Major aging-associated RNA expressions change at two distinct age-positions.

ABSTRACT:

Background

Genome-wide expression profiles are altered during biological aging and can describe molecular regulation of tissue degeneration. Age-regulated mRNA expression trends from cross-sectional studies could describe how aging progresses. We developed a novel statistical methodology to identify age-regulated expression trends in cross-sectional datasets.

Results

We studied six cross-sectional RNA expression profiles from different human tissues. Our methodology, capable of overcoming technical and genetic background differences, identified an age-regulation in four of the tissues. For the identification of expression trends, five regression models were compared and the quadratic model was found as the most suitable for this study. After k-means clustering of the age-ass

SUBMITTER: Gheorghe M 

PROVIDER: S-EPMC3930826 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature