Integrating transcriptomics with metabolic modeling predicts biomarkers and drug targets for Alzheimer's disease.

ABSTRACT: Accumulating evidence links numerous abnormalities in cerebral metabolism with the progression of Alzheimer's disease (AD), beginning in its early stages. Here, we integrate transcriptomic data from AD patients with a genome-scale computational human metabolic model to characterize the altered metabolism in AD, and employ state-of-the-art metabolic modelling methods to predict metabolic biomarkers and drug targets in AD. The metabolic descriptions derived are first tested and validated on a large scale versus existing AD proteomics and metabolomics data. Our analysis shows a significant decrease in the activity of several key metabolic pathways, including the carnitine shuttle, folate metabolism and mitochondrial transport. We predict several metabolic biomarkers of AD progression in the b

SUBMITTER: Stempler S 

PROVIDER: S-EPMC4134302 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature