Analysis of nonlinear gene expression progression reveals extensive pathway and age-specific transitions in aging human brains.

ABSTRACT: Several recent gene expression studies identified hundreds of genes that are correlated with age in brain and other tissues in human. However, these studies used linear models of age correlation, which are not well equipped to model abrupt changes associated with particular ages. We developed a computational algorithm for age estimation in which the expression of each gene is treated as a dichotomized biomarker for whether the subject is older or younger than a particular age. In addition, for each age-informative gene our algorithm identifies the age threshold with the most drastic change in expression level, which allows us to associate genes with particular age periods. Analysis of human aging brain expression datasets from three frontal cortex regions showed that different pathways und

SUBMITTER: Cao K 

PROVIDER: S-EPMC3789733 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature