A mathematical model which examines age-related stochastic fluctuations in DNA maintenance methylation

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2021-02-06 DOI:10.1101/2021.02.05.429896
L. Zagkos, Jason Roberts, M. M. Auley
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引用次数: 3

Abstract

Due 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. We quantify the uncertainty of the eventual cite-specific methylation levels for different values of methylation age, depending on the initial methylation levels. 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 intermediate methylation levels tend to be more susceptible to dramatic DNA methylation changes towards both hypomethylation and hypermethylation, due to increasing methylation age.
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一个数学模型,检验年龄相关的DNA维持甲基化随机波动
由于其复杂性和普遍性,衰老过程仍然是一个持久的生物学难题。许多分子机制和生化过程已成为衰老的代名词。然而,最近的研究发现,表观遗传学在衰老和健康寿命中起着关键作用。特别是与年龄相关的DNA甲基化变化提供了监测生物衰老轨迹的可能性,甚至可以用来预测癌症、阿尔茨海默病和心血管疾病等疾病的发病。在分子水平上,新出现的证据强烈表明,控制DNA甲基化的调控过程受细胞内随机性的影响。在分子水平上,从实验上充分理解随机性对DNA甲基化水平的影响具有挑战性。一个理想的解决方案是使用数学模型来捕捉随机性及其结果的本质。在本文中,我们提出了一个新的随机模型,该模型可以解释基因启动子内特定的甲基化水平。根据初始甲基化水平,我们量化了不同甲基化年龄值的最终引物特异性甲基化水平的不确定性。我们的模型预测了在CpG岛屿上观测到的双稳态水平。此外,具有不同噪声水平的模拟表明,不确定性主要通过稳定性的高甲基化区域传播,特别是对于大值的输入噪声。该模型的一个关键结果是,由于甲基化年龄的增加,具有中等甲基化水平的CpG岛往往更容易受到DNA甲基化向低甲基化和高甲基化方向变化的影响。
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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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