Epigenetic predictor of age

Abstract

From the moment of conception, we begin to age. A decay of cellular structures, gene regulation, and DNA sequence ages cells and organisms. DNA methylation patterns change with increasing age and contribute to age related disease. Here we identify 88 sites in or near 80 genes for which the degree of cytosine methylation is significantly correlated with age in saliva of 34 male identical twin pairs between 21 and 55 years of age. Furthermore, we validated sites in the promoters of three genes and replicated our results in a general population sample of 31 males and 29 females between 18 and 70 years of age. The methylation of three sites--in the promoters of the EDARADD, TOM1L1, and NPTX2 genes--is linear with age over a range of five decades. Using just two cytosines from these loci, we built a regression model that explained 73% of the variance in age, and is able to predict the age of an individual with an average accuracy of 5.2 years. In forensic science, such a model could estimate the age of a person, based on a biological sample alone. Furthermore, a measurement of relevant sites in the genome could be a tool in routine medical screening to predict the risk of age-related diseases and to tailor interventions based on the epigenetic bio-age instead of the chronological age.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1. Detection of gene co-methylation modules in human saliva in twins.

(a) Branches of the hierarchical cluster tree define five co-methylation modules which are assigned a color as can be seen from the first color band underneath the tree. Probes that could not be clustered into one of these modules were coded grey. Every probe represents a line in the hierarchical cluster tree. Distance between two probes is shown as height on the y-axis. The second color band encodes the age relationships of each gene. Genes with positive age correlations are colored in blue. (b) Barplots showing age relationships of modules. Specifically, the y-axis shows the mean Student T-statistic testing whether the methylation status of a probe is correlated with age. Note that the green module is enriched for probes that have a significant positive correlation with age. A t-statistic value of 2 or higher indicates a significant correlation (p

Figure 2. Percentage methylation versus age for three markers validated in three sample sets.

Original twin samples are blue, male control samples are red, female control samples green. Linear trendlines are shown in the colors of the individual sample sets a) Edaradd r = −0.81 (twins), r = −0.73 (male controls), r = −0.75 (female controls) b) NPTX2 r = 0.52 (twins), r = 0.79 (male controls), r = 0.03 (female controls) c) Tom1L1 r = −0.70 (twins), r = −0.49 (male controls), r = −0.24 (female controls).

Figure 3. Predicted versus observed age of all subjects using a leave-one-out model.

A multivariate regression model was fit on all but one sample and its predicted age (y-axis) was related to the truly observed age of the left out sample (x-axis). The predicted values are highly correlated with the observed ages (r = 0.83, p = 2.2×10−16, n = 66), and the average absolute difference between the predicted and the observed age is 5.2 years.