Open AccessTowards a gene expression biomarker set for human biological age
Author(s) -
Holly Alice C.,
Melzer David,
Pilling Luke C.,
Henley William,
Hernandez Dena G.,
Singleton Andrew B.,
Bandinelli Stefania,
Guralnik Jack M.,
Ferrucci Luigi,
Harries Lorna W.
Publication year - 2013
Publication title -
aging cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.103
H-Index - 140
eISSN - 1474-9726
pISSN - 1474-9718
DOI - 10.1111/acel.12044
Subject(s) - biological age , biology , gene expression , biomarker , age groups , gene , demography , genetics , evolutionary biology , sociology
Summary 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.