These authors contributed equally to this publication.
Towards a gene expression biomarker set for human biological age
Version of Record online: 30 JAN 2013
© 2013 The Authors Aging Cell © 2013 Blackwell Publishing Ltd/Anatomical Society of Great Britain and Ireland
Volume 12, Issue 2, pages 324–326, April 2013
How to Cite
Holly, A. C., Melzer, D., Pilling, L. C., Henley, W., Hernandez, D. G., Singleton, A. B., Bandinelli, S., Guralnik, J. M., Ferrucci, L. and Harries, L. W. (2013), Towards a gene expression biomarker set for human biological age. Aging Cell, 12: 324–326. doi: 10.1111/acel.12044
- Issue online: 17 MAR 2013
- Version of Record online: 30 JAN 2013
- Accepted manuscript online: 12 JAN 2013 03:48AM EST
- biological aging;
- mRNA expression;
- cell senescence;
- predictive model
We have previously described a statistical model capable of distinguishing young (age <65 years) from old (age ≥75 years) individuals. Here we studied the performance of a modified model in three populations and determined whether individuals predicted to be biologically younger than their chronological age had biochemical and functional measures consistent with a younger biological age. Those with ‘younger’ gene expression patterns demonstrated higher muscle strength and serum albumin, and lower interleukin-6 and blood urea concentrations relative to ‘biologically older’ individuals (odds ratios 2.09, 1.64, 0.74, 0.74; P = 2.4 × 10−2, 3.5 × 10−4, 1.8 × 10−2, 1.5 × 10−2, respectively). We conclude that our expression signature of age is robust across three populations and may have utility for estimation of biological age.