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Open AccessJournal ArticleDOI

Epigenetic Predictor of Age

TLDR
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.
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.

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Journal ArticleDOI

DNA methylation age of human tissues and cell types

TL;DR: It is proposed that DNA methylation age measures the cumulative effect of an epigenetic maintenance system, and can be used to address a host of questions in developmental biology, cancer and aging research.
Journal ArticleDOI

DNA methylation arrays as surrogate measures of cell mixture distribution

TL;DR: This work presents a method, similar to regression calibration, for inferring changes in the distribution of white blood cells between different subpopulations using DNA methylation signatures, in combination with a previously obtained external validation set consisting of signatures from purified leukocyte samples.
Journal ArticleDOI

Genome-wide Methylation Profiles Reveal Quantitative Views of Human Aging Rates

TL;DR: A quantitative model of aging is built using measurements at more than 450,000 CpG markers from the whole blood of 656 human individuals, aged 19 to 101, to measure the rate at which an individual's methylome ages, which is impacted by gender and genetic variants.
Journal ArticleDOI

DNA methylation-based biomarkers and the epigenetic clock theory of ageing

TL;DR: Biomarkers of ageing based on DNA methylation data enable accurate age estimates for any tissue across the entire life course and link developmental and maintenance processes to biological ageing, giving rise to a unified theory of life course.
Journal ArticleDOI

Inflammaging: a new immune–metabolic viewpoint for age-related diseases

TL;DR: It is argued that chronic diseases are not only the result of ageing and inflammaging; these diseases also accelerate the ageing process and can be considered a manifestation of accelerated ageing, and the use of new biomarkers capable of assessing biological versus chronological age in metabolic diseases is proposed.
References
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Epigenetic differences arise during the lifetime of monozygotic twins

TL;DR: Older monozygous twins exhibited remarkable differences in their overall content and genomic distribution of 5-methylcytosine DNA and histone acetylation, affecting their gene-expression portrait, indicating how an appreciation of epigenetics is missing from the understanding of how different phenotypes can be originated from the same genotype.
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