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Hierarchy and control of ageing-related methylation networks

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...

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Autores principales: Palla, Gergely, Pollner, Péter, Börcsök, Judit, Major, András, Molnár, Béla, Csabai, István
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8480875/
https://www.ncbi.nlm.nih.gov/pubmed/34534207
http://dx.doi.org/10.1371/journal.pcbi.1009327
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author Palla, Gergely
Pollner, Péter
Börcsök, Judit
Major, András
Molnár, Béla
Csabai, István
author_facet Palla, Gergely
Pollner, Péter
Börcsök, Judit
Major, András
Molnár, Béla
Csabai, István
author_sort Palla, Gergely
collection PubMed
description 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.
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spelling pubmed-84808752021-09-30 Hierarchy and control of ageing-related methylation networks Palla, Gergely Pollner, Péter Börcsök, Judit Major, András Molnár, Béla Csabai, István PLoS Comput Biol Research Article 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. Public Library of Science 2021-09-17 /pmc/articles/PMC8480875/ /pubmed/34534207 http://dx.doi.org/10.1371/journal.pcbi.1009327 Text en © 2021 Palla et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Palla, Gergely
Pollner, Péter
Börcsök, Judit
Major, András
Molnár, Béla
Csabai, István
Hierarchy and control of ageing-related methylation networks
title Hierarchy and control of ageing-related methylation networks
title_full Hierarchy and control of ageing-related methylation networks
title_fullStr Hierarchy and control of ageing-related methylation networks
title_full_unstemmed Hierarchy and control of ageing-related methylation networks
title_short Hierarchy and control of ageing-related methylation networks
title_sort hierarchy and control of ageing-related methylation networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8480875/
https://www.ncbi.nlm.nih.gov/pubmed/34534207
http://dx.doi.org/10.1371/journal.pcbi.1009327
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