Computational prediction of changes in brain metabolic fluxes during Parkinson's disease from mRNA expression.

ABSTRACT:

Background

Parkinson's disease is a widespread neurodegenerative disorder which affects brain metabolism. Although changes in gene expression during disease are often measured, it is difficult to predict metabolic fluxes from gene expression data. Here we explore the hypothesis that changes in gene expression for enzymes tend to parallel flux changes in biochemical reaction pathways in the brain metabolic network. This hypothesis is the basis of a computational method to predict metabolic flux changes from post-mortem gene expression measurements in Parkinson's disease (PD) brain.

Results

We use a network model of central metabolism and optimize the correspondence between relative changes in fluxes and in gene expression. To this end we apply the Least-squares with Equalitie

SUBMITTER: Supandi F 

PROVIDER: S-EPMC6135490 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature