Abstract
DNA methylation provides one of the most widely studied biomarkers of ageing. Since the methylation of CpG dinucleotides function as switches in cellular mechanisms, it is plausible to assume that by proper adjustment of these switches age may be tuned. Though, adjusting hundreds of CpG methylation levels coherently may never be feasible and changing just a few positions may lead to biologically unstable state. A prominent example of methylation-based age estimators is provided by Horvath's clock, based on 353 CpG dinucleotides, showing a high correlation (not necessarily causation) with chronological age across multiple tissue types. On this small subset of CpG dinucleotides we demonstrate how the adjustment of one methylation level leads to a cascade of changes at other sites. Among the studied subset, we locate the most important CpGs (and related genes) that may have a large influence on the rest of the sub-system. According to our analysis, the structure of this network is way more hierarchical compared to what one would expect based on ensembles of uncorrelated connections. Therefore, only a handful of CpGs is enough to modify the system towards a desired state. When propagation of the change over the network is taken into account, the resulting modification in the predicted age can be significantly larger compared to the effect of isolated CpG perturbations. By adjusting the most influential single CpG site and following the propagation of methylation level changes we can reach up to 5.74 years in virtual age reduction, significantly larger than without taking into account of the network control. Extending our approach to the whole methylation network may identify key nodes that have controller role in the ageing process.
Highlights
An ancient desire of humanity is to understand, slow, or even halt and reverse ageing
The chronological age correlates with the methylation level of some locations of the DNA
There is an important caveat to keep in mind when interpreting our results is that we demonstrate the hierarchy, control and perturbation of the methylation network only on a small, somewhat ‘artificially’ isolated subset of the orders of magnitude large set of all CpG dinucleotides of the human genome
Summary
An ancient desire of humanity is to understand, slow, or even halt and reverse ageing. In related studies it was soon realised that certain biomarkers can rather precisely predict the functional capability of tissues, organs and even patients [1, 2]. Individuals of the same chronological age can still show great heterogeneity in the tissue and organismal functions, and could possess different risks for age-associated diseases as judged from their biological ages. The most promising age-predictive biomarkers are the ones based on DNA-methylation [5,6,7], which can be used for basically any source of DNA from sorted cells through tissues to organs, and can predict the biological age across the whole life span from prenatal tissues to tissues obtained from centenarians [5]. DNA methylation-related markers are important in endocrinology [8], cell biology [9], biodemography [10], lifestyle factors [11], and medicine [12]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
