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Open Access Methodology article

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

Marius Gheorghe1, Marc Snoeck4, Michael Emmerich3, Thomas Bäck3, Jelle J Goeman25 and Vered Raz1*

Author Affiliations

1 Department of Human and Clinical Genetics, Leiden University Medical Centre, Leiden, The Netherlands

2 Department of Medical Statistics, Leiden University Medical Centre, Leiden, The Netherlands

3 Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands

4 Department of Anaestasia, Canisius-Wilhelmina Hospital, Nijmegen, The Netherlands

5 Biostatistics, Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands

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BMC Genomics 2014, 15:132  doi:10.1186/1471-2164-15-132

Published: 14 February 2014

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-associated probes, expression trends were found to change at two major age-positions in brain cortex and in Vastus lateralis muscles. The first age-position was found to occur during the fifth decade and a later one during the eighth decade. In kidney cortex, however, only one age-position was identified correlating with a late age-position. Functional mapping of genes at each age-position suggests that calcium homeostasis and lipid metabolisms are initially affected and subsequently, in elderly mitochondria, apoptosis and hormonal signaling pathways are affected.

Conclusions

Our results suggest that age-associated temporal changes in human tissues progress at distinct age-positions, which differ between tissues and in their molecular composition.

Keywords:
Human aging; Expression profiles; Quadratic regression model; Kmeans clustering