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

Effects of obesity on cholesterol metabolism and its implications for healthy ageing.

This article has been published in a revised form in Nutrition Research Reviews [https://doi.org/10.1017/S0954422419000258]. This version is free to view and download for private research and study only. Not for re-distribution or re-use. © copyright holder.The last few decades have witnessed a global rise in the number of older people. Despite this demographic shift, morbidity within this population group is high. Many factors influence healthspan; however an obesity pandemic is emerging as a significant determinant of older peoples’ health. It is well established obesity adversely effects several metabolic systems. However, due to its close association with overall cardiometabolic health, the impact obesity has on cholesterol metabolism needs to be recognised. The aim of this review is to critically discuss the effects obesity has on cholesterol metabolism and to reveal its significance for healthy 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