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Aging Cell. 2013 Apr;12(2):324-6. doi: 10.1111/acel.12044. Epub 2013 Jan 30.

Towards a gene expression biomarker set for human biological age.

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Institute of Biomedical and Clinical Science, Exeter Medical School, University of Exeter, Exeter, EX2 5DW, UK.


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.

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