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dc.contributor.authorZagkos, Loukas
dc.contributor.authorRoberts, Jason A.
dc.contributor.authorMc Auley, Mark T.
dc.date.accessioned2022-08-30T14:55:55Z
dc.date.available2022-08-30T14:55:55Z
dc.date.issued2021-11-11
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/627132/Zagkos%20et%20al%202021.pdf?sequence=1
dc.identifier.citationZagkos, L., Roberts, J., Mc Auley, M. T. (2021). A mathematical model which examines age-related stochastic fluctuations in DNA maintenance methylation. Experimental Gerontology, 156, 111623. https://doi.org/10.1016/j.exger.2021.111623en_US
dc.identifier.issn0531-5565
dc.identifier.doi10.1016/j.exger.2021.111623
dc.identifier.urihttp://hdl.handle.net/10034/627132
dc.description.abstractDue to its complexity and its ubiquitous nature the ageing process remains an enduring biological puzzle. Many molecular mechanisms and biochemical process have become synonymous with ageing. However, recent findings have pinpointed epigenetics as having a key role in ageing and healthspan. In particular age related changes to DNA methylation offer the possibility of monitoring the trajectory of biological ageing and could even be used to predict the onset of diseases such as cancer, Alzheimer's disease and cardiovascular disease. At the molecular level emerging evidence strongly suggests the regulatory processes which govern DNA methylation are subject to intracellular stochasticity. It is challenging to fully understand the impact of stochasticity on DNA methylation levels at the molecular level experimentally. An ideal solution is to use mathematical models to capture the essence of the stochasticity and its outcomes. In this paper we present a novel stochastic model which accounts for specific methylation levels within a gene promoter. Uncertainty of the eventual site-specific methylation levels for different values of methylation age, depending on the initial methylation levels were analysed. Our model predicts the observed bistable levels in CpG islands. In addition, simulations with various levels of noise indicate that uncertainty predominantly spreads through the hypermethylated region of stability, especially for large values of input noise. A key outcome of the model is that CpG islands with high to intermediate methylation levels tend to be more susceptible to dramatic DNA methylation changes due to increasing methylation age.en_US
dc.publisherElsevieren_US
dc.relation.urlhttps://www.sciencedirect.com/science/article/abs/pii/S0531556521004058?via%3Dihuben_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.subjectDNA methylationen_US
dc.subjectStochasticityen_US
dc.subjectWhite noiseen_US
dc.subjectAgeingen_US
dc.subjectHealth-spanen_US
dc.titleA Mathematical Model which Examines Age-Related Stochastic Fluctuations in DNA Maintenance Methylationen_US
dc.typeArticleen_US
dc.contributor.departmentUniversity of Chester; Imperial College Londonen_US
dc.identifier.journalExperimental Gerontologyen_US
or.grant.openaccessYesen_US
rioxxterms.funderunfundeden_US
rioxxterms.identifier.projectunfundeden_US
rioxxterms.versionAMen_US
rioxxterms.versionofrecord10.1016/j.exger.2021.111623en_US
rioxxterms.licenseref.startdate2022-11-11
dcterms.dateAccepted2021-11-04
rioxxterms.publicationdate2021-11-11
dc.date.deposited2022-08-30en_US
dc.indentifier.issn0531-5565en_US


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