Institute of Biomedical and Clinical Science, Exeter Medical School, University of Exeter, Exeter, EX2 5DW, UK.
Aging Cell. 2013 Apr;12(2):324-6. doi: 10.1111/acel.12044. Epub 2013 Jan 30.
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.
我们之前描述了一种能够区分年轻(年龄 <65 岁)和年老(年龄≥75 岁)个体的统计模型。在这里,我们研究了一个改良模型在三个人群中的表现,并确定了那些预测生物学年龄比实际年龄年轻的个体是否具有与更年轻的生物学年龄一致的生化和功能指标。与“生物学上更老”的个体相比,具有“更年轻”基因表达模式的个体表现出更高的肌肉力量和血清白蛋白水平,以及更低的白细胞介素-6 和血尿素浓度(比值比 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),分别)。我们得出结论,我们的年龄表达特征在三个人群中是稳健的,并且可能对估计生物学年龄有用。