An evolutionary perspective of lifespan and epigenetic inheritance

In the last decade epigenetics has come to the fore as a discipline which is central to biogerontology. Age associated epigenetic changes are routinely linked with pathologies, including cardiovascular disease, cancer, and Alzheimer's disease; moreover, epigenetic clocks are capable of correlating biological age with chronological age in many species including humans. Recent intriguing empirical observations also suggest that inherited epigenetic effects could influence lifespan/longevity in a variety of organisms. If this is the case, an imperative exists to reconcile lifespan/longevity associated inherited epigenetic processes with the evolution of ageing. This review will critically evaluate inherited epigenetic effects from an evolutionary perspective. The overarching aim is to integrate the evidence which suggests epigenetic inheritance modulates lifespan/longevity with the main evolutionary theories of ageing

Cardiovascular disease and healthy ageing

Cardiovascular diseases are main cause of morbidity and mortality in the Western World. Cardiovascular disease increases in its prevalence with age and the burden of this condition is set to increase with an Ageing global population. There are many factors that impact cardiovascular disease risk. The aim of this brief commentary is to explore some of these factors; specifically, we will examine the role of social status, nutrition and, psychological stress in modulating cardiovascular disease risk. Our aim is to emphasise the multidimensional nature of this condition and to stress that a more complete understanding of the mechanisms which underpin its pathology can only be achieved by adopting an integrated approach which treats the progression of this disease in a more holistic fashion

Computationally modeling lipid metabolism and aging: A mini-review

This is an Version of Record of an article published in Computational and Structural Biotechnology Journal in 15 November 2014, available online: http://dx.doi.org/10.1016/j.csbj.2014.11.006 This is an open-access article distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/ licenses/by/3.0/One of the greatest challenges in biology is to improve the understanding of the mechanisms which underpin aging and how these affect health. The need to better understand aging is amplified by demographic changes, which have caused a gradual increase in the global population of older people. Aging western populations have resulted in a rise in the prevalence of age-related pathologies. Of these diseases, cardiovascular disease is the most common underlying condition in older people. The dysregulation of lipid metabolism due to aging impinges significantly on cardiovascular health. However, the multifaceted nature of lipid metabolism and the complexities of its interaction with aging make it challenging to understand by conventional means. To address this challenge computational modeling, a key component of the systems biology paradigm is being used to study the dynamics of lipid metabolism. This mini-review briefly outlines the key regulators of lipid metabolism, their dysregulation, and how computational modeling is being used to gain an increased insight into this system

Computationally Modelling Cholesterol Metabolism and Atherosclerosis

Cardiovascular disease (CVD) is the leading cause of death globally. The underlying pathological driver of CVD is atherosclerosis. The primary risk factor for atherosclerosis is elevated low-density lipoprotein cholesterol (LDL-C). Dysregulation of cholesterol metabolism is synonymous with a rise in LDL-C. Due to the complexity of cholesterol metabolism and atherosclerosis mathematical models are routinely used to explore their non-trivial dynamics. Mathematical modelling has generated a wealth of useful biological insights, which have deepened our understanding of these processes. To date however, no model has been developed which fully captures how whole-body cholesterol metabolism intersects with atherosclerosis. The main reason for this is one of scale. Whole body cholesterol metabolism is defined by macroscale physiological processes, while atherosclerosis operates mainly at a microscale. This work describes how a model of cholesterol metabolism was combined with a model of atherosclerotic plaque formation. This new model is capable of reproducing the output from its parent models. Using the new model, we demonstrate how this system can be utilized to identify interventions that lower LDL-C and abrogate plaque formation

Computationally modeling lipid metabolism and aging: A mini-review

One of the greatest challenges in biology is to improve the understanding of the mechanisms which underpin aging and how these affect health. The need to better understand aging is amplified by demographic changes, which have caused a gradual increase in the global population of older people. Aging western populations have resulted in a rise in the prevalence of age-related pathologies. Of these diseases, cardiovascular disease is the most common underlying condition in older people. The dysregulation of lipid metabolism due to aging impinges significantly on cardiovascular health. However, the multifaceted nature of lipid metabolism and the complexities of its interaction with aging make it challenging to understand by conventional means. To address this challenge computational modeling, a key component of the systems biology paradigm is being used to study the dynamics of lipid metabolism. This mini-review briefly outlines the key regulators of lipid metabolism, their dysregulation, and how computational modeling is being used to gain an increased insight into this system

LDL-C levels in older people: Cholesterol Homeostasis and the Free Radical Theory of Ageing Converge

