Aging of blood can be tracked by DNA methylation changes at just three CpG sites

By C. I. Weidner, Qiong Lin, C. Koch, L. Eisele, F. Beier, P. Ziegler, D. Bauerschlag, K. Jöckel, R. Erbel, Thomas W. Mühleisen and 3 more. Genome Biology, 2014

825 citations recorded by the source corpus.

Human aging is associated with DNA methylation changes at specific sites in the genome. These epigenetic modifications may be used to track donor age for forensic analysis or to estimate biological age. We perform a comprehensive analysis of methylation profiles to narrow down 102 age-related CpG sites in blood. We demonstrate that most of these age-associated methylation changes are reversed in induced pluripotent stem cells (iPSCs). Methylation levels at three age-related CpGs - located in the genes ITGA2B, ASPA and PDE4C - were subsequently analyzed by bisulfite pyrosequencing of 151 blood samples. This epigenetic aging signature facilitates age predictions with a mean absolute deviation from chronological age of less than 5 years. This precision is higher than age predictions based on telomere length. Variation of age predictions correlates moderately with clinical and lifestyle parameters supporting the notion that age-associated methylation changes are associated more with biological age than with chronological age. Furthermore, patients with acquired aplastic anemia or dyskeratosis congenita - two diseases associated with progressive bone marrow failure and severe telomere attrition - are predicted to be prematurely aged. Our epigenetic aging signature provides a simple biomarker to estimate the state of aging in blood. Age-associated DNA methylation changes are counteracted in iPSCs. On the other hand, over-estimation of chronological age in bone marrow failure syndromes is indicative for exhaustion of the hematopoietic cell pool. Thus, epigenetic changes upon aging seem to reflect biological aging of blood.

Subfields: Genetics, Molecular Biology, Physiology

View Paper: https://www.semanticscholar.org/paper/0f6e835032e3772734602ced01ee15b919bae54c

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Citations in the corpus

An epigenetic biomarker of aging for lifespan and healthspan (2018, background): “Chronological time has been shown to elicit predictable hypo- and hyper-methylation changes at many regions across the genome [3-7], and as a result, the first generation of DNAm based biomarkers of aging were developed to predict chronological chronological age [8-13].”
DNA methylation age of blood predicts all-cause mortality in later life (2015, positive): “Weidner et al. [12] proposed an age predictor based on three CpGs taken from a methylation array with fewer total CpG sites than the Hannum and Horvath models (27 k probes versus 450 k probes).”
A toolkit for quantification of biological age from blood chemistry and organ function test data: BioAge (2021, background): “Among those showing most promise are a family of algorithms applied to DNA methylation data that estimate a person’s biological age or mortality risk [11-18].”
Epigenetics and aging (2016, background): “However, the reproducibility of DNA methylation changes during aging at some sites is such that age prediction can be made fairly accurately by analyzingDNAmethylation patterns in only three specific CpG sites, at least for blood DNA (154).”
Measuring biological age using omics data (2022, background): “Since these landmark studies in 2013, several other epigenetic clocks have been built, including those by Weidner et al. 54 (3-CpG clock), Lin et al. 55 (99-CpG clock) and Vidal-Bralo et al. 56 (8-CpG clock).”