provides a snap shot of biochemical pathways at a particular point in time. It is the comprehensive study of the metabolome, the repertoire of bio-chemicals (or small molecules) present in cells, tissue and body fluid. It has been earmarked as an important area to develop under the NIH roadmap initiative. We have already established sophisticated biochemical and informatics platforms in metabolomics that have enabled us to define initial signatures for several CNS disorders including an initial cerebrospinal fluid (CSF) derived signature for AD. We plan to use these complementary metabolomics technologies to capture comprehensive biochemical changes and biochemical signatures at various stages of AD in relation to pathologic and clinical status. Specifically, we will perform CSF metabolomics in a sample of AD patients with pathologically confirmed diagnoses and matched control samples to interrogate specific pathways and confirm hypotheses generated by our pilot studies. In addition, we will prospectively collect plasma samples and CSF samples from living AD patients and controls to test secondary hypotheses pertaining to utility of plasma metabolomics, and its correlation with CSF metabolomics as well as cognitive changes over time in the same set of individuals. Finally, we plan to examine fasting plasma lipomic patterns in AD patients and controls, in relation to other metabolomic parameters. These studies may serve to highlight new impaired pathways in the disease and identify potential targets for drug developments.
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