The cardiovascular disease (CVD) risk factor, low density lipoprotein cholesterol (LDL-C) increases with age, up until the midpoint of life in males and females. However, LDL-C can decrease with age in older men and women. Intriguingly, a recent systematic review also revealed an inverse association between LDL-C levels and cardiovascular mortality in older people; low levels of LDL-C were associated with reduced risk of mortality. Such findings are puzzling and require a biological explanation. In this paper a hypothesis is proposed to explain these observations. We hypothesize that the free radical theory of ageing (FRTA) together with disrupted cholesterol homeostasis can account for these observations. Based on this hypothesis, dysregulated hepatic cholesterol homeostasis in older people is characterised by two distinct metabolic states. The first state accounts for an older person who has elevated plasma LDL-C. This state is underpinned by the FRTA which suggests there is a decrease in cellular antioxidant capacity with age. This deficiency enables hepatic reactive oxidative species (ROS) to induce the total activation of HMG-CoA reductase, the key rate limiting enzyme in cholesterol biosynthesis. An increase in cholesterol synthesis elicits a corresponding rise in LDL-C, due to the downregulation of LDL receptor synthesis, and increased production of very low density lipoprotein cholesterol (VLDL-C). In the second state of dysregulation, ROS also trigger the total activation of HMG-CoA reductase. However, due to an age associated decrease in the activity of cholesterol-esterifying enzyme, acyl CoA: cholesterol acyltransferase, there is restricted conversion of excess free cholesterol (FC) to cholesterol esters. Consequently, the secretion of VLDL-C drops, and there is a corresponding decrease in LDL-C. As intracellular levels of FC accumulate, this state progresses to a pathophysiological condition akin to nonalcoholic fatty liver disease. It is our conjecture this deleterious state has the potential to account for the inverse association between LDL-C level and CVD risk observed in older people

Systems biology and synthetic biology: A new epoch for toxicology research

Copyright © 2015 Mark T. Mc Auley et al. This is an open access article distributed under the Creative Commons Attribution License 3.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Systems biology and synthetic biology are emerging disciplines which are becoming increasingly utilised in several areas of bioscience. Toxicology is beginning to benefit from systems biology and we suggest in the future that is will also benefit from synthetic biology. Thus, a new era is on the horizon. This review illustrates how a suite of innovative techniques and tools can be applied to understanding complex health and toxicology issues. We review limitations confronted by the traditional computational approaches to toxicology and epidemiology research, using polycyclic aromatic hydrocarbons (PAHs) and their effects on adverse birth outcomes as an illustrative example. We introduce how systems toxicology (and their subdisciplines, genomic, proteomic, and metabolomic toxicology) will help to overcome such limitations. In particular, we discuss the advantages and disadvantages of mathematical frameworks that computationally represent biological systems. Finally, we discuss the nascent discipline of synthetic biology and highlight relevant toxicological centred applications of this technique, including improvements in personalised medicine. We conclude this review by presenting a number of opportunities and challenges that could shape the future of these rapidly evolving disciplines.Veronica M. Miller would like to acknowledge funding from Alexander and Bo McInnis and the Autism Research Institute for her toxicological studies and support

A new mathematical model of folate homeostasis in E. coli highlights the potential importance of the folinic acid futile cycle in cell growth.

Folate (vitamin B9) plays a central role in one-carbon metabolism in prokaryotes and eukaryotes. This pathway mediates the transfer of one-carbon units, playing a crucial role in nucleotide synthesis, methylation, and amino acid homeostasis. The folinic acid futile cycle adds a layer of intrigue to this pathway, due to its associations with metabolism, cell growth, and dormancy. It also introduces additional complexity to folate metabolism. A logical way to deal with such complexity is to examine it by using mathematical modelling. This work describes the construction and analysis of a model of folate metabolism, which includes the folinic acid futile cycle. This model was tested under three in silico growth conditions. Model simulations revealed: 1) the folate cycle behaved as a stable biochemical system in three growth states (slow, standard, and rapid); 2) the initial concentration of serine had the greatest impact on metabolite concentrations; 3) 5-formyltetrahydrofolate cyclo-ligase (5-FCL) activity had a significant impact on the levels of the 7 products that carry the one-carbon donated from folates, and the redox couple NADP/NADPH; this was particularly evident in the rapid growth state; 4) 5-FCL may be vital to the survival of the cells by maintaining low levels of homocysteine, as high levels can induce toxicity; and 5) the antifolate therapeutic trimethoprim had a greater impact on folate metabolism with higher nutrient availability. These results highlight the important role of 5-FCL in intracellular folate homeostasis and mass generation under different metabolic scenarios. [Abstract copyright: Copyright © 2023 Elsevier B.V. All rights reserved.

Mathematical models of DNA methylation dynamics: Implications for health and ageing

DNA methylation status is a key epigenetic process which has been intimately associated with gene regulation. In recent years growing evidence has associated DNA methylation status with a variety of diseases including cancer, Alzheimers disease and cardiovascular disease. Moreover, changes to DNA methylation have also recently been implicated in the ageing process. The factors which underpin DNA methylation are complex, and remain to be fully elucidated. Over the years mathematical modelling has helped to shed light on the dynamics of this important molecular system. Although the existing models have contributed significantly to our overall understanding of DNA methylation, they fall-short of fully capturing the dynamics of this process. In this paper we develop a linear and nonlinear model which captures more fully the dynamics of the key intracellular events which characterise DNA methylation. In particular the outcomes of our linear model result in gene promoter specific methylation levels which are more biologically plausible than those revealed by previous mathematical models. In addition, our non-linear model predicts DNA methylation promoter bistability which is commonly observed experimentally. The findings from our models have implications for our current understanding of how changes to the dynamics which underpin DNA methylation affect ageing and